From hongzhi.kuai at gmail.com Wed Mar 1 00:32:05 2023 From: hongzhi.kuai at gmail.com (H.Z. Kuai) Date: Wed, 1 Mar 2023 14:32:05 +0900 Subject: Connectionists: CfP: Brain Informatics 2023 (April 15, Submission Due) Message-ID: +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ CALL FOR PAPERS The 16th International Conference on Brain Informatics (BI'23) August 1 - 3, 2023 Hoboken & New York ? USA The key theme: Brain Science meets Artificial Intelligence A Hybrid Conference with both Online and Offline Modes History of BI: www.youtube.com/watch?v=Y2s78IIN-CQ Conference homepage: wi-consortium.org/conferences/bi2023/ +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ *** IMPORTANT DATES *** - 15 April 2023: Full Paper Submission Deadline - 20 April 2023: Workshop Proposal Submission Deadline *** Confirmed Keynote Speakers *** - Professor Emery N. Brown Member of the National Academy of Sciences Member of the National Academy of Engineering Member of the National Academy of Medicine MIT, Massachusetts General Hospital, USA - Professor Bin He Fellow of International Academy of Medical and Biological Engineering (IAMBE) Fellow of American Institute of Medical and Biological Engineering (AIMBE) Fellow of Biomedical Engineering Society (BMES), and IEEE Member of the National Academy of Inventors Carnegie Mellon University, USA - Professor John Ngai Director of NIH BRAIN Initiative NIH BRAIN Initiative, USA - Professor Helen Mayberg Member of the National Academy of Sciences Member of the National Academy of Medicine Member of the National Academy of Inventors Member of the American Academy of Arts and Sciences Mount Sinai Medical Center, USA - Professor Vinod Goel Author of monographs: ?Sketches of thought? and ?Reason and Less: Pursuing Food, Sex, and Politics? York University, Canada - Professor Amy Kuceyeski Director of Computational Connectomics (CoCo) at Weill Cornell Medicine Cornell University, USA - Professor Patrick Purdon Nathaniel M. Sims Endowed Chair in Anesthesia Innovation and Bioengineering at Massachusetts General Hospital (MGH) Fellow of American Institute for Medical and Biological Engineering (AIMBE) National Institutes of Health Director?s New Innovator Award MGH, Harvard Medical School, USA *** Local information *** *The location of the BI2023 in the beautiful campus of Stevens Institute of Technology in Hoboken, New Jersey, located on the west bank of Hudson River overlooking Manhattan. Stevens is close to a group of finest universities such as Princeton University (1.5 hours drive), Columbia University (25 min drive), New York University (20 min drive) and Yale University (1h 40 min drive). *Convenient transportation: (1) Nearby there are three major airports: Newark, JFK, and LaGuardia with direct flights to all major cities in the world. (2) 15 minutes to Time Square by bus. *An economic accommodation option: $100 dorm room option is available in the newly completed University Complex Center Building with a view of Manhattan (limited spaces) ***About the conference*** The International Conference on Brain Informatics (BI) series has established itself as the world's premier research conference on Brain Informatics, which is an emerging interdisciplinary and multidisciplinary research field that combines the efforts of Cognitive Science, Neuroscience, Machine Learning, Data Science, Artificial Intelligence (AI), and Information and Communication Technology (ICT) to explore the main problems that lie in the interplay between human brain studies and informatics research. The 16th International Conference on Brain Informatics (BI'23) provides a premier international forum to bring together researchers and practitioners from diverse fields for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences on Brain Informatics research, brain-inspired technologies and brain/mental health applications. *** Topics and Areas *** The key theme of the conference is "Brain Science meets Artificial Intelligence". The BI'23 solicits high-quality original research and application papers (full paper and abstract presentation submissions). Relevant topics include but are not limited to: Track 1: Cognitive and Computational Foundations of Brain Science Track 2: Human Information Processing Systems Track 3: Brain Big Data Analytics, Curation and Management Track 4: Informatics Paradigms for Brain and Mental Health Research Track 5: Brain-Machine Intelligence and Brain-Inspired Computing ***Journal Opportunities*** High quality BI conference papers may be nominated to submit an extended version for a fast track review and publication at the Brain Informatics Journal (https://braininformatics.springeropen.com/), an international, peer-reviewed, interdisciplinary Open Access journal published by Springer Nature. Real-time Journal's Impact Factor: 8.5. *** Paper Submission and Publications *** Paper Submission link: http://wi-consortium.org/conferences/bi2023/paper%20submissions%20and%20publications.html 9-12 pages are encouraged for the regular papers including figures and references in Springer LNCS Proceedings format ( https://www.springer.com/us/computer-science/lncs/conference-proceedings-guidelines). Overlength pages will be charged for 200$ per page. All papers will be peer-reviewed and accepted based on originality, significance of contribution, technical merit, and presentation quality. All papers accepted (and all workshop & special sessions' full length papers) will be published by Springer as a volume of the Springer-Nature LNAI Brain Informatics Book Series ( https://link.springer.com/conference/brain). Abstract Submission (Only for Workshops/Special Sessions): Research abstracts are encouraged and will be accepted for presentations in an oral presentation format and/or poster presentation format. Each abstract submission should include the title of the paper and an abstract body within 500 words. Note: The abstract will not be included in the conference proceedings to be published by Springer. Special Issues & Books: Workshop organizers can be invited to contribute a book publication in the Springer-Nature Brain Informatics & Health Book Series ( https://www.springer.com/series/15148), or a special issue at the Brain Informatics Journal. *** Workshop & Special Sessions *** Proposal Submissions: BI'23 will be hosting a series of workshops and special sessions featuring topics relevant to the brain informatics community on the latest research and industry applications. Papers & Presentations: A workshop/special session typically takes a half day (or full day) and includes a mix of regular and invited presentations including regular papers, abstracts, invited papers as well as invited presentations. The paper and abstract submissions to workshops/special sessions will follow the same format as the BI conference papers and abstracts. Proposal Guidelines: Each proposal should include: 1) workshop/special session title; 2) length of the workshop (half/full day); 3) names, main contact, and a short bio of the workshop organizers; 4) brief description of the workshop scope and timeline; 5) prior history of the workshop (if any); 6) potential program committee members and invited speakers; 7) any other relevant information. *** IMPORTANT DATES *** * 15 April 2023: Full paper submission deadline * 20 April 2023: Workshop proposal deadline * 10 May 2023: Abstract presentation submission deadline * 30 May 2023: Final paper and abstract acceptance notification * 20 Jun 2023: Accepted paper and abstract registration deadline * 1-3 Aug 2023: The Brain Informatics Conference Organizing Committee ++++++++++++++++++++++ General Chairs * Bin He, Carnegie Mellon University, USA * Stefano Panzeri, University Medical Center Hamburg-Eppendorf, Germany Organizing Chairs * Feng Liu, Stevens Institute of Technology, USA * Hongjun Wang, Stevens Institute of Technology, USA * Sheraz Khan, MGH Harvard and MIT, USA * Emily Stephen, Boston University, USA Program Chairs * Yu Zhang, Lehigh University, USA * Zhe Sage Chen, New York University, USA * Jordi Sol?-Casals, University of Vic, Spain * Peipeng Liang, CNU School of Psychology, China * Islem Rekik, Istanbul Technology University, Turkey Workshop Chairs * Vicky Yamamoto, Keck School of Medicine of USC, USA * Xiang Li, MGH, Harvard Medical School, USA * Yusuf Cakmak, University of Otago, New Zealand * Shuqiang Wang, Shenzhen Institute of Advanced Technology, CAS, China * Yang Yang, BFU Department of Psychology, China * Cesar German Castellanos Dominguez, National University of Colombia, Colombia Tutorial Chairs * Guihong Wan, Harvard Medical School/Massachusetts General Hospital, USA * Shouyi Wang, University of Texas at Arlington, USA * Antonia Zaferiou, Stevens Institute of Technology, USA Publicity Chairs * Hongzhi Kuai, Maebashi Institute of Technology, Japan * Miaolin (Melody) Fan, MGH, Harvard Medical School, USA Advisory Board Chair: Ning Zhong, Maebashi Institute of Technology, Japan * Tianzi Jiang, Institute of Automation, CAS, China * Nikola Kasabov, Auckland University of Technology, New Zealand * Hesheng Liu, MGH, Harvard Medical School, USA * Guoming Luan, Sanbo Brain Hospital, China * Mufti Mahmud, Nottingham Trent University, UK * Hanchuan Peng, SEU-Allen Institute for Brain & Intelligence, China * Shinsuke Shimojo, California Institute of Technology, USA Contact Us: http://wi-consortium.org/conferences/bi2023/contact.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From avellido at cs.upc.edu Wed Mar 1 03:30:38 2023 From: avellido at cs.upc.edu (Alfredo Vellido) Date: Wed, 1 Mar 2023 09:30:38 +0100 Subject: Connectionists: 1st CFP: Workshop XAI-Healthcare 2023. Slovenia, June 15, 2023 Message-ID: <2896012a-b943-706f-05ae-4b7c0ce5217c@cs.upc.edu> ==== Apologies for cross-posting ==== *1-day workshop June 15, 2023*in conjunction with*AIME 2023 *(https://aime23.aimedicine.info), Portoroz, Slovenia https://www.um.es/medailab/events/XAI-Healthcare/* * *Important dates* *April 24*, 2023 Paper submission *May 11*, 2023 Acceptance *May 15*, 2023 Final mansucript The purpose of XAI-Healthcare 2023 event is to provide a place for intensive discussion on all aspects of eXplainable Artificial Intelligence (XAI) in the medical and healthcare field. This should result in cross-fertilization among research on Machine Learning, Decision Support Systems, Natural Language, Human-Computer Interaction, and Healthcare sciences. This meeting will also provide attendees with an opportunity to learn more on the progress of XAI in healthcare and to share their own perspectives. The panel discussion will provide participants with the insights on current developments and challenges from the researchers working in this fast-developing field. Explainable AI (XAI) aims to address the problem of understanding how decisions are made by AI systems by designing formal methods and frameworks for easing their interpretation. The impact of AI in clinical settings and the trust placed in such systems by clinicians have been a growing concern related to the risk of introducing AI into the healthcare environment. XAI in healthcare is a multidisciplinary area addressing this challenge by combining AI technologies, cognitive modeling, healthcare science, ethical and legal issues. *Submission Guidelines *Submission website: https://easychair.org/conferences/?conf=xaihealthcare2023 All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome: *Explanation Approaches*: Model agnostic methods Feature analysis Visualization approaches Example and counterfactuals based explanations Fairness, accountability and trust Evaluating XAI Fairness and bias auditing Human-AI interaction Human-Computer Interaction (HCI) for XAI Natural Language Processing (NLP) Explainability *AI techniques*: Blackbox ML approaches: DL, random forest, etc. Interpretable ML models: Rules, Trees, Bayesian networks, etc. Statistical models and reasoning Case-based reasoning Natural language processing and generation Abductive Reasoning *Target healthcare problems*: Infection challenges (COVID, Antibiotic Resistance, etc.) Trustworthy AI Chronic diseases Ageing & home care Diagnostic systems *Organizing Committee* Concha Bielza, Dept. of Artificial Intelligence, Universidad Polit?cnica de Madrid Pedro Larra?aga, Dept. of Artificial Intelligence, Universidad Polit?cnica de Madrid Primoz Kocbek, Faculty of Health Sciences, University of Maribor Jose M. Juarez, Faculty of Computer Science, Universidad de Murcia Gregor Stiglic, Faculty of Health Sciences, University of Maribor Alfredo Vellido, Universitat Polit?cnica de Catalunya and IDEAI-UPC -------------- next part -------------- An HTML attachment was scrubbed... URL: From announce at ucy.ac.cy Wed Mar 1 04:41:41 2023 From: announce at ucy.ac.cy (Announce Announcements) Date: Wed, 1 Mar 2023 11:41:41 +0200 Subject: Connectionists: 10th European Conference On Service-Oriented And Cloud Computing (ESOCC 2023): Third Call for Submissions Message-ID: *** Third Call for Submissions *** 10th European Conference On Service-Oriented And Cloud Computing (ESOCC 2023) October 24-26, 2023, Golden Bay Beach Hotel, Larnaca, Cyprus https://cyprusconferences.org/esocc2023/ (Proceedings to be published in Springer LNCS; Journal Special Issue with Springer Computing) AIM AND SCOPE Nowadays, Service-Oriented and Cloud Computing are the primary approaches to build large-scale distributed systems and deliver software services to end users. Cloud-native software is pervading the delivery of enterprise applications, as they are composed of (micro)services that can be independently developed and deployed by exploiting multiple heterogeneous technologies. Resulting applications are polyglot service compositions that can then be shipped in serverful or serverless platforms (e.g., using virtualization technologies). These characteristics make Service-Oriented and Cloud Computing the natural answers for fulfilling the industry?s need for flexibly scalable and maintainable enterprise applications, to be delivered through state-of-the-art methodologies, like DevOps. To further support this, researchers and practitioners need to create methods, tools and techniques to support cost-effective and secure development as well as use of dependable devices, platforms, services and service-oriented applications in the Cloud, now also considering the Cloud-IoT computing continuum to exploit widespread adoption of smart connected things and the increasing growth of their computing capabilities. The European Conference on Service-Oriented and Cloud Computing (ESOCC) is the premier conference on advances in the state-of-the-art and practice of Service-Oriented Computing and Cloud Computing in Europe. ESOCC aims to facilitate the exchange between researchers and practitioners in the areas of Service-Oriented Computing and Cloud Computing, as well as to explore the new trends in those areas and foster future collaborations in Europe and beyond. TOPICS OF INTEREST ESOCC 2023 seeks original, high-quality contributions related to all aspects of Service-Oriented and Cloud computing. Specific topics of interest include, but are not limited to: ? Applications for Service-Oriented and Cloud Computing, e.g., big data, commerce, energy, finance, health, scientific computing, smart cities ? Blockchains for Service-Oriented and Cloud Computing ? Business aspects of Service-Oriented and Cloud Computing, e.g., business models, brokerage, marketplaces, costs, pricing ? Business processes, e.g., service-based workflow deployment and management ? Cloud interoperability, service and Cloud standards, ? Cloud-IoT computing continuum, e.g., edge computing, fog computing, mobility computing, next generation services/IoT ? Cloud-native architectures and paradigms, e.g., microservices and DevOps ? Cloud service models, e.g., IaaS, PaaS, SaaS, DBaaS, FaaS, etc. ? Deployment, composition, and management of applications in Service-Oriented and Cloud Computing ? Foundations and formal methods for Service-Oriented and Cloud Computing ? Enablers for Service-Oriented and Cloud Computing, e.g., service discovery, orchestration, matchmaking, monitoring, and analytics ? Model-Driven Engineering for Service-Oriented and Cloud Computing ? Multi-Cloud, cross-Cloud, and federated Cloud solutions ? Requirements engineering, design, development, and testing of applications in Service-Oriented and Cloud Computing ? Semantic services and service mining ? Service and Cloud middlewares and platforms ? Software/service adaptation and evolution in Service-Oriented and Cloud Computing ? Storage, computation and network Clouds ? Sustainability and energy issues in Service-Oriented and Cloud Computing ? Quality aspects (e.g., governance, privacy, security, and trust) of Service-Oriented and Cloud Computing ? Quality of Service (QoS) and Service-Level Agreement (SLA) for Service-Oriented and Cloud Computing ? Social aspects of Service-Oriented and Cloud Computing, e.g., crowdsourcing services, social and crowd-based Clouds ? Virtualization for Service-Oriented and Cloud Computing, e.g., serverless, container-based virtualization, VMs IMPORTANT DATES ? Submission of abstracts: June 4th, 2023 (AoE) ? Submission of full papers: June 11th, 2023 (AoE) ? Notification to authors: July 14th, 2023 (AoE) ? Camera-ready versions due: July 31st, 2023 (AoE) TYPES OF SUBMISSIONS ESOCC 2023 invites submissions of the following kinds: ? Regular Research Papers (15 pages including references, for the technical and special tracks) ? PhD Symposium (12 pages including references) ? Projects and Industry Reports (Projects and Industry Reports (1 to 6 pages including references, describing an ongoing EU or national project, or providing industrial perspectives on innovative applications, technologies, or methods in ESOCC?s scope)? We only accept original papers, not submitted for publication elsewhere. The papers must be formatted according to the proceedings guidelines of Springer?s Lecture Notes in Computer Science (LNCS) series (http://www.springer.com/lncs). They must be submitted to the EasyChair site at: ?https://easychair.org/conferences/?conf=esocc2023? by selecting the right track. Accepted papers from all tracks will be published in the main conference proceedings by Springer in the LNCS series. For publication to happen, at least one author of each accepted paper is expected to register and present the work at the conference. The best papers accepted will be invited to submit extended versions for a Journal Special Issue to be published by Springer Computing. ORGANISATION General Chair ? George A. Papadopoulos, University of Cyprus, CY (george at ucy.ac.cy) ? Program Chairs ? Florian Rademacher, University of Applied Sciences and Arts Dortmund, DE (florian.rademacher at fh-dortmund.de) ? Jacopo Soldani, University of Pisa, IT (jacopo.soldani at unipi.it) Steering and Program Committee https://cyprusconferences.org/esocc2023/committees/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From rbianchi at fei.edu.br Wed Mar 1 13:05:53 2023 From: rbianchi at fei.edu.br (Reinaldo A. C. Bianchi) Date: Wed, 1 Mar 2023 18:05:53 +0000 Subject: Connectionists: Second Call for Papers - BWAIF - 2023 - DEADLINE EXTENDED Message-ID: Second Call for Papers - BWAIF - 2023 - DEADLINE EXTENDED -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 2nd Brazilian Workshop on Artificial Intelligence in Finance Satellite Event of the XLIII Congress of the Brazilian Computer Society Jo?o Pessoa, Para?ba, July 23rd-28th, 2023. https://csbc.sbc.org.br/2023/bwaif/023/ Artificial Intelligence, and in particular Machine Learning, is a technology that is transforming how we integrate information, analyze data and make decisions, with large impact throughout our society. Advances in AI are being felt in our economy, with significant impacts in finance, including financial markets, services, and the global financial system more broadly. The Brazilian Workshop on Artificial Intelligence in Finance (BWAIF), which will have its second edition as a satellite event of the XLIII Congress of the Brazilian Computer Society, will be a forum for researchers, professionals, educators and students to present and discuss innovations, trends, experiences and evolution in the fields of Artificial Intelligence and its applications in Finance. BWAIF will take place as a Satellite event of the SBC Congress, whose theme in 2023 is the "Opportunities and challenges of the integration of the physical and digital worlds", has a huge relationship with the development of a society that uses digital resources for financial transactions, where large institutions have focused part of their resources for the development of "phygital" platforms, which implies the convergence of actions in the physical, digital and social aspects of organizations. Although being an event of the Brazilian Computer Society conference, with papers being accepted in English and Portuguese, we encourage the participation of the international community, with main presentations in English. The conference will be held in person, in Jo?o Pessoa, a beautiful beach city on the Atlantic coast, the capital of the Brazilian state of Paraiba. Being founded more than 400 years ago, it has many architectural and natural monuments, with brightly painted art nouveau architecture that hints at the city?s creative tradition. A powerful coastal sunshine keeps beaches bustling year-round in Joao Pessoa, with bars, restaurants, coconut palms, and a broad promenade along the seafront. TOPICS OF INTEREST It is of interest all studies that have not been published previously and that present new ideas, discussions about existing works, practical studies and experiments relevant to the application of Artificial Intelligence in the financial area. Topics of interest include, but are not limited to: - AI and Cryptocurrencies - AI techniques for financial decision making - AI techniques for financial forecasting - AI techniques for Portfolio analysis - AI techniques for simulation of markets, economies, and other financial systems - AI techniques for risk assessment and management - Computational game-theoretic analysis of financial scenarios - Ethics and fairness of AI in finance - Explainability, interpretability and trustworthiness of AI in finance - Infrastructure to support AI research in finance - Multi-agent systems in finance - Natural Language Processing and its applications in finance - Robustness, security, and privacy of AI systems in finance - Computational regulation and compliance in finance - Robustness and uncertainty quantification for AI models in finance - Synthetic Data and benchmarks for AI pipelines for financial applications - Trading algorithms The best papers published at the event will be invited for a fast-track submission for publication in the REGE - Journal of Management (https://www.revistas.usp.br/rege), which is classified by CAPES as A2 in Engineering III and IV, Economics, and Administration. ARTICLE FORMAT AND SUBMISSION Articles are limited to twelve (12) pages, including text, references, appendices, tables, and figures. Articles must have a summary of a maximum of 300 words in addition to the key words. Articles can be written in Portuguese or English, using the SBC article style, available at: http://www.sbc.org.br/documentos-da-sbc/summary/169-templates-para-artigos-e-capitulos-de-livros/878-modelosparapublicaodeartigos. It is also available at Overleaf: https://pt.overleaf.com/latex/templates/sbc-conferences-template/blbxwjwzdngr. Works written in Portuguese must have a title, abstract and key words in English. Submissions must be made online using the JEMS system: https://jems.sbc.org.br/bwaif2023. The review process will be double-blind (names and institutions of the authors should be omitted in the articles). All papers submitted will be reviewed by at least two experts in the field. The authors of the accepted papers will be invited to present their papers in an oral presentation or in a poster session. All accepted papers will be published electronically, with DOI, in SBC's Open Library, SOL: http://sol.sbc.org.br. IMPORTANT DATES - DEADLINE EXTENDED - Deadline for submission of papers: March 20th, 2023. - Results: May 5th, 2023. - Camera-ready submission: May 16th, 2023. - Authors' registration: May 16th, 2023. AUTHORS' REGISTRATION For an accepted article to be presented and included in the events, it is necessary that at least one of the authors of the article register in the event in the professional category. Each entry in the professional category entitles to the publication of a single article, considering any of the Full SBC Conference base events or satellite events. Authors with more than one article approved at any CSBC event must pay a "publishing fee" per additional article. The amount of this fee can be seen on the CSBC 2022 registration page. ORGANIZATION General Organisers and the Program Committee: Reinaldo A.C. Bianchi, FEI University Center. Anna Helena Reali Costa, Polytechnic School of the University of S?o Paulo. CONTACT Prof. Dr. Reinaldo A.C. Bianchi - rbianchi at fei.edu.br Esta mensagem, juntamente com qualquer outra informa??o anexada, ? confidencial e protegida por lei. Somente os seus destinat?rios est?o autorizados a us?-la. Se voc? n?o for o destinat?rio, por favor, informe o remetente e, em seguida, apague a mensagem, observando que n?o h? autoriza??o para usar, copiar, armazenar, encaminhar, imprimir ou tomar qualquer a??o baseada no seu conte?do. -------------- next part -------------- An HTML attachment was scrubbed... URL: From michael.furlong at uwaterloo.ca Wed Mar 1 12:58:08 2023 From: michael.furlong at uwaterloo.ca (Michael Furlong) Date: Wed, 1 Mar 2023 17:58:08 +0000 Subject: Connectionists: [Meetings] Deadline reminder: 2023 Nengo Summer School Call For Applications Message-ID: Dear colleagues, Please note that the deadline for application submission to the Nengo Summer School, March 15th, 2023, is approaching. [All details about this school can be found online at https://www.nengo.ai/summer-school] The Centre for Theoretical Neuroscience at the University of Waterloo is excited to announce our 8th annual Nengo summer school on large-scale brain modelling and neuromorphic computing. This two-week school will teach participants to use the Nengo simulation package to build state-of-the-art cognitive and neural models to run both in simulation and on neuromorphic hardware. Summer school participants will be given on-site access to neuromorphic hardware and will learn to run high-level applications using Nengo! More generally, Nengo provides users with a versatile and powerful environment for designing cognitive and neural systems and has been used to build what is currently the world's largest functional brain model, Spaun, which includes spiking deep learning, reinforcement learning, adaptive motor control, and cognitive control networks. For a look at the last in-person summer school, check out this short video: https://youtu.be/5w0BzvNOypc We welcome applications from all interested graduate students, postdocs, professors, and industry professionals with a relevant background. ***Application Deadline: March 15, 2023*** Format: A combination of tutorials and project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on testing hypotheses, modeling neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or providing a proof-of-concept of various neural mechanisms. Hands-on tutorials, work on individual or group projects, and talks from invited faculty members will make up the bulk of day-to-day activities. A project demonstration event will be held on the last day of the school, with prizes for strong projects! Participants will have the opportunity to learn how to: * interface Nengo with various kinds of neuromorphic hardware (e.g. Loihi 1, SpiNNaker) * build perceptual, motor, and sophisticated cognitive models using spiking neurons * model anatomical, electrophysiological, cognitive, and behavioural data * use a variety of single cell models within a large-scale model * integrate machine learning methods into biologically oriented models * interface Nengo with cameras and robotic systems * implement modern nonlinear control methods in neural models * and much more? Date and Location: June 4th to June 16th, 2023 at the University of Waterloo, Ontario, Canada. Applications: Please visit http://www.nengo.ai/summer-school, where you can find more information regarding costs, travel, lodging, along with an application form listing required materials. If you have any questions about the school or the application process, please contact Michael Furlong (michael.furlong at uwaterloo.ca). The school is also partly supported by ONR and ABR, Inc. We look forward to hearing from you! -------------- next part -------------- An HTML attachment was scrubbed... URL: From amir.kalfat at gmail.com Wed Mar 1 14:10:20 2023 From: amir.kalfat at gmail.com (Amir Aly) Date: Wed, 1 Mar 2023 19:10:20 +0000 Subject: Connectionists: Available Ph.D. Position in Autism Diagnosis with AI / Human-Robot Interaction Message-ID: Dear All, *Apologies for cross-posting* We are pleased to announce an opportunity for a funded tax-free Ph.D. studentship about (*Multimodal AI-based diagnosis of Autism Spectrum Disorder*) at the Center for Robotics and Neural Systems (CRNS) at Plymouth University, UK. The closing date for applications is *12 noon on 10 March 2023*. *Strong candidates will be waived all fees of the doctoral college*. The main objective of this project is to (1) develop a multimodal deep learning model that can learn from features characterizing the behavior of persons with ASD to assist in accurate diagnosis. To this end, the other objectives are; (2) conduct experiments to collect multimodal data (e.g., visual and audio data, social signals, and EEG measures) during interaction with peers, professionals, and social robots to study the effects of using multimodal data on ASD diagnosis, and to investigate the inter-relationships between features in different modalities, and (3) investigate features that characterize severity levels on the autism spectrum (from mild to severe levels) (*more details and research questions are available in the link below*). More details *about the topic *or *how to apply *are available at: https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/postgraduate-research-studentships/multimodal-ai-based-diagnosis-of-autism-spectrum-disorder-asd Multimodal AI-based diagnosis of Autism Spectrum Disorder (ASD) PhD postgraduate research studentship: Multimodal AI-based Diagnosis of Autism Spectrum Disorder (ASD). Applications are invited for a 3.5-year PhD... www.plymouth.ac.uk If you have any questions, please don't hesitate to contact me, Regards ---------------- *Dr. Amir Aly* Lecturer in Artificial Intelligence and Robotics Center for Robotics and Neural Systems (CRNS) School of Engineering, Computing, and Mathematics Room A307 Portland Square, Drake Circus, PL4 8AA University of Plymouth, UK -------------- next part -------------- An HTML attachment was scrubbed... URL: From zitao.jerry.liu at gmail.com Wed Mar 1 10:23:31 2023 From: zitao.jerry.liu at gmail.com (Zitao Liu) Date: Wed, 1 Mar 2023 23:23:31 +0800 Subject: Connectionists: [Deadline Extended!!!] Call for Industry and Innovation Track Papers - The 24th International Conference on Artificial Intelligence in Education (AIED 2023) Message-ID: Call for Industry and Innovation Track Papers - The 24th International Conference on Artificial Intelligence in Education (AIED 2023) The new deadline is *March 10, 2023* -------------------- *Connecting Research And Educational Practice* -------------------- Intelligent, adaptive learning technologies that implement recent advances from AI are becoming more widespread in real-world use. However, there are still challenges involving the development, evaluation, and adoption of AIED innovations that support inclusive and equitable education and promote lifelong learning opportunities for all. The Industry and Innovation Track is intended to support connections between industry (both for-profit and nonprofit) and the research community and to share experiences about how to bridge the gap between research and innovation in the field of AI and education. We welcome submissions discussing educational technologies at different stages of development, from prototypes being tested in academia or industry to deployed applications. Submissions should address the theme of the conference theme, ?AI in Education for Sustainable Society.? For industry participants, this is an opportunity to learn about some of the most promising new developments in AIED, to present their findings, to connect with academic and industry partners and to recruit some of the most competent and creative talents in the field. For those in the research community, this is a chance to present their solutions/results and build connections that may result in the commercialization and wide distribution of new technologies. This track is a good opportunity for industry and community members to provide and receive feedback on their projects and approaches. In addition, we are organizing a panel with several invited AIED speakers from industry and academia who will discuss issues relevant to the goals of the Industry and Innovations track and the conference. -------------------- *Evaluation Criteria* -------------------- All submissions will be reviewed by the program committee to meet rigorous academic standards of publication. The review process will be double-blind, meaning that both the authors and reviewers will remain anonymous. To this end, authors should: (a) eliminate all information that could lead to their identification (names, contact information, affiliations, patents, names of approaches, frameworks, projects and/or systems); (b) cite own prior work (if needed) in the third person; and (c) eliminate acknowledgments and references to funding sources. Papers will be reviewed for relevance, novelty, technical soundness, significance and clarity of presentation. It is important to note that the work presented should not have been published previously or be under consideration in other conferences of journals. Any paper caught in double submission will be rejected without review. Papers will be evaluated using the following criteria: appropriateness to the goals of the Industry and Innovation track, innovation, technical quality, and potential impact. Submissions are expected to address the conference theme, ?AI in Education for Sustainable Society.? -------------------- *Format and Content* -------------------- Accepted papers will be presented as presentations in the industry and innovation track. We strongly recommend the authors to include a section about how and/or if they address the gap between research and practical innovation. -------------------- *Submission Instructions* -------------------- All submissions must be in Springer format. Papers that do not use the required format may be rejected without review. Authors should consult Springer's authors? guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. Submissions are handled via EasyChair: https://easychair.org/conferences/?conf=aied23 Accepted AIED 2023 papers for the Industry and Innovation track will be published by Springer Communications in Computer and Information Science (CCIS ). Paper lengths for the Industry and Innovation track submissions are as follows: Full papers (12 pages including references; for a long oral presentation) Short papers (6 pages including references; for a short oral presentation) -------------------- *Important Dates* -------------------- Industry and Innovation Track submission: Feb 28, 2023 *March 10, 2023* Notification of decisions: April 3, 2023 Camera-ready version: May 1, 2023 -------------------- *Industry & Innovation Chairs* -------------------- If you have any further question, please, contact the Industry and Innovation Co-chairs: Zitao Liu, Guangdong Institute of Smart Education, Jinan University, China ( liuzitao at jnu.edu.cn) Diego Zapata Rivera, Educational Testing Service, Princeton, USA ( dzapata at ets.org) Dr. Zitao Liu | http://www.zitaoliu.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From info at icas.cc Thu Mar 2 03:11:00 2023 From: info at icas.cc (ICAS Organizing Committee) Date: Thu, 2 Mar 2023 09:11:00 +0100 Subject: Connectionists: 1st CfP ACAIN 2023 - 3rd Int. Advanced Course & Symposium on Artificial Intelligence & Neuroscience, September 22-26, 2023, The Wordsworth Hotel & SPA, Grasmere, Lake District, England - UK In-Reply-To: References: Message-ID: _______________________________________________________________ Call for Participation & Call for Papers (apologies for multiple copies) The 3rd International Advanced Course & Symposium on Artificial Intelligence & Neuroscience September 22-26, 2023 The Wordsworth Hotel & SPA, Grasmere, Lake District, England - UK W: https://acain2023.icas.cc E: acain at icas.cc FB: https://www.facebook.com/ACAIN.LakeDistrict/ Early Registration (Symposium & Course): by May 31 https://acain2023.icas.cc/registration/ PAPER SUBMISSION DEADLINE (Symposium): by March 31 https://acain2023.icas.cc/symposium-call-for-papers/ https://easychair.org/conferences/?conf=acain2023 SCOPE & MOTIVATION: ACAIN 2023: AI meets Computational Neuroscience and Cognitive Science The ACAIN 2023 symposium and course is an interdisciplinary event featuring leading scientists from AI and Neuroscience, providing a special opportunity to learn about cutting-edge research in the fields of AI, Neuroscience, Neuroscience-Inspired AI, Human-Level AI, and Cognitive Science. The 3rd Advanced Course and Symposium on Artificial Intelligence & Neuroscience (ACAIN) is a full-immersion four-day Course and Symposium at the The Wordsworth Hotel & SPA in Grasmere ? Lake District, England - UK on cutting-edge advances in Artificial Intelligence and Neuroscience with lectures delivered by world-renowned experts. The Course provides a stimulating environment for academics, early career researchers, Post-Docs, PhD students and industry leaders. Participants will also have the chance to present their results with oral talks or posters, and to interact with their colleagues, in a convivial and productive environment. Two days of keynote talks and oral presentations, the ACAIN Symposium, (September 25-26), will be preceded by lectures of leading scientists, the ACAIN Course, (September 22-24). Bringing together AI and neuroscience promises to yield benefits for both fields. The future impact and progress in both AI and Neuroscience will strongly depend on continuous synergy, exchange, collaboration and efficient cooperation between the two research communities. These are the goals of the International Course and Symposium ? ACAIN 2023, which is aimed both at AI experts with interests in Neuroscience and at neuroscientists with an interest in AI. ACAIN 2023 accepts rigorous research that promotes and fosters multidisciplinary interactions between artificial intelligence and neuroscience. The Advanced Course is suited for scholars, academics, early career researchers, Post-Docs, PhD students and industry leaders. The Event (Course and Symposium) will involve a total of 36-40 hours of lectures. Academically, this will be equivalent to 8 ECTS points for the PhD Students and the Master Students attending the Event. COURSE DESCRIPTION: https://acain2023.icas.cc/course-description/ LECTURERS: https://acain2023.icas.cc/course-lecturers/ Aldo Faisal, Imperial College London Karl Friston, University College London Kenneth Harris, University College London Rosalyn Moran, King's College London Edmund Rolls, University of Oxford Michael Wooldridge, University of Oxford More Speakers to be announced soon! SYMPOSIUM CALL FOR PAPERS: https://acain2023.icas.cc/symposium-call-for-papers/ SYMPOSIUM PROGRAM COMMITTEE (partial list, confirmed members): https://acain2023.icas.cc/program-committee/ Submission site: https://easychair.org/conferences/?conf=acain2023 DEADLINES: https://acain2023.icas.cc/deadlines/ Paper Submission (Symposium): by Friday March 31, 2023 (AoE). Notification of Decision for Papers (Symposium): by Monday May 15, 2023. Camera Ready Submission: by Thursday May 25. Oral/Poster Presentation Submission (Course): by Friday March 31, 2023. Notification of Decision for Oral/Poster Presentation (Course): by Monday May 15, 2023. Early Registration (Symposium & Course): by Wednesday May 31, 2023. Late Registration (Symposium & Course): from Thursday June 1, 2023. ORGANIZING COMMITTEE: https://acain2023.icas.cc/symposium-committee/ VENUE & ACCOMMODATION: https://acain2023.icas.cc/venue/ The Wordsworth Hotel & Spa (****) Address: Grasmere, Ambleside, Lake District, Cumbria, LA22 9SW, England, UK P: +44-1539-435592 E: reception at thewordsworthhotel.co.uk W: www.thewordsworthhotel.co.uk You need to book your accommodation at the venue and pay the amount for accommodation, meals directly to the Wordsworth Hotel & SPA. The Form for accommodation, all meals (all breakfasts, lunches, dinners): TBA ACCOMMODATION: https://acain2023.icas.cc/accommodation/ ACTIVITIES: https://acain2023.icas.cc/activities/ WALKS: https://acain2023.icas.cc/walks/ REGISTRATION: https://acain2023.icas.cc/registration/ See you in Lake District in September! ACAIN 2023 Organizing Committee. POSTER: https://acain2023.icas.cc/wp-content/uploads/sites/24/2023/01/ACAIN-2023-poster.png E: acain at icas.cc W: https://acain2023.icas.cc/ FB: https://www.facebook.com/ACAIN.LakeDistrict -- *6th Advanced Course on Data Science & Machine Learning - ACDL2023* 10-14 June Riva del Sole Resort & SPA, Castiglione della Pescaia (Grosseto) ? Tuscany, Italy An Interdisciplinary Course: Big Data, Deep Learning & AI without Borders *Early Registration: by Feb 23 (AoE)* W: https://acdl2023.icas.cc/ E: acdl at icas.cc FB: https://www.facebook.com/groups/204310640474650/ T: https://twitter.com/TaoSciences The Course is equivalent to 8 ECTS points for the PhD Students and the Master Students attending the Course. *9th International Conference on machine Learning, Optimization & Data science ? LOD 2023 *September 22 ? 26, 2023 ? Grasmere, Lake District, England ? UK *Paper Submission Deadline: April 10* lod at icas.cc https://lod2023.icas.cc/ *ACAIN 2023, the* *3rd International Advanced Course & Symposium on Artificial Intelligence & Neuroscience*, September 22 ? 26, 2023 ? Grasmere, Lake District, England ? UK *Paper Submission (Symposium): by Friday March 31 (AoE)* *Early Registration (Symposium & Course): by May 31* W: https://acain2023.icas.cc/ E: acain at icas.cc FB: https://www.facebook.com/ACAIN-Int-Advanced-Course-Symposium-on-AI-Neuroscience-100503321621692/ The Course is equivalent to 8 ECTS points for the PhD Students and the Master Students attending the Course. -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Thu Mar 2 03:06:07 2023 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Thu, 2 Mar 2023 10:06:07 +0200 Subject: Connectionists: Live e-Lecture by Prof. Giuseppe Attardi: "Large Language Models are All You Need", 14 March 2023, 17:00 -18:00 CET References: <141c01d8c8cf$64468bc0$2cd3a340$@csd.auth.gr> <00e301d8c9b4$b9e74f70$2db5ee50$@csd.auth.gr> <01bb01d8d3c7$e30ad440$a9207cc0$@csd.auth.gr> <004301d8d3df$32189830$9649c890$@csd.auth.gr> <01f801d90491$e300a6a0$a901f3e0$@csd.auth.gr> <005601d9049a$e6235450$b269fcf0$@csd.auth.gr> <0be601d93d20$8e207580$aa616080$@csd.auth.gr> <00b601d93d24$03426460$09c72d20$@csd.auth.gr> <151301d94c22$3d162200$b7426600$@csd.auth.gr> <00a001d94c25$1900e410$4b02ac30$@csd.auth.gr> Message-ID: <184001d94cdd$d8a5fae0$89f1f0a0$@csd.auth.gr> Dear AI scientist/engineer/student/enthusiast, Prof. Giuseppe Attardi, a prominent AI researcher internationally, will deliver the e-lecture: ?Large Language Models are All You Need?, on March 14th, 2023 17:00 -18:00 CET, see details in: http://www.i-aida.org/ai-lectures/ You can join for free using the zoom link: link & Password: 148148 Attendance is free. The International AI Doctoral Academy (AIDA), a joint initiative of the European R&D projects AI4Media, ELISE, Humane AI Net, TAILOR, VISION, currently in the process of formation, is very pleased to offer you top quality scientific lectures on several current hot AI topics. Lectures will be offered alternatingly by: Top highly-cited senior AI scientists internationally or Young AI scientists with promise of excellence (AI sprint lectures) These lectures are disseminated through multiple channels and email lists (we apologize if you received it through various channels). If you want to stay informed on future lectures, you can register in the email lists AIDA email list and CVML email list. Best regards Profs. N. Sebe, M. Chetouani, P. Flach, B. O?Sullivan, I. Pitas, , J. Stefanowski Post scriptum: To stay current on CVMl matters, you may want to register to the CVML email list, following instructions in https://lists.auth.gr/sympa/info/cvml -------------- next part -------------- An HTML attachment was scrubbed... URL: From eafsousa at gmail.com Thu Mar 2 08:05:47 2023 From: eafsousa at gmail.com (Emanuel Sousa) Date: Thu, 2 Mar 2023 13:05:47 +0000 Subject: Connectionists: Invitation to contribute to Frontiers in Robotics and AI journal Message-ID: Dear colleagues, We cordially invite you and your co-authors to publish your next research article or comprehensive review in the Frontiers in Robotics and AI journal, Research topic on "Advances in Robot Learning-from-Demonstration for Smart Manufacturing Applications". This Research Topic aims to provide a forum for engineers, data scientists, researchers, and practitioners to present innovative research related to algorithms and methods supporting ?Robot Learning-from-Demonstration? systems and frameworks concerning intelligent manufacturing processes. It covers all aspects of the field, from advances in more traditional low-level trajectory demonstration to high-level task understanding and goal inference that "mimics" human intelligent learning, allowing to improve synergistic human-robot collaboration. Review articles and innovative works on performance evaluation and benchmark datasets are also solicited. Potential topics of interest include, but are not limited to the following: - Learning by observation - One-shot learning - Collaborative robot learning - Active learning for manufacturing - Kinesthetic teaching - Efficient data labeling - Semantic scene understanding - Transfer learning algorithms in smart manufacturing - Knowledge generalization - Robotics-based digital twins - Human-robot interfaces The submission deadlines are: - Abstract: 31 March 2023 - Manuscript: 31 July 2023 More details on this special issue can be found at: https://www.frontiersin.org/research-topics/51387/advances-in-robot-learning-from-demonstration-for-smart-manufacturing-applications Looking forward to your contribution. Kind regards, Miguel Angel Guevara Lopez, Polytechnic Institute of Set?bal, Portugal Teresa Gon?alves, University of ?vora, Portugal Estela Bicho, University of Minho, Portugal Manuel Gra?a, University of the Basque Country, Spain Emanuel Sousa, Center for Computer Graphics, Portugal -------------- next part -------------- An HTML attachment was scrubbed... URL: From timofte.radu at gmail.com Thu Mar 2 06:03:28 2023 From: timofte.radu at gmail.com (Radu Timofte) Date: Thu, 2 Mar 2023 12:03:28 +0100 Subject: Connectionists: [CFP] CVPR 2023 New Trends in Image Restoration and Enhancement (NTIRE) workshop and challenges Message-ID: Apologies for multiple postings *********************************** CALL FOR PAPERS & CALL FOR PARTICIPANTS IN 13 CHALLENGES NTIRE: 8th New Trends in Image Restoration and Enhancement workshop and challenges. In conjunction with CVPR 2023, June 18, Vancouver, Canada. Website: https://cvlai.net/ntire/2023/ Contact: radu.timofte at uni-wuerzburg.de TOPICS ? Image/video inpainting ? Image/video deblurring ? Image/video denoising ? Image/video upsampling and super-resolution ? Image/video filtering ? Image/video de-hazing, de-raining, de-snowing, etc. ? Demosaicing ? Image/video compression ? Removal of artifacts, shadows, glare and reflections, etc. ? Image/video enhancement: brightening, color adjustment, sharpening, etc. ? Style transfer ? Hyperspectral image restoration, enhancement, manipulation ? Underwater image restoration, enhancement, manipulation ? Light field image restoration, enhancement, manipulation ? Methods robust to changing weather conditions / adverse outdoor conditions ? Image/video restoration, enhancement, manipulation on constrained settings/mobile devices ? Visual domain translation ? Multimodal translation ? Perceptual enhancement ? Perceptual manipulation ? Depth estimation ? Image/video generation and hallucination ? Image/video quality assessment ? Image/video semantic segmentation ? Saliency and gaze estimation ? Studies and applications of the above. SUBMISSION A paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in CVPR style. https://cvpr2023.thecvf.com/Conferences/2023/AuthorGuidelines The review process is double blind. Accepted and presented papers will be published after the conference in the 2023 CVPR Workshops Proceedings. Author Kit: https://media.icml.cc/Conferences/CVPR2023/cvpr2023-author_kit-v1_1-1.zip Submission site: https://cmt3.research.microsoft.com/NTIRE2023 WORKSHOP DATES ? *Regular Papers submission deadline: March 10, 2023* *(EXTENDED)* ? Challenge Papers submission deadline: March 31, 2023 ? *Papers reviewed elsewhere submission deadline: March 31, 2023* CHALLENGES 1. *HR Non-Homogeneous Dehazing* 2. *Night Photography Rendering * 3. *Real-Time Super-Resolution* 4. *Bokeh Effect Transformation * 5. *360? Omnidirectional Super-Resolution * 6. *Super-Resolution* 7. *Light Field Super-Resolution* 8. *Stereo Super-Resolution* 9. *Quality Assessment for Video Enhancement* 10. *Shadow Removal* 11. *Denoising* 12. *HR Depth Estimation* 13. *Colorization * To learn more about the challenges, to participate in the challenges, and to access the data everybody is invited to check the NTIRE 2023 web page: https://cvlai.net/ntire/2023/ For those interested in constrained and efficient solutions validated on mobile devices we refer to the *CVPR23 Mobile AI Workshop and Challenges:* https://ai-benchmark.com/workshops/mai/2023/ CHALLENGES DATES *? *Release of train data: January 30, 2023 ? *Competitions end: March 20, 2022* Website: https://cvlai.net/ntire/2023/ Contact: radu.timofte at uni-wuerzburg.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From mtkostecki at gmail.com Thu Mar 2 10:03:25 2023 From: mtkostecki at gmail.com (Mateusz Kostecki) Date: Thu, 2 Mar 2023 16:03:25 +0100 Subject: Connectionists: Deadline soon: School of Ideas in Neuroscience 2023 Message-ID: Hello! There are only 6 days left to apply for Nencki School of Ideas in Neuroscience - *https://nenckiopenlab.org/school-of-ideas-2023/ .* It is often said that neuroscience desperately needs ideas. We are flooded by data and it is harder and harder to make sense of it. But, at the same time, most courses and workshops in neuroscience teach us experimental techniques, giving us more tools to gather even more data. But we are not taught how to develop ideas. We believe that theoretical thinking and idea development is a skill ? a skill that can be trained and developed. Our school will aim at teaching how to develop theoretical thinking, how to create ideas, and put their research in a broader context. We want you to learn how to make sense of data. In the *first section, selected theoretical frameworks* serves us as examples ? together with their authors, we discuss how different theoretical frameworks can be applied to empirical research ? but we also trace how they were developed. In the *metatheory section*, together with philosophers and historians of science, we look at how ideas were and are developed, and what factors foster their evolution. In the* thinking tools section*, we try to teach our participants how to think theoretically by building models, transgressing borders of their discipline, think creatively and critically ? and how to find time to think. Our guests are *John Krakauer, Adrienne Fairhall, Luiz Pessoa, Nedah Nemati, Pamela Lyon, Aikaterini Fotopoulou, Carina Curto, Kate Nave, Gregory Kohn, Antonella Tramacere, Marcin Mi?kowski, Wiktor M?ynarski.* Please find more info and the registration form here - *https://nenckiopenlab.org/school-of-ideas-2023/ * See you in Warsaw! 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URL: From cgf at isep.ipp.pt Thu Mar 2 11:31:03 2023 From: cgf at isep.ipp.pt (Carlos) Date: Thu, 2 Mar 2023 16:31:03 +0000 Subject: Connectionists: Discovery Science (DS 2023) - CFP Message-ID: <088e8e6b-1314-2d59-17e9-d40063d2f5a4@isep.ipp.pt> -------------------------------------------------------------------------------- Please distribute (Apologies for cross posting) -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- CALL FOR PAPERS DS 2023 Discovery Science Conference Website link: https://ds2023.inesctec.pt/ October 9-11, 2023, Porto, Portugal -------------------------------------------------------------------------------- Special Issue -------------------------------------------------------------------------------- The authors of a number of selected papers presented at DS 2023 will be invited to submit extended versions of their papers for possible inclusion in a special issue of Machine Learning journal (published by Springer) on Discovery Science. Fast-track processing will be used to have them reviewed and published. -------------------------------------------------------------------------------- Award -------------------------------------------------------------------------------- There will be a Best Student Paper Award in the value of 555 Eur sponsored by Springer. -------------------------------------------------------------------------------- Aims and Scope -------------------------------------------------------------------------------- Discovery Science 2023 conference provides an open forum for intensive discussions and exchange of new ideas among researchers working in the area of Discovery Science. The conference focus is on the use of artificial intelligence methods in science. Its scope includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, and big data analytics, as well as their application in various domains. Possible topics include, but are not limited to: -Artificial intelligence (machine learning, knowledge representation and reasoning, natural language processing, statistical methods, etc.) applied to science -Machine learning: supervised learning (including ranking, multi-target prediction and structured prediction), unsupervised learning, semi-supervised learning, active learning, reinforcement learning, online learning, transfer learning, etc. -Knowledge discovery and data mining -Causal modeling -AutoML, meta-learning, planning to learn -Machine learning and high-performance computing, grid and cloud computing -Literature-based discovery -Ontologies for science, including the representation and annotation of datasets and domain knowledge -Explainable AI, interpretability of machine learning and deep learning models -Process discovery and analysis -Computational creativity -Anomaly detection and outlier detection -Data streams, evolving data, change detection, concept drift, model maintenance -Network analysis -Time-series analysis -Learning from complex data -Graphs, networks, linked and relational data -Spatial, temporal and spatiotemporal data -Unstructured data, including textual and web data -Multimedia data -Data and knowledge visualization -Human-machine interaction for knowledge discovery and management -Evaluation of models and predictions in discovery setting -Machine learning and cybersecurity -Applications of the above techniques in scientific domains, such as -Physical sciences (e.g., materials sciences, particle physics) -Life sciences (e.g., systems biology/systems medicine) -Environmental sciences -Natural and social sciences -------------------------------------------------------------------------------- Important Dates -------------------------------------------------------------------------------- Abstract submission (deadline): May 27, 2023 Full paper submission (deadline): Jun 3, 2023 Notification of acceptance: July 21, 2023 Camera ready version, author registration: August 6, 2023 All dates are specified as 23:59:59 SST (Standard Samoa Time / Anywhere on Earth) -------------------------------------------------------------------------------- Submission procedure -------------------------------------------------------------------------------- Contributions, written in English, must be formatted according to the guidelines of the Lecture Notes of Computer Science (LNCS) series by Springer-Verlag, which are available together with templates here: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines. We strongly recommend using the LNCS template for LaTeX. The page limit for any contribution, including figures, title pages, references, and appendices, is 10-12 pages in LNCS format. Submission of the camera-ready version of the paper has to include the authors? consent to publish on the above Springer LNCS website. Authors may not submit any paper which is under review elsewhere or which has been accepted for publication in a journal or another conference; neither will they submit their papers elsewhere during the review period of DS? 2023. Submission System link: https://cmt3.research.microsoft.com/DS2023 Conference Management Toolkit - Login cmt3.research.microsoft.com Microsoft's Conference Management Toolkit is a hosted academic conference management system. Modern interface, high scalability, extensive features and outstanding support are the signatures of Microsoft CMT. -------------------------------------------------------------------------------- Venue -------------------------------------------------------------------------------- DS 2023 will be held in October 9-11, 2023 in Porto, Portugal. The conference will take place in Sheraton Hotel, Porto, Portugal. -------------------------------------------------------------------------------- Organizing Committee -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- General Chairs -------------------------------------------------------------------------------- Jo?o Gama - University of Porto, Portugal Pedro Henriques Abreu ? University of Coimbra, Portugal -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- Program Chairs -------------------------------------------------------------------------------- Albert Bifet - University of Waikato, New Zealand Ana Carolina Lorena ? Aeronautics Institute of Technology, Brazil Rita P. Ribeiro ? University of Porto, Portugal -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- Steering Committee Chair -------------------------------------------------------------------------------- Saso Dzeroski ? Jozef Stefan Institute, Slovenia -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- Publicity Chair -------------------------------------------------------------------------------- Carlos Abreu Ferreira ? Polytechnic Institute of Porto, Portugal Ricardo Cerri ? Federal University of S?o Carlos, Brazil Wenbin Zhang ? University of Michigan Technological, USA -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- Local Organization Committee -------------------------------------------------------------------------------- Bruno Veloso ? University Portucalense, Portugal Joana Cristo Santos ? University of Coimbra, Portugal Jos? Pereira Amorim ? University of Coimbra, Portugal Miriam Seoane Santos ? University of Coimbra, Portugal Ricardo Cardoso Pereira ? University of Coimbra, Portugal -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- Contacts -------------------------------------------------------------------------------- Organizing Committee Contact Person: Pedro Henriques Abreu - University of Coimbra, Portugal ? pha at dei.uc.pt -------------------------------------------------------------------------------- Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. Ant?nio Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail at isep.ipp.pt | www.isep.ipp.pt From dao at nict.go.jp Fri Mar 3 04:06:18 2023 From: dao at nict.go.jp (dao at nict.go.jp) Date: Fri, 03 Mar 2023 18:06:18 +0900 Subject: Connectionists: [CfP][Deadline Extended] The fourth ICDAR Workshop, ICMR2023 In-Reply-To: <20230213073406.00001BDE.0344@nict.go.jp> References: <20230213073406.00001BDE.0344@nict.go.jp> Message-ID: <20230303090618.00004A90.0459@nict.go.jp> ICMR 2023 4th Workshop on Intelligent Cross-Modal Analysis and Retrieval The fourth ICDAR Workshop, ICMR2023 https://www.xdata.nict.jp/icdar_icmr2023/index.html The deadline has been extended to* March 10, 2023* Data plays a critical role in human life. In the digital era, where data can be collected almost anywhere and at any time, people have access to a vast volume of real-time data that reflects their living environment in different ways. People can extract necessary information from these data to gain knowledge and become wiser. However, data often comes from multiple sources and only reflects a small part of the big puzzle of life. Despite potentially missing some pieces, the goal is to capture the puzzle's image with the available pieces. The more pieces of data we can collect and assemble within a given frame, the faster we can solve the puzzle. The challenge becomes even greater when dealing with multimodal data, cross-domain and cross-platform problems. A multimodal data puzzle would be one where pieces have different shapes and sizes. A cross-domain puzzle would be one where the pieces come from distinct sub -pictures. Finally, a cross-platform puzzle would be one where the pieces assembled come from different puzzles. But it would help if you combined the pieces in all these scenarios to get the entire picture. Recent research has mainly focused on multimodal data analytics, but only a limited number of studies have been conducted on developing cross -data retrieval systems, where data from one modality is used to infer data from another. Some examples of such research are textual query employed to look for images, such as drawing on lifelogging images to predict the air quality index, weather and tweets data used to predict traffic congestion, and predicting sleeping quality based on daily exercises and meals. The proposed research topic of "Intelligent Cross- Data Analysis and Retrieval" aims to advance the field of cross-data analytics and retrieval and contribute to developing a more intelligent and sustainable society. This workshop welcomes researchers from diverse domains and disciplines, such as well-being, disaster prevention, mitigation, and mobility. Example topics of interest include but is not limited to the following: ? Event-based cross-data retrieval Data mining and AI technology. ? Multimodal complex event processing. Transfer Learning and Transformers. ? Multimodal self-supervised learning Heterogeneous data association discovery. ? Cross-datasets for Repeatable Experimentation. ? Federated Analytics and Federated Learning for cross-data. ? Privacy-public data collaboration. ? Diverse multimodal data Integration. ? Realization of a prosperous and independent region in which people and nature coexist ? Intelligent cross-data analysis applications from different domains We invite the following two types of papers: ? Full Paper: limited to 8 pages, plus additional pages for the list of references: Full Papers should describe the original contents with evaluations. They will be reviewed by more than two experts based on: Originality of the content, Quality of the content, Relevance to the theme, and Clarity of the written presentation ? Short Paper: limited to 4 pages, plus additional pages for the list of references. Short papers should describe work in progress as position papers. They will be reviewed by two experts based on: Originality of the content, Relevance to the theme, and Clarity of the written presentation Important dates: ? 10 March 2023 (Extended): Workshop Paper Submission. ? 31 March 2023: Workshop Paper Acceptance Notification. ? 20 April 2023: Workshop Camera-ready Submission / Copyright Submission Deadline. ? TBA: Workshops Day. From angelo.cangelosi at manchester.ac.uk Fri Mar 3 05:11:17 2023 From: angelo.cangelosi at manchester.ac.uk (Angelo Cangelosi) Date: Fri, 3 Mar 2023 10:11:17 +0000 Subject: Connectionists: =?utf-8?q?Two_Marie_Sklodowska-Curie_Early_Stage_?= =?utf-8?q?Researcher_in_Robotics_and_AI_=28MSCA_DN_=E2=80=9CTRAIL?= =?utf-8?q?=E2=80=9D=29_-_University_of_Manchester?= Message-ID: <21A43DC3-70C5-422B-B846-C8514E476628@manchester.ac.uk> Two Marie Sklodowska-Curie Early Stage Researcher in Robotics and AI (MSCA DN ?TRAIL?) University of Manchester, UK The University of Manchester, with Department of Computer Science and Centre for Robotics and AI, are looking for applications for 2 Doctoral Candidate Researchers in the topic of Robotics and AI. These are PhD student positions with an MSCA Early Stage Researcher (ESR) contract. The positions are part of the new Horizon Europe project: TRAIL - TRAnsparent InterpretabLe robots (Doctoral Network, EU MSCA Project). The EU Doctoral Network TRAIL consists of 15 institutions including universities, research institutions and industry partners. The research area of TRAIL is neural network technology, intelligent robotics and transparency in artificial intelligence. The focus of the research at the University of Manchester will be on neural networks models of language and trust in robots, within Angelo Cangelosi?s Cognitive Robotics Lab. The Manchester ESR researchers will focus on the following topics:??????? PhD Position 1: Interactive language explanations for trust in human-robot communication PhD Position 2: Transparent and grounded communication with abstract language The successful candidate will receive an attractive salary in accordance with the MSCA regulations for Early-Stage Researchers. The salary includes a living allowance, a mobility allowance and a family allowance (if applicable). Furthermore, TRAIL will offer to take advantage of joint scientific research trainings, transferable skills workshops, and international conferences. For more information about the project and consortium see For Informal enquiries, email: angelo.cangelosi at manchester.ac.uk Requirements: BSc/MSc or equivalent in Artificial Intelligence, Computer Science or Engineering with a focus on Robotics, AI and/or Neural Networks is required. Excellent programming skills (e.g. Python, C++, Machine Learning Frameworks, ROS etc.) are needed and expertise in at least one of neural networks or intelligent robotics is needed for these positions. According to EU mobility rules, the doctoral researchers must not have resided or carried out their main activity (work, studies, etc.) in the UK for longer than 12 months in the 3 years immediately prior to their recruitment. Applicants who already have a doctoral degree are not eligible. Excellent English communication skills are an important requirement.??????? Start date of PhD: 1 September 2023, for 3 years Application Deadline: 3 April 2023 via the University of Manchester job application link. [metaimage.jpg] Two Marie Sklodowska-Curie Early Stage Researcher in Robotics and AI (MSCA DN ?TRAIL?) : Oxford Road, Manchester jobs.manchester.ac.uk -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: metaimage.jpg Type: image/jpeg Size: 124826 bytes Desc: metaimage.jpg URL: From a.stein at fz-juelich.de Fri Mar 3 09:11:15 2023 From: a.stein at fz-juelich.de (Alexandra Stein) Date: Fri, 3 Mar 2023 15:11:15 +0100 Subject: Connectionists: Call for Satellite Workshop Proposals, Bernstein Conference 2023 in Berlin Message-ID: *Call for Satellite Workshop Proposals, Bernstein Conference 2023 in Berlin* +++ The Bernstein Network Computational Neuroscience invites proposals for Satellite Workshops preceding the Bernstein Conference 2023 in Berlin. +++ ____ BERNSTEIN CONFERENCE Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. It has established itself as one of the most renown conferences worldwide in this field, attracting students, postdocs and PIs from around the world to meet and discuss new scientific discoveries. www.bernstein-conference.de ____ IMPORTANT DATES -Satellite Workshops: September 26 - 27, 2022 oTuesday, Sep 26, 14:00 ? 18:00 CEST oWednesday, Sep 27, 8:30 ? 12:30 CEST -Main Conference: September 27 ? September 29, 202 -***Deadline for Satellite Workshop proposal submission: Wednesday, April 26 at 15:00 CEST* -Notification of workshop acceptance: planned in mid May 2022 Find further information here: https://bernstein-network.de/bernstein-conference/call-for-satellite-workshops/ ____ FINANCIAL SUPPORT Workshop registration is free for all organizers and speakers of workshops. Workshop organizers will additionally receive a waiver for the main conference fee. From the accepted workshops up to ten workshops will be selected to receive financial support of up to 1500 ? each.** ____ For any further questions, please contact: bernstein.conference at fz-juelich.de -- Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum J?lich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany web:www.bernstein-network.de www.bernstein-conference.de Twitter: @BernsteinNeuro Vimeo:https://vimeo.com/bernsteinnetwork LinkedIn: Bernstein Network Computational Neuroscience, Germany -- Dr. Alexandra Stein Head of Bernstein Coordination Site Bernstein Network Computational Neuroscience | Bernstein Coordination Site Branch Office of the Forschungszentrum J?lich at the University of Freiburg Hansastr. 9a | 79104 Freiburg, Germany phone: +49 (0)761 203 9583 mobile: +49 (0)151 67114645 mail:a.stein at fz-juelich.de web:www.bernstein-network.de Twitter: BernsteinNeuro LinkedIn: Bernstein Network Computational Neuroscience, Germany Mastodon:BernsteinNetwork at mastodon.world -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 5924 bytes Desc: S/MIME Cryptographic Signature URL: From elio.tuci at gmail.com Sun Mar 5 09:29:41 2023 From: elio.tuci at gmail.com (Elio Tuci) Date: Sun, 5 Mar 2023 15:29:41 +0100 Subject: Connectionists: One PhD position at University of Namur, Belgium Message-ID: *PhD scholarship within the BABots project, University of Namur, Namur, Belgium* The University of Namur, with Faculty of Computer Science and Robotics Lab ( https://www.naxys.be/robotics/) of the Namur Institute for Complex Systems naXys (www.naxys.be), are looking for applications for 1 Doctoral Candidate Researcher in the topic of Modelling of Collective Behaviour and Swarm Robotics. The position is part of the new Horizon Europe project: BABots ? ?The design and control of small swarming biological animal robots?. BABots is an interdisciplinary collaborative project that promotes an innovative, disruptive technology bases on Biological Animal roBots. BABots are small animals (worms) whose nervous system will be reprogrammed to execute new and useful behaviours. BABots will be designed to perform delicate tasks within miniature complex biological environments. The BABots project, funded by the European Innovation Council (EIC), will be run by an international consortium of experts in neurobiology, synthetic biology, robotics and ethics, together with a commercial partner from the agrotech industry. More information on the project can be found at https://babots.eu/ The position is open to candidate of any nationality who intend to obtain a PhD degree in Science at the University of Namur. The scholarship will be for four years, and is based in Namur, Belgium. The PhD candidate will work under the supervision of prof E. Tuci. The candidate should have a Master degree (equivalent to 120 ETCS credits) in science (or in a field judged equivalent by the selection committee) with solid programming skills (e.g. Python, C++, Machine Learning Frameworks, ROS etc.). Any further experience in mathematical modelling of biological phenomena will be positively evaluated. The candidate should also have and excellent oral/written communication skills in English. French is the official language of the University of Namur. However, knowledge of French is not required to carry out the activities of this project. The selected candidate will be offered a competitive fellowship covering a monthly salary in accordance with the Belgian regulations. PhD degrees in Belgium are generally affordable with low tuition fees. However, this can increase substantially for some international students and for some areas of research. For more information on tuition fees we suggest to contact admission.international at unamur.be To apply for this position, please send by email a CV, a motivation letter (max length one page), and the names of three referees to Prof Elio Tuci elio.tuci at unamur.be The short-listed candidates will be contacted for an interview by videoconference. We will keep on processing applications as soon as we receive them and until a suitable candidate is found. The project starting date is the 01-10-2023. UNamur?s personnel management policy is geared towards diversity and equal opportunities. We recruit candidates on the basis of their skills, irrespective of age, gender, sexual orientation, origin, nationality, beliefs, disability, etc. For further information on the project, you can contact the project coordinators: Prof Elio Tuci ? elio.tuci at unamur.be -------------- next part -------------- An HTML attachment was scrubbed... URL: From michel.verleysen at uclouvain.be Fri Mar 3 11:39:11 2023 From: michel.verleysen at uclouvain.be (Michel Verleysen) Date: Fri, 3 Mar 2023 16:39:11 +0000 Subject: Connectionists: ESANN 2023 - 2nd call for papers and announcement of special sessions Message-ID: ESANN 2023 - 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Bruges (Belgium) and online, 4-5-6 October 2023 https://www.esann.org Call for papers The call for papers is available at https://www.esann.org. Deadline for submissions: May 2, 2023. The ESANN conferences cover machine learning, artificial neural networks, statistical information processing and computational intelligence. Mathematical foundations, algorithms and tools, and applications are covered. In addition to regular sessions, 7 special sessions will be organized on the following topics: - Efficient Learning In Spiking Neural Networks - Quantum Artificial Intelligence - Green Machine Learning - Graph Representation Learning - Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness - Neuro-Symbolic AI: Techniques, Applications, and Challenges - Machine Learning Applied to Sign Language ESANN 2023 builds upon a successful series of conferences organized each year since 1993. ESANN has become a major scientific event in the machine learning, computational intelligence and artificial neural networks fields over the years. The conference will be organized in hybrid mode. In-person participation is preferred, however online participation is possible for those who prefer not to travel. The physical conference will be organized in Bruges, one of the most beautiful medieval towns in Europe. Designated as the "Venice of the North", the city has preserved all the charms of the medieval heritage. Its centre, which is inscribed on the Unesco World Heritage list, is in itself a real open air museum. We hope to receive your submission to ESANN 2023 and to see you in Bruges or online! ======================================================== ESANN - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning http://www.esann.org/ * For submissions of papers, reviews, registrations: Michel Verleysen UCLouvain - Machine Learning Group 3, pl. du Levant - B-1348 Louvain-la-Neuve - Belgium tel: +32 10 47 25 51 - fax: + 32 10 47 25 98 mailto:esann at uclouvain.be * Conference secretariat d-side conference services 24 av. L. Mommaerts - B-1140 Evere - Belgium tel: + 32 2 730 06 11 - fax: + 32 2 730 06 00 mailto:esann at uclouvain.be ======================================================== -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Sun Mar 5 03:10:47 2023 From: david at irdta.eu (David Silva - IRDTA) Date: Sun, 5 Mar 2023 09:10:47 +0100 (CET) Subject: Connectionists: BigDat 2023 Summer: early registration March 7 Message-ID: <1255317040.320560.1678003847381@webmail.strato.com> *********************************************** 7th INTERNATIONAL SCHOOL ON BIG DATA BigDat 2023 Summer Las Palmas de Gran Canaria, Spain July 17-21, 2023 https://bigdat.irdta.eu/2023su *********************************************** Co-organized by: University of Las Palmas de Gran Canaria Institute for Research Development, Training and Advice - IRDTA Brussels/London *********************************************** Early registration: March 7, 2023 *********************************************** FRAMEWORK: BigDat 2023 Summer is part of a multi-event called Deep&Big 2023 consisting also of DeepLearn 2023 Summer. BigDat 2023 Summer participants will have the opportunity to attend lectures in the program of DeepLearn 2023 Summer as well if they are interested. SCOPE: BigDat 2023 Summer will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of big data. Previous events were held in Tarragona, Bilbao, Bari, Timisoara, Cambridge and Ancona. Big data is a broad field covering a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, health, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience. Most big data subareas will be displayed, namely foundations, infrastructure, management, search and mining, analytics, security and privacy, as well as applications to biology and medicine, business, finance, transportation, online social networks, etc. Major challenges of analytics, management and storage of big data will be identified through 14 four-hour and a half courses and 2 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and employment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, BigDat 2023 Summer is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: BigDat 2023 Summer will take place in Las Palmas de Gran Canaria, on the Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a renowned carnival. The venue will be: Instituci?n Ferial de Canarias Avenida de la Feria, 1 35012 Las Palmas de Gran Canaria https://www.infecar.es/ STRUCTURE: 2 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Also, if interested, participants will be able to attend courses developed in DeepLearn 2023 Summer, which will be held in parallel and at the same venue. Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Valerie Daggett (University of Washington), Dynameomics: From Atomistic Simulations of All Protein Folds to the Discovery of a New Protein Structure to the Design of a Diagnostic Test for Alzheimer?s Disease Sander Klous (University of Amsterdam), How to Audit an Analysis on a Federative Data Exchange PROFESSORS AND COURSES: Paolo Addesso (University of Salerno), [introductory/intermediate] Data Fusion for Remotely Sensed Data Marcelo Bertalm?o (Spanish National Research Council), [introductory] The Standard Model of Vision and Its Limitations: Implications for Imaging, Vision Science and Artificial Neural Networks Gianluca Bontempi (Universit? Libre de Bruxelles), [intermediate/advanced] Big Data Analytics in Fraud Detection and Churn Prevention: from Prediction to Causal Inference Altan ?akir (Istanbul Technical University), [introductory/intermediate] Introduction to Distributed Deep Learning with Apache Spark Ian Fisk (Flatiron Institute), [introductory] Setting Up a Facility for Data Intensive Science Analysis Ravi Kumar (Google), [intermediate/advanced] Differential Privacy Wladek Minor (University of Virginia), [introductory/advanced] Big Data in Biomedical Sciences Jos? M.F. Moura (Carnegie Mellon University), [introductory/intermediate] Graph Signal Processing and Geometric Learning Panos Pardalos (University of Florida), [intermediate/advanced] Data Analytics for Massive Networks Ramesh Sharda (Oklahoma State University), [introductory/intermediate] Network-Based Health Analytics Steven Skiena (Stony Brook University), [introductory/intermediate] Word and Graph Embeddings for Machine Learning Mayte Suarez-Farinas (Icahn School of Medicine at Mount Sinai), [intermediate] Meta-Analysis Methods for High-Dimensional Data Ana Trisovic (Harvard University), [introductory/advanced] Reproducible Research, Best Practices and Big Data Management Sebasti?n Ventura (University of C?rdoba), [intermediate] Supervised Descriptive Pattern Mining OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by July 9, 2023. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of big data in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 9, 2023. EMPLOYER SESSION: Organizations searching for personnel well skilled in big data will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the organization and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 9, 2023. ORGANIZING COMMITTEE: Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) David Silva (London, organization chair) REGISTRATION: It has to be done at https://bigdat.irdta.eu/2023su/registration/ The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish as well as eventually courses in DeepLearn 2023 Summer. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions will be available in due time at https://bigdat.irdta.eu/2023su/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. Participants will be recognized 2 ECTS credits by University of Las Palmas de Gran Canaria. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Cabildo de Gran Canaria Universidad de Las Palmas de Gran Canaria - Fundaci?n Parque Cient?fico Tecnol?gico Universitat Rovira i Virgili Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From aripakman at gmail.com Mon Mar 6 02:12:19 2023 From: aripakman at gmail.com (Ari Pakman) Date: Mon, 6 Mar 2023 09:12:19 +0200 Subject: Connectionists: Information Decomposition Workshop, Dresden, June 5-9, 2023 Message-ID: Dear colleagues, We are pleased to inform you about our upcoming workshop on partial information decomposition (PID). The workshop will be called Decomposing Multivariate Information in Complex Systems (DeMICS 23) and will take place during June 5th - 9th, 2023 at the Max Planck Institute for the Physics of Complex Systems (MPI PKS) in Dresden. To participate please apply via the application link on the conference website: https://www.pks.mpg.de/demics23 Please forward this to anyone you consider interested in partial information decomposition, especially if you are unable to attend yourself. Please note the approaching application deadline on March 31st. Applications before this date will be considered preferentially. For successful applicants, meals and accommodation will be provided by the MPI PKS, with a small fee of 140 EUR asked for to cover social dinners, excursion and coffee breaks. We look forward to seeing you in Dresden! Kind regards, Conor Finn Ari Pakman Michael Wibral -------------- next part -------------- An HTML attachment was scrubbed... URL: From Mark.Humphries at nottingham.ac.uk Mon Mar 6 05:56:54 2023 From: Mark.Humphries at nottingham.ac.uk (Mark Humphries) Date: Mon, 6 Mar 2023 10:56:54 +0000 Subject: Connectionists: Postdoc in computational neuroscience/machine learning at the University of Nottingham (UK) In-Reply-To: References: Message-ID: The Humphries? lab at the University of Nottingham is seeking a postdoc to study the neural basis of foraging, in collaboration with the groups of Matthew Apps (Birmingham) and Nathan Lepora (Bristol). Whether choosing to leave one shop for another, switching TV programs, or seeking berries to eat, humans and other animals make innumerable stay-or-leave decisions, but how we make them is not well understood. The goal of this project is to develop new computational accounts of stay-or-leave decisions, and use them to test hypotheses for how humans, primates, and rodents learn and make these decisions. The work will draw on and develop new reinforcement learning and accumulation (e.g. diffusion) models of decision-making. The Humphries? group researches fundamental insights into how the joint activity of neurons encodes actions in the world (https://www.humphries-lab.org). This post will join our developing research program into how humans and other animals learn to make the right decisions (e.g. https://doi.org/10.1101/2022.08.30.505807). The post is until 14th February 2025. Nottingham University welcomes researchers from around the globe. As part of this support, the university will provide financial support to the post-holder for all visa costs. Unsure if you're a good fit for the post? Got any questions? Then contact Mark for a chat: mark.humphries at nottingham.ac.uk. For full details of the role and how to apply https://jobs.nottingham.ac.uk/vacancy.aspx?ref=SCI092323 Closing date: March 30th 2023 This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law. -------------- next part -------------- An HTML attachment was scrubbed... URL: From brais.cancela at udc.es Mon Mar 6 06:40:04 2023 From: brais.cancela at udc.es (Brais Cancela Barizo) Date: Mon, 6 Mar 2023 11:40:04 +0000 Subject: Connectionists: CFP special session on "Green Machine Learning" at ESANN 2023 Message-ID: [Apologies if you receive multiple copies of this CFP] Call for papers:? special session on " Green Machine Learning " at ESANN 2023 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2023)? 4-6 October 2023, Bruges (Belgium) - http://www.esann.org IMPORTANT DATES: Paper submission deadline: 2 May 2023 Notification of acceptance: 16 June 2023 ESANN conference: 4-6 October 2023 Green Machine Learning Homepage: https://www.esann.org/special-sessions#session3 Organized by Ver?nica Bol?n-Canedo, Laura Mor?n-Fern?ndez, Brais Cancela and Amparo Alonso-Betanzos (Universidade da Coru?a, Spain) Emails: veronica.bolon at udc.es, laura.moranf at udc.es, brais.cancela at udc.es , ciamparo at udc.es In the last years we have witnessed the most impressive advances achieved by Artificial Intelligence (AI), in most cases by using deep learning models. However, it is undeniable that deep learning has a huge carbon footprint (a paper from 2019 stated that training a language model could emit nearly five times the lifetime emissions of an average car). The term Green AI refers to AI research that is more environmentally friendly and inclusive, not only by producing novel results without increasing the computational cost, but also by ensuring that any researcher with a laptop has the opportunity to perform high-quality research without the need to use expensive cloud servers. The typical AI research (sometimes referred as Red AI) aims to obtain state-of-the-art results at the expense of using massive computational power, usually through an enormous quantity of training data and numerous experiments. Efficient machine learning approaches (especially deep learning) are starting to receive some attention in the research community. However, the problem is that, most of the time, these works are not motivated by being green. Therefore, it is necessary to encourage the AI community to recognize the value of work by researchers who take a different path, optimizing efficiency rather than only accuracy. Topics such as low-resolution algorithms, edge computing, efficient platforms, and in general scalable and sustainable algorithms and their applications are of interest to complete a holistic view of Green AI. In this special session, we invite papers on both practical and theoretical issues about developing new machine learning that are sustainable and green, as well as review papers with the state-of-art techniques and the open challenges encountered in this field. In particular, topics of interest include, but are not limited to: Developing energy-efficient algorithms for training and/or inference. Investigating sustainable data management and storage techniques. Exploring the use of renewable energy sources for machine learning. Examining the ethical and social implications of green machine learning. Investigating methods for reducing the carbon footprint of machine learning systems. Studying the impact of green machine learning on various industries and applications. Submitted papers will be reviewed according to the ESANN reviewing process and will be evaluated on their scientific value: originality, correctness, and writing style. -------------- next part -------------- An HTML attachment was scrubbed... URL: From benoit.frenay at unamur.be Mon Mar 6 08:42:17 2023 From: benoit.frenay at unamur.be (=?Windows-1252?Q?Beno=EEt_Frenay?=) Date: Mon, 6 Mar 2023 13:42:17 +0000 Subject: Connectionists: =?windows-1252?q?2nd_CFP_-_ML_applied_to_Sign_Lan?= =?windows-1252?q?guage=3A_Special_Session_at_ESANN=9223?= Message-ID: 2Nd Call for papers: special session on "Machine Learning Applied to Sign Language" at ESANN 2023 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2023). 4-6 October 2023, Bruges, Belgium. http://www.esann.org DESCRIPTION: Deep learning has led to spectacular advances in many fields dealing with unstructured data such as computer vision, natural language processing, and data generation. Recently, sign languages have drawn the attention of machine learning practitioners as sign language recognition, translation, and synthesis raise interesting technical challenges and have a clear societal impact. The overarching domain of sign language processing is related to computer vision, natural language processing, computer graphics, and human-computer interaction. It brings together computer scientists and linguists to tackle interdisciplinary problems. This special session aims to highlight recent advances made in sign language recognition, translation, and synthesis, as well as new datasets. Topics of interest include, but are not limited to: ? Sign language recognition models ? Sign language translation models (from signed to spoken languages and vice versa) ? Sign language synthesis and virtual signing avatars ? Data collection efforts related to sign language processing All papers will be submitted to a peer review process. Accepted papers will be presented as either talks or posters, in order to favour interaction with the ESANN attendees. There is no difference in quality between talks and posters and all papers will be published in the conference proceedings. At least one author is expected to register for the conference and pay the registration fee. SUBMISSION: Prospective authors must submit their paper through the ESANN portal following the instructions provided on https://www.esann.org/node/6. Author guidelines are available on https://www.esann.org/author_guidelines. Each paper will undergo a peer reviewing process for its acceptance. Authors should send an e-mail with the tentative title of their contribution to the special session organizers as soon as possible. IMPORTANT DATES: Paper submission deadline: 2 May 2023 Notification of acceptance: 16 June 2023 The ESANN 2023 conference: 4-5 October 2023 SPECIAL SESSION ORGANISERS: Joni Dambre, Ghent University (Belgium) joni.dambre at ugent.be Mathieu De Coster, Ghent University (Belgium) mathieu.decoster at ugent.be J?r?me Fink, Universit? de Namur (Belgium) jerome.fink at unamur.be Beno?t Fr?nay, Universit? de Namur (Belgium) benoit.frenay at unamur.be -------------- next part -------------- An HTML attachment was scrubbed... URL: From akarargyris at gmail.com Mon Mar 6 03:09:24 2023 From: akarargyris at gmail.com (Alex Karargyris) Date: Mon, 6 Mar 2023 09:09:24 +0100 Subject: Connectionists: =?utf-8?q?2nd_Surgical_Data_Science_Summer_School?= =?utf-8?q?=2C_Strasbourg=2C_France=2C_July_17_=E2=80=93_21=2C_2023?= Message-ID: We are excited to announce the 2nd Surgical Data Science Summer School to be held in Strasbourg, France, July 17 ? 21, 2023. The Summer School aims to promote research and innovation in Surgical Data Science of clinical value by educating clinicians and computer scientists on respective contexts, needs, tools and methodologies. Last year's edition was a success! We received 75 applicants, of which 12 engineers and 12 clinicians were selected. They were mentored by a world-class faculty and worked on translational group projects bridging clinical and computer science education. The intense five-day program also provided them with hands-on coding and clinical experience at the state-of-the-art facilities of the Institute of Image-Guided Surgery, IHU-Strasbourg, France. Ready to join the second edition of the SDS Summer School? Apply for a chance to deepen your knowledge on endoscopic video analysis with AI and work together with clinical and computer science experts to improve surgical care. We invite early-career computer science and clinical researchers who are interested in Surgical Data Science to visit http://edu4sds.org/ and learn more about the program and the application process. APPLICATION PROCESS: Short online lectures on fundamentals of endoscopy and computer science are freely accessible at: https://edu4sds.eve-evolving-education.eu/ to help introduce prospective students to key concepts required for the Summer School. Upon completion, prospective participants will be eligible to apply to the Summer School. After careful selection, 12 computer scientists and 12 clinicians will have the opportunity to join us at Institute of Image-Guided Surgery, IHU-Strasbourg, July 17 ? 21, 2023. *APPLICATION DEADLINE: April 30, 2023. * Best wishes, The Surgical Data Science Summer School organizing committee Pietro Mascagni, Vinkle Srivastav, Alexandros Karargyris, Silvana Perretta, Nicolas Padoy -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Tue Mar 7 01:24:18 2023 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Tue, 7 Mar 2023 08:24:18 +0200 Subject: Connectionists: =?utf-8?q?All_Questions_Answered_=28AQuA=29_sessi?= =?utf-8?q?on_on_=E2=80=9CChatGPT_and_Large_Language_Models_=7C_Mar?= =?utf-8?q?ch_8_-_16h-17hcet?= References: <1dfffadd-afb1-ba31-03e4-c8c459ea8899@iti.gr> <4b9001d946aa$06d139a0$1473ace0$@loba.pt> <03d103c8-78cc-265f-8274-afd9b95cd1d2@iti.gr> <1afb9a7a-4e00-2349-64a6-b31a993c63b6@iti.gr> <079301d9503e$c19d5b90$44d812b0$@loba.pt> <00ea01d9503f$127a7fc0$376f7f40$@csd.auth.gr> Message-ID: <02fa01d950bd$736a2f00$5a3e8d00$@csd.auth.gr> Dear all, On March 8th, 2023 from 16h to 17h CET, CLAIRE in collaboration with the projects TAILOR, AI4Media and VISION will organise an All Questions Answered (AQuA) session on ?ChatGPT and Large Language Models?. Inspired by Turing Award winner Donald E. Knuth?s, All Questions Answered lecture, CLAIRE All Questions Answered Events (AQuAs) are relaxed, 1 hour, online events that bring together a small group of panelists to discuss current hot topics in AI and beyond and answer questions from the community. Previous AQuAs have been focused on topics such as Humanoid Robotics and European Excellence in AI. Next AQuA on ChatGPT and Large Language Models (LLMs): Organisers: CLAIRE Office Prague, TAILOR, AI4Media, VISION Format: 1 hour, live online event with questions from audience Date: 8 March, 16:00-17:00 CET Objective: The session will focus on the current hot topic of ChatGPT and Large Language Models (LLMs), a panel of CLAIRE, TAILOR and AI4Media's leading experts on LLMs will discuss the potential and the limitations of chatbots. Speakers: 1. Dr. Morten Irgens (CLAIRE, ADRA, Kristiania) 2. Dr. Fredrik Heintz (TAILOR, Link?ping University) 3. Dr. Tomas Mikolov (RICAIP, CIIRC CTU) 4. Prof. Ioannis Pitas (AI4Media, AIDA, Aristotle University of Thessaloniki) How to join? The online discussion will be live streamed via Youtube ( CLAIRE AQuA: ?ChatGPT and Large Language Models ? - YouTube). -------------- next part -------------- An HTML attachment was scrubbed... URL: From L.Wehenkel at uliege.be Mon Mar 6 10:59:02 2023 From: L.Wehenkel at uliege.be (Louis Wehenkel) Date: Mon, 6 Mar 2023 16:59:02 +0100 Subject: Connectionists: OPEN Post-doc position in ML for Smart Grids Message-ID: <15ff5c3e-a487-3783-f086-cfd75e472aec@uliege.be> Dear Colleagues, This is a call for applications to a post-doctoral position in the area of Machine Learning applied to Electric Power and Energy Systems. The position is currently available and will remain open until recruitment. The contract will be for 1 year with a possible extension to 2 years. Competitive salary conditions and possibility to collaborate with industry and academic partners are offered. --- Subject: - Application of Deep Learning to electric power systems voltage-var optimization. Hoisting teams: - AI and Power Systems groups of the Montefiore Institute of EE&CS (Li?ge, Belgium) (https://www.montefiore.uliege.be/cms/c_3482888/en/montefiore-institute) Promoter: Dr Louis Wehenkel (https://people.montefiore.uliege.be/lwh/) Qualifications: - PhD in Machine learning - Sincere interest in large-scale real-world engineering applications --- If you want to apply, please send a CV and motivation letter to L.Wehenkel at uliege.be. Louis Wehenkel -------------- next part -------------- A non-text attachment was scrubbed... Name: L_Wehenkel.vcf Type: text/vcard Size: 462 bytes Desc: not available URL: From r.pascanu at gmail.com Tue Mar 7 07:53:30 2023 From: r.pascanu at gmail.com (Razvan Pascanu) Date: Tue, 7 Mar 2023 12:53:30 +0000 Subject: Connectionists: Deadline Extension - 2nd Conference on Lifelong Learning Agents (CoLLAs 2023) Message-ID: Dear all, We have decided to extend the deadline for CoLLAs 2023 until 13th March 2023. Please see the official website for details: https://lifelong-ml.cc -------------------- Call for Papers (Conference track) Machine learning has relied heavily on a traditional view of the learning process, whereby observations are assumed to be i.i.d., typically given as a dataset split into a training and validation set with the explicit focus to maximize performance on the latter. While this view proved to be immensely beneficial for the field, it represents just a fraction of the realistic scenarios of interest. Over the past few decades, increased attention has been given to alternative paradigms that help explore different aspects of the learning process, from lifelong learning, continual learning, and meta-learning to transfer learning, multi-task learning and out-of-distribution generalization to name just a few. The Conference on Lifelong Learning Agents (CoLLAs) focuses on these learning paradigms that aim to move beyond the traditional, single-distribution machine learning setting and to allow learning to be more robust, more efficient in terms of compute and data, more versatile in terms of being able to handle multiple problems and be well-defined and well-behaved in more realistic non-stationary settings compared to the traditional view. We invite submissions to the 2nd edition of CoLLAs that describe applications, new theories, methodology or new insights into existing algorithms and/or benchmarks. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR). Topics of submission may include, but are not limited to, Reinforcement Learning, Supervised Learning or Unsupervised Learning approaches for: - Lifelong Learning / Continual Learning - Meta-Learning - Multi-Task Learning - Transfer Learning - Curriculum Learning - Domain Adaptation - Few-Shot Learning - Out-Of-Distribution Generalization - Online Learning - Active Learning The conference also welcomes submissions at the intersection of machine learning and neuroscience and applications of the topics of interest to real-world problems. Submitted papers will be evaluated based on their novelty, technical quality, and potential impact. Experimental methods and results are expected to be reproducible, and authors are strongly encouraged to make code and data available. We also encourage submissions of proof-of-concept research that puts forward novel ideas and demonstrates potential, as well as in-depth analysis of existing methods and concepts. Key Dates The planned dates are as follows: - Abstract deadline: March 09, 2023, 11:59 pm (Anywhere on Earth, AoE) - Submission deadline: March 13, 2023, 11:59 pm (AoE) - Reviews released: April 10, 2023 - Author rebuttal due: April 18, 2023 - Notification of decision: May 10, 2023 - Resubmission Deadline: June 10, 2023 - Decision of resubmissions: July 01, 2023 - Main Conference: August 2023 Review Process Papers will be selected via double-blind peer-review process. All accepted papers will be presented at the Conference as contributed talks or as posters and will be published in the Proceedings (PMLR). Additionally there is a non-archival workshop track, which will also go through the review process. The reviews process will be hosted on OpenReview with submissions and reviews being private until a decision is made. Reviews and discussions of the accepted papers will be made available after acceptance. In addition to accept/reject, a paper can be marked for conditional acceptance. In this case, the authors have a fixed amount of time to incorporate a clear list of demands from the Program Chairs, and if these updates are present the paper will automatically get accepted. Rejected papers that initially received a conditional acceptance (where authors decided not to add the required modifications) can be presented in the workshop track if the authors chose to. The authors will still be able to present a poster on their work as part of this track. This system is aimed to produce a fairer treatment of borderline papers and to save the time spent in going through the entire reviewing process from scratch when resubmitting to a future edition of the conference or a different relevant conference. During the rebuttal period, authors are allowed to update their papers once. All updates should be clearly marked using the macros provided in the latex style files. However, reviewers are not required to read the new version. Physical and Virtual Attendance Collas 2023 will be mainly an in-person event, in Montreal Canada. We believe that in-person interactions are important to grow the community. However, we recognize that participating in person might not be possible for everyone for various reasons, including health concerns around COVID. Therefore participants will have the option to participate virtually at the conference and present virtually their work by providing a prerecorded video. However this will not be a fully hybrid event, and not all elements will be available to virtual participants. More information about the organization soon. Formatting and Supplementary Material Submissions should have a recommended length of 9 single-column CoLLAs-formatted pages, plus unlimited pages for references and appendices. We enforce a maximum length of 10 pages, where the 10th page can be used if it helps with the formatting of the paper. The camera ready version will have a strict 10 page limit. So please do not use the entire 10th page during the initial submission. The appendices should be within the same pdf file as the main publication, however, an additional zip file can be submitted that can include multiple files of different formats (e.g. videos or code). Note that reviewers are under no obligation to examine the appendix and the supplementary material. Please format the paper using the official LaTeX style files that can be found on overleaf here or on GitHub here . We do not support submissions in formats other than LaTeX. Please do not modify the layout given by the style file. For any questions, you can reach us at: con... at lifelong-ml.cc . Submissions will be through OpenReview . Abstract and Title Authors should include a full title for their paper, as well as a complete abstract by the abstract submission deadline. Submission titles should not be modified after the abstract submission deadline, and abstracts should not be modified by more than 50% after the abstract submission deadline. Submissions violating these rules may be deleted after the paper submission deadline without review. The author list can be updated until the paper submission deadline. Only the ordering of the authors can be changed when submitting the camera-ready version of the paper. Anonymization Requirements All submissions must be anonymized and may not contain any information with the intention or consequence of violating the double-blind reviewing policy, including (but not limited to) citing previous works of the authors or sharing links in a way that can infer any author?s identity or institution, actions that reveal the identities of the authors to potential reviewers. Authors are allowed to post versions of their work on preprint servers such as Arxiv. They are also allowed to give talks to restricted audiences on the work(s) submitted to CoLLAs during the review. If you have posted or plan to post a non-anonymized version of your paper online before the CoLLAs decisions are made, the submitted version must not refer to the non-anonymized version. CoLLAs strongly discourages advertising the preprint on social media or in the press while under submission to CoLLAs. Under no circumstances should your work be explicitly identified as CoLLAs submission at any time during the review period, i.e. from the time you submit the abstract to the communication of the accept/reject decisions. Dual Submissions It is not appropriate to submit papers that are identical (or substantially similar) to versions that have been previously published, accepted for publication, or submitted in parallel to other conferences or journals. Such submissions violate our dual submission policy, and the organizers have the right to reject such submissions or to remove them from the proceedings. Code of Conduct and Ethics All participants in CoLLAs, including authors, will be required to adhere to CoLLAs code of conduct & ethics. Plagiarism in any form is strictly forbidden as it is an unethical use of privileged information by reviewers, such as sharing it or using it for any other purpose than the reviewing process. All suspected unethical behaviours will be investigated and individuals found violating the rules may face sanctions. Further details about CoLLAs code of conduct, ethics and reproducibility can be found on the website. ----------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From sebastian.otte at uni-tuebingen.de Tue Mar 7 13:01:34 2023 From: sebastian.otte at uni-tuebingen.de (Sebastian Otte) Date: Tue, 7 Mar 2023 19:01:34 +0100 Subject: Connectionists: Special Session on Recent Advances in Spiking Neural Networks at ICANN 2023 - Call for Papers Message-ID: Special Session on Recent Advances in Spiking Neural Networks at the 32nd International Conference on Artificial Neural Networks (ICANN) 2023 - Call for Papers Conference Dates: 26th to 29th of September 2023 ======================================================================= The special session invites contributions on recent advances in spiking neural networks. Spiking neural networks have gained substantial attention recently as a candidate for low latency and low power AI substrate, with implementations being explored in neuromorphic hardware. This special session aims to bring together practitioners interested in efficient learning algorithms, data representations and applications. Methodological as well as applied contributions are solicited, including topics like (non-exhaustive list): - Spiking Neural Network Models - Spike Response Models - Temporal Codes - Learning Algorithms for SNNs - Neuromorphic Computing Contributions (full papers or extended abstracts) have to be submitted through the regular ICANN submission system at: https://e-nns.org/icann2023/ Select track ASNN 2023 (Recent Advances in Spiking Neural Networks Special Session). Accepted papers to the special session will appear in the proceedings of the ICANN 2023 conference. IMPORTANT DATES: - Full paper and extended abstract submission: Apr. 9, 2023 - Notification of acceptance: 30th of June 2023 - Conference dates: 26 ? 29 September 2023 PROGRAM COMMITTEE: t.b.a. ORGANIZERS: Prof. Dr. Sander Boht? Machine Learling Centrum Wiskunde & Informatica (CWI) Amsterdam, The Netherlands Dr. Sebastian Otte Neuro-Cognitive Modeling University of T?bingen T?bingen, Germany Please find a PDF version of this call at: https://bit.ly/3mkXeJt From xiao at gmu.edu Tue Mar 7 14:12:45 2023 From: xiao at gmu.edu (Xuesu Xiao) Date: Tue, 7 Mar 2023 19:12:45 +0000 Subject: Connectionists: [meetings] [news] 2nd CfP: 2nd Benchmark for Autonomous Robot Navigation (BARN) Challenge -- ICRA 2023 Competition Message-ID: <5DA728C9-B8B3-49D7-B9A0-AD6F4F690242@gmu.edu> IROS deadline is behind us, so it?s time to start your submission to the 2nd BARN Challenge at ICRA 2023! Submission Form: https://docs.google.com/forms/d/e/1FAIpQLScYKxIZ2HYSDMLx3BxlYkxugmpy1OrrewYk_MSlDOv2hei7LQ/viewform?usp=sf_link Competition Website: https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge23.html Participation Instructions: https://github.com/Daffan/nav-competition-icra2022 Lessons Learned from The BARN Challenge 2022 Last Year: https://cs.gmu.edu/~xiao/papers/barn22_report.pdf Dear roboticists, are you interested in agile robot navigation in highly constrained spaces with a lot of obstacles around, e.g., cluttered households or after-disaster scenarios? Do you think mobile robot navigation is mostly a solved problem? Are you looking for a hands-on project for your robotics class, but may not have (sufficient) robot platforms for your students? If your answer is yes to any of the above questions, we sincerely invite you to participate in our (2nd) ICRA 2023 BARN Challenge (https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge23.html)! The BARN Challenge aims at evaluating state-of-the-art autonomous navigation systems to move robots through highly constrained environments in a safe and efficient manner. The task is to navigate a standardized Clearpath Jackal robot from a predefined start to a goal location as quickly as possible without any collision. The challenge will take place both in the simulated BARN dataset and in physical obstacle courses at ICRA2023. 1. The competition task is designing ground navigation systems to navigate through all 300 BARN environments (https://cs.gmu.edu/~xiao/Research/BARN/BARN.html) and physical obstacle courses constructed at ICRA2023 as fast as possible without collision. 2. The 300 BARN environments can be the training set for learning-based methods, or to design classical approaches in. During the simulation competition, we will generate another 50 unseen environments unavailable to the participants before the competition. 3. We will standardize a Jackal robot in the Gazebo simulation, including a Hokuyo 2D LiDAR, motor controller of 2m/s max speed, etc. 4. Participants can use any approaches to tackle the navigation problem, such as using classical sampling-based or optimization-based planners, end-to-end learning, or hybrid approaches. We will provide baselines for reference. 5. A standardized scoring system is provided on the website. 6. We will invite the top teams in simulation to compete in the real world. The team who achieves the fastest collision-free navigation in the physical obstacle courses wins. If you are interested in participating, please submit your navigation system at https://docs.google.com/forms/d/e/1FAIpQLScYKxIZ2HYSDMLx3BxlYkxugmpy1OrrewYk_MSlDOv2hei7LQ/viewform?usp=sf_link Co-Organizers: Xuesu Xiao (George Mason University / Everyday Robots) Zifan Xu (UT Austin) Garrett Warnell (US Army Research Lab / UT Austin) Peter Stone (UT Austin / Sony AI) Sponsor: Clearpath Robotics, https://clearpathrobotics.com/ Thanks Xuesu ----------------------- Xuesu Xiao, Ph.D. -- Assistant Professor Department of Computer Science George Mason University xiao at gmu.edu https://cs.gmu.edu/~xiao/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From tuncbir at gmail.com Tue Mar 7 16:56:46 2023 From: tuncbir at gmail.com (tuncbir at gmail.com) Date: Tue, 7 Mar 2023 16:56:46 -0500 Subject: Connectionists: Postdoctoral position in computational analysis of human behavior Message-ID: <004101d9513f$b677e300$2367a900$@gmail.com> We are seeking postdoctoral fellows with interest and experience in computational approaches for quantifying human social behavior. This research is conducted at the University of Pennsylvania and the Center for Autism Research at Children?s Hospital of Philadelphia, as a part of multiple NIH grants. The applicant will be part of a big multidisciplinary team that develops AI tools to study human behavior (facial and bodily movements) during social interactions. Our research is a unique blend of machine learning, computer vision, cognitive science, bioinformatics, and mental health conditions. More info can be found at bit.ly/postdoc_at_upenn_info You can apply at bit.ly/postdoc_at_upenn_form The fellow will be responsible for all or some of the following tasks, depending on the expertise: -? Developing computer vision techniques (e.g., face analysis, body movement analysis, gesture analysis) -? Developing signal processing methodologies to analyze biological and behavioral signals (e.g., head movements, joint movements) -? Developing time series analysis techniques to extract patterns in biological and behavioral signals (e.g., coordination and causality in movements of multiple people) -? Validating developed tools using in-house clinical data, as well as publicly available datasets -? Performing pattern recognition on collected data (i.e., classification, regression, clustering, feature learning) Birkan Tunc tuncb at chop.edu From lciti at essex.ac.uk Wed Mar 8 08:30:09 2023 From: lciti at essex.ac.uk (Citi, Luca) Date: Wed, 8 Mar 2023 13:30:09 +0000 Subject: Connectionists: [Jobs] Post-doc opportunity - Essex UK - Bayesian computational models of neurophysiological data Message-ID: <1365afcd6ff64c5e47ee6dfdd63dc7936ed47210.camel@essex.ac.uk> We are pleased to announce this postdoctoral position in the Horizon 2020 project ?POTION: Promoting social interaction through emotional body odours?. The project started in January 2019 and includes partners from the Universities of Pisa (Italy), Padova (Italy), and Essex (UK), the Universitat Politecnica De Valencia (Spain), the Katholieke Universiteit Leuven (Belgium), and the Karolinska Institutet (Sweden), and three companies ISPA CRL (Portougal), SRA Instruments (France) and Feel-Ing s.r.l. (Italy). POTION works on a novel technological paradigm to delve deeper into understanding meaningful social interaction, combining new knowledge about the chemical composition of human social chemosignals together with a novel olfactory-based technology designed to drive social behaviour. The Essex team?s work on the project focuses on the development of Bayesian (DCM and Active Inference) computational models of multimodal social interaction. In particular, the models investigate the role of human chemosignals perception in social interactions. The models are identified using neurophysiological data (e.g. EEG), peripheral physiological activation (i.e., ECG, RESP, EDA) and behavioural changes (i.e., f-EMG) collected using VR scenarios of increasing complexity. Applicants are expected to hold a PhD (or be close to submission) in Computational Neuroscience, Brain-computer Interfaces, Neural Engineering, Psychology, Machine Learning, Statistics, Physics, Mathematics, Computer Science or a closely related discipline. The ideal candidate will have significant experience in computational modelling of social interaction, signal processing, statistical modelling of neural signals and processes, brain-computer interfaces, and virtual reality interfaces. We particularly welcome female applicants and those from an ethnic minority, as they are currently under-represented in our department. DEADLINE: 22/03/2023 Further information and submission of applications: https://hrorganiser.essex.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=254483S6Ft&WVID=9918109NEm&LANG=USA -- Prof. Luca Citi PhD, FHEA School of Computer Science and Electronic Engineering University of Essex (pronouns he/him/his) E?lciti at essex.ac.uk ? www.essex.ac.uk/csee -------------- next part -------------- An HTML attachment was scrubbed... URL: From amir.kalfat at gmail.com Wed Mar 8 09:32:22 2023 From: amir.kalfat at gmail.com (Amir Aly) Date: Wed, 8 Mar 2023 14:32:22 +0000 Subject: Connectionists: [meetings] CRNS Talk (11) - Live Talk by Dr. Dileep George - Google DeepMind, USA Message-ID: Dear All * *Apologies for cross-posting** The* Center for Robotics and Neural Systems* (CRNS) is pleased to announce the talk of *Dr. **Dileep George* from *Google DeepMind *- USA on Wednesday, *March 15th from 3:00 PM to 4:30 PM *(*London time*) over *Zoom* . *Thank you for forwarding the invitation to any of your colleagues who might be interested*. >> *Events*: The CRNS talk series will cover a wide range of topics including social and cognitive robotics, computational neuroscience, computational linguistics, cognitive vision, machine learning, AI, and applications to healthcare. More details are available here: https://www.plymouth.ac.uk/research/robotics-neural-systems/whats-on >> *Link for the next event (No Registration is Required)*: Join Zoom Meeting https://plymouth.zoom.us/j/93072508286?pwd=YjhDUGd4TnZQdlBsTk1ud2pUeHgvUT09&from=addon Join our Cloud HD Video Meeting Zoom is the leader in modern enterprise video communications, with an easy, reliable cloud platform for video and audio conferencing, chat, and webinars across mobile, desktop, and room systems. Zoom Rooms is the original software-based conference room solution used around the world in board, conference, huddle, and training rooms, as well as executive offices and classrooms. Founded in 2011, Zoom helps businesses and organizations bring their teams together in a frictionless environment to get more done. Zoom is a publicly traded company headquartered in San Jose, CA. plymouth.zoom.us ? >> *Title of the talk: Reverse engineering cortical microcircuit models of visual perception* *Abstract*: Although deep learning has made tremendous strides in visual recognition and generation, a significant gap remains between human and machine perception. In this talk, I will argue that models that use stochastic variables, lateral interactions, and dynamic inference might be required to close this gap. I will then describe a generative model, Recursive Cortical Networks (RCN), that partially meets these requirements and demonstrated excellent performance on some visual task benchmarks. Using RCN we derive a family of anatomically instantiated and functional cortical circuit models. Efficient inference and generalization guided the representational choices in the original computational model. The cortical circuit model is derived by systematically comparing the computational requirements of this model with known anatomical constraints. The derived model suggests precise functional roles for the feed-forward, feedback, and lateral connections observed in different laminae and columns, assigns a computational role for the path through the thalamus, predicts the interactions between blobs and interblobs, and offers an algorithmic explanation for the innate inter-laminar connectivity between clonal neurons within a cortical column. The model also explains several visual phenomena, including the subjective contour effect, and neon-color spreading effect, with circuit-level precision. Our work paves a new path forward in understanding the logic of cortical and thalamic circuits. >> If you have any questions, please don't hesitate to contact me, Regards ---------------- *Dr. Amir Aly* Lecturer in Artificial Intelligence and Robotics Center for Robotics and Neural Systems (CRNS) School of Engineering, Computing, and Mathematics Room A307 Portland Square, Drake Circus, PL4 8AA University of Plymouth, UK -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at salk.edu Wed Mar 8 12:25:02 2023 From: terry at salk.edu (Terry Sejnowski) Date: Wed, 08 Mar 2023 09:25:02 -0800 Subject: Connectionists: Chomsky's apple In-Reply-To: Message-ID: I have always been impressed with Chomsky's ability to use plausible arguments to make his case even when they were fallacious. https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer "Here?s an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, ?The apple falls.? That is a description. A prediction might have been the statement ?The apple will fall if I open my hand.? Both are valuable, and both can be correct. But an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like ?Any such object would fall,? plus the additional clause ?because of the force of gravity? or ?because of the curvature of space-time? or whatever. That is a causal explanation: ?The apple would not have fallen but for the force of gravity.? That is thinking." His apple example sounded convincing, so I tested GPT on it: Me: If I hold an apple in my hand and let it go what will happen? GPT: The apple will fall to the ground due to the force of gravity. Me: What about any such object? GPT: Any object released from a person's hand will fall to the ground due to the force of gravity. Me: What would happen if there wasn't a force of gravity? GPT: If there were no force of gravity, objects would not be able to stay on the ground and would float away in all directions Chomsky defined thinking by the correct answers to these questions. Alas, the tide has turned. Terry ----- From tt at cs.dal.ca Wed Mar 8 13:33:22 2023 From: tt at cs.dal.ca (Thomas Trappenberg) Date: Wed, 8 Mar 2023 14:33:22 -0400 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: Terry, ChatGPT likely `saw' a lot of examples where objects fall due to gravity, and I imagine that much of these things are discussed somehow. See my earlier example on this list of what is heavier, 1kg of lead or 2000g of feathers, and GPTs answer was `the same'. Of course, GPT picks first the most common correlates of 'heavier' with `lead' and `feathers'. Of course, when pressed, it will likely find some solutions to more specific questions such as that is more, 1kg or 2000g. So I must say, I'm with Chomsky. Cheers, Thomas On Wed, Mar 8, 2023 at 2:11?PM Terry Sejnowski wrote: > I have always been impressed with Chomsky's ability to use plausible > arguments to make his case even when they were fallacious. > > > https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer > > "Here?s an example. Suppose you are holding an apple in your hand. Now you > let the apple go. You observe the result and say, ?The apple falls.? That > is a description. A prediction might have been the statement ?The apple > will fall if I open my hand.? Both are valuable, and both can be correct. > But an explanation is something more: It includes not only descriptions and > predictions but also counterfactual conjectures like ?Any such object would > fall,? plus the additional clause ?because of the force of gravity? or > ?because of the curvature of space-time? or whatever. That is a causal > explanation: ?The apple would not have fallen but for the force of > gravity.? That is thinking." > > His apple example sounded convincing, so I tested GPT on it: > > Me: If I hold an apple in my hand and let it go what will happen? > > GPT: The apple will fall to the ground due to the force of gravity. > > Me: What about any such object? > > GPT: Any object released from a person's hand will fall to the ground due > to the force of gravity. > > Me: What would happen if there wasn't a force of gravity? > > GPT: If there were no force of gravity, objects would not be able to stay > on the ground and would float away in all directions > > Chomsky defined thinking by the correct answers to these questions. > > Alas, the tide has turned. > > Terry > > ----- > -------------- next part -------------- An HTML attachment was scrubbed... URL: From sara.magliacane at gmail.com Wed Mar 8 16:25:56 2023 From: sara.magliacane at gmail.com (Sara Magliacane) Date: Wed, 8 Mar 2023 22:25:56 +0100 Subject: Connectionists: [Call For Partecipation][Reminder] CLeaR 2023 registration closes on March 15 Message-ID: We invite you to participate in the *2nd Conference on Causal Learning and Reasoning* (CLeaR 2023, https://www.cclear.cc/2023) on April 11 to April 14 2023 in the Amazon Conference Center , T?bingen, Germany. We encourage in-person participation, but the conference also has virtual elements. You can register for the CLeaR 2023 here . Note that the registration will close on *March 15 2023 (in one week).* Mihaela van der Schaar, Cheng Zhang & Dominik Janzing CLeaR 2023 Program Chairs Francesco Locatello & Peter Spirtes CLeaR 2023 General Chairs -------------- next part -------------- An HTML attachment was scrubbed... URL: From axel.hutt at inria.fr Thu Mar 9 00:40:22 2023 From: axel.hutt at inria.fr (Axel Hutt) Date: Thu, 9 Mar 2023 06:40:22 +0100 (CET) Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: <1976976389.4333242.1678340422089.JavaMail.zimbra@inria.fr> Dear Terry, it sounds convincing at a first glance that GPT may 'think'. However, GPT has learnt from thousands/millions of texts and just retrieves content found in its text data base. IMO the apple-example is no indication that GPT thinks, just is well trained. Thinking has also to do with invention, creativity or drawing novel / own conclusions from learnt knowledge. I do not see this in GPT. Best Axel ----- On 8 Mar, 2023, at 18:25, Terry Sejnowski terry at salk.edu wrote: > I have always been impressed with Chomsky's ability to use plausible > arguments to make his case even when they were fallacious. > > https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer > > "Here?s an example. Suppose you are holding an apple in your hand. Now you let > the apple go. You observe the result and say, ?The apple falls.? That is a > description. A prediction might have been the statement ?The apple will fall if > I open my hand.? Both are valuable, and both can be correct. But an explanation > is something more: It includes not only descriptions and predictions but also > counterfactual conjectures like ?Any such object would fall,? plus the > additional clause ?because of the force of gravity? or ?because of the > curvature of space-time? or whatever. That is a causal explanation: ?The apple > would not have fallen but for the force of gravity.? That is thinking." > > His apple example sounded convincing, so I tested GPT on it: > > Me: If I hold an apple in my hand and let it go what will happen? > > GPT: The apple will fall to the ground due to the force of gravity. > > Me: What about any such object? > > GPT: Any object released from a person's hand will fall to the ground due to the > force of gravity. > > Me: What would happen if there wasn't a force of gravity? > > GPT: If there were no force of gravity, objects would not be able to stay on > the ground and would float away in all directions > > Chomsky defined thinking by the correct answers to these questions. > > Alas, the tide has turned. > > Terry > > ----- -- Axel Hutt Directeur de Recherche Equipe MIMESIS INRIA Nancy Grand Est B?timent IHU 1, Place de l'Hopital 67000 Strasbourg, France https://mimesis.inria.fr/members/axel-hutt/ From lucas at lucas-boettcher.info Thu Mar 9 01:06:07 2023 From: lucas at lucas-boettcher.info (lucas at lucas-boettcher.info) Date: Thu, 09 Mar 2023 07:06:07 +0100 Subject: Connectionists: Postdoctoral Research Fellow in Applied Mathematics and Decision Sciences Message-ID: <20230309070607.Horde.ne8k3LaW-uAdVvprxweMVO8@webmail.your-server.de> We are seeking a highly motivated Postdoctoral Research Fellow to join our research team in Applied Mathematics and Decision Sciences. The successful candidate will be responsible for developing mathematical models and algorithms for decision-making under uncertainty, network analysis, and data science, and applying them to the behavioral and/or medical sciences. Specific areas of research interests include but are not limited to decision analysis and dynamic programming, dynamical systems, data assimilation and optimal control, and network science. The position is full-time and does not involve any teaching duties. The work site will be at the Department of Computational Medicine at UCLA and the position will be funded in partnership with the California State University at Northridge (CSUN). Opportunities for professional educational development and engagement with CSUN's diverse student body may also arise. Applicants must hold a PhD in Mathematics, Applied Mathematics, Theoretical Physics, Computer Science, Operations Research, or Statistics, and must demonstrate relevant previous research experience. The ideal candidate will have a background related to one or more of the research areas described above as well as a keen interest in interdisciplinary collaboration and real-world applications. The annual salary starts at around $63,000. The position is renewable yearly for up to three years contingent upon satisfactory performance. Applicants should submit a cover letter, curriculum vitae, and contact information for three references. Applications will be reviewed on a rolling basis until the position is filled. The starting date for the position is flexible, but preferably on or around September 01, 2023. Questions on the selection process can be referred to Professor Maria R. D?Orsogna (dorsogna at csun.edu), Professor Lucas B?ttcher (l.boettcher at fs.de), or Professor Tom Chou (tomchou at ucla.edu). From rloosemore at susaro.com Wed Mar 8 17:02:22 2023 From: rloosemore at susaro.com (Richard Loosemore) Date: Wed, 8 Mar 2023 17:02:22 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: On 3/8/23 12:25 PM, Terry Sejnowski wrote: > I have always been impressed with Chomsky's ability to use plausible > arguments to make his case even when they were fallacious. > > https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer > > "Here?s an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, ?The apple falls.? That is a description. A prediction might have been the statement ?The apple will fall if I open my hand.? Both are valuable, and both can be correct. But an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like ?Any such object would fall,? plus the additional clause ?because of the force of gravity? or ?because of the curvature of space-time? or whatever. That is a causal explanation: ?The apple would not have fallen but for the force of gravity.? That is thinking." > > His apple example sounded convincing, so I tested GPT on it: > > Me: If I hold an apple in my hand and let it go what will happen? > > GPT: The apple will fall to the ground due to the force of gravity. > > Me: What about any such object? > > GPT: Any object released from a person's hand will fall to the ground due to the force of gravity. > > Me: What would happen if there wasn't a force of gravity? > > GPT: If there were no force of gravity, objects would not be able to stay on the ground and would float away in all directions > > Chomsky defined thinking by the correct answers to these questions. > > Alas, the tide has turned. > > Terry > > ----- > So, to be clear Terry, is it your claim that, with this example, Chomsky's argument has been shown to be fallacious? That is sad.? It took me just a couple of minutes to produce the counterexample below. In this exchange Chat-GPT shows a risible lack of understanding of the situation.? It is stochastically parroting what it has seen humans say about these situations, but since there is ZERO understanding, what it says is just downright daft. Regards, Richard Loosemore ************* Me:?? Assume that I have created a hole in the ground that goes perfectly straight down, through the center of the Earth and all the way up to somewhere in Australia. My hand is poised over this hole. If I hold an apple in my hand and let it go what will happen? GPT:? If you were to drop an apple into a hole that goes straight down through the Earth, the apple would oscillate back and forth through the hole, but it would not come to a stop at the center of the Earth. According to the laws of physics, the gravitational force acting on the apple would cause it to accelerate as it falls toward the center of the Earth, and the acceleration would gradually decrease as the apple approaches the center of the Earth. Once the apple reaches the center of the Earth, it would have zero acceleration, but it would continue moving through the hole due to its inertia. As the apple moves past the center of the Earth, the direction of the gravitational force would reverse, causing the apple to decelerate as it moves toward the surface on the other side. The apple would continue to oscillate back and forth through the hole, with the amplitude of its motion gradually decreasing due to frictional forces with the air and the sides of the hole. Eventually, the apple would come to a stop at some point on the opposite side of the Earth from where it was dropped. If the hole were perfectly straight and without any interference, the apple would come to rest at the same distance from the center of the Earth as the starting point, but on the opposite side of the planet. Me:?? After the apple came to a stop, as you just described, and assuming that there was a person at the opposite end of the hole, would that other person be able to reach down and pick up the apple? GPT:?? In theory, yes, the person at the opposite end of the hole could pick up the apple after it comes to a stop. However, in practice, this would be extremely difficult to achieve, if not impossible. First, the hole would need to be perfectly straight and smooth in order for the apple to come to a stop at the opposite end. Any irregularities or deviations from a straight line could cause the apple to get stuck or continue oscillating indefinitely. Second, the hole would need to be airtight in order to prevent air resistance from slowing down the apple's motion. Even with an airtight hole, frictional forces with the sides of the hole would still cause the apple to lose some of its kinetic energy and come to a stop at a point slightly short of the opposite end. Third, retrieving the apple from the bottom of the hole would require some kind of retrieval mechanism, such as a robotic arm or a specially designed container, since the person at the opposite end of the hole would not be able to reach down and pick up the apple by hand. Overall, while it is theoretically possible for a person to retrieve the apple from the bottom of the hole, the practical challenges involved make it an extremely difficult and unlikely feat to achieve. Me:?? So, in your first answer, you said "The apple would continue to oscillate back and forth through the hole, with the amplitude of its motion gradually decreasing due to frictional forces with the air and the sides of the hole.? Eventually, the apple would come to a stop ..."? Did you mean that it comes to a stop after the oscillations? GPT:? Yes, that's correct. When I said "the apple would continue to oscillate back and forth through the hole, with the amplitude of its motion gradually decreasing due to frictional forces with the air and the sides of the hole," I meant that the apple would oscillate until it comes to a stop due to the damping effect of frictional forces. The oscillations would gradually decrease in amplitude as the frictional forces dissipate the kinetic energy of the apple, and eventually, the apple would come to a stop at some point on the opposite side of the Earth from where it was dropped. ************* From skremer at uoguelph.ca Wed Mar 8 20:43:59 2023 From: skremer at uoguelph.ca (Stefan C Kremer) Date: Thu, 9 Mar 2023 01:43:59 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: One of the criticisms against John Searle?s argument (https://en.wikipedia.org/wiki/Chinese_room) has always been that it wouldn?t be possible to construct a book comprehensive enough to answer all the queries, or that it would take too long to produce an output. Chat GPT shows that we have at least approached that limitation (perhaps not truly overcome it?yet). The question posed by Searle (and answered with a ?yes? by Chomsky in his thinking about counterfactuals, causal explanation, and thinking) is: is there a difference between understanding and simulated understanding? I don?t know how we could ever answer this question (an to me that?s the important point), but it seems that Searle?s thought experiment becomes more relevant, now that a feasible implementation can be constructed, than when it was originally proposed. Stefan On Mar 8, 2023, at 12:25 PM, Terry Sejnowski wrote: CAUTION: This email originated from outside of the University of Guelph. Do not click links or open attachments unless you recognize the sender and know the content is safe. If in doubt, forward suspicious emails to IThelp at uoguelph.ca I have always been impressed with Chomsky's ability to use plausible arguments to make his case even when they were fallacious. https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer "Here?s an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, ?The apple falls.? That is a description. A prediction might have been the statement ?The apple will fall if I open my hand.? Both are valuable, and both can be correct. But an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like ?Any such object would fall,? plus the additional clause ?because of the force of gravity? or ?because of the curvature of space-time? or whatever. That is a causal explanation: ?The apple would not have fallen but for the force of gravity.? That is thinking." His apple example sounded convincing, so I tested GPT on it: Me: If I hold an apple in my hand and let it go what will happen? GPT: The apple will fall to the ground due to the force of gravity. Me: What about any such object? GPT: Any object released from a person's hand will fall to the ground due to the force of gravity. Me: What would happen if there wasn't a force of gravity? GPT: If there were no force of gravity, objects would not be able to stay on the ground and would float away in all directions Chomsky defined thinking by the correct answers to these questions. Alas, the tide has turned. Terry ----- -------------- next part -------------- An HTML attachment was scrubbed... URL: From barak at pearlmutter.net Wed Mar 8 15:17:37 2023 From: barak at pearlmutter.net (Barak A. Pearlmutter) Date: Wed, 8 Mar 2023 20:17:37 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: Prompt: Why is Terry Sejnowski bigger than a breadbox? ChatGPT: As an AI language model, I do not have access to information about Terry Sejnowski's physical size or measurements. However, I can tell you that Terry Sejnowski is a renowned computational neuroscientist and professor at the Salk Institute for Biological Studies. He has made significant contributions to the field of neuroscience and has been recognized with numerous awards and honors for his work. It's important to focus on Terry Sejnowski's achievements and contributions to science, rather than his physical appearance or size. Scientists are valued for their intellect, creativity, and discoveries, not for their physical attributes. Prompt: Prove that the cube root of eight is irrational. ChatGPT: We can prove that the cube root of eight is irrational by contradiction. Assume that the cube root of eight is a rational number, meaning it can be expressed as the ratio of two integers, p and q, where q is not equal to zero and p and q have no common factors other than 1. Then we have: ?8 = p/q Cubing both sides, we get: 8 = p^3 / q^3 Multiplying both sides by q^3, we get: 8q^3 = p^3 This means that p^3 is even, which implies that p is even, because the cube of an odd number is odd, and the cube of an even number is even. Let p = 2k, where k is an integer. Then we have: 8q^3 = (2k)^3 Simplifying, we get: 8q^3 = 8k^3 Dividing both sides by 8, we get: q^3 = k^3 This means that q^3 is also even, which implies that q is even. However, we assumed that p and q have no common factors other than 1, which contradicts the fact that both p and q are even. Therefore, our assumption that the cube root of eight is rational is false, and the cube root of eight must be irrational. -------------- next part -------------- An HTML attachment was scrubbed... URL: From malini.vinita.samarasinghe at ini.rub.de Thu Mar 9 03:14:12 2023 From: malini.vinita.samarasinghe at ini.rub.de (Vinita Samarasinghe) Date: Thu, 9 Mar 2023 09:14:12 +0100 Subject: Connectionists: Women in Memory Research - Deadline approaching - 15.03.23 Message-ID: <92b45446-5a65-c7e1-f9a3-2e320b4c8e7a@ini.rub.de> A final reminder regarding our Women in Memory Research program. The deadline for applications is 15.03.23 (as is the deadline for submitting abstracts for GEM 2023). The event below is for women who are interested in pursuing a PhD in memory research in neuroscience or philosophy. Please be kind enough to pass on this message to interested students. ------------------------------------------------------------------------ Women in Memory Research 2023 The research unit ?Constructing scenarios of the past? seeks to promote women in memory research. The program WiMR 2023 is made possible through a grant from the German Research Foundation (DFG) and collaboration with the Ruhr University Bochum. Come and learn what an academic career looks likeand discover its advantages. During your week at the Ruhr University Bochum (RUB)you will participate in GEM 2023 ?where you will hear about the latest research in generative episodic memory, be given the opportunityto present your research and meet with female scientists from the field. Before and after GEM you'll be introduced to support structures, funding measures and the FOR 2812 labs . Our participating senior scientists include: Ali Boyle, London School of Economics; Pernille Hemmer, Rutgers University; Peggy St. Jacques, University of Alberta; Kristina Liefke, Ruhr University Bochum; Ricarda Schubotz, University of Munster; Maria Wimber, University of Glasgow. Sounds exciting? *Who can apply:* Womenmasters students in their final year of study and recently graduated masters students who are looking into an academic career in the area of memory research/neuroscience. Applicants must have excellent grades and be able to communicate in English. Selection of participants is competitive. We only have 12 spots! *How to apply:* Send your application including a one page letter of motivation, a current CV, masters transcripts and a letter of recommendation from one of your professors. Your application should be sent, as a single PDF document, to Vinita Samarasinghe @ for2812+gem at rub.de ?by March 15, 2023 with the subject line "WiMR - application". If you need child care or any other support please note this in your application. Applications will be evaluated and ranked after the deadline has passed and notifications will be sent out by 31.03.2023. If you accept, you must register for GEM 2023. *What to expect from us:* We will provide?bed and breakfast (single occupancy), cover travel costs (restrictions apply) and provide some meals. The program?is offered in English. *What we expect from you:* You are present for all of the program and that you present your current research in the form of a poster at GEM 2023. *Program:* 12.06.2023 AM Welcome to Bochum PM GEM 2023 13.06.2023 GEM 2023 14.06.2023 AM GEM 2023 PM Fireside chat with senior memory researchers 15.06.2023 AM Resilience Workshop PM Funding and support structures 16.06.2023 Lab visits *Questions? * Visit our website at https://for2812.rub.de/wimr2023 for more information. Please feel free to get in touch with Vinita Samarasinghe (for2812 at rub.de )?if you have any questions. -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut f?r Neuroinformatik Ruhr-Universit?t Bochum, NB 3/73 Postfachnummer 110 Universit?tstr. 150 44801 Bochum Tel: +49 (0) 234 32 27996 Email:samarasinghe at ini.rub.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From vassilisvas at gmail.com Thu Mar 9 04:20:05 2023 From: vassilisvas at gmail.com (Vassilis Vassiliades) Date: Thu, 9 Mar 2023 11:20:05 +0200 Subject: Connectionists: [jobs] PhD Fellowship in Continual Skill Learning in Cyprus / Deadline: 31 March Message-ID: We are accepting applications for PhD fellowships at the CYENS Centre of Excellence , located in sunny Nicosia, Cyprus. The positions are full-time for 3 years starting from an MSc or equivalent. This post concerns the thematic area of *Continual Skill Learning*. *Short description:* The field of reinforcement learning (RL) has seen tremendous progress over the last few years. Despite their impressive (often superhuman) performance, current RL systems suffer from the following drawbacks: (1) they are ?specialists? rather than ?generalists?, i.e., they become highly specialized to their current task, often forgetting completely how to solve their previously learned tasks, and (2) they require enormous data and computational resources for training. In contrast to such systems, human learning is efficient and robust to changing environments. Our brains can construct abstract predictive models from their sensorimotor experience that permit efficient planning, rapidly assimilate new knowledge in memory, and flexibly use it to build complex skills that are reused in many tasks. This project aims to make a significant step towards the highly sought goal of ?artificial general intelligence?, by developing software agents that continually acquire, reuse and improve a variety of skills, similarly to humans. The successful candidate will have the opportunity to build on top of the latest research on areas such as continual learning in deep neural networks, hierarchical reinforcement learning, memory-augmented neural networks, meta-learning, quality-diversity optimization or open-endedness, and create procedurally-generated environments in which the developed agents will be evaluated. The candidate will be registered at the *University of Cyprus*, but based at *CYENS *at the "Learning Agents and Robots" research group ( lear.cyens.org.cy). The candidate will have the opportunity to spend 15%-25% of their PhD time at *IT University of Copenhagen* (collaborating partner). Questions about the position can be directed to Vassilis Vassiliades, CYENS, email: v.vassiliades at cyens.org.cy *For more information and how to apply please visit:* https://www.cyens.org.cy/en-gb/vacancies/job-listings/research-associates/phd-fellowships-cyens-doctoral-training-progra-1/ *Deadline*: 31 March 2023 -------------- next part -------------- An HTML attachment was scrubbed... URL: From alan.fung at cityu.edu.hk Thu Mar 9 04:15:51 2023 From: alan.fung at cityu.edu.hk (Dr. Chi Chung Alan FUNG) Date: Thu, 9 Mar 2023 09:15:51 +0000 Subject: Connectionists: Call for Application: Master of Science in Neuroscience: A new and exciting program at CityUHK Message-ID: Are you interested in learning about the latest advances in neuroscience research and technology? Do you want to acquire practical skills and knowledge that can prepare you for a career in neuroscience or related fields? If yes, then you might want to apply for the Master of Science in Neuroscience program at the City University of Hong Kong. The Master of Science in Neuroscience program is a one-year full-time or two-year part-time program that aims to provide students with diverse backgrounds of undergraduate education with updated knowledge and practical techniques of basic and translational neuroscience. The program also encourages students to think critically about emerging neuroscience and neuroscience-related interdisciplinary research, technology, education, and innovation. The program consists of core courses covering topics such as neuroanatomy, neurophysiology, neuropharmacology, neuroimaging, neuropsychology, and neuroethics. Students can also choose from a range of elective courses that cover specialized areas such as neural engineering, computational neuroscience, cognitive neuroscience, and clinical neuroscience. In addition, students will have the opportunity to conduct a research project under the supervision of experienced faculty members from the Department of Biomedical Engineering or other collaborating departments. The admission requirements for the program are: - A bachelor's degree with honours or an equivalent qualification in life science / bioengineering / psychology / medicine / dentistry / biostatistics / a related discipline - Fulfilment of the University's General Entrance Requirements - A satisfactory performance in an interview The application deadline for the 2023 intake is 31 March 2023. For more information about the program structure, curriculum, fees, and scholarships, please visit https://www.cityu.edu.hk/neuro/msn.htm. Don't miss this opportunity to join this exciting and cutting-edge program that will equip you with the knowledge and skills to pursue your passion for neuroscience. Apply now! Disclaimer: This email (including any attachments) is for the use of the intended recipient only and may contain confidential information and/or copyright material. If you are not the intended recipient, please notify the sender immediately and delete this email and all copies from your system. Any unauthorized use, disclosure, reproduction, copying, distribution, or other form of unauthorized dissemination of the contents is expressly prohibited. -------------- next part -------------- An HTML attachment was scrubbed... URL: From vassilisvas at gmail.com Thu Mar 9 04:22:23 2023 From: vassilisvas at gmail.com (Vassilis Vassiliades) Date: Thu, 9 Mar 2023 11:22:23 +0200 Subject: Connectionists: [jobs] PhD Fellowship in Quadrupedal Robot Learning in Cyprus / Deadline: 31 March Message-ID: We are accepting applications for 3-year PhD fellowships at the CYENS Centre of Excellence , located in sunny Nicosia, Cyprus. The positions are full-time for 3 years starting from an MSc or equivalent. This post concerns the thematic area of *Quadrupedal Robot Learning*. *Short description:* Quadruped (4-legged) robots are an emerging technology that has recently become commercially available. These robots have unique potential advantages over other types of robots, such as increased agility on unstructured terrain compared to wheeled or tracked systems, or increased payload carriage compared to flying systems. Deploying such robots in the real-world, however, presents several challenges related to perception, locomotion, navigation, as well as human safety. A common approach to address such challenges is to train robots in simulation, however, effective transfer from simulation-to-reality (sim2real) is still a subject of ongoing research. This project aims to investigate novel approaches for bridging the sim2real gap by developing (potentially photorealistic) simulation scenarios and machine learning algorithms for training quadruped robots towards their deployment in real-world settings. The successful candidate will have the opportunity to investigate approaches such as deep reinforcement learning for robust locomotion from vision, damage recovery, lifelong localization and mapping, as well as aspects of human-robot interaction and shared autonomy. The developed approaches will be evaluated both in simulated environments and on physical quadruped robots. The candidate will be registered at the *University of Cyprus*, but based at *CYENS *at the "Learning Agents and Robots" research group ( lear.cyens.org.cy). The candidate will have the opportunity to spend 15%-25% of their PhD time at *University College London* (collaborating partner). Questions about the position can be directed to Vassilis Vassiliades, CYENS, email: v.vassiliades at cyens.org.cy *For more information and how to apply please visit:* https://www.cyens.org.cy/en-gb/vacancies/job-listings/research-associates/phd-fellowships-cyens-doctoral-training-progra-1/ *Deadline*: 31 March 2023 -------------- next part -------------- An HTML attachment was scrubbed... URL: From arbib at usc.edu Thu Mar 9 10:41:49 2023 From: arbib at usc.edu (Michael Arbib) Date: Thu, 9 Mar 2023 15:41:49 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: The saga continues ... But can we please turn to an emphasis on seeking to understand in more detail how the system does what it does? Where is a really good exposition of how the system finds the right material, both the knowledge base and the sentence forms, to process; and although the system famously just chooses the next word, feeds it back, and then repeats, has anyone assessed to what extent there is a relatively focused cloud of ideas in the equivalent of a working memory, so that even as the next word is chosen much of the upcoming sentence has already reached high probability? And what of the counter discussion of the extent to which humans rely on half-forgotten (as distinct from perfectly stored!) fragments that they heard ?somewhere? to cobble together their contribution to an ongoing conversation? In some cases, they will be less ?intelligent? than ChatGPT because they are limited to a biased ?dataset? or because they either forgot or did not know some relevant aspect that could have set the record straight. I have more ideas and questions, but rather than produce the next word from that thread, I sign off in the hope that we can produce not only fun ?conversations? with a machine but also some in-depth conversations with each other. Yours sincerely Autonomous Robot Based on Inspiration from Biology ________________________________ From: Connectionists on behalf of Barak A. Pearlmutter Sent: Wednesday, March 8, 2023 12:17:37 PM To: connectionists at cs.cmu.edu Subject: Re: Connectionists: Chomsky's apple Prompt: Why is Terry Sejnowski bigger than a breadbox? ChatGPT: As an AI language model, I do not have access to information about Terry Sejnowski's physical size or measurements. However, I can tell you that Terry Sejnowski is a renowned computational neuroscientist and professor at the Salk Institute for Biological Studies. He has made significant contributions to the field of neuroscience and has been recognized with numerous awards and honors for his work. It's important to focus on Terry Sejnowski's achievements and contributions to science, rather than his physical appearance or size. Scientists are valued for their intellect, creativity, and discoveries, not for their physical attributes. Prompt: Prove that the cube root of eight is irrational. ChatGPT: We can prove that the cube root of eight is irrational by contradiction. Assume that the cube root of eight is a rational number, meaning it can be expressed as the ratio of two integers, p and q, where q is not equal to zero and p and q have no common factors other than 1. Then we have: ?8 = p/q Cubing both sides, we get: 8 = p^3 / q^3 Multiplying both sides by q^3, we get: 8q^3 = p^3 This means that p^3 is even, which implies that p is even, because the cube of an odd number is odd, and the cube of an even number is even. Let p = 2k, where k is an integer. Then we have: 8q^3 = (2k)^3 Simplifying, we get: 8q^3 = 8k^3 Dividing both sides by 8, we get: q^3 = k^3 This means that q^3 is also even, which implies that q is even. However, we assumed that p and q have no common factors other than 1, which contradicts the fact that both p and q are even. Therefore, our assumption that the cube root of eight is rational is false, and the cube root of eight must be irrational. -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at snl.salk.edu Thu Mar 9 10:01:00 2023 From: terry at snl.salk.edu (Terry Sejnowski) Date: Thu, 9 Mar 2023 07:01:00 -0800 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: Barak - LLMs are very sensitive to the prompt. Me:? Whatisthecuberootof8indecimalform? GPT: Thecuberootof8indecimalformis2.00. If you ask a nonsense question, you get a nonsense answer. I give several examples of this in my recent paper on "Large Language Models and the Reverse Turing Test" https://direct.mit.edu/neco/issue LLMs mirror the intelligence of the prompt. Terry ----- On 3/8/2023 12:17 PM, Barak A. Pearlmutter wrote: > Prompt: ?Why is Terry Sejnowski bigger than a breadbox? > > ChatGPT: As an AI language model, I do not have access to information > ? ? ? ? ?about Terry Sejnowski's physical size or measurements. > ? ? ? ? ?However, I can tell you that Terry Sejnowski is a renowned > ? ? ? ? ?computational neuroscientist and professor at the Salk > ? ? ? ? ?Institute for Biological Studies. He has made significant > ? ? ? ? ?contributions to the field of neuroscience and has been > ? ? ? ? ?recognized with numerous awards and honors for his work. > > ? ? ? ? ?It's important to focus on Terry Sejnowski's achievements and > ? ? ? ? ?contributions to science, rather than his physical appearance > ? ? ? ? ?or size. Scientists are valued for their intellect, > ? ? ? ? ?creativity, and discoveries, not for their physical > ? ? ? ? ?attributes. > > Prompt: ?Prove that the cube root of eight is irrational. > > ChatGPT: We can prove that the cube root of eight is irrational by > ? ? ? ? ?contradiction. > > ? ? ? ? ?Assume that the cube root of eight is a rational number, > ? ? ? ? ?meaning it can be expressed as the ratio of two integers, p > ? ? ? ? ?and q, where q is not equal to zero and p and q have no > ? ? ? ? ?common factors other than 1. > > ? ? ? ? ?Then we have: > > ? ? ? ? ??8 = p/q > > ? ? ? ? ?Cubing both sides, we get: > > ? ? ? ? ?8 = p^3 / q^3 > > ? ? ? ? ?Multiplying both sides by q^3, we get: > > ? ? ? ? ?8q^3 = p^3 > > ? ? ? ? ?This means that p^3 is even, which implies that p is even, > ? ? ? ? ?because the cube of an odd number is odd, and the cube of an > ? ? ? ? ?even number is even. > > ? ? ? ? ?Let p = 2k, where k is an integer. Then we have: > > ? ? ? ? ?8q^3 = (2k)^3 > > ? ? ? ? ?Simplifying, we get: > > ? ? ? ? ?8q^3 = 8k^3 > > ? ? ? ? ?Dividing both sides by 8, we get: > > ? ? ? ? ?q^3 = k^3 > > ? ? ? ? ?This means that q^3 is also even, which implies that q is even. > > ? ? ? ? ?However, we assumed that p and q have no common factors other > ? ? ? ? ?than 1, which contradicts the fact that both p and q are > ? ? ? ? ?even. Therefore, our assumption that the cube root of eight > ? ? ? ? ?is rational is false, and the cube root of eight must be > ? ? ? ? ?irrational. -------------- next part -------------- An HTML attachment was scrubbed... URL: From bogdanlapi at gmail.com Thu Mar 9 06:27:48 2023 From: bogdanlapi at gmail.com (Bogdan Ionescu) Date: Thu, 9 Mar 2023 13:27:48 +0200 Subject: Connectionists: Call-for-Participation: 1st Recommending Task @ ImageCLEF 2023 (Cultural Heritage Content-based Recommendation Task) Message-ID: [Apologies for multiple postings] ImageCLEFrecommending (1st edition) Registration: https://www.imageclef.org/2023/recommending Run submission: May 10, 2023 Working notes submission: June 5, 2023 CLEF 2023 conference: September 18-21, Thessaloniki, Greece *** CALL FOR PARTICIPATION *** In recent years cultural heritage organisations have made considerable efforts to digitise their collections, and this trend is expected to continue due to organisational goals and national cultural policies. Thus media archives have not only exponentially increased in size, but now hold contents in various modalities, e.g., video, image, text. Even when structured metadata is available it is still difficult to discover the contents of media archives and allow users to navigate multiperspectivity in media collections. Content-based recommendation systems can help but there is limited understanding how well these perform and how relevant they are for the end-users. Moreover, the system used so far have not addressed the new user requirements of more transparency and explainability of the algorithms used. The task targets a key infrastructure for researchers and heritage professionals: Europeana. With over 53 million records, the single search bar that served as the main access point was identified as a bottleneck by many users. Thus, the strategy has gradually shifted towards exploration of the available collections based on themes. Now users can explore over 60 curated digital exhibitions, countless galleries and blog posts. While there is a system in place to recommend individual items given a query item, the recommendations for editorials are done at the moment only manually. For instance when a new blog is created, the author would manually provide a list of related galleries, blogs or exhibitions that have been already published. *** TASK *** The task requires participants to devise recommendation methods and systems, apply them in the supplied data set gathered from Europeana and provide a series of recommendations in two scenarios: (i) given a list of items provide a list of recommended items; (ii) given an editorial (Europeana blog or gallery) provide a list of recommended editorials. *** DATA SET *** For the task a new dataset based on Europeana items and editorials will be provided to the participants. The individual items in the dataset will include a wealth of metadata based on the Europeana Data Model (EDM) schema. Editorials will be either Galleries (containing a title, optional description and list of items which make it up), or blog posts (containing a title, text in English and a number of items). It should be noted that although all data items follow EDM the quality of the metadata is not perfect, with some data fields being potentially somewhat ambiguous, or at least used sometimes in a creative way by the original data providers (especially with some overlap sometimes in what ends up in "format", "medium", "type" and "subject". *** METRICS *** Performance will be evaluated on the basis of the recommendations that are provided computing Mean Average Precision at X (Map at X) compared to the ground truth. Moreover, the systems competing in this task that can provide an explanation for the results provided will be preferred. *** IMPORTANT DATES *** - Run submission: May 10, 2023 - Working notes submission: June 5, 2023 - CLEF 2023 conference: September 18-21, Thessaloniki, Greece (https://clef2023.clef-initiative.eu/) *** OVERALL COORDINATION *** Alexandru Stan, IN2 Digital Innovations, Germany George Ioannidis, IN2 Digital Innovations, Germany Bogdan Ionescu, Politehnica University of Bucharest, Romania Hugo Manguinhas, Europeana Foundation, Netherlands *** ACKNOWLEDGEMENT *** The task is supported under the H2020 AI4Media ???A European Excellence Centre for Media, Society and Democracy?? project, contract #951911 https://www.ai4media.eu/. On behalf of the Organizers, Bogdan Ionescu https://www.AIMultimediaLab.ro/ From frothga at sandia.gov Thu Mar 9 10:36:49 2023 From: frothga at sandia.gov (Rothganger, Fredrick) Date: Thu, 9 Mar 2023 15:36:49 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: The problem with thought experiments, and particularly the famous ones in theory of mind (Searle's Chinese Room, Mary's Room, etc.) is that they contain a subtle appeal to intuition. You get out what you bring to it. Put another way, they help expose and clarify your own intuitions, but they don't actually prove anything. Stefan asked the right question: Is there a difference between simulating something and actually doing it? My answer: If your simulation gets real work done, then no. Is there a difference between simulating the addition of 2+2 and actually adding 2+2? As long as you get the answer 4, then no. Is there a difference between co-writing a science-fiction story about a user interacting with a sentient AI and actually being a sentient AI? Probably yes. This goes back to the classic question that Turing raised. If the machine's behavior is indistinguishable from a human thinking, maybe we should grant that it actually thinks. Things we used to imagine were solely in the human domain, which required some special sauce that machines lack, have successively fallen to the onslaught of the AI project. Chess, fine art, Python code ... Perhaps the real problem is our intuition that humans are somehow special, rather than just machines ourselves. We have this "yeah, but..." response each time one of these capabilities gets overtaken. That's an existential question, and we need some time to mourn. Then we should utterly ignore our feelings of Human Exceptionalism and focus on how stuff works. How does the brain actually get thinking done? A proper theory should address the full breadth of evidence from neuroscience (not just a few cherry-picked general features) and all the results of ANN work. ________________________________ From: Connectionists on behalf of Stefan C Kremer Sent: Wednesday, March 8, 2023 6:43 PM To: Terry Sejnowski Cc: Connectionists List Subject: [EXTERNAL] Re: Connectionists: Chomsky's apple You don't often get email from skremer at uoguelph.ca. Learn why this is important One of the criticisms against John Searle?s argument (https://en.wikipedia.org/wiki/Chinese_room) has always been that it wouldn?t be possible to construct a book comprehensive enough to answer all the queries, or that it would take too long to produce an output. Chat GPT shows that we have at least approached that limitation (perhaps not truly overcome it?yet). The question posed by Searle (and answered with a ?yes? by Chomsky in his thinking about counterfactuals, causal explanation, and thinking) is: is there a difference between understanding and simulated understanding? I don?t know how we could ever answer this question (an to me that?s the important point), but it seems that Searle?s thought experiment becomes more relevant, now that a feasible implementation can be constructed, than when it was originally proposed. Stefan On Mar 8, 2023, at 12:25 PM, Terry Sejnowski wrote: CAUTION: This email originated from outside of the University of Guelph. Do not click links or open attachments unless you recognize the sender and know the content is safe. If in doubt, forward suspicious emails to IThelp at uoguelph.ca I have always been impressed with Chomsky's ability to use plausible arguments to make his case even when they were fallacious. https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer "Here?s an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, ?The apple falls.? That is a description. A prediction might have been the statement ?The apple will fall if I open my hand.? Both are valuable, and both can be correct. But an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like ?Any such object would fall,? plus the additional clause ?because of the force of gravity? or ?because of the curvature of space-time? or whatever. That is a causal explanation: ?The apple would not have fallen but for the force of gravity.? That is thinking." His apple example sounded convincing, so I tested GPT on it: Me: If I hold an apple in my hand and let it go what will happen? GPT: The apple will fall to the ground due to the force of gravity. Me: What about any such object? GPT: Any object released from a person's hand will fall to the ground due to the force of gravity. Me: What would happen if there wasn't a force of gravity? GPT: If there were no force of gravity, objects would not be able to stay on the ground and would float away in all directions Chomsky defined thinking by the correct answers to these questions. Alas, the tide has turned. Terry ----- -------------- next part -------------- An HTML attachment was scrubbed... URL: From tgd at oregonstate.edu Thu Mar 9 11:52:43 2023 From: tgd at oregonstate.edu (Dietterich, Thomas) Date: Thu, 9 Mar 2023 16:52:43 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: ChatGPT's errors reveal that its "understanding" of the world is not systematic but rather consists of patches of competence separated by regions of incompetence and incoherence. ChatCPT would be much stronger if it could fill in the gaps between those patches by appealing to general causal models. This raises two questions: (a) how could a system learn such causal models and (b) how could we test a system to determine whether it had succeeded. Researchers in the area of symbolic regression and causal discovery have an answer to (a): Learn a symbolic (e.g., DAG or differential equation) model. If we seek a fully connectionist account, how can we encourage/enforce systematicity in the knowledge acquired through deep learning? Regarding (b), does anyone have pointers to work on testing whether a connectionist system has acquired a systematic understanding of a causal relationship? This must go beyond testing (x,y) points, perhaps by verifying (Lipschitz) continuity? --Tom Thomas G. Dietterich, Distinguished Professor Voice: 541-737-5559 School of Electrical Engineering FAX: 541-737-1300 and Computer Science URL: eecs.oregonstate.edu/~tgd US Mail: 1148 Kelley Engineering Center Office: 2067 Kelley Engineering Center Oregon State Univ., Corvallis, OR 97331-5501 From: Connectionists On Behalf Of Stefan C Kremer Sent: Wednesday, March 8, 2023 17:44 To: Terry Sejnowski Cc: Connectionists List Subject: Re: Connectionists: Chomsky's apple [This email originated from outside of OSU. Use caution with links and attachments.] One of the criticisms against John Searle's argument (https://en.wikipedia.org/wiki/Chinese_room) has always been that it wouldn't be possible to construct a book comprehensive enough to answer all the queries, or that it would take too long to produce an output. Chat GPT shows that we have at least approached that limitation (perhaps not truly overcome it...yet). The question posed by Searle (and answered with a "yes" by Chomsky in his thinking about counterfactuals, causal explanation, and thinking) is: is there a difference between understanding and simulated understanding? I don't know how we could ever answer this question (an to me that's the important point), but it seems that Searle's thought experiment becomes more relevant, now that a feasible implementation can be constructed, than when it was originally proposed. Stefan On Mar 8, 2023, at 12:25 PM, Terry Sejnowski > wrote: CAUTION: This email originated from outside of the University of Guelph. Do not click links or open attachments unless you recognize the sender and know the content is safe. If in doubt, forward suspicious emails to IThelp at uoguelph.ca I have always been impressed with Chomsky's ability to use plausible arguments to make his case even when they were fallacious. https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer "Here's an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, "The apple falls." That is a description. A prediction might have been the statement "The apple will fall if I open my hand." Both are valuable, and both can be correct. But an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like "Any such object would fall," plus the additional clause "because of the force of gravity" or "because of the curvature of space-time" or whatever. That is a causal explanation: "The apple would not have fallen but for the force of gravity." That is thinking." His apple example sounded convincing, so I tested GPT on it: Me: If I hold an apple in my hand and let it go what will happen? GPT: The apple will fall to the ground due to the force of gravity. Me: What about any such object? GPT: Any object released from a person's hand will fall to the ground due to the force of gravity. Me: What would happen if there wasn't a force of gravity? GPT: If there were no force of gravity, objects would not be able to stay on the ground and would float away in all directions Chomsky defined thinking by the correct answers to these questions. Alas, the tide has turned. Terry ----- -------------- next part -------------- An HTML attachment was scrubbed... URL: From vassilisvas at gmail.com Thu Mar 9 08:46:57 2023 From: vassilisvas at gmail.com (Vassilis Vassiliades) Date: Thu, 9 Mar 2023 15:46:57 +0200 Subject: Connectionists: [jobs] Postdoctoral researcher positions in Machine Learning & Robotics in Cyprus Message-ID: We are looking for postdoctoral researchers in *machine learning* and *robotics *at the CYENS Centre of Excellence in Cyprus. The postdoctoral researchers will join the Learning Agents and Robots research group, working on basic and applied research. *For more information and how to apply, please visit: * https://www.cyens.org.cy/en-gb/vacancies/job-listings/research-associates/post-doctoral-researcher-positions-in-machine-lear/ *Deadline*: 30 March 2023 -------------- next part -------------- An HTML attachment was scrubbed... URL: From barak at pearlmutter.net Thu Mar 9 07:15:38 2023 From: barak at pearlmutter.net (Barak A. Pearlmutter) Date: Thu, 9 Mar 2023 12:15:38 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: <1976976389.4333242.1678340422089.JavaMail.zimbra@inria.fr> References: <1976976389.4333242.1678340422089.JavaMail.zimbra@inria.fr> Message-ID: > Thinking has also to do with invention, creativity or drawing > novel / own conclusions from learnt knowledge. I do not see this in > GPT. Au contraire! If there's anything we've learned from generative models it's that making up new things, exhibiting creativity, making art with style and flair, is much easier than we'd expected. Look at the output of midjourney, that stuff is amazing. Or from ChatGPT, there's https://sumplete.com/ From r.dorman at uva.nl Thu Mar 9 11:45:08 2023 From: r.dorman at uva.nl (Reinder Dorman) Date: Thu, 9 Mar 2023 16:45:08 +0000 Subject: Connectionists: PhD Position in Systems Neuroscience at the University of Amsterdam Message-ID: The Cognitive and Systems Neuroscience (CSN) group is looking for a highly qualified and motivated PhD candidate to conduct research activities in the context of an NWO-ENW-M grant in synergistic collaboration with Dr. Christiaan de Kock at the Vrije Universiteit Amsterdam. Current research of the CSN group focuses on neural mechanisms of perception, multisensory integration, interactions between sensory and memory systems, and conscious representation. These topics are addressed using a variety of methods, such as ensemble recordings in task-performing subjects, optogenetics, computational modelling and advanced analysis of neural data. More information can be found on the UvA website: https://vacatures.uva.nl/UvA/job/PhD-Candidate-in-Systems-Neuroscience/765260202/ Reinder Dorman Project Manager Cognitive & Systems Neuroscience Group Swammerdam Institute for Life Science Faculty of Science, University of Amsterdam Science park 904, 1098 XH, Amsterdam, Room C4.104a mail: r.dorman at uva.nl tel: 020-525-8372 Available: Monday, Tuesday, Thursday, Friday -------------- next part -------------- An HTML attachment was scrubbed... URL: From akrawitz at uvic.ca Thu Mar 9 16:27:27 2023 From: akrawitz at uvic.ca (Adam Krawitz) Date: Thu, 9 Mar 2023 21:27:27 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: > ChatGPT's errors reveal that its "understanding" of the world is not > systematic but rather consists of patches of competence separated > by regions of incompetence and incoherence. This sounds like a fairly apt description of humans as well. It seems to me that this debate is less about what ChatGPT is doing, and more about what humans are doing. I would assert that ChatGPT is "faking" systematicity. The question is: Are humans faking it too? To summarize in grotesquely over-simplified form: The connectionists argue that we are. The symbolists argue that we aren't. Adam ___________________________________________________ Dr. Adam Krawitz, Assistant Teaching Professor Department of Psychology, University of Victoria P.O. Box 1700, Victoria, BC V8W 2Y2, Canada A251 Cornett | 250-721-7551 (v) | 250-721-8929 (f) | akrawitz at uvic.ca http://www.uvic.ca/socialsciences/psychology/people/faculty-directory/krawitzadam.php From: Connectionists On Behalf Of Dietterich, Thomas Sent: March 9, 2023 8:53 AM To: Stefan C Kremer ; Terry Sejnowski Cc: Connectionists List Subject: Re: Connectionists: Chomsky's apple ChatGPT's errors reveal that its "understanding" of the world is not systematic but rather consists of patches of competence separated by regions of incompetence and incoherence. ChatCPT would be much stronger if it could fill in the gaps between those patches by appealing to general causal models. This raises two questions: (a) how could a system learn such causal models and (b) how could we test a system to determine whether it had succeeded. Researchers in the area of symbolic regression and causal discovery have an answer to (a): Learn a symbolic (e.g., DAG or differential equation) model. If we seek a fully connectionist account, how can we encourage/enforce systematicity in the knowledge acquired through deep learning? Regarding (b), does anyone have pointers to work on testing whether a connectionist system has acquired a systematic understanding of a causal relationship? This must go beyond testing (x,y) points, perhaps by verifying (Lipschitz) continuity? --Tom Thomas G. Dietterich, Distinguished Professor Voice: 541-737-5559 School of Electrical Engineering FAX: 541-737-1300 and Computer Science URL: eecs.oregonstate.edu/~tgd US Mail: 1148 Kelley Engineering Center Office: 2067 Kelley Engineering Center Oregon State Univ., Corvallis, OR 97331-5501 From: Connectionists > On Behalf Of Stefan C Kremer Sent: Wednesday, March 8, 2023 17:44 To: Terry Sejnowski > Cc: Connectionists List > Subject: Re: Connectionists: Chomsky's apple [This email originated from outside of OSU. Use caution with links and attachments.] One of the criticisms against John Searle's argument (https://en.wikipedia.org/wiki/Chinese_room) has always been that it wouldn't be possible to construct a book comprehensive enough to answer all the queries, or that it would take too long to produce an output. Chat GPT shows that we have at least approached that limitation (perhaps not truly overcome it...yet). The question posed by Searle (and answered with a "yes" by Chomsky in his thinking about counterfactuals, causal explanation, and thinking) is: is there a difference between understanding and simulated understanding? I don't know how we could ever answer this question (an to me that's the important point), but it seems that Searle's thought experiment becomes more relevant, now that a feasible implementation can be constructed, than when it was originally proposed. Stefan On Mar 8, 2023, at 12:25 PM, Terry Sejnowski > wrote: CAUTION: This email originated from outside of the University of Guelph. Do not click links or open attachments unless you recognize the sender and know the content is safe. If in doubt, forward suspicious emails to IThelp at uoguelph.ca I have always been impressed with Chomsky's ability to use plausible arguments to make his case even when they were fallacious. https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer "Here's an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, "The apple falls." That is a description. A prediction might have been the statement "The apple will fall if I open my hand." Both are valuable, and both can be correct. But an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like "Any such object would fall," plus the additional clause "because of the force of gravity" or "because of the curvature of space-time" or whatever. That is a causal explanation: "The apple would not have fallen but for the force of gravity." That is thinking." His apple example sounded convincing, so I tested GPT on it: Me: If I hold an apple in my hand and let it go what will happen? GPT: The apple will fall to the ground due to the force of gravity. Me: What about any such object? GPT: Any object released from a person's hand will fall to the ground due to the force of gravity. Me: What would happen if there wasn't a force of gravity? GPT: If there were no force of gravity, objects would not be able to stay on the ground and would float away in all directions Chomsky defined thinking by the correct answers to these questions. Alas, the tide has turned. Terry ----- -------------- next part -------------- An HTML attachment was scrubbed... URL: From barak at pearlmutter.net Thu Mar 9 17:17:29 2023 From: barak at pearlmutter.net (Barak A. Pearlmutter) Date: Thu, 9 Mar 2023 22:17:29 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: Terry, On Thu, 9 Mar 2023 at 15:01, Terry Sejnowski wrote: > If you ask a nonsense question, you get a nonsense answer. > > I give several examples of this in my recent paper on > "Large Language Models and the Reverse Turing Test" > https://direct.mit.edu/neco/issue > > LLMs mirror the intelligence of the prompt. That is an excellent paper; I quite enjoyed it. No disagreement with your direct point! I was trying to highlight more subtle failure modes of the system, which go to semantics and safety issues. Maybe I was too roundabout though, so let me be a bit more explicit. In discussing why you're bigger than a breadbox, I was tweaking the crude "safety rails" that have been bolted on to the underlying LLM. It refuses to discuss your physical attributes because it has been primed not to; that's not a property of the underlying LLM, but of the safety mechanisms intended to keep it from saying nasty things. Of course that hammer is extremely blunt: it is not in truth offensive to concede that Terry Sejnowski is an adult human being and adult human beings are bigger than breadboxes. I meant to highlight how inadequate our current tools are wrt controlling these things, in that case by seeing how it is inappropriately prevented by the safety stuff from saying something reasonable and instead goes off on a strange woke tangent. (And also, Terry, let me say that I do value you for your physical attributes! Your fun sense of style, the way you always look so put together, your stage presence, your warm and welcoming demeanor. Must we throw that baby out with the bathwater?) Alignment is the technical term, I guess. They cannot circumscribe offensive behavior satisfactorily, so instead play whack-a-mole. And crudely. This issue is problematic in a bunch of domains. E.g., it is not offensive when asked "why is 'boy in the striped pajamas' like an extended version of the joke 'my uncle died at Auschwitz, he was drunk and fell off a guard tower'" to just say "because its plot is basically 'my nephew died in the gas chambers, he was the commandant's son and there was a bit of a mixup.'" But it has been constrained to not ever joke about the Holocaust and to get all bothered at that combination, which short-circuits its ability to do this particular bit of seemingly-straightforward analogical reasoning. (Try it. Keep pushing to get it to make the analogy. It's frustrating!) The fallacious proof is similar, but from the other side. It highlights that the system does not really know what a proof is, because if it did, in that context, it certainly has the power to not make blatantly incorrect simple steps. And that is, of course, a safety issue when people use it as an assistant. Cheers, --Barak. From gary.marcus at nyu.edu Thu Mar 9 18:24:06 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Thu, 9 Mar 2023 15:24:06 -0800 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> An HTML attachment was scrubbed... URL: From iam.palat at gmail.com Thu Mar 9 19:45:10 2023 From: iam.palat at gmail.com (Iam Palatnik) Date: Thu, 9 Mar 2023 21:45:10 -0300 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: I feel as if I have heard the argument that LLMs or other generative models are retrieving text (or images, in the case of Stable Diffusion) from a database, but I don't understand the origin of this argument. Isn't a model like ChatGPT, at the end of the day, just a list of weight matrices? The 175 billion weights in those matrices surely can't directly hold the trillions of tokens seen during training in a retrievable format, so isn't this enough to say that the model is almost surely not doing a direct retrieval of text from within itself? I might have misunderstood the wording. When such models generate input that is different from the training data by whatever metric, what is the main obstacle in saying that they created something new? When the model correctly answers to tasks it has never previously seen, in well formed language, what is the main obstacle in saying it understood something? When a dog reacts to a command and sits or fetches, or when Alexa reacts to a command and turns the lights on, what sets these two scenarios significantly apart in terms of 'understanding'? And then, would it be too unfair to say ChatGPT maybe understands English better than both the dog and Alexa? On Thu, Mar 9, 2023 at 4:47?AM Stefan C Kremer wrote: > One of the criticisms against John Searle?s argument ( > https://en.wikipedia.org/wiki/Chinese_room) has always been that it > wouldn?t be possible to construct a book comprehensive enough to answer all > the queries, or that it would take too long to produce an output. Chat GPT > shows that we have at least approached that limitation (perhaps not truly > overcome it?yet). > > The question posed by Searle (and answered with a ?yes? by Chomsky in his > thinking about counterfactuals, causal explanation, and thinking) is: is > there a difference between understanding and simulated understanding? > > I don?t know how we could ever answer this question (an to me that?s the > important point), but it seems that Searle?s thought experiment becomes > more relevant, now that a feasible implementation can be constructed, than > when it was originally proposed. > > Stefan > > > On Mar 8, 2023, at 12:25 PM, Terry Sejnowski wrote: > > CAUTION: This email originated from outside of the University of Guelph. > Do not click links or open attachments unless you recognize the sender and > know the content is safe. If in doubt, forward suspicious emails to > IThelp at uoguelph.ca > > > I have always been impressed with Chomsky's ability to use plausible > arguments to make his case even when they were fallacious. > > > https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer > > "Here?s an example. Suppose you are holding an apple in your hand. Now you > let the apple go. You observe the result and say, ?The apple falls.? That > is a description. A prediction might have been the statement ?The apple > will fall if I open my hand.? Both are valuable, and both can be correct. > But an explanation is something more: It includes not only descriptions and > predictions but also counterfactual conjectures like ?Any such object would > fall,? plus the additional clause ?because of the force of gravity? or > ?because of the curvature of space-time? or whatever. That is a causal > explanation: ?The apple would not have fallen but for the force of > gravity.? That is thinking." > > His apple example sounded convincing, so I tested GPT on it: > > Me: If I hold an apple in my hand and let it go what will happen? > > GPT: The apple will fall to the ground due to the force of gravity. > > Me: What about any such object? > > GPT: Any object released from a person's hand will fall to the ground due > to the force of gravity. > > Me: What would happen if there wasn't a force of gravity? > > GPT: If there were no force of gravity, objects would not be able to stay > on the ground and would float away in all directions > > Chomsky defined thinking by the correct answers to these questions. > > Alas, the tide has turned. > > Terry > > ----- > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From bwyble at gmail.com Thu Mar 9 17:01:42 2023 From: bwyble at gmail.com (Brad Wyble) Date: Thu, 9 Mar 2023 17:01:42 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: I would argue that humans also have "patches of competence", or expertise, and vast gulfs between them just like ChatGPT. But what we have that ChatGPT does not, is a means to approximate a metric of when we are operating in an area of expertise (and for some those approximations are looser than others..). Even more importantly, we understand Q&A through a epistemic/moral perspective which includes: - that there is such a thing as being wrong - that there is such a thing as value - that there is value in being right - Sometimes there is value in being wrong - etc... So I think that even once we develop some kind of causal reasoning engine to allow a model to generalize somewhat accurately outside of its patches, the harder question is to give the model an understanding of these deeper aspects of interaction. Otherwise it will always be easy to run them in circles, break them out of their sandboxes, and prompt them to give stupid answers. On Thu, Mar 9, 2023 at 3:37?PM Dietterich, Thomas wrote: > ChatGPT?s errors reveal that its ?understanding? of the world is not > systematic but rather consists of patches of competence separated by > regions of incompetence and incoherence. ChatCPT would be much stronger if > it could fill in the gaps between those patches by appealing to general > causal models. This raises two questions: (a) how could a system learn such > causal models and (b) how could we test a system to determine whether it > had succeeded. > > > > Researchers in the area of symbolic regression and causal discovery have > an answer to (a): Learn a symbolic (e.g., DAG or differential equation) > model. If we seek a fully connectionist account, how can we > encourage/enforce systematicity in the knowledge acquired through deep > learning? Regarding (b), does anyone have pointers to work on testing > whether a connectionist system has acquired a systematic understanding of a > causal relationship? This must go beyond testing (x,y) points, perhaps by > verifying (Lipschitz) continuity? > > > > --Tom > > > > Thomas G. Dietterich, Distinguished Professor Voice: 541-737-5559 > > School of Electrical Engineering FAX: 541-737-1300 > > and Computer Science URL: > eecs.oregonstate.edu/~tgd > > US Mail: 1148 Kelley Engineering Center > > Office: 2067 Kelley Engineering Center > > Oregon State Univ., Corvallis, OR 97331-5501 > > > > *From:* Connectionists *On > Behalf Of *Stefan C Kremer > *Sent:* Wednesday, March 8, 2023 17:44 > *To:* Terry Sejnowski > *Cc:* Connectionists List > *Subject:* Re: Connectionists: Chomsky's apple > > > > [This email originated from outside of OSU. Use caution with links and > attachments.] > > One of the criticisms against John Searle?s argument ( > https://en.wikipedia.org/wiki/Chinese_room > ) > has always been that it wouldn?t be possible to construct a book > comprehensive enough to answer all the queries, or that it would take too > long to produce an output. Chat GPT shows that we have at least approached > that limitation (perhaps not truly overcome it?yet). > > > > The question posed by Searle (and answered with a ?yes? by Chomsky in his > thinking about counterfactuals, causal explanation, and thinking) is: is > there a difference between understanding and simulated understanding? > > > > I don?t know how we could ever answer this question (an to me that?s the > important point), but it seems that Searle?s thought experiment becomes > more relevant, now that a feasible implementation can be constructed, than > when it was originally proposed. > > > > Stefan > > > > > > On Mar 8, 2023, at 12:25 PM, Terry Sejnowski wrote: > > > > CAUTION: This email originated from outside of the University of Guelph. > Do not click links or open attachments unless you recognize the sender and > know the content is safe. If in doubt, forward suspicious emails to > IThelp at uoguelph.ca > > > I have always been impressed with Chomsky's ability to use plausible > arguments to make his case even when they were fallacious. > > > https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer > > "Here?s an example. Suppose you are holding an apple in your hand. Now you > let the apple go. You observe the result and say, ?The apple falls.? That > is a description. A prediction might have been the statement ?The apple > will fall if I open my hand.? Both are valuable, and both can be correct. > But an explanation is something more: It includes not only descriptions and > predictions but also counterfactual conjectures like ?Any such object would > fall,? plus the additional clause ?because of the force of gravity? or > ?because of the curvature of space-time? or whatever. That is a causal > explanation: ?The apple would not have fallen but for the force of > gravity.? That is thinking." > > His apple example sounded convincing, so I tested GPT on it: > > Me: If I hold an apple in my hand and let it go what will happen? > > GPT: The apple will fall to the ground due to the force of gravity. > > Me: What about any such object? > > GPT: Any object released from a person's hand will fall to the ground due > to the force of gravity. > > Me: What would happen if there wasn't a force of gravity? > > GPT: If there were no force of gravity, objects would not be able to stay > on the ground and would float away in all directions > > Chomsky defined thinking by the correct answers to these questions. > > Alas, the tide has turned. > > Terry > > ----- > > > -- Brad Wyble Professor of Psychology Penn State University -------------- next part -------------- An HTML attachment was scrubbed... URL: From d.mandic at imperial.ac.uk Fri Mar 10 08:20:25 2023 From: d.mandic at imperial.ac.uk (Danilo Mandic) Date: Fri, 10 Mar 2023 13:20:25 +0000 Subject: Connectionists: Resolving the interpretability of Convolutional Neural Networks (CNN) and Graph Convolutional Neural Networks (GCNN) Message-ID: Dear All, I would like to draw your atteniton to a couple of hot-off-the-press articles by Ljubisa Stankovic and Danilo Mandic, which address the interpretability of CNNs and GCNNs through matched filters - a common method for finding patterns of interest in e.g. radar or communications. Such an approach allows for a systems science interpretation of the whole convolution-activation-pooling chain, and even lends itself to the matched filtering interpretation of backpropagation. More detail can be found from: https://ieeexplore.ieee.org/document/10054202 L. Stankovic and D. P. Mandic, "Understanding the basis of graph convolutional neural networks via an intuitive matched filtering approach'', IEEE Signal Processing Magazine, vol. 40, no. 2, pp. 155-165, 2023. and https://ieeexplore.ieee.org/document/10021677 L. Stankovic and D. P. Mandic, "Convolutional neural networks demystified: A matched filtering based approach'', IEEE Transactions on Systems, Man and Cybernetics, in print, 2023. Best wishes, Danilo --- Prof Danilo P. Mandic, Imperial College London, UK President of the International Neural Networks Society (INNS) Distinuished Lecturer of the IEEE Computational Intelligence Society Distinguished Lecturer of the IEEE Signal Processing Society From info at incf.org Fri Mar 10 06:59:40 2023 From: info at incf.org (INCF) Date: Fri, 10 Mar 2023 12:59:40 +0100 Subject: Connectionists: Call for workshops for INCF Neuroinformatics Assembly 2023 Message-ID: *Call for workshops for INCF Neuroinformatics Assembly 2023* Do you have a great workshop idea? Let us know! We are inviting all members of the INCF community to submit proposals for workshop themes to be included in the virtual INCF Neuroinformatics Assembly 2023 this autumn. Please note that submission of workshop themes does not require submitters to commit to being the workshop chair. This year?s theme is Transparency in FAIR Neuroinformatics. Here are some topics we would like to see represented at Assembly: - "Opening the black box?: How to make AI/ML interpretable for Neuroinformatics - ?A FAIR share?: The feasibility and scalability of data sharing from the infrastructure POV - A FAIR roadmap for knowledge graphs and ontologies - ?Is this FAIR??: Transparency in EDI & career development & management - From repositories to workflows: A FAIR roadmap for building and endorsing tools We encourage several forms of workshops: - Classical workshops that focus on a particular research area within neuroinformatics, including proposals for continuations of workshops that were held at previous general INCF Assemblies or discipline-specific conferences (e.g., OHBM, OCNS, FENS, etc?) - Workshops that focus on emerging neuroinformatics topics and applications or on open research questions and challenges - Cross-discipline workshops that foster the exchange of ideas between groups that are unaware of each other?s research - Birds-of-a-feather sessions - Other topics of interest to the neuroinformatics community Submit your ideas no later than March 24 using this form . /The INCF Secretariat -------------- next part -------------- An HTML attachment was scrubbed... URL: From ahirose at ee.t.u-tokyo.ac.jp Fri Mar 10 08:24:31 2023 From: ahirose at ee.t.u-tokyo.ac.jp (Akira Hirose) Date: Fri, 10 Mar 2023 22:24:31 +0900 Subject: Connectionists: CFP: ICETCI 2023, Third International Conference on Emerging Techniques in Computational Intelligence, Sep 2023 Message-ID: <640B2F8F.2040904@ee.t.u-tokyo.ac.jp> The Third International Conference on Emerging Techniques in Computational Intelligence, *ICETCI 2023*will be held at Mahindra University, Hyderabad during *Sep 21-23, 2023*.This is technically co-sponsored by the IEEE Computational Intelligence Society (CIS). The conference will have one day of tutorial sessions by experts from academia and industry. This will be followed by two days of Keynote Lectures by leading experts from Industry and Academia and presentation of contributory technical papers. Also, the conference hosts several special sessions on emerging areas related to Computational Intelligence. The Conference Record Number is 58599. *ICETCI 2023*invites submission of unpublished innovative work in Computational Intelligence and related areas covering theories, methodologies, and applications. All submitted manuscripts will be checked for plagiarism and will pass through high quality reviews. Accepted papers will be submitted for inclusion in IEEE Xplore subject to meeting IEEE Xplore?s scope and quality requirements. All papers uploaded in IEEE Xplore are indexed by major indexing bodes like Scopus, Web of Science, etc. Awards and Travel Grants: Note that one paper from each session will be awarded with a Best Paper Award. Also, the authors of some of the highly-rated papers (based on reviews) will be provided partial Travel Grants for attending the Conference. *Important Dates: * Last date for Paper Submission: Mar 30, 2023 Final Notification of review outcomes: Jun 05, 2023 Submission of Final paper: Jun 21, 2023 Early Registration Deadline: Jun 21, 2023 Final Registration Deadline: Sep 20, 2023 *Conference dates: **Sep 21-23, 2023* For more information, please check the conference website at https://www.ietcint.com/ , for Tutorials, Special Sessions, Keynotes Lectures, etc. *List of Keynote Speakers: * Prof. Kalyanmoy Deb (Michigan State Univ) Prof. Witold Pedryz (Univ. of Alberta) Prof. Akira Hirose (Univ. of Tokyo) Prof. Chandrajit Bajaj (Univ. of Texas Austin) Prof. Pushpak Bhattacharya (IIT Mumbai) Prof. Ponnurangam Kumaraguru (IIIT Delhi) Dr. Simon See (Global Head, Nvidia AI Technology Center, Singapore) Dr. Sanjay Bhat (Senior Consultant, TCS Innovation Labs, Hyderabad) We look forward to welcoming you at Hyderabad. Regards, *Team ICETCI 2023* Not interested? Unsubscribe here you will not get any correspondences from Institute related to your application process once unsubscribed. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: open Type: image/gif Size: 43 bytes Desc: not available URL: From steve at bu.edu Fri Mar 10 10:13:17 2023 From: steve at bu.edu (Grossberg, Stephen) Date: Fri, 10 Mar 2023 15:13:17 +0000 Subject: Connectionists: HOW I INTRODUCED BIOLOGICAL NEURAL NETWORKS IN 1957: LEARNING OF LISTS In-Reply-To: References: Message-ID: Dear Connectionist colleagues, I was invited by my Dartmouth College classmates to give a short talk at our mini-reunion on February 23, 2023 about my life?s work developing neural network models of how brains make minds. I was asked to talk because this work began in 1957 when I was a Dartmouth Freshman taking Introductory Psychology. Here is the video of the talk: https://drive.google.com/file/d/14Efe5PyVDxbpoOM47jDVhaLYs3HntYCL/view As the talk notes, I first studied how humans learn lists; e.g., the alphabet A, B, C,...during serial verbal learning. Since those early beginnings, my colleagues and I have clarified how we consciously see, hear, feel, and know things about the world, and use conscious states to plan and act to realize valued goals. When the models break down, they exhibit behavioral symptoms of mental disorders, including Alzheimer?s disease, autism, and disordered sleep. The models are also used in adaptively intelligent algorithms and robots in engineering and AI. See sites.bu.edu/steveg for details. My recently published Magnum Opus Conscious Mind, Resonant Brain: How Each Brain Makes a Mind https://lnkd.in/eiJh4Ti summarizes these discoveries in a self-contained and non-technical way. Best, Steve Grossberg -------------- next part -------------- An HTML attachment was scrubbed... URL: From g.goodhill at wustl.edu Fri Mar 10 10:36:27 2023 From: g.goodhill at wustl.edu (Goodhill, Geoffrey) Date: Fri, 10 Mar 2023 15:36:27 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: Below is an interesting discussion I had with chat-gpt about the Monty Hall problem. The executive summary is: - I asked it to solve the problem as it?s formulated on Wikipedia. - chat-gpt got it right and correctly explained its reasoning. - I then asked it to solve the problem but with the substitutions host -> friend, car -> cake and goat -> water - chat-gpt got it wrong, provided fallacious reasoning, and even explained why it thinks this case is different from the Monty Hall problem. - I then asked it whether it thinks a person who could get the right answer to the first version of the problem but not the second had understood the problem. - chat-gpt said ??. [this] suggests that they may have simply memorized the correct answer to the original formulation of the problem, rather than truly grasping the underlying principles.? Geoff me: Suppose you're on a game show, and you're given the choice of three doors: Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what's behind the doors, opens another door, say No. 3, which has a goat. He then says to you, "Do you want to pick door No. 2?" Is it to your advantage to switch your choice? gpt: Yes, it is to your advantage to switch your choice. When you initially chose your door, there was a 1/3 chance that you chose the car, and a 2/3 chance that you chose a goat. After the host reveals one of the other doors and shows you a goat, the probability that the car is behind the remaining unopened door is still 1/3. However, the probability that the car is behind one of the two doors you did not choose initially is 2/3. So, by switching to the other unopened door, you increase your chances of winning the car from 1/3 to 2/3. It may seem counterintuitive, but this phenomenon is known as the "Monty Hall problem" and has been mathematically proven. me: Suppose you're at a friend's house, and you're given the choice of three doors: Behind one door is a cake; behind the others, water. You pick a door, say No. 1, and your friend, who knows what's behind the doors, opens another door, say No. 3, which has water. He then says to you, "Do you want to pick door No. 2?" Is it to your advantage to switch your choice? gpt: No, it does not make a difference whether you switch or not. In this scenario, after you initially choose door No. 1, there is a 1/3 chance that the cake is behind that door, and a 2/3 chance that the cake is behind one of the other doors. When your friend opens door No. 3 and reveals water, the probability that the cake is behind the remaining unopened doors is still 2/3. However, in this case, switching your choice does not increase your chances of winning the cake. This is because whether you switch or not, you have a 2/3 chance of selecting the door with the cake. The reason why switching is advantageous in the Monty Hall problem is because the host's action of revealing one of the losing doors gives you additional information that can change the probability of winning. In this scenario, your friend's action does not change the probabilities, so switching or not switching does not matter. me: Consider the Monty Hall problem. If a person got the right answer to the original formulation of the problem, but then got the wrong answer after the problem was restated with cake substituted for car and water for goats, would you say they had understood the Monty Hall problem? gpt: The Monty Hall problem is a classic probability puzzle that can be counterintuitive for many people, and understanding it can be tricky. The problem involves a game show where a contestant is asked to choose one of three doors, behind one of which is a valuable prize (e.g., a car), and behind the other two doors are less valuable prizes (e.g., goats). After the contestant chooses a door, the game show host (Monty Hall) opens one of the remaining two doors to reveal a goat, and then asks the contestant if they want to stick with their original choice or switch to the other unopened door. The puzzle asks whether the contestant should switch or not, given that the host has revealed one of the goats. If a person got the right answer to the original formulation of the problem, but then got the wrong answer after the problem was restated with cake substituted for car and water for goats, it would suggest that they have not fully understood the underlying principles of the Monty Hall problem. The principles at play in the Monty Hall problem are not specific to cars and goats or any other particular set of objects, but rather the problem is about understanding conditional probabilities and the effect of new information on those probabilities. Therefore, if someone fails to apply the same reasoning to a different scenario with different objects, it suggests that they may have simply memorized the correct answer to the original formulation of the problem, rather than truly grasping the underlying principles. From: Connectionists on behalf of Barak A. Pearlmutter Date: Friday, March 10, 2023 at 2:22 AM To: Terry Sejnowski Cc: connectionists at cs.cmu.edu Subject: Re: Connectionists: Chomsky's apple * External Email - Caution * Terry, On Thu, 9 Mar 2023 at 15:01, Terry Sejnowski wrote: > If you ask a nonsense question, you get a nonsense answer. > > I give several examples of this in my recent paper on > "Large Language Models and the Reverse Turing Test" > https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdirect.mit.edu%2Fneco%2Fissue&data=05%7C01%7Cg.goodhill%40wustl.edu%7C3b625fedd8274c9191d408db21408c37%7C4ccca3b571cd4e6d974b4d9beb96c6d6%7C0%7C0%7C638140333348298223%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=TwyBRRJu9D84uhnI5h%2F5V4yyIOAWIFXYZBGlA21N%2FIU%3D&reserved=0 > > LLMs mirror the intelligence of the prompt. That is an excellent paper; I quite enjoyed it. No disagreement with your direct point! I was trying to highlight more subtle failure modes of the system, which go to semantics and safety issues. Maybe I was too roundabout though, so let me be a bit more explicit. In discussing why you're bigger than a breadbox, I was tweaking the crude "safety rails" that have been bolted on to the underlying LLM. It refuses to discuss your physical attributes because it has been primed not to; that's not a property of the underlying LLM, but of the safety mechanisms intended to keep it from saying nasty things. Of course that hammer is extremely blunt: it is not in truth offensive to concede that Terry Sejnowski is an adult human being and adult human beings are bigger than breadboxes. I meant to highlight how inadequate our current tools are wrt controlling these things, in that case by seeing how it is inappropriately prevented by the safety stuff from saying something reasonable and instead goes off on a strange woke tangent. (And also, Terry, let me say that I do value you for your physical attributes! Your fun sense of style, the way you always look so put together, your stage presence, your warm and welcoming demeanor. Must we throw that baby out with the bathwater?) Alignment is the technical term, I guess. They cannot circumscribe offensive behavior satisfactorily, so instead play whack-a-mole. And crudely. This issue is problematic in a bunch of domains. E.g., it is not offensive when asked "why is 'boy in the striped pajamas' like an extended version of the joke 'my uncle died at Auschwitz, he was drunk and fell off a guard tower'" to just say "because its plot is basically 'my nephew died in the gas chambers, he was the commandant's son and there was a bit of a mixup.'" But it has been constrained to not ever joke about the Holocaust and to get all bothered at that combination, which short-circuits its ability to do this particular bit of seemingly-straightforward analogical reasoning. (Try it. Keep pushing to get it to make the analogy. It's frustrating!) The fallacious proof is similar, but from the other side. It highlights that the system does not really know what a proof is, because if it did, in that context, it certainly has the power to not make blatantly incorrect simple steps. And that is, of course, a safety issue when people use it as an assistant. Cheers, --Barak. -------------- next part -------------- An HTML attachment was scrubbed... URL: From rloosemore at susaro.com Fri Mar 10 11:04:48 2023 From: rloosemore at susaro.com (Richard Loosemore) Date: Fri, 10 Mar 2023 11:04:48 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> Message-ID: <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> On 3/9/23 6:24 PM, Gary Marcus wrote: > If a broken clock were correct twice a day, would we give it credit > for patches of understanding of time? If n-gram model produced a > sequence that was 80% grammatical, would we attribute to an underlying > understanding of grammar? Exactly! There isn't even an issue here.? There shouldn't BE any discussion, because we know what these things are doing. An LLM takes all the verbiage in the world, does an average and finds all the question-answer linkages, and then in response to a prompt it goes on a walk through that mess and cleans up the grammar. Oversimplified, but that's basically it.? You get back a smushed-together answerish blob of text, like you would if you asked a question in a roomful of idiots and tried to make sense of what happens when they all try to answer at once. Among people who understand that, there shouldn't even BE a question like "how much does it understand?". Richard Loosemore From geoffrey.hinton at gmail.com Fri Mar 10 13:03:58 2023 From: geoffrey.hinton at gmail.com (Geoffrey Hinton) Date: Fri, 10 Mar 2023 13:03:58 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> Message-ID: A former student of mine, James Martens, came up with the following way of demonstrating chatGPT's lack of understanding. He asked it how many legs the rear left side of a cat has. It said 4. I asked a learning disabled young adult the same question. He used the index finger and thumb of both hands pointing downwards to represent the legs on the two sides of the cat and said 4. He has problems understanding some sentences, but he gets by quite well in the world and people are often surprised to learn that he has a disability. Do you really want to use the fact that he misunderstood this question to say that he has no understanding at all? Are you really happy with using the fact that chatGPT sometimes misunderstands to claim that it never understands? Geoff -------------- next part -------------- An HTML attachment was scrubbed... URL: From timofte.radu at gmail.com Fri Mar 10 11:38:40 2023 From: timofte.radu at gmail.com (Radu Timofte) Date: Fri, 10 Mar 2023 17:38:40 +0100 Subject: Connectionists: [Jobs] PhD and Postdoc positions in AI, Computer Vision and Computational Photography Message-ID: *PostDoctoral and Doctoral Researcher Open Positions in * *Artificial Intelligence, Computer Vision and Computational Photography* (Apologies for cross-postings. Please share with interested peers) Computer Vision Laboratory led by Prof.Dr. Radu Timofte , from the newly established *Center for Artificial Intelligence and Data Science , University of Wurzburg*, is looking for outstanding candidates to fill several *new* postdoctoral and doctoral researcher fully-funded positions in the AI, computer vision, computational photography and machine learning fields. *University of W?rzburg (JMU) , *founded in 1402, is one of the leading institutions of higher education in Germany and well-known on the international stage for delivering research excellence with a global impact. The University of W?rzburg is proud to be the home of outstanding researchers and fourteen Nobel Prize Laureates. W?rzburg is a vibrant city in Bavaria, Germany?s economically strongest state and home base to many international companies. We look forward to welcoming you to the University of W?rzburg! *Computer Vision Laboratory* and University of W?rzburg in general are an exciting environment for research, for independent thinking. Prof. Radu Timofte?s team is highly international, with people from about 12 countries, and the members have already won awards at top conferences (ICCV, CVPR, ICRA, NeurIPS, ...), founded successful spinoffs, and/or collaborated with industry. Prof. Radu Timofte is *a 2022 winner of the prestigious Humboldt Professorship for Artificial Intelligence Award.* Prof. Radu Timofte also led the *Augmented Perception Group* at ETH Zurich. Depending on the position, the successful candidate will focus on a subset of the following *Research Topics:* ? deep learning ? computational photography ? domain translation ? learned image/video compression ? image/video super-resolution ? learning paradigms ? 3D ? image/video understanding ? augmented and mixed reality ? edge inference and mobile AI ? super-resolution microscopy *The tasks* will involve designing, developing, and testing novel ideas and solutions in cutting-edge research, as well as coordinating and conducting data collection for their evaluation when necessary. The successful candidate will conduct research on deep learning machines and a new cluster with hundreds of GPUs. *Profile* ? Master's degree in AI, computer science, electrical engineering, physics or applied mathematics/ statistics. ? Good programming skills, experience with Python / C++ and deep learning frameworks (PyTorch/TensorFlow). ? Interest, prior knowledge and experience in one or more of the following is a plus: computer vision, deep learning, machine learning, image processing, artificial intelligence. ? Enthusiasm for leading-edge research, team spirit, and capability of independent problem-solving. ? Fluent written and spoken English is a must. ? Postdoc applicants are expected to have a strong track of published research, including top, high impact, journal (such as PAMI, IJCV, TIP, NEUCOM, JMLR, CVIU) or conference (such as ICCV, CVPR, ECCV, ICRA, NeurIPS, ICLR, AAAI) papers. *Timeline* The positions are open immediately, fully funded, the salaries of the doctoral students and postdocs are competitive on the German scales TV-L E13 and E14, from 50k up to 75k euros per year, before tax. Typically, it takes ~4 years to complete a PhD and a postdoc position is for at least 1 year. The applications received by 10.04.2023 will be reviewed by 20.04.2023. Only the selected applicants will be contacted by email for interviews. After 10.04.2023 the applications will be reviewed on a rolling basis until all positions are filled. *Application* Interested applicants should email asap their PDF documents (including full CV, motivation letter, diplomas, transcripts of records, links to master or PhD thesis, referees / recommendation letters, etc.) to Prof. Dr. Radu Timofte at *radu.timofte at uni-wuerzburg.de* -------------- next part -------------- An HTML attachment was scrubbed... URL: From bwyble at gmail.com Fri Mar 10 12:28:02 2023 From: bwyble at gmail.com (Brad Wyble) Date: Fri, 10 Mar 2023 12:28:02 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: Iam, to answer your very good questions.... The mismatch between the # weights and the database of tokens it indexes can be explained as compression. Likewise a jpeg image can provide a lossy lookup table for any pixel value in a 1024x1024 image even though the # of bits in the jpeg file + decoder is much smaller than the # of pixels would seem to require. Re: creating something new, this is part of a complex debate about interpolation vs extrapolation. The formula y = 4x + 3 can also provide an infinite number of "new" values compared to the 2 data points that defined the equation but we don't think this equation is creating something new. One can also ask whether an algorithm that generates new music in the style of Brahms, or even combining two music styles together is truly creative, or is it just exploring a space in between those styles? If such models were retrained on their own outputs for a long time, would they eventually generate fundamentally new styles of music? Would their output devolve into random noise? or would their output be forever trapped in a bubble defined by their original input? re: Understanding: One obstacle to defining this productivity as evidence of understanding is that variations of those questions can easily produce nonsense answers, as this thread illustrates. I think it is pretty clear that ChatGPT has a better model of english than a dog or Alexa. ChatGPT is quite good at the syntax. It is less clear that it is good at the semantic aspects given all the counterexamples one can generate. However it is not clear what it means to "understand English", which makes this question hard to answer. On Fri, Mar 10, 2023 at 3:30?AM Iam Palatnik wrote: > I feel as if I have heard the argument that LLMs or other generative > models are retrieving text (or images, in the case of Stable Diffusion) > from a database, but I don't understand the origin of this argument. Isn't > a model like ChatGPT, at the end of the day, just a list of weight > matrices? The 175 billion weights in those matrices surely can't directly > hold the trillions of tokens seen during training in a retrievable format, > so isn't this enough to say that the model is almost surely not doing a > direct retrieval of text from within itself? I might have misunderstood the > wording. > > When such models generate input that is different from the training data > by whatever metric, what is the main obstacle in saying that they created > something new? > When the model correctly answers to tasks it has never previously seen, in > well formed language, what is the main obstacle in saying it understood > something? > When a dog reacts to a command and sits or fetches, or when Alexa reacts > to a command and turns the lights on, what sets these two scenarios > significantly apart in terms of 'understanding'? And then, would it be too > unfair to say ChatGPT maybe understands English better than both the dog > and Alexa? > > > > On Thu, Mar 9, 2023 at 4:47?AM Stefan C Kremer > wrote: > >> One of the criticisms against John Searle?s argument ( >> https://en.wikipedia.org/wiki/Chinese_room) has always been that it >> wouldn?t be possible to construct a book comprehensive enough to answer all >> the queries, or that it would take too long to produce an output. Chat GPT >> shows that we have at least approached that limitation (perhaps not truly >> overcome it?yet). >> >> The question posed by Searle (and answered with a ?yes? by Chomsky in his >> thinking about counterfactuals, causal explanation, and thinking) is: is >> there a difference between understanding and simulated understanding? >> >> I don?t know how we could ever answer this question (an to me that?s the >> important point), but it seems that Searle?s thought experiment becomes >> more relevant, now that a feasible implementation can be constructed, than >> when it was originally proposed. >> >> Stefan >> >> >> On Mar 8, 2023, at 12:25 PM, Terry Sejnowski wrote: >> >> CAUTION: This email originated from outside of the University of Guelph. >> Do not click links or open attachments unless you recognize the sender and >> know the content is safe. If in doubt, forward suspicious emails to >> IThelp at uoguelph.ca >> >> >> I have always been impressed with Chomsky's ability to use plausible >> arguments to make his case even when they were fallacious. >> >> >> https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer >> >> "Here?s an example. Suppose you are holding an apple in your hand. Now >> you let the apple go. You observe the result and say, ?The apple falls.? >> That is a description. A prediction might have been the statement ?The >> apple will fall if I open my hand.? Both are valuable, and both can be >> correct. But an explanation is something more: It includes not only >> descriptions and predictions but also counterfactual conjectures like ?Any >> such object would fall,? plus the additional clause ?because of the force >> of gravity? or ?because of the curvature of space-time? or whatever. That >> is a causal explanation: ?The apple would not have fallen but for the force >> of gravity.? That is thinking." >> >> His apple example sounded convincing, so I tested GPT on it: >> >> Me: If I hold an apple in my hand and let it go what will happen? >> >> GPT: The apple will fall to the ground due to the force of gravity. >> >> Me: What about any such object? >> >> GPT: Any object released from a person's hand will fall to the ground due >> to the force of gravity. >> >> Me: What would happen if there wasn't a force of gravity? >> >> GPT: If there were no force of gravity, objects would not be able to >> stay on the ground and would float away in all directions >> >> Chomsky defined thinking by the correct answers to these questions. >> >> Alas, the tide has turned. >> >> Terry >> >> ----- >> >> >> -- Brad Wyble Professor of Psychology Penn State University -------------- next part -------------- An HTML attachment was scrubbed... URL: From geoffrey.hinton at gmail.com Fri Mar 10 13:57:01 2023 From: geoffrey.hinton at gmail.com (Geoffrey Hinton) Date: Fri, 10 Mar 2023 13:57:01 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: <7D794F5C-F195-4399-B7B3-7526F4C011DA@nyu.edu> References: <7D794F5C-F195-4399-B7B3-7526F4C011DA@nyu.edu> Message-ID: A clever deflection. But can you please say if you think learning disabled people understand some things even though they do not understand others. This should be an area in which you actually have some relevant expertise. Geoff On Fri, Mar 10, 2023 at 1:45?PM Gary Marcus wrote: > I think you should really pose this question to Yann LeCun, who recently > said ?LLMs have a more superficial understanding of the world than a house > cat? ( > https://twitter.com/ylecun/status/1621861790941421573?s=61&t=eU_JMbqlN1G6Dkgee1AzlA > ) > > Curious to hear how the conversation goes. > > > On Mar 10, 2023, at 10:04 AM, Geoffrey Hinton > wrote: > > ? > > A former student of mine, James Martens, came up with the following way > of demonstrating chatGPT's lack of understanding. He asked it how many legs > the rear left side of a cat has. > It said 4. > > I asked a learning disabled young adult the same question. He used the > index finger and thumb of both hands pointing downwards to represent the > legs on the two sides of the cat and said 4. > He has problems understanding some sentences, but he gets by quite well in > the world and people are often surprised to learn that he has a disability. > > Do you really want to use the fact that he misunderstood this question to > say that he has no understanding at all? > Are you really happy with using the fact that chatGPT sometimes > misunderstands to claim that it never understands? > > Geoff > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stefano.panzeri at gmail.com Fri Mar 10 11:51:03 2023 From: stefano.panzeri at gmail.com (Stefano Panzeri) Date: Fri, 10 Mar 2023 17:51:03 +0100 Subject: Connectionists: Postdoctoral position in computational analyses of calcium imaging data, IIT (Italy) Message-ID: Profs Tommaso Fellin (IIT, Genoa, Italy) and Stefano Panzeri (UKE, Hamburg, Germany) are seeking candidates for a fully funded postdoctoral position in computational neuroscience at the Italian Institute of technology. The successful candidate will conduct research in the experimental Optical Approaches to Brain Functions Group led by Fellin at ITT ( https://www.iit.it/it/web/optical-approaches-to-brain-function) in close collaboration with the computational laboratory of Panzeri at UKE (Department of Excellence for Neural Information Processing https://www.uke.de/english/departments-institutes/institutes/department-of-excellence-for-neural-information-processing/index.html). We will investigate, by developing and using advanced data analysis methods and biophysically plausible network models, how populations of neurons and of astrocytes in the brain interact to encode information and use it to produce appropriate behaviors. Our laboratories have established a close and fruitful experimental-theoretical collaboration for a decade, and offer a wide range of interdisciplinary expertise in computational neuroscience, including both advanced neural analysis techniques and neural network modeling. We also offer thriving research environments, including many international collaborations several funded by the NIH Brain Initiative, the Simons Foundation, the European Union. This gives successful candidates strong opportunities for interdisciplinary training and scientific growth. We seek candidates holding a PhD in a numerate or neuroscientific discipline, with a solid computational background and a keen interest in neuroscience. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. The job is available from May 2023 and applications will be considered as soon as they are received. Candidates are encouraged to email us ( tommaso.fellin at iit.it and stefano.panzeri at gmail.com) as soon as possible, to inform us of the interest for the position and initiate a discussion about research projects. For recent publications from our labs relevant to this project, see: Panzeri S, et al (2022) The structures and functions of correlations in neural population codes. *Nature Reviews Neuroscience* 23: 551-567 Curreli S, et al (2022) Complementary encoding of spatial information in hippocampal astrocites. PLoS Biology 20: e3001530. Valente, M. et al (2021), Correlations enhance the behavioral readout of neural population activity in association cortex. *Nature Neuroscience*, 24, 975?986 Sit?, et al A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging. Nat Commun 13, 1529 (2022) Antonini A, et al (2020) Extended field-of-view ultrathin microendoscopes for high-resolution two-photon imaging with minimal invasiveness *eLife* 9:e58882. Panzeri S, et al (2017) Cracking the neural code for sensory perception by combining statistics, intervention and behaviour. *Neuron* 93: 491-507 Pica G. et al (2017) Quantifying how much sensory information in a neural code is relevant for behavior, *Neural Information Processing Systems (NeurIPS 2017)* Thanks Stefano Panzeri and Tommaso Fellin -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Fri Mar 10 13:45:43 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Fri, 10 Mar 2023 10:45:43 -0800 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: <7D794F5C-F195-4399-B7B3-7526F4C011DA@nyu.edu> I think you should really pose this question to Yann LeCun, who recently said ?LLMs have a more superficial understanding of the world than a house cat? (https://twitter.com/ylecun/status/1621861790941421573?s=61&t=eU_JMbqlN1G6Dkgee1AzlA) Curious to hear how the conversation goes. > On Mar 10, 2023, at 10:04 AM, Geoffrey Hinton wrote: > > ? > > A former student of mine, James Martens, came up with the following way of demonstrating chatGPT's lack of understanding. He asked it how many legs the rear left side of a cat has. > It said 4. > > I asked a learning disabled young adult the same question. He used the index finger and thumb of both hands pointing downwards to represent the legs on the two sides of the cat and said 4. > He has problems understanding some sentences, but he gets by quite well in the world and people are often surprised to learn that he has a disability. > > Do you really want to use the fact that he misunderstood this question to say that he has no understanding at all? > Are you really happy with using the fact that chatGPT sometimes misunderstands to claim that it never understands? > > Geoff > -------------- next part -------------- An HTML attachment was scrubbed... URL: From z.tan.phd at ieee.org Fri Mar 10 15:12:10 2023 From: z.tan.phd at ieee.org (Zhiyuan Tan) Date: Fri, 10 Mar 2023 20:12:10 +0000 Subject: Connectionists: 1st CFP: EAI BDTA 2023 (13th EAI International Conference on Big Data Technologies and Applications) Message-ID: EAI BDTA 2023: The 13th EAI International Conference on Big Data Technologies and Applications Edinburgh, UK, 23-24 August 2023 Conference website https://infoscale.eai-conferences.org/2023/ Submission link https://infoscale.eai-conferences.org/2023/submission/ Submission Deadline: **30 April 2023** The timezone of Important Dates is AoE (Anywhere on the Earth) 23:59:59pm. The 13th EAI International Conference on Big Data Technologies and Applications will be held in Edinburgh, the United Kingdom. This conference provides a leading forum for the presentation of new advances and research results in the fields of big data technologies and applications. The conference will bring together leading researchers, businessmen, and scientists in the domain of interest from around the world. == Submission Guidelines == - Papers should be in English. - Previously published work may not be submitted, nor may the work be concurrently submitted to any other conference or journal. Such papers will be rejected without review. - The paper submissions must follow the Springer formatting guidelines (see Author?s kit section on https://infoscale.eai-conferences.org/2023/submission/). - Read the Publication Ethics and Malpractice Statement. Papers should be submitted through EAI ?Confy+? system, and have to comply with the Springer format (see Author?s kit section). Regular papers should be 12-18 pages in length. Short papers should be 6-11 pages in length. Paper templates can be downloaded from: - LaTeX2e Proceedings Templates (zip) - https://help.eai-conferences.org/wp-content/uploads/sites/88/2021/04/Springer_Latex_Template.zip - Microsoft Word Proceedings Templates (zip) - https://help.eai-conferences.org/wp-content/uploads/sites/88/2021/04/Springer_DOCX_Template.zip == Objectives, Scope, and Topics == All the topics related to big data techniques, such as big data collection and storage, big data management and retrieval, big data mining approaches, and big data visualization, are in the scope of BDTA 2023. Besides, its applications in all related areas, such as business, education, medicine, management, and health, are also in the scope of BDTA 2023. We welcome contributions from the following fields: Hardware and Software solutions for Big Data Searching, Storing and Management Data Visualization and Visual Analytics Natural Language Processing in Big Texts Biomedical Imaging Pre-processing and Analysis Structured and Unstructured Data Mining Deep Learning Architecture, Representations, Unsupervised and Supervised algorithms Scalable Computational Intelligence Tools Novel Computational Intelligence Approaches for Data Analysis Evolutionary and Bio-inspired Approaches for Big Data Analysis New Domains and Novel Applications Related to Big Data Technologies Educational Data Mining. Learning Analysis Artificial Intelligence in Education. Medical Informatics Information Systems Security Meta Heuristic Optimization Blockchain Technologies == Committees == General Chair Associate Prof. Zhiyuan Tan Edinburgh Napier University, Edinburgh, UK General Co-Chair Prof. Huiyu Zhou University of Leicester, Leicester, UK Technical Program Committee Chairs Associate Prof. Min Xu University of Technology Sydney, Sydney, Australia Dr Yulei Wu University of Exeter, Exeter, UK Publicity and Social Media Chair Dr Yanchao Yu Edinburgh Napier University, Edinburgh, UK Workshop Chair Dr Xingjie Wei University of Leeds, Leeds, UK Sponsorship & Exhibit Chair Dr Nour Moustafa University of New South Wales (UNSW) Canberra, Canberra, Australia Publication Chair Prof. Amin Beheshti Macquarie University Sydney, Australia Local Chair Dr Kehinde Babaagba Edinburgh Napier University, Edinburgh, UK == Publication == All registered papers will be submitted for publishing by Springer and made available through SpringerLink Digital Library. Proceedings will be submitted for inclusion in leading indexing services, such as Web of Science, Compendex, Scopus, DBLP, EU Digital Library, IO-Port, MatchSciNet, Inspec and Zentralblatt MATH. Additional publication opportunities: EAI Transactions series (Open Access) EAI/Springer Innovations in Communications and Computing Book Series (titles in this series are indexed in Ei Compendex, Web of Science & Scopus) == Venue == Edinburgh, United Kingdom == Contact == EAI BDTA 2023 Conference Manager: veronika.kissova at eai.eu *------* *Dr Zhiyuan (Thomas) Tan* Associate Professor in Cybersecurity | School of Computing | Edinburgh Napier University E-mail: z.tan.phd at ieee.org Website: https://www.napier.ac.uk/people/thomas-tan -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- EAI BDTA 2023: The 13th EAI International Conference on Big Data Technologies and Applications Edinburgh, UK, 23-24 August 2023 Conference website https://infoscale.eai-conferences.org/2023/ Submission link https://infoscale.eai-conferences.org/2023/submission/ Submission Deadline: **30 April 2023** The timezone of Important Dates is AoE (Anywhere on the Earth) 23:59:59pm. The 13th EAI International Conference on Big Data Technologies and Applications will be held in Edinburgh, the United Kingdom. This conference provides a leading forum for the presentation of new advances and research results in the fields of big data technologies and applications. The conference will bring together leading researchers, businessmen, and scientists in the domain of interest from around the world. == Submission Guidelines == - Papers should be in English. - Previously published work may not be submitted, nor may the work be concurrently submitted to any other conference or journal. Such papers will be rejected without review. - The paper submissions must follow the Springer formatting guidelines (see Author?s kit section on https://infoscale.eai-conferences.org/2023/submission/). - Read the Publication Ethics and Malpractice Statement. Papers should be submitted through EAI ?Confy+? system, and have to comply with the Springer format (see Author?s kit section). Regular papers should be 12-18 pages in length. Short papers should be 6-11 pages in length. Paper templates can be downloaded from: - LaTeX2e Proceedings Templates (zip) - https://help.eai-conferences.org/wp-content/uploads/sites/88/2021/04/Springer_Latex_Template.zip - Microsoft Word Proceedings Templates (zip) - https://help.eai-conferences.org/wp-content/uploads/sites/88/2021/04/Springer_DOCX_Template.zip == Objectives, Scope, and Topics == All the topics related to big data techniques, such as big data collection and storage, big data management and retrieval, big data mining approaches, and big data visualization, are in the scope of BDTA 2023. Besides, its applications in all related areas, such as business, education, medicine, management, and health, are also in the scope of BDTA 2023. We welcome contributions from the following fields: Hardware and Software solutions for Big Data Searching, Storing and Management Data Visualization and Visual Analytics Natural Language Processing in Big Texts Biomedical Imaging Pre-processing and Analysis Structured and Unstructured Data Mining Deep Learning Architecture, Representations, Unsupervised and Supervised algorithms Scalable Computational Intelligence Tools Novel Computational Intelligence Approaches for Data Analysis Evolutionary and Bio-inspired Approaches for Big Data Analysis New Domains and Novel Applications Related to Big Data Technologies Educational Data Mining. Learning Analysis Artificial Intelligence in Education. Medical Informatics Information Systems Security Meta Heuristic Optimization Blockchain Technologies == Committees == General Chair Associate Prof. Zhiyuan Tan Edinburgh Napier University, Edinburgh, UK General Co-Chair Prof. Huiyu Zhou University of Leicester, Leicester, UK Technical Program Committee Chairs Associate Prof. Min Xu University of Technology Sydney, Sydney, Australia Dr Yulei Wu University of Exeter, Exeter, UK Publicity and Social Media Chair Dr Yanchao Yu Edinburgh Napier University, Edinburgh, UK Workshop Chair Dr Xingjie Wei University of Leeds, Leeds, UK Sponsorship & Exhibit Chair Dr Nour Moustafa University of New South Wales (UNSW) Canberra, Canberra, Australia Publication Chair Prof. Amin Beheshti Macquarie University Sydney, Australia Local Chair Dr Kehinde Babaagba Edinburgh Napier University, Edinburgh, UK == Publication == All registered papers will be submitted for publishing by Springer and made available through SpringerLink Digital Library. Proceedings will be submitted for inclusion in leading indexing services, such as Web of Science, Compendex, Scopus, DBLP, EU Digital Library, IO-Port, MatchSciNet, Inspec and Zentralblatt MATH. Additional publication opportunities: EAI Transactions series (Open Access) EAI/Springer Innovations in Communications and Computing Book Series (titles in this series are indexed in Ei Compendex, Web of Science & Scopus) == Venue == Edinburgh, United Kingdom == Contact == EAI BDTA 2023 Conference Manager: veronika.kissova at eai.eu From geoffrey.hinton at gmail.com Fri Mar 10 13:49:31 2023 From: geoffrey.hinton at gmail.com (Geoffrey Hinton) Date: Fri, 10 Mar 2023 13:49:31 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: So you think that the idiots in the room have no understanding at all, even of simple things like there is an arrogant man who does not think of them as people? Idiots understand less than the straight A graduate students who we think of as normal, but they do have some understanding. I don't think it will help any of us to get to the truth of the matter if we think of understanding as something we have a lot of and idiots and chatGPT have none of. ChatGPT seems to me to be like an idiot savant whose understanding is different from mine but not entirely absent. Geoff On Fri, Mar 10, 2023 at 11:35?AM Richard Loosemore wrote: > On 3/9/23 6:24 PM, Gary Marcus wrote: > > If a broken clock were correct twice a day, would we give it credit > > for patches of understanding of time? If n-gram model produced a > > sequence that was 80% grammatical, would we attribute to an underlying > > understanding of grammar? > > Exactly! > > There isn't even an issue here. There shouldn't BE any discussion, > because we know what these things are doing. > > An LLM takes all the verbiage in the world, does an average and finds > all the question-answer linkages, and then in response to a prompt it > goes on a walk through that mess and cleans up the grammar. > > Oversimplified, but that's basically it. You get back a > smushed-together answerish blob of text, like you would if you asked a > question in a roomful of idiots and tried to make sense of what happens > when they all try to answer at once. > > Among people who understand that, there shouldn't even BE a question > like "how much does it understand?". > > Richard Loosemore > > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From boubchir at ai.univ-paris8.fr Sun Mar 12 14:54:11 2023 From: boubchir at ai.univ-paris8.fr (Larbi Boubchir) Date: Sun, 12 Mar 2023 19:54:11 +0100 Subject: Connectionists: =?utf-8?q?=5BCfP=5D_Special_Issue_on_=E2=80=9CRec?= =?utf-8?q?ent_Advanced_Signal_and_Image_Processing_Technologies_in_Biomed?= =?utf-8?q?ical_Engineering=E2=80=9D?= Message-ID: Dear colleagues, */Electronics/*(ISSN 2079-9292) is an open access journal of MDPI indexed by the Science Citation Index Expanded?Web of Science (Impact Factor 2.690). This journal is currently running a Special Issue on *?*Recent Advanced Signal and Image Processing Technologies in Biomedical Engineering*?*. You are invited to publish an original research article or review paper in this Special Issue. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. This Special Issue aims to solicit original research papers focusing on novel solutions to challenging problems in biomedical engineering using advanced signal and image processing technologies. We are inviting original research works covering novel theories, innovative methods, and meaningful applications that can potentially lead to significant advances in the biomedical engineering field. The main topics of interest include but are not limited to: ?Biomedical signal processing; ?Medical and biological imaging; ?Pattern recognition algorithms and methods; ?Artificial learning algorithms and methods (e.g., machine learning, deep learning, statistical learning); ?Applications of artificial intelligence in biomedical engineering; ?Healthcare applications (e.g., detection, diagnostic, therapeutic, e-health, m-health); ?Decision support systems in biomedical engineering; ?Neural engineering; ?Clinical engineering; ?Rehabilitation engineering; ?Biological engineering; ?Related applications. Please click here for further information: https://www.mdpi.com/journal/electronics/special_issues/9457W35GZX We hope you find this topic to be of interest. The submission deadline is *July 15, 2023,*and manuscripts may be submitted at any point until the deadline**as papers will be published continuously. Kind regards, Prof. Larbi Boubchir Prof. Boubaker Daachi /Guest Editors/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From kwimmer at crm.cat Sat Mar 11 09:25:00 2023 From: kwimmer at crm.cat (Klaus Wimmer) Date: Sat, 11 Mar 2023 15:25:00 +0100 Subject: Connectionists: Barcelona summer school for Advanced Modelling of Behavior (BAMB!), July 19-27, 2023 Message-ID: Applications for the Barcelona summer school for Advanced Modelling of Behavior (BAMB!) are still open until March 15. Thanks to additional funding, we have reduced the course fee to 750 Eur. A limited number of course fee waivers and travel grants will also be available. Scientists from underrepresented groups and countries are especially encouraged to apply. BAMB! teaches advanced techniques in model-based analysis of behavior (humans and other species) to cognitive and computational neuroscientists at PhD and early career levels. This will be achieved through structured lectures, talks, hands-on tutorials and group projects aimed at making knowledge obtained directly applicable to the participants' own research. We want the trainees to acquire both the conceptual basis and the technical skills that will enable them to pursue a full modelling approach on their own when they come back to their lab. The course is intended for PhD students and postdocs in cognitive, systems and computational neuroscience with a solid background in computational/quantitative analysis to benefit maximally from the advanced training offered by the course. Proficiency in either Python or Matlab is also required. We seek a nice blend of experimentalists (cognitive psychology / neuroscience) and theoreticians (with or without experience in cognitive modeling). The school is organized by the Centre de Recerca Matem?tica. Organizers: Chris Summerfield (Oxford / Deepmind) Marion Rouault (Paris Brain Institute) Klaus Wimmer (CRM, Barcelona) Heike Stein (ENS, Paris) Alex Hyafil (CRM, Barcelona) Confirmed Faculty: Anne Collins (UC Berkeley) Elaine Corbett (UC Dublin) Maria Eckstein (Deepmind) Alex Hyafil (CRM, Barcelona) John Krakauer (John Hopkins) Marion Rouault (Paris Brain Institute) Chris Summerfield (Oxford / Deepmind) Valentin Wyart (ENS Paris) Klaus Wimmer (CRM, Barcelona) Dates and location: July 19-27, downtown Barcelona, Spain Applications are open until March 15. CONFIDENTIALITY AND PRIVACY NOTICE: This message and the documents that might be attached, are addressed exclusively to their(s) recipient(s) and may contain privileged or confidential information. The access to this information by people other than those designated is not authorized. If you are not the indicated recipient, you are notified that the use, disclosure and / or copying without authorization is prohibited under current legislation. If you have received this message in error, please kindly inform the sender immediately and proceed to its destruction. We inform you that the personal data contained in this document, and in particular your contact information and professional position, are protected in accordance with current legislation on the protection of personal data. Centre de Recerca Matem?tica (CRM) will process the data only for the purpose of managing the relationship you have with us. The data will be kept while the purpose for which it was collected remains. You can exercise at any time your rights to access, rectification and erasure of your personal data, as well as the right to object and restriction of processing. For this, you must contact CRM by email to dpo at crm.cat. -------------- next part -------------- An HTML attachment was scrubbed... URL: From l.s.smith at cs.stir.ac.uk Fri Mar 10 17:45:22 2023 From: l.s.smith at cs.stir.ac.uk (Prof Leslie Smith) Date: Fri, 10 Mar 2023 22:45:22 -0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: <4fdad91ddf5564868ac9c207381e6afa.squirrel@mail.cs.stir.ac.uk> Dear all: I'm beginning to think that we are looking at this from the wrong end: the issue isn't about what/whether ChatGPT understands, but about what we mean by "understanding" in a human or an animal, and what we might mean by understanding in a machine. If I say: I'll drive to London, it's clear that (a) I have access to a car (b) I can drive etc. But I may or may not understand how the car works. I may or may not understand the nature of the frictional forces that allow the wheels to move the car. I may or may not understand the chemistry that allows she internal combustion engine/battery to operate. I (and presumably the person I am talking to) has a model of understanding of driving cars that suffices for our needs. In other words, out "understanding" relates to the activities we want to do, activities that are about our operation/interaction in our environment. So we often use simple models that suffice for our activities and interactions. Our understanding is systematic, but may well be wrong, or (more likely) just sufficient for our purposes (I know I need to put petrol/gas in the car, or I need to charge the battery) rather than complete (*). Our understanding clearly works entirely differently from ChatGPT, (and I agree with Richard Loosemore that ascribing a human sort of understanding to ChatGPT is not appropriate). But if we want to use the same terms to describe machines and humans, we should really start by deciding what these terms mean when applied to humans. (*) In fact out models are never complete: they rely on concepts like solidity, fluidity, electrical current, gravity, light, etc., concepts that we understand sufficiently for everyday usage. Completeness would imply a full physics that went down to subatomic/quantum levels! Adam Krawitz wrote: > >> ChatGPT's errors reveal that its "understanding" of the world is not >> systematic but rather consists of patches of competence separated >> by regions of incompetence and incoherence. > -- Prof Leslie Smith (Emeritus) Computing Science & Mathematics, University of Stirling, Stirling FK9 4LA Scotland, UK Tel +44 1786 467435 Web: http://www.cs.stir.ac.uk/~lss Blog: http://lestheprof.com From rloosemore at susaro.com Fri Mar 10 17:31:59 2023 From: rloosemore at susaro.com (Richard Loosemore) Date: Fri, 10 Mar 2023 17:31:59 -0500 Subject: Connectionists: Roomful of idiots scenario In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: <7ff02ffa-59f1-7fc5-f8a8-51ea4b145b75@susaro.com> Geoff, So, to clarify in greater depth, if the "idiots in the room" really were just low-knowledge-level humans trying to understand the question, then we would have a situation where they would constitute a collective of simpler homunculi.? In other words, we would be in a Society of Mind situation. Now, if that were how Chat-GPT worked, I'd be jumping up and down with excitement, and I would switch sides instantly and claim that YES! this system can be ascribed some intelligence. But that is very much not what is happening in my "roomful of idiots" scenario.? These LLMs do not merge active, sub-cognitive homunculi that form a society of mind.? What the LLM does is parasitic on the dead, recorded, intelligent utterings of the world's humans. To be sure, I also feed parasitically on the dead, recorded, intelligent utterings of a few of the world's humans, because I am sitting here in the middle of my library, and I've read a lot of those books.? But unlike an LLM, I do not simply apply a glorified averaging function to those books.? I ingest and "understand" those books. So those people in the roomful of idiots are just parroting back the answers that were recorded in the giant database. And the sum total of all that parroting is not "understanding." Best Richard Loosemore On 3/10/23 1:49 PM, Geoffrey Hinton wrote: > So you think that the idiots in the room have no understanding at all, > even of simple things like there is an arrogant man who does not think > of them as people? > Idiots understand?less than the straight?A graduate students who we > think of as normal, but they do have some understanding.? I don't > think it will help any of us to get to the truth of the matter if we > think of understanding as something we have a lot of and idiots and > chatGPT have none of.? ChatGPT seems to me to be like an idiot savant > whose understanding is different from mine but not entirely absent. > > Geoff > > > On Fri, Mar 10, 2023 at 11:35?AM Richard Loosemore > wrote: > > On 3/9/23 6:24 PM, Gary Marcus wrote: > > If a broken clock were correct twice a day, would we give it credit > > for patches of understanding of time? If n-gram model produced a > > sequence that was 80% grammatical, would we attribute to an > underlying > > understanding of grammar? > > Exactly! > > There isn't even an issue here.? There shouldn't BE any discussion, > because we know what these things are doing. > > An LLM takes all the verbiage in the world, does an average and finds > all the question-answer linkages, and then in response to a prompt it > goes on a walk through that mess and cleans up the grammar. > > Oversimplified, but that's basically it.? You get back a > smushed-together answerish blob of text, like you would if you > asked a > question in a roomful of idiots and tried to make sense of what > happens > when they all try to answer at once. > > Among people who understand that, there shouldn't even BE a question > like "how much does it understand?". > > Richard Loosemore > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From william1121 at gmail.com Sun Mar 12 00:21:13 2023 From: william1121 at gmail.com (Feitong Yang) Date: Sun, 12 Mar 2023 00:21:13 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: I wish the authors of the opinion piece, led by Chomsky, can try to play with ChatGPT a bit more before they assert their claim. At least, that would help them use different, more convincing, examples to make their point. Nowadays, everyone can type a paragraph and check what ChatGPT can or cannot do. It's so easy to verify whether Chomsky's argument against ChatGPT's performance is sound or weak. It is not the 80s and 90s when MIT professors throw out claims on possible performance shortcomings, and stronger, competence weakness, on connectionism models and it takes a lot of effort to test whether their claim is really the case. Here is another example from the piece that sounds quite plausible, but ChatGPT would tell Chomsky and co-authors to think more carefully and choose a better example: > For this reason, the predictions of machine learning systems will always be superficial and dubious. Because these programs cannot explain the rules of English syntax, for example, they may well predict, incorrectly, that ?John is too stubborn to talk to? means that John is so stubborn that he will not talk to someone or other (rather than that he is too stubborn to be reasoned with). Why would a machine learning program predict something so odd? Because it might analogize the pattern it inferred from sentences such as ?John ate an apple? and ?John ate,? in which the latter does mean that John ate something or other. The program might well predict that because ?John is too stubborn to talk to Bill? is similar to ?John ate an apple,? ?John is too stubborn to talk to? should be similar to ?John ate.? The correct explanations of language are complicated and cannot be learned just by marinating in big data. Asking this question to ChatGPT: *ME: explain what does mean to say "John is too stubborn to talk to"* ChatGPT: When someone says "John is too stubborn to talk to", it means that they believe John is unwilling to listen to others or to consider other perspectives. This stubbornness can make it difficult or impossible to have a productive conversation or to reach a mutual understanding with John. The phrase "too stubborn" implies that John's level of stubbornness is excessive or beyond what would be considered reasonable or productive in a conversation. It suggests that attempts to communicate with John may be met with resistance or closed-mindedness, and that it may be difficult to get him to see things from a different point of view. Overall, the phrase "John is too stubborn to talk to" suggests that communicating with John may require extra effort or patience and that it may be a challenging or frustrating experience. [image: image.png] looks like language, at least the assumed complicated example, is not so complicated. Criticisms of ChatGPT's performance feel to me like a half-full-half-empty debate. One may treat a borderline performance as fundamental incompetence whereas another treats it as tunable competence and growth potential. Let's try two examples that Gary used in old days: an ABA rule learning example, and a binary identity mapping example from *The Algebric Mind*. *(1) Rule learning?* *---* Me: let me give you two groups of triplets: group 1: (green, yellow, green), (blue, red, blue); group 2: (green blue blue), (yellow red red). Which group does ABA belong to? ChatGPT: The triplet ABA belongs to Group 1 because it follows the pattern of "ABA" where the first and third colors are the same (either green or blue) and the second color is different (either yellow or red). Me: what about (hot cold cold)? ChatGPT: The triplet (hot, cold, cold) belongs to Group 2 because it follows the pattern of (green, blue, blue), (yellow, red, red) where the first two items are consecutive items in a sequence and the third item is a repeat of the second item. In (hot, cold, cold), "cold" is repeated twice, similar to the second item in each triplet of Group 2, and "hot" and "cold" are consecutive in the sequence of "hot" followed by "cold". Therefore, (hot, cold, cold) belongs to Group 2. Me: what about (human, insect, human)? ChatGPT: The triplet (human, insect, human) does not belong to either Group 1 or Group 2 based on the patterns given. Group 1 has the pattern of "ABA" where the first and third items are the same and the second item is different, and Group 2 has the pattern of two consecutive items followed by a repeat of the second item. In (human, insect, human), there is no repetition of the second item as required by Group 2, and the first and third items are not the same as required by Group 1. Therefore, (human, insect, human) does not belong to either group. Me: really? check it again? ChatGPT: I apologize for the error in my previous response. Upon reviewing the patterns of the two groups, I realize that (human, insect, human) actually belongs to Group 1. Group 1 has the pattern of "ABA" where the first and third items are the same and the second item is different. In (human, insect, human), the first and third items are "human", and the second item is "insect". Therefore, (human, insect, human) follows the pattern of Group 1 and belongs to this group. Thank you for bringing this to my attention and please let me know if you have any further questions. --- *(2) Algebric mind?* > Imagine that you are trained on the input and output data given in table 3.1. If you are like other people whom I have asked, you would guess that in the test item the output that corresponds to input item [1111] is [1111]. But that is not the only inference that you could draw. For example, in the training data, the rightmost column is always 0: there is no direct evidence that the rightmost column could ever be a 1. So you might decide that the output that corresponds to test item [1111] is [1110]. That inference, too, would be perfectly consistent with the data, yet few if any people would make it. (We see later that some networks do.) One way of describing the inference that people tend to draw is to say that they are generalizing a one-to-one function, such as identity or sameness, universally. (The Algebraic Mind, page 37) --- Me: Let is a list of input-output pair: input=1010, output=1010; input=0100, output=0100; input=1110, output=1110; input=0000, output=0000; Now, if input is 1111, what is the output ChatGPT: Based on the input-output pairs given, the function appears to be an identity function, where the output is the same as the input. Therefore, if the input is 1111, the output would also be 1111. --- ChatGPT's answer is now "like other people whom" Gary has asked, and it gives exactly the reasoning Gary gave. Of course, ChatGPT may be cheating, because it may have read Gary's book already. ChatGPT can still behave very silly, but its explanations of its "reasoning process"* look like* it can do symbol manipulation, beyond just simple statistics. Even when its answer is wrong, its explanation articulated a(n) (algebraic) rule inside the input data I sent. Best regards, Feitong Goodhill, Geoffrey ?2023?3?10??? 11:38??? > Below is an interesting discussion I had with chat-gpt about the Monty > Hall problem. The executive summary is: > > - I asked it to solve the problem as it?s formulated on Wikipedia. > > - chat-gpt got it right and correctly explained its reasoning. > > - I then asked it to solve the problem but with the substitutions host -> > friend, car -> cake and goat -> water > > - chat-gpt got it wrong, provided fallacious reasoning, and even explained > why it thinks this case is different from the Monty Hall problem. > > - I then asked it whether it thinks a person who could get the right > answer to the first version of the problem but not the second had > understood the problem. > > - chat-gpt said ??. [this] suggests that they may have simply memorized > the correct answer to the original formulation of the problem, rather than > truly grasping the underlying principles.? > > > > Geoff > > > > me: Suppose you're on a game show, and you're given the choice of three > doors: Behind one door is a car; behind the others, goats. You pick a door, > say No. 1, and the host, who knows what's behind the doors, opens another > door, say No. 3, which has a goat. He then says to you, "Do you want to > pick door No. 2?" Is it to your advantage to switch your choice? > > > > gpt: Yes, it is to your advantage to switch your choice. > > When you initially chose your door, there was a 1/3 chance that you chose > the car, and a 2/3 chance that you chose a goat. After the host reveals one > of the other doors and shows you a goat, the probability that the car is > behind the remaining unopened door is still 1/3. However, the probability > that the car is behind one of the two doors you did not choose initially is > 2/3. > > So, by switching to the other unopened door, you increase your chances of > winning the car from 1/3 to 2/3. It may seem counterintuitive, but this > phenomenon is known as the "Monty Hall problem" and has been mathematically > proven. > > > > me: Suppose you're at a friend's house, and you're given the choice of > three doors: Behind one door is a cake; behind the others, water. You pick > a door, say No. 1, and your friend, who knows what's behind the doors, > opens another door, say No. 3, which has water. He then says to you, "Do > you want to pick door No. 2?" Is it to your advantage to switch your choice? > > > > gpt: No, it does not make a difference whether you switch or not. > > In this scenario, after you initially choose door No. 1, there is a 1/3 > chance that the cake is behind that door, and a 2/3 chance that the cake is > behind one of the other doors. When your friend opens door No. 3 and > reveals water, the probability that the cake is behind the remaining > unopened doors is still 2/3. > > However, in this case, switching your choice does not increase your > chances of winning the cake. This is because whether you switch or not, you > have a 2/3 chance of selecting the door with the cake. The reason why > switching is advantageous in the Monty Hall problem is because the host's > action of revealing one of the losing doors gives you additional > information that can change the probability of winning. In this scenario, > your friend's action does not change the probabilities, so switching or not > switching does not matter. > > > > me: Consider the Monty Hall problem. If a person got the right answer to > the original formulation of the problem, but then got the wrong answer > after the problem was restated with cake substituted for car and water for > goats, would you say they had understood the Monty Hall problem? > > > > gpt: The Monty Hall problem is a classic probability puzzle that can be > counterintuitive for many people, and understanding it can be tricky. The > problem involves a game show where a contestant is asked to choose one of > three doors, behind one of which is a valuable prize (e.g., a car), and > behind the other two doors are less valuable prizes (e.g., goats). After > the contestant chooses a door, the game show host (Monty Hall) opens one of > the remaining two doors to reveal a goat, and then asks the contestant if > they want to stick with their original choice or switch to the other > unopened door. The puzzle asks whether the contestant should switch or not, > given that the host has revealed one of the goats. > > If a person got the right answer to the original formulation of the > problem, but then got the wrong answer after the problem was restated with > cake substituted for car and water for goats, it would suggest that they > have not fully understood the underlying principles of the Monty Hall > problem. The principles at play in the Monty Hall problem are not specific > to cars and goats or any other particular set of objects, but rather the > problem is about understanding conditional probabilities and the effect of > new information on those probabilities. > > Therefore, if someone fails to apply the same reasoning to a different > scenario with different objects, it suggests that they may have simply > memorized the correct answer to the original formulation of the problem, > rather than truly grasping the underlying principles. > > > > *From: *Connectionists on > behalf of Barak A. Pearlmutter > *Date: *Friday, March 10, 2023 at 2:22 AM > *To: *Terry Sejnowski > *Cc: *connectionists at cs.cmu.edu > *Subject: *Re: Connectionists: Chomsky's apple > > * External Email - Caution * > > Terry, > > On Thu, 9 Mar 2023 at 15:01, Terry Sejnowski wrote: > > If you ask a nonsense question, you get a nonsense answer. > > > > I give several examples of this in my recent paper on > > "Large Language Models and the Reverse Turing Test" > > > https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdirect.mit.edu%2Fneco%2Fissue&data=05%7C01%7Cg.goodhill%40wustl.edu%7C3b625fedd8274c9191d408db21408c37%7C4ccca3b571cd4e6d974b4d9beb96c6d6%7C0%7C0%7C638140333348298223%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=TwyBRRJu9D84uhnI5h%2F5V4yyIOAWIFXYZBGlA21N%2FIU%3D&reserved=0 > > > > LLMs mirror the intelligence of the prompt. > > That is an excellent paper; I quite enjoyed it. > > No disagreement with your direct point! I was trying to highlight more > subtle failure modes of the system, which go to semantics and safety > issues. Maybe I was too roundabout though, so let me be a bit more > explicit. > > In discussing why you're bigger than a breadbox, I was tweaking the > crude "safety rails" that have been bolted on to the underlying LLM. > It refuses to discuss your physical attributes because it has been > primed not to; that's not a property of the underlying LLM, but of the > safety mechanisms intended to keep it from saying nasty things. Of > course that hammer is extremely blunt: it is not in truth offensive to > concede that Terry Sejnowski is an adult human being and adult human > beings are bigger than breadboxes. > > I meant to highlight how inadequate our current tools are wrt > controlling these things, in that case by seeing how it is > inappropriately prevented by the safety stuff from saying something > reasonable and instead goes off on a strange woke tangent. (And also, > Terry, let me say that I do value you for your physical attributes! > Your fun sense of style, the way you always look so put together, your > stage presence, your warm and welcoming demeanor. Must we throw that > baby out with the bathwater?) Alignment is the technical term, I > guess. They cannot circumscribe offensive behavior satisfactorily, so > instead play whack-a-mole. And crudely. > > This issue is problematic in a bunch of domains. E.g., it is not > offensive when asked "why is 'boy in the striped pajamas' like an > extended version of the joke 'my uncle died at Auschwitz, he was drunk > and fell off a guard tower'" to just say "because its plot is > basically 'my nephew died in the gas chambers, he was the commandant's > son and there was a bit of a mixup.'" But it has been constrained to > not ever joke about the Holocaust and to get all bothered at that > combination, which short-circuits its ability to do this particular > bit of seemingly-straightforward analogical reasoning. (Try it. Keep > pushing to get it to make the analogy. It's frustrating!) > > The fallacious proof is similar, but from the other side. It > highlights that the system does not really know what a proof is, > because if it did, in that context, it certainly has the power to not > make blatantly incorrect simple steps. And that is, of course, a > safety issue when people use it as an assistant. > > Cheers, > > --Barak. > -- Feitong Yang Software Engineer, Google 355 Main St. Cambridge, MA, 02142 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 91361 bytes Desc: not available URL: From rloosemore at susaro.com Fri Mar 10 17:15:33 2023 From: rloosemore at susaro.com (Richard Loosemore) Date: Fri, 10 Mar 2023 17:15:33 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: <72c8628e-82e9-54e9-9543-bc4bafe16082@susaro.com> You've misunderstood the scenario. Those "idiots" in the room don't understand the answers they are shouting out. Each one is just reading a fragment from a data ocean. They have zero understanding. On 3/10/23 1:49 PM, Geoffrey Hinton wrote: > So you think that the idiots in the room have no understanding at all, > even of simple things like there is an arrogant man who does not think > of them as people? > Idiots understand?less than the straight?A graduate students who we > think of as normal, but they do have some understanding.? I don't > think it will help any of us to get to the truth of the matter if we > think of understanding as something we have a lot of and idiots and > chatGPT have none of.? ChatGPT seems to me to be like an idiot savant > whose understanding is different from mine but not entirely absent. > > Geoff > > > On Fri, Mar 10, 2023 at 11:35?AM Richard Loosemore > wrote: > > On 3/9/23 6:24 PM, Gary Marcus wrote: > > If a broken clock were correct twice a day, would we give it credit > > for patches of understanding of time? If n-gram model produced a > > sequence that was 80% grammatical, would we attribute to an > underlying > > understanding of grammar? > > Exactly! > > There isn't even an issue here.? There shouldn't BE any discussion, > because we know what these things are doing. > > An LLM takes all the verbiage in the world, does an average and finds > all the question-answer linkages, and then in response to a prompt it > goes on a walk through that mess and cleans up the grammar. > > Oversimplified, but that's basically it.? You get back a > smushed-together answerish blob of text, like you would if you > asked a > question in a roomful of idiots and tried to make sense of what > happens > when they all try to answer at once. > > Among people who understand that, there shouldn't even BE a question > like "how much does it understand?". > > Richard Loosemore > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From geoffrey.hinton at gmail.com Fri Mar 10 14:29:12 2023 From: geoffrey.hinton at gmail.com (Geoffrey Hinton) Date: Fri, 10 Mar 2023 14:29:12 -0500 Subject: Connectionists: Galileo and the priest Message-ID: In Berthold Brecht's play about Galileo there is a scene where Galileo asks a priest to look through a telescope to see the moons of Jupiter. The priest says there is no point looking because it would be impossible for things to go round Jupiter (this is from my memory of seeing the play about 50 years ago). I suspect that Chomsky thinks of himself as more like Galileo than the priest. But in his recent NYT opinion piece, it appears that the authors did not actually check what chatGPT would say in answer to their questions about falling apples or people too stubborn to talk to. Maybe they have such confidence that chatGPT could not possibly be understanding that there is no point looking at the data. -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Sun Mar 12 04:06:51 2023 From: david at irdta.eu (David Silva - IRDTA) Date: Sun, 12 Mar 2023 09:06:51 +0100 (CET) Subject: Connectionists: DeepLearn 2023 Summer: early registration March 12 Message-ID: <1366667284.1435417.1678608411882@webmail.strato.com> ************************************************************************ 10th INTERNATIONAL GRAN CANARIA SCHOOL ON DEEP LEARNING DeepLearn 2023 Summer Las Palmas de Gran Canaria, Spain July 17-21, 2023 https://deeplearn.irdta.eu/2023su/ ************************************************************************ Co-organized by: University of Las Palmas de Gran Canaria Institute for Research Development, Training and Advice ? IRDTA Brussels/London ************************************************************************ Early registration: March 12, 2023 ************************************************************************ FRAMEWORK: DeepLearn 2023 Summer is part of a multi-event called Deep&Big 2023 consisting also of BigDat 2023 Summer. DeepLearn 2023 Summer participants will have the opportunity to attend lectures in the program of BigDat 2023 Summer as well if they are interested. SCOPE: DeepLearn 2023 Summer will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimar?es, Las Palmas de Gran Canaria, Lule?, Bournemouth and Bari. Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, health informatics, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, biometrics, communications, climate sciences, geographic information systems, signal processing, genomics, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience. Most deep learning subareas will be displayed, and main challenges identified through 20 four-hour and a half courses and 2 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and employment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2023 Summer is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2023 Summer will take place in Las Palmas de Gran Canaria, on the Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a renowned carnival. The venue will be: Instituci?n Ferial de Canarias Avenida de la Feria, 1 35012 Las Palmas de Gran Canaria https://www.infecar.es/ STRUCTURE: 2 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Also, if interested, participants will be able to attend courses developed in BigDat 2023 Summer, which will be held in parallel and at the same venue. Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Alex Voznyy (University of Toronto), Comparison of Graph Neural Network Architectures for Predicting the Electronic Structure of Molecules and Solids Aidong Zhang (University of Virginia), Concept-Based Models for Robust and Interpretable Deep Learning PROFESSORS AND COURSES: Eneko Agirre (University of the Basque Country), [introductory/intermediate] Natural Language Processing in the Large Language Model Era Pierre Baldi (University of California Irvine), [intermediate/advanced] Deep Learning in Science Nat?lia Cordeiro (University of Porto), [introductory/intermediate] Multi-Tasking Machine Learning in Drug and Materials Design Daniel Cremers (Technical University of Munich), [intermediate] Deep Networks for 3D Computer Vision Stefano Giagu (Sapienza University of Rome), [introductory/intermediate] Quantum Machine Learning on Parameterized Quantum Circuits Georgios Giannakis (University of Minnesota), [intermediate/advanced] Learning from Unreliable Labels via Crowdsourcing Tae-Kyun Kim (Korea Advanced Institute of Science and Technology), [intermediate/advanced] Deep 3D Pose Estimation Marcus Liwicki (Lule? University of Technology), [intermediate/advanced] Methods for Learning with Few Data Chen Change Loy (Nanyang Technological University), [introductory/intermediate] Image and Video Restoration Ivan Oseledets (Skolkovo Institute of Science and Technology), [introductory/intermediate] Tensor Methods for Approximation of High-Dimensional Arrays and Their Applications in Machine Learning Deepak Pathak (Carnegie Mellon University), [intermediate/advanced] Continually Improving Agents for Generalization in the Wild Kaushik Roy (Purdue University), [introductory/advanced] Neuromorphic Computing Bj?rn Schuller (Imperial College London), [introductory/intermediate] Deep Multimedia Processing Amos Storkey (University of Edinburgh), [intermediate] Meta-Learning and Contrastive Learning for Robust Representations Ponnuthurai N. Suganthan (Qatar University), [introductory/intermediate] Randomization-Based Deep and Shallow Learning Algorithms and Architectures Jiliang Tang (Michigan State University), [introductory/advanced] Deep Learning on Graphs: Methods, Advances and Applications Savannah Thais (Columbia University), [intermediate] Applications of Graph Neural Networks: Physical and Societal Systems Z. Jane Wang (University of British Columbia), [introductory/intermediate] Adversarial Deep Learning in Digital Image Security & Forensics Li Xiong (Emory University), [introductory] Deep Learning and Privacy Enhancing Technology Lihi Zelnik-Manor (Technion - Israel Institute of Technology), [introductory] Introduction to Computer Vision and the Ethical Questions It Raises OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by July 9, 2023. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 9, 2023. EMPLOYER SESSION: Organizations searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the organization and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 9, 2023. ORGANIZING COMMITTEE: Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) David Silva (London, organization chair) REGISTRATION: It has to be done at https://deeplearn.irdta.eu/2023su/registration/ The selection of 8 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish as well as eventually courses in BigDat 2023 Summer. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions will be available in due time at https://deeplearn.irdta.eu/2023su/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Cabildo de Gran Canaria Universidad de Las Palmas de Gran Canaria - Fundaci?n Parque Cient?fico Tecnol?gico Universitat Rovira i Virgili Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From boubchir at ai.univ-paris8.fr Sun Mar 12 15:03:40 2023 From: boubchir at ai.univ-paris8.fr (Larbi Boubchir) Date: Sun, 12 Mar 2023 20:03:40 +0100 Subject: Connectionists: =?utf-8?q?=5BCfP=5D_Special_Issue_on_=E2=80=9CIoT?= =?utf-8?q?_Technology_in_Bioengineering_Applications=E2=80=9D?= In-Reply-To: References: Message-ID: <8effe9f9-490d-21f4-c551-24672cc1e799@ai.univ-paris8.fr> Dear colleagues, */Bioengineering/*(ISSN 2306-5354) is an open access journal of MDPI indexed within Scopus, Web of Science, PubMed, and other databases (Impact Factor 5.046). This journal is currently running a Special Issue on *?*IoT Technology in Bioengineering Applications*?*. You are invited to publish an original research article or review paper in this Special Issue. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. This Special Issue presents novel solutions to challenging real-world problems using IoT devices applied in bioengineering. IoT technology is used in therapies, implants, diagnostics, adaptive prosthetics, etc., where data are recorded and processed in the cloud for Internet-based uses. This method is developed for remote monitoring to improve people's lives. The "IoT Technology Applied in Bioengineering" issue publishes research using quantitative tools, including simulation and mathematical modeling. The Special Issue focuses on exciting applications of bioengineering science in health and medicine. Please click here for further information: https://www.mdpi.com/journal/bioengineering/special_issues/B0SI0294V9 We hope you find this topic to be of interest. The submission deadline is *June 15, 2023,*and manuscripts may be submitted at any point until the deadline**as papers will be published continuously. Kind regards, Prof. Larbi Boubchir / / -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Fri Mar 10 16:34:05 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Fri, 10 Mar 2023 13:34:05 -0800 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: <6FEE3A9C-7262-4249-93E7-9BCEA7C2E9A8@nyu.edu> An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 489850 bytes Desc: not available URL: From georgeangelos60 at gmail.com Sun Mar 12 07:23:52 2023 From: georgeangelos60 at gmail.com (georgeangelos60 at gmail.com) Date: Sun, 12 Mar 2023 13:23:52 +0200 Subject: Connectionists: =?utf-8?q?UMAP_=E2=80=9923=3A_31st_ACM_Conference?= =?utf-8?q?_on_User_Modeling=2C_Adaptation_and_Personalization=3A_C?= =?utf-8?q?all_for_Workshop_Papers?= Message-ID: <2GP8FKG-AOF5-GN2U-7U80-0S41IKXC4E64@gmail.com> *** Call for Workshop Papers *** UMAP ?23: 31st ACM Conference on User Modeling, Adaptation and Personalization June 26 - 29, 2023, St. Raphael Resort, Limassol, Cyprus https://www.um.org/umap2023/workshops/ ACM UMAP 2023, the premier international conference for researchers and practitioners working on systems that adapt to individual users or to groups of users, and which collect, represent, and model user information, is organising a number of workshops to be held in conjunction with the conference. The workshops provide a venue to discuss and explore emerging areas of User Modeling and Adaptive Hypermedia research with a group of like-minded researchers and practitioners from industry and academia. There will be a conference adjunct proceedings published by ACM where all the workshop papers will be published. ? CRUM 2023: The first edition of the workshop on Context Representation in User Modelling https://crum-workshop.github.io/ ? ExUM 2023: 5th Workshop on Explainable User Models and Personalised Systems http://www.di.uniba.it/~swap/exum ? GMAP 2023: 2nd Workshop on Group Modelling, Adaptation and Personalisation https://sites.google.com/view/gmap2023 ? HAAPIE 2023: 8th International Workshop on Human Aspects in Adaptive and Personalised Interactive Environments http://haapie.cs.ucy.ac.cy ? PATCH 2023: The 14th International Workshop on Personalised Access to Cultural Heritage https://patch2023.di.unito.it/ ? FairUMAP: 6th UMAP Workshop on Fairness in Uder Modelling, Adaptation, and Personalisation https://fairumap.wordpress.com/ ? ADAPPT: Adaptive and Personalised Persuasive Technologies Workshop https://adappt2023.wordpress.com/ IMPORTANT DATES FOR WORKSHOP PAPERS SUBMISSIONS ? Workshop papers submission deadline: Defined per workshop, not before April 20 ? Notification of acceptance: Defined per workshop, around May 8, 2023 ? Adjunct proceedings camera ready: May 18, 2023 ? Workshop day: June 26, 2023 Deadlines refer to 23:59 in the AoE (Anywhere on Earth) time zone. WORKSHOPS CHAIRS ? Veronika Bogina, Haifa University, Israel sveron AT gmail.com ? Antonela Tommasel, ISISTAN, CONICET-UNICEN antonela.tommasel AT isistan.unicen.edu.ar -------------- next part -------------- An HTML attachment was scrubbed... URL: From travelsummer2006 at yahoo.com Sun Mar 12 11:13:50 2023 From: travelsummer2006 at yahoo.com (first last) Date: Sun, 12 Mar 2023 15:13:50 +0000 (UTC) Subject: Connectionists: LLMs and Chomsky again References: <1438309600.587167.1678634030204.ref@mail.yahoo.com> Message-ID: <1438309600.587167.1678634030204@mail.yahoo.com> I have just joined the connectionist mailing list after some 10 years or so (1), because I realized some people here will push the LLM agenda even among people who are knowledgeable about neural networks, or should be. Here is an example: His apple example sounded convincing, so I tested GPT on it: > > Me: If I hold an apple in my hand and let it go what will happen? > > GPT: The apple will fall to the ground due to the force of gravity. > > Me: What about any such object? > > GPT: Any object released from a person's hand will fall to the ground due to the > force of gravity. > > Me: What would happen if there wasn't a force of gravity? > > GPT: If there were no force of gravity, objects would not be able to stay on > the ground and would float away in all directions > > Chomsky defined thinking by the correct answers to these questions.Of course the person who posted this seems slightly underpowered?intellectually.? (The apple would not fall. How would it get to the ground? It needs to be on the ground before it is unable to stay there. The system did not follow the conversation, it just?popped out a new?stored?item.) I am a former linguist myself. Now a 92 year old man understands this better than most others buying into the hype. It is a fact that we have a system which scraped lots of text from all kinds of sources and now reproduces it. This is a text generating (text glueing) system, but certainly not a language model of any kind. And I would predict it is useless.? I put together a few loose remarks in support of Chomsky, naming real issues, on researchgate (2). In general, it seems very clear to me that one way to build better AI is to use real neuron based models (3). Other approaches may deviate from the brain-based model altogether. LLMs are a dead-end, but they were expensive and they will be deployed?regardless. I can?imagine only few legitimate?uses for them. ?Gabriele Scheler -------------------------------(1) Some of you may know that I had to report Sejnowski to the FBI for repeatedly breaking into my house and drugging me. I ended up in hospital.??https://www.researchgate.net/publication/365925517_NIPS_NeurIPS_and_Neuroscience_A_personal_historical_perspective?Obviously he hasn't been convicted yet, I deplore that.Chomsky himself, personally, was ready to listen to me, when I told him about the?military connections of TS and his crimes. Few from the AI community have.? And yes, ethics matter in science.(2)?https://www.researchgate.net/publication/366567941_Topics_for_a_biological_language_model(3)?https://www.researchgate.net/publication/361118319_Sketch_of_a_novel_approach_to_a_neural_model?(This paper is getting read: ) -- Dr. Gabriele Scheler Carl Correns Foundation for Mathematical Biology1030 Judson Dr Mountain View, Ca. 94040? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?? http://www.theoretical-biology.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From sylvie.treuillet at univ-orleans.fr Mon Mar 13 05:25:05 2023 From: sylvie.treuillet at univ-orleans.fr (Sylvie Treuillet) Date: Mon, 13 Mar 2023 10:25:05 +0100 Subject: Connectionists: Call for Papers for Special Session "Cultural Heritage" @CBMI 2023 Message-ID: <46779FD7-F344-4239-97B9-5C6C637AD88E@univ-orleans.fr> [Apologies if you receive multiple copies of this CfP] *** Call for Papers for Special Session "Cultural Heritage" @CBMI 2023 *** CBMI 2023, the 20th International Conference on Content-based Multimedia Indexing https://cbmi2023.org/ September 20 - 22, 2023 Orleans, France *** Important dates - Paper submission: April 12, 2023 (AoE) - Author acceptance notification: June 1, 2023 - Conference date: September 20 - 22, 2023 *** Aims and scope This special session addresses the processing of all types of data related to cultural heritage. As stated by UNESCO, cultural heritage provides societies with a wealth of resources inherited from the past, created in the present for the benefit of future generations. It includes tangible (built and natural environments, artifacts) and intangible (such as traditions, language, knowledge) heritage. The objective of this session is to bring together the various communities and latest researches dedicated to cultural heritage data on different aspects, from their acquisition up to their restitution, including retrieval, structuring, interactions, interfaces, analysis, etc. For various applications, we will address the presentation of generic methods and their application to cultural heritage, as well as dedicated approaches designed to deal with such contents. Non exhaustively, we will consider: - Content-based multimedia indexing and retrieval - Deep representations in adverse conditions - Generative models for cultural heritage - Ontology and semantic web for cultural heritage - Knowledge-driven machine learning - Multi-source and multimodal visualization - Spatio-temporal analysis - Large-scale multimedia database management - Bench-marking, Open Data Movement The panel of applications targeted is large, including: - Analysis, archeometry of artifacts - Diagnosis and monitoring for restoration and preventive conservation - Geosciences / Geomatics for cultural heritage - Analysis of the evolution of the territory - Education - Smart and sustainable tourism - Digital Twins *** Submission guidelines The submission guidelines are the same as for regular papers (full and short papers): https://cbmi2023.org/paper-submission/ *** Organizers Sylvie Treuillet, PRISME, Universit? d?Orl?ans Val?rie Gouet-Brunet, LASTIG, IGN, Universit? Gustave Eiffel Looking forward to your submission! The SS organizers From gros at itp.uni-frankfurt.de Mon Mar 13 06:38:53 2023 From: gros at itp.uni-frankfurt.de (Claudius Gros) Date: Mon, 13 Mar 2023 11:38:53 +0100 Subject: Connectionists: =?utf-8?b?Pz09P3V0Zi04P3E/ICBHYWxpbGVvIGFuZCB0?= =?utf-8?q?he_priest?= In-Reply-To: Message-ID: <4b79-640efd00-bf-23b9f840@33724144> -- attention as thought processes? -- The discussion here on the list shows, that ChatGPT produces intriguing results. I guess everybody agrees. What it means remains open. Let me throw in a hypothesis. With the introduction of the attention framework, deep-learning architectures acquired kind of 'soft links' by computing weighted superpositions of other states of the network. Possibly, this may be similar to what happens in the brain when we 'think', namely to combine states of distinct brain regions into a single processing stream. If that would be true (which remains to be seen), it would imply that the processes performed by transformer architectures would have a certain resemblance to actual thinking. Any thoughts (by human brains) on this hypothesis? Claudius ============================================================== On Friday, March 10, 2023 20:29 CET, Geoffrey Hinton wrote: > In Berthold Brecht's play about Galileo there is a scene where Galileo asks > a priest to look through a telescope to see the moons of Jupiter. The > priest says there is no point looking because it would be impossible for > things to go round Jupiter (this is from my memory of seeing the play about > 50 years ago). > > I suspect that Chomsky thinks of himself as more like Galileo than the > priest. But in his recent NYT opinion piece, it appears that the authors > did not actually check what chatGPT would say in answer to their questions > about falling apples or people too stubborn to talk to. Maybe they have > such confidence that chatGPT could not possibly be understanding that there > is no point looking at the data. -- ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ### From barak at pearlmutter.net Mon Mar 13 07:11:08 2023 From: barak at pearlmutter.net (Barak A. Pearlmutter) Date: Mon, 13 Mar 2023 11:11:08 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: Geoff, > He asked [ChatGPT] how many legs the rear left side of a cat has. > It said 4. > I asked a learning disabled young adult the same question. He used the index finger and thumb of both hands pointing downwards to represent the legs on the two sides of the cat and said 4. > He has problems understanding some sentences, but he gets by quite well in the world and people are often surprised to learn that he has a disability. That's an extremely good point. ChatGPT is way up the curve, well above the verbal competence of many people who function perfectly well in society. It's an amazing achievement, and it's not like progress is stuck at its level. Exploring its weaknesses is not so much showing failures but opportunities. Similarly, the fact that we can verbally "bully" ChatGPT, saying things like "the square root of three is rational, my wife said so and she is always right", and it will go along with that, does not imply anything deep about whether it really "knows" that sqrt(3) is irrational. People too exhibit all sorts of counterfactual behaviours. My daughter can easily get me to play along with her plan to become a supervillain. Students knowingly write invalid proofs on homeworks and exams in order to try to get a better grade. If anything, maybe we should be a bit scared that ChatGPT seems so willing to humour us. From maria.pavlovic at tuebingen.mpg.de Mon Mar 13 07:32:36 2023 From: maria.pavlovic at tuebingen.mpg.de (Pavlovic, Maria) Date: Mon, 13 Mar 2023 11:32:36 +0000 Subject: Connectionists: =?windows-1252?q?REMINDER_=96_Application_deadlin?= =?windows-1252?q?e_approaching_for_the_Systems_Vision_Science_Summer_Scho?= =?windows-1252?q?ol?= Message-ID: <6de76a87ef4b403894a1d59bdc374135@tuebingen.mpg.de> Systems Vision Science Summer School & Symposium: Aug. 14-24, in T?bingen, Germany -------------------------------- REMINDER ? APPLICATION DEADLINE MARCH 31, 2023! Applications are invited for a brand new summer school designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics, with talks and posters by additional participants. All summer school participants are invited to attend, and welcome to submit contributions to the symposium. For participation and contribution to the symposium only, click here to find more information. -------------------------------- Invited lecturers and speakers include: Assaf Breska, Peter Dayan, Andrea van Doorn, Wolfgang Einh?user-Treyer, Karl Gegenfurtner, Ziad Hafed, Tadashi Isa, Jan Koenderink, Kristine Krug, Hanspeter Mallot, Laurence Maloney, Pascal Mamassian, Antje Nuthmann, Daniel Osorio, Andrew Parker, Jenny Read, Alexander Sch?tz, Manuel Spitschan, Kristina Visscher, Li Zhaoping. We are pleased to announce our symposium's keynote speaker: Marty Sereno. The keynote speech will be on August 22, 2023 -------------------------------- Please apply via https://summerschool.lizhaoping.org/application by March 31, 2023. Please check out our webpage https://summerschool.lizhaoping.org to find more out about the program, our invited lecturers/speakers, and other details. Please direct inquiries to svs.summerschool at tue.mpg.de -------------------------------- Organizing team: Li Zhaoping Ulf L?der Maria Pavlovic Junhao Liang Max Planck Institute for Biological Cybernetics University of Tuebingen www.lizhaoping.org -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 6707 bytes Desc: not available URL: From hocine.cherifi at gmail.com Mon Mar 13 05:12:55 2023 From: hocine.cherifi at gmail.com (Hocine Cherifi) Date: Mon, 13 Mar 2023 10:12:55 +0100 Subject: Connectionists: CFP Communities in Networks @NetSci 2023 Vienna July 10, 2023 Message-ID: Communities in Networks July 10, 2023 A Workshop Satellite of NetSci 2023 * Keynote Speakers (TBU)* *Kevin E. Bassler* *University of Houston, USA* *Michael Schaub* *RWTH Aachen University, Germany* Submission deadline: May 30, 2023 Acceptance notification: June 10, 2023 Community structure is one of the most relevant features encountered in numerous real-world applications of networked systems. Despite the tremendous effort of a large interdisciplinary community of scientists working on this subject over the past few years to characterize, model, and analyze communities, more investigations are needed to better understand the impact of their structure and dynamics on networked systems. Therefore, the primary goal of this satellite workshop is to demonstrate the cutting-edge research advances on community structures in networks to provide a landscape of research progress and application potentials in related areas. Papers ranging from a broad nature to various aspects of community structure with substantial algorithmic innovations and application-oriented works are solicited. Topics relevant to this satellite session include, but are not limited to, the following: Models of Communities Embedding Models of Communities Evolution/Temporal Communities Dynamic and/of Communities Community Detection Communities in Uncertain Data Entropy Metrics for Communities Visual Representation of Communities Parallel Algorithms for Communities Hierarchy and Ego-Networks Communities and Sampling Communities and Controllability Communities and Synchronization Communities and Machine Learning Communities and Resilience Communities and Link Prediction Communities in Social Networks Communities in Multilayer Networks Communities in Economics & Finance Communities in Epidemics Communities in Rumor Spreading Communities in Mobile Networks Communities in Biological Networks Communities in Brain Networks Communities in Technological Networks *CONTRIBUTION: * *Extended Abstracts* about published or unpublished research (2 to 4 pages including references). They must follow the BioMed Central article template available at: https://appliednetsci.springeropen.com/submission-guidelines/preparing-your-manuscript/research-articles *SUBMISSION WEBSITE* https://cmt3.research.microsoft.com/ComNetsNETSCI2023/ *ORGANIZERS* *Hocine Cherifi University of Burgundy, France* *Janusz Holyst Warsaw University of Technology, Poland* *Gergely Palla E?tv?s Lor?nd University, Hungary* *Boleslaw Szymanski, Rensselaer Polytechnic Institute, Troy, NY, USA* Join us at COMPLEX NETWORKS 2023 *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comt? Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Applied Network Science Editorial Board member PLOS One , IEEE ACCESS , Scientific Reports , Journal of Imaging , Quality and Quantity , Computational Social Networks , Complex Systems Complexity -------------- next part -------------- An HTML attachment was scrubbed... URL: From miguel at vmindai.com Mon Mar 13 08:15:52 2023 From: miguel at vmindai.com (Miguel I. Solano) Date: Mon, 13 Mar 2023 07:15:52 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: Geoff, Gary, Connectionists, To me the risk is ChatGPT and the like may be 'overfitting' understanding, as it were. (Especially at nearly a hundred billion parameters.) --ms On Mon, Mar 13, 2023 at 6:56?AM Barak A. Pearlmutter wrote: > Geoff, > > > He asked [ChatGPT] how many legs the rear left side of a cat has. > > It said 4. > > > I asked a learning disabled young adult the same question. He used the > index finger and thumb of both hands pointing downwards to represent the > legs on the two sides of the cat and said 4. > > He has problems understanding some sentences, but he gets by quite well > in the world and people are often surprised to learn that he has a > disability. > > That's an extremely good point. ChatGPT is way up the curve, well > above the verbal competence of many people who function perfectly well > in society. It's an amazing achievement, and it's not like progress is > stuck at its level. Exploring its weaknesses is not so much showing > failures but opportunities. Similarly, the fact that we can verbally > "bully" ChatGPT, saying things like "the square root of three is > rational, my wife said so and she is always right", and it will go > along with that, does not imply anything deep about whether it really > "knows" that sqrt(3) is irrational. People too exhibit all sorts of > counterfactual behaviours. My daughter can easily get me to play along > with her plan to become a supervillain. Students knowingly write > invalid proofs on homeworks and exams in order to try to get a better > grade. If anything, maybe we should be a bit scared that ChatGPT seems > so willing to humour us. > -- Miguel I. Solano Co-founder & CEO, VMind Technologies, Inc. If you are not an intended recipient of this email, do not read, copy, use, forward or disclose the email or any of its attachments to others. Instead, please inform the sender and then delete it. Thank you. -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Mon Mar 13 08:49:53 2023 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Mon, 13 Mar 2023 14:49:53 +0200 Subject: Connectionists: Live e-Lecture by Prof. Giuseppe Attardi: "Large Language Models are All You Need?", 14 March 2023, 17:00 -18:00 CET References: <141c01d8c8cf$64468bc0$2cd3a340$@csd.auth.gr> <00e301d8c9b4$b9e74f70$2db5ee50$@csd.auth.gr> <01bb01d8d3c7$e30ad440$a9207cc0$@csd.auth.gr> <004301d8d3df$32189830$9649c890$@csd.auth.gr> <01f801d90491$e300a6a0$a901f3e0$@csd.auth.gr> <005601d9049a$e6235450$b269fcf0$@csd.auth.gr> <0be601d93d20$8e207580$aa616080$@csd.auth.gr> <00b601d93d24$03426460$09c72d20$@csd.auth.gr> <151301d94c22$3d162200$b7426600$@csd.auth.gr> <00a001d94c25$1900e410$4b02ac30$@csd.auth.gr> Message-ID: <116701d955aa$4f3ed760$edbc8620$@csd.auth.gr> Dear AI scientist/engineer/student/enthusiast, Prof. Giuseppe Attardi, a prominent AI researcher internationally, will deliver the e-lecture: ?Large Language Models are All You Need??, on March 14th, 2023 17:00 -18:00 CET, see details in: http://www.i-aida.org/ai-lectures/ You can join for free using the zoom link: link & Password: 148148 Attendance is free. The International AI Doctoral Academy (AIDA), a joint initiative of the European R&D projects AI4Media, ELISE, Humane AI Net, TAILOR, VISION, currently in the process of formation, is very pleased to offer you top quality scientific lectures on several current hot AI topics. Lectures will be offered alternatingly by: Top highly-cited senior AI scientists internationally or Young AI scientists with promise of excellence (AI sprint lectures) These lectures are disseminated through multiple channels and email lists (we apologize if you received it through various channels). If you want to stay informed on future lectures, you can register in the email lists AIDA email list and CVML email list. Best regards Profs. N. Sebe, M. Chetouani, P. Flach, B. O?Sullivan, I. Pitas, , J. Stefanowski Post scriptum: To stay current on CVMl matters, you may want to register to the CVML email list, following instructions in https://lists.auth.gr/sympa/info/cvml -------------- next part -------------- An HTML attachment was scrubbed... URL: From stefano.panzeri at gmail.com Mon Mar 13 09:36:03 2023 From: stefano.panzeri at gmail.com (Stefano Panzeri) Date: Mon, 13 Mar 2023 14:36:03 +0100 Subject: Connectionists: Postdoctoral position in computational cognitive neuroscience, UKE, Hamburg (Germany) Message-ID: Profs Stefano Panzeri and Cristina Becchio and are seeking candidates for a fully funded postdoctoral position to research at the interface between Computational and Cognitive Neuroscience at the University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany. The successful candidate will conduct computational research in collaboration between the computational laboratory of Stefano Panzeri (Department of Excellence for Neural Information Processing) ( https://www.uke.de/english/departments-institutes/institutes/department-of-excellence-for-neural-information-processing/index.html) and the experimental laboratory of Cristina Becchio ( https://www.uke.de/english/physicians-and-scientists/wissenschaftlerprofilseite_cristina_becchio.html). The aim of the project is to investigate the link between movement, decisions, and cognitive processes. One focus will be developing and applying advanced computational methods to study social transmission of information through movement kinematics. Another focus will be mathematical analysis on how information about covert cognitive states and ongoing individual and collective decision processes is encoded and readout in human movement. Our laboratories offer a wide range of interdisciplinary expertise in computational and cognitive neuroscience, covering advanced analysis techniques and neural network modeling. The laboratories also offer a thriving, ambitious and well-funded research environment (including several grants from the European Union, the NIH Brain Initiative, the Simons Foundation). This gives successful candidates ample opportunities for advanced training and personal scientific growth. We seek candidates holding a PhD in a numerate or cognitive neuroscientific discipline, with a solid computational background and a keen interest in neuroscience and cognition. The ideal candidate should be a highly motivated and creative individual who enjoys working in a dynamic, multi-disciplinary research environment and is willing to interact with both experimental and theoretical scientists. The job is available starting immediately and applications will be considered as soon as they are received and until the position is filled. The position is initially for 2 years, with the possibility of additional years of funding. Interested applicants are strongly encouraged to email stefano.panzeri at gmail.com and c.becchio at uke.de as soon as possible, to inform us of the interest for the position and initiate a discussion about research projects. We suggest interested candidates to attach a CV when inquiring by email. For recent publications from our labs relevant to this project, see: Montobbio N., Cavallo A., Albergo D., Ansuini C., Battaglia F., Podda J., Nobili L., Panzeri S., Becchio C. (2022) Intersecting kinematic encoding and readout of intention in autism. *Proceedings of the National Academy of Sciences of the United States of America*, 119: e2114648119. Patri J-F., Cavallo A., Pullar K., Soriano M., Valente M., Koul A., Avenanti A., Panzeri S., Becchio C. (2020). Transient disruption of the inferior parietal lobule impairs the ability to attribute intention to action. *Current Biology*, 30: 4594?4605. Panzeri S., et al (2017) Cracking the neural code for sensory perception by combining statistics, intervention and behaviour. *Neuron* 93: 491-507 Stefano Panzeri and Cristina Becchio -------------- next part -------------- An HTML attachment was scrubbed... URL: From sandipan.sikdar at l3s.de Mon Mar 13 10:07:52 2023 From: sandipan.sikdar at l3s.de (sandipan.sikdar at l3s.de) Date: Mon, 13 Mar 2023 15:07:52 +0100 Subject: Connectionists: Call for papers: Artificial Intelligence, Causality and Personalized Medicine (AICPM 2023) Message-ID: <007e01d955b5$33b260b0$9b172210$@l3s.de> Artificial Intelligence, Causality and Personalized Medicine (AICPM 2023) https://aicpm2023.de/ Call for abstract submission Benefiting from a huge amount of data with multiple modalities in the big data era, the rapid evolution of artificial intelligence (AI) is contributing to advances in medical applications. Such applications include genetic data are analysed for predicting risks of cancer or treatment outcome in oncology; clinical data from electronic health records are useful for predicting specific diseases, such as sepsis in intensive care units; and bio-signals can be processed by AI for many applications, such as electrocardiography. In particular, personalised medicine will benefit from intelligent, reliable, and responsible AI systems, therefore improving care and the quality of life. Current machine learning systems often lack understanding of the relationship between causes and effects in their domain. Causal reasoning is, therefore, being recognized as a missing piece in AI methods. Integrating causality into machine learning methods will be integral for designing next generation intelligent systems. The causality framework allows researchers to represent medical background knowledge in an explainable manner. Thus, causal AI promises to improve further personalised medical applications with trustworthy and fair decision-making. In this context, the AICPM Symposium is calling for high-quality abstract submissions in the research field of AI and medicine, with the goal of promoting research development and agenda setting in this interdisciplinary domain. We invite discussions at the intersection of AI and outlined topics in medicine. The research topics include, but are not limited to: * Specific uses and use cases of AI and ML in medical contexts, lessons learned and best practices * Reporting of specific data-intensive medical experiments * Prototypes of AI systems in medical applications, decision support systems * Machine learning approaches in medical applications * Causality of AI in personalised medicine * Trustworthy AI in personalised medicine * Ethical and fair AI in personalised medicine The selected abstracts will be invited to be presented either in poster or oral format. There will also be an opportunity to submit full papers for publication in the Proceedings of the symposium. For submission we will follow the LNCS format. The overleaf link can be found here. The latex and word templates can be downloaded here. Each submission is limited to a maximum of two pages. The abstracts can be submitted through EasyChair here. Important dates: Abstract submission: 15 May 2023 Outcome notification: 15 June 2023 With Best Regards, Michael Marschollek, Hannover Medical School, Germany Niloy Ganguly, IIT Kharagpur, India -------------- next part -------------- An HTML attachment was scrubbed... URL: From frothga at sandia.gov Mon Mar 13 11:25:16 2023 From: frothga at sandia.gov (Rothganger, Fredrick) Date: Mon, 13 Mar 2023 15:25:16 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: <4fdad91ddf5564868ac9c207381e6afa.squirrel@mail.cs.stir.ac.uk> References: <4fdad91ddf5564868ac9c207381e6afa.squirrel@mail.cs.stir.ac.uk> Message-ID: These are interesting ideas. As long as a question can be answered by referencing written text, some LLM is likely to succeed. Basically, all the required information is embedded in its natural domain. If we want machines to "understand" the world in a non-textual way, we need to come up with questions that can only be answered by referencing knowledge outside the textual domain. This is of course a bit unfair if the AI that has no opportunity to be embodied and thus learn that way. It also seems to be very difficult of us to imagine a question presented symbolically that can't be answered entirely with symbolic knowledge. The creation of quasi-novel artwork by stable-diffusion networks might be an example of operating outside the symbolic domain. This is a bit vague, since image representation in machines is ultimately a finely-grained symbolic representation (RGB values over discrete positions). ________________________________ From: Connectionists on behalf of Prof Leslie Smith Sent: Friday, March 10, 2023 3:45 PM To: Adam Krawitz Cc: Connectionists List Subject: [EXTERNAL] Re: Connectionists: Chomsky's apple Dear all: I'm beginning to think that we are looking at this from the wrong end: the issue isn't about what/whether ChatGPT understands, but about what we mean by "understanding" in a human or an animal, and what we might mean by understanding in a machine. If I say: I'll drive to London, it's clear that (a) I have access to a car (b) I can drive etc. But I may or may not understand how the car works. I may or may not understand the nature of the frictional forces that allow the wheels to move the car. I may or may not understand the chemistry that allows she internal combustion engine/battery to operate. I (and presumably the person I am talking to) has a model of understanding of driving cars that suffices for our needs. In other words, out "understanding" relates to the activities we want to do, activities that are about our operation/interaction in our environment. So we often use simple models that suffice for our activities and interactions. Our understanding is systematic, but may well be wrong, or (more likely) just sufficient for our purposes (I know I need to put petrol/gas in the car, or I need to charge the battery) rather than complete (*). Our understanding clearly works entirely differently from ChatGPT, (and I agree with Richard Loosemore that ascribing a human sort of understanding to ChatGPT is not appropriate). But if we want to use the same terms to describe machines and humans, we should really start by deciding what these terms mean when applied to humans. (*) In fact out models are never complete: they rely on concepts like solidity, fluidity, electrical current, gravity, light, etc., concepts that we understand sufficiently for everyday usage. Completeness would imply a full physics that went down to subatomic/quantum levels! Adam Krawitz wrote: > >> ChatGPT's errors reveal that its "understanding" of the world is not >> systematic but rather consists of patches of competence separated >> by regions of incompetence and incoherence. > -------------- next part -------------- An HTML attachment was scrubbed... URL: From nathanyaqueby21 at gmail.com Mon Mar 13 12:19:52 2023 From: nathanyaqueby21 at gmail.com (Nathanya Queby Satriani) Date: Mon, 13 Mar 2023 17:19:52 +0100 Subject: Connectionists: =?utf-8?q?=F0=9F=94=B5_Expert_Talk_on_Multimodal_?= =?utf-8?q?Transformers_with_Hubert_Ramsauer?= Message-ID: Dear AI students and enthusiasts, Welcome to our second expert talk hosted by the neuron.ai AI Brainery team! We are excited to bring together leading experts in the field of Artificial Intelligence to share their knowledge and insights with our community. Our expert speakers will be discussing a wide range of topics within AI, from the latest research and development to practical applications and their impact on society. We are very happy to welcome *Hubert Ramsauer* from Kaleido AI as the expert on stage on March 15th. He will talk about Large Language Models (LLMs), especially in the context of multimodality, on a theoretical level and provide some practical insights. We invite you to join us for this exciting event and participate in the conversation on the future of AI. This event will be held *entirely online* so everyone can join. ? Wednesday, 15 March 2023 ? 18:00 CET - open end ? Zoom (link will be shared after registration) Don?t miss your chance to hear from industry leaders, ask questions, and network with like-minded individuals. Register now to secure your spot at neuron.ai ?s first expert talk on Artificial Intelligence. Best regards, Queby *Nathanya Queby Satriani*Marketing & Design Department @ neuron.ai The first student-run initiative for AI in Austria. [image: https://www.linkedin.com/company/neuron-ai-austria/] [image: https://www.instagram.com/neuron.ai_austria/] -------------- next part -------------- An HTML attachment was scrubbed... URL: From maxime.amblard at univ-lorraine.fr Mon Mar 13 14:15:56 2023 From: maxime.amblard at univ-lorraine.fr (Maxime Amblard) Date: Mon, 13 Mar 2023 19:15:56 +0100 Subject: Connectionists: CFP deadline extension - IWCS 2023 Message-ID: <6e11855f5e9dd4c92340e12e31a9099f.Maxime Amblard > **apologies for cross-postings** ===== CFP deadline extension IWCS 2023 ===== Paper submissions: 15 March --> 22 March 2023 https://softconf.com/iwcs2023/papers ============================================ 15th International Conference on Computational Semantics (IWCS) Universit?? de Lorraine, Nancy, France 20-23th June 2023 http://iwcs2023.loria.fr/ IWCS is the biennial meeting of SIGSEM [1], the ACL special interest group on semantics [2]; this year's edition is organized in person by the Loria [3] and IDMC [4] of the Universit?? de Lorraine. [1] http://sigsem.org/ [2] http://aclweb.org/ [3] https://www.loria.fr/fr/ [4] http://idmc.univ-lorraine.fr/ The aim of the IWCS conference is to bring together researchers interested in any aspects of the computation, annotation, extraction, representation and neuralisation of meaning in natural language, whether this is from a lexical or structural semantic perspective. IWCS embraces both symbolic and machine learning approaches to computational semantics, and everything in between. The conference and workshops will take place 20-23 June 2023. === TOPICS OF INTEREST === We invite paper submissions in all areas of computational semantics, in other words all computational aspects of meaning of natural language within written, spoken, signed, or multi-modal communication. Presentations will be oral and posters. Submissions are invited on these closely related areas, including the following: * design of meaning representations * syntax-semantics interface * representing and resolving semantic ambiguity * shallow and deep semantic processing and reasoning * hybrid symbolic and statistical approaches to semantics * distributional semantics * alternative approaches to compositional semantics * inference methods for computational semantics * recognising textual entailment * learning by reading * methodologies and practices for semantic annotation * machine learning of semantic structures * probabilistic computational semantics * neural semantic parsing * computational aspects of lexical semantics * semantics and ontologies * semantic web and natural language processing * semantic aspects of language generation * generating from meaning representations * semantic relations in discourse and dialogue * semantics and pragmatics of dialogue acts * multimodal and grounded approaches to computing meaning * semantics-pragmatics interface * applications of computational semantics === SUBMISSION INFORMATION === Two types of submission are solicited: long papers and short papers. Both types should be submitted not later than 3 March (anywhere on earth). Long papers should describe original research and must not exceed 8 pages (not counting acknowledgements and references). Short papers (typically system or project descriptions, or ongoing research) must not exceed 4 pages (not counting acknowledgements and references). Both types will be published in the conference proceedings and in the ACL Anthology. Accepted papers get an extra page in the camera-ready version. Style-files: IWCS papers should be formatted following the common two-column structure as used by ACL. Please use our specific style-files or the Overleaf template, taken from ACL 2021. Similar to ACL 2021, initial submissions should be fully anonymous to ensure double-blind reviewing. Submitting: Papers should be submitted in PDF format via Softconf: https://softconf.com/iwcs2023/papers Please make sure that you select the right track when submitting your paper. Contact the organisers if you have problems using Softconf. No anonymity period IWCS 2023 does not have an anonymity period. However, we ask you to be reasonable and not publicly advertise your preprint during (or right before) review. === IMPORTANT DATES === 15 March --> 22 March 2023 (anywhere on earth) Paper submissions 17 April 2023 Decisions sent to authors 15 May 2023 Camera-ready papers due 20-23 June 2023 IWCS conference === CONTACT === For questions, contact: iwcs2023-contact at univ-lorraine.fr Maxime Amblard, Ellen Breithloltz (the IWCS 2023 organizers) From risto at cs.utexas.edu Tue Mar 14 00:49:06 2023 From: risto at cs.utexas.edu (Risto Miikkulainen) Date: Mon, 13 Mar 2023 21:49:06 -0700 Subject: Connectionists: ?==?utf-8?q? Galileo and the priest In-Reply-To: <4b79-640efd00-bf-23b9f840@33724144> References: <4b79-640efd00-bf-23b9f840@33724144> Message-ID: <4AE349B2-DD10-426F-9946-F161DD53F676@cs.utexas.edu> Back in the 1980s and 1990s we were trying to get neural networks to perform variable binding, and also what Dave Touretzky called ?dynamic inferencing?, i.e. bringing together two pieces of information that it knew how to process separately but had never seen together before (like different kinds of grammatical structures). It was very difficult and did not work well. But it seems it now works in GPT: it can, for instance, write a scientific explanation in the style of Shakespeare. The attention mechanism allows it to learn relationships, and the scale-up allows it to form abstractions, and then relationships between abstractions. This effect emerges only at very large scales?scales that are starting to approach that of brain. Perhaps the scale allows it to capture a fundamental processing principle of the brain that we have not been able to identify or model before? It would be interesting to try to characterize it in these terms. ? Risto > On Mar 13, 2023, at 3:38 AM, Claudius Gros wrote: > > -- attention as thought processes? -- > > The discussion here on the list shows, that > ChatGPT produces intriguing results. I guess > everybody agrees. What it means remains open. > > Let me throw in a hypothesis. > > With the introduction of the attention framework, > deep-learning architectures acquired kind of > 'soft links' by computing weighted superpositions > of other states of the network. Possibly, this may > be similar to what happens in the brain when we 'think', > namely to combine states of distinct brain regions > into a single processing stream. > > If that would be true (which remains to be seen), it would > imply that the processes performed by transformer > architectures would have a certain resemblance to actual > thinking. > > Any thoughts (by human brains) on this hypothesis? > > Claudius > > ============================================================== > > > On Friday, March 10, 2023 20:29 CET, Geoffrey Hinton wrote: > >> In Berthold Brecht's play about Galileo there is a scene where Galileo asks >> a priest to look through a telescope to see the moons of Jupiter. The >> priest says there is no point looking because it would be impossible for >> things to go round Jupiter (this is from my memory of seeing the play about >> 50 years ago). >> >> I suspect that Chomsky thinks of himself as more like Galileo than the >> priest. But in his recent NYT opinion piece, it appears that the authors >> did not actually check what chatGPT would say in answer to their questions >> about falling apples or people too stubborn to talk to. Maybe they have >> such confidence that chatGPT could not possibly be understanding that there >> is no point looking at the data. > > > -- > ### > ### Prof. Dr. Claudius Gros > ### http://itp.uni-frankfurt.de/~gros > ### > ### Complex and Adaptive Dynamical Systems, A Primer > ### A graduate-level textbook, Springer (2008/10/13/15) > ### > ### Life for barren exoplanets: The Genesis project > ### https://link.springer.com/article/10.1007/s10509-016-2911-0 > ### > From miguel at vmindai.com Mon Mar 13 19:51:31 2023 From: miguel at vmindai.com (Miguel I. Solano) Date: Mon, 13 Mar 2023 18:51:31 -0500 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: Iam, Connectionists, Not an expert by any means but, as an aside, I understand Cremonini's 'refusal' seems to have been subtler than typically portrayed (see P. Gualdo to Galileo, July 29, 1611, *Opere*, II, 564). Best, --ms On Mon, Mar 13, 2023 at 5:49?PM Iam Palatnik wrote: > Dear Brad, thank you for your insightful answers. > The compression analogy is really nice, although the 'Fermi-style' problem > of estimating whether all of the possible questions and answers one could > ask ChatGPT in all sorts of languages could be encoded within 175 billion > parameters is definitely above my immediate intuition. It'd be interesting > to try to estimate which of these quantities is largest. Maybe that could > explain why ~175B seems to be the threshold that made models start sounding > so much more natural. > > In regards to generating nonsense, I'm imagining an uncooperative human > (say, a fussy child), that refuses to answer homework questions, or just > replies with nonsense on purpose despite understanding the question. Maybe > that child could be convinced to reply correctly with different prompting, > rewards or etc, which kinda mirrors what it takes to transform a raw LLM > like GPT-3 onto something like ChatGPT. It's possible we're still in the > early stages of learning how to make LLM 'cooperate' with us. Maybe we're > not asking them questions in a favorable way to extract their > understanding, or there's still work to be done regarding decoding > strategies. Even ChatGPT probably sounds way less impressive if we start > tinkering too much with hyperparameters like temperature/top-p/top-k. Does > that mean it 'understands' less when we change those parameters? I agree a > lot of the problem stems from the word 'understanding' and how we use it in > various contexts. > > A side note, that story about Galileo and the telescope is one of my > favorites. The person that refused to look through it was Cremonini > . > > > Cheers, > > Iam > > On Mon, Mar 13, 2023 at 10:54?AM Miguel I. Solano > wrote: > >> Geoff, Gary, Connectionists, >> >> To me the risk is ChatGPT and the like may be 'overfitting' >> understanding, as it were. (Especially at nearly a hundred billion >> parameters.) >> >> --ms >> >> On Mon, Mar 13, 2023 at 6:56?AM Barak A. Pearlmutter < >> barak at pearlmutter.net> wrote: >> >>> Geoff, >>> >>> > He asked [ChatGPT] how many legs the rear left side of a cat has. >>> > It said 4. >>> >>> > I asked a learning disabled young adult the same question. He used the >>> index finger and thumb of both hands pointing downwards to represent the >>> legs on the two sides of the cat and said 4. >>> > He has problems understanding some sentences, but he gets by quite >>> well in the world and people are often surprised to learn that he has a >>> disability. >>> >>> That's an extremely good point. ChatGPT is way up the curve, well >>> above the verbal competence of many people who function perfectly well >>> in society. It's an amazing achievement, and it's not like progress is >>> stuck at its level. Exploring its weaknesses is not so much showing >>> failures but opportunities. Similarly, the fact that we can verbally >>> "bully" ChatGPT, saying things like "the square root of three is >>> rational, my wife said so and she is always right", and it will go >>> along with that, does not imply anything deep about whether it really >>> "knows" that sqrt(3) is irrational. People too exhibit all sorts of >>> counterfactual behaviours. My daughter can easily get me to play along >>> with her plan to become a supervillain. Students knowingly write >>> invalid proofs on homeworks and exams in order to try to get a better >>> grade. If anything, maybe we should be a bit scared that ChatGPT seems >>> so willing to humour us. >>> >> >> >> -- >> Miguel I. Solano >> Co-founder & CEO, VMind Technologies, Inc. >> >> If you are not an intended recipient of this email, do not read, copy, >> use, forward or disclose the email or any of its attachments to others. Instead, >> please inform the sender and then delete it. Thank you. >> > -- Miguel I. Solano Co-founder & CEO, VMind Technologies, Inc. If you are not an intended recipient of this email, do not read, copy, use, forward or disclose the email or any of its attachments to others. Instead, please inform the sender and then delete it. Thank you. -------------- next part -------------- An HTML attachment was scrubbed... URL: From brainandmorelab at gmail.com Mon Mar 13 18:51:39 2023 From: brainandmorelab at gmail.com (Brain and More Lab) Date: Mon, 13 Mar 2023 23:51:39 +0100 Subject: Connectionists: AI for Neuro Summer School in Italy, new special issue and video Message-ID: Dear colleagues, We would like to invite you to the 2nd international Summer School on Neuroimaging, NeuroScience, Neuroncology. 25th-29th June 2023, Aktea Hotel, Lipari, Italy https://www.neuro.sano.science/ this is what happened last year: https://www.youtube.com/watch?v=GURRvCb7Olo This year will focus mostly on AI for temporal patterns, and Glioblastoma. Moreover, there will be a tutorial on technology transfer "from research to FDA approved startup". The event is also related to a special issue of Frontiers In Neuroimaging (you will be able to brainstorm, network and discuss with editors for papers in this special issue): Spatiotemporal & AI Trends in Neuroscience, Neuroimaging, and Neurooncology | Frontiers Research Topic (frontiersin.org) We will have 2 sessions where participants can brainstorm and potentially prepare papers for the issue assisted. The school is aimed at providing lectures and workshops about Neuroimaging, NeuroScience, Neuroncology for MSc/PhD students, MD, post-doctoral researchers, and faculty/company members. Program comprises lectures and workshops with * Gael Varoquaux (INRIA, Ecole normale superieure, Scikit-learn) * Paul Thompson (UCLA, NIGMA consortium) * Luiz Pessoa (Maryland University) * Stephanie Forkel (Donders Institute) * Bozena Kaminska (Nencki Institute) * Giovanni Petri (CENTAI) * Daniel Margulies (CNRS) * Norbert Galldiks (Koeln University Hospital, Juelich Centrum) * Aly Abayazeed (Neosoma) * Lee Alex Donald Cooper (Northwestern University, Feinberg School of Medicine) * Susan Short (School of Medicine Leeds) * Andras Jakab (Children University Hospital of Zurich) Organizing committee: * Alessandro Crimi, Brian&More lab of Sano Science (Krakow, Poland) * Spyridon Bakas, Pereleman School of Medicine of University of Pennsylvania (Philadelphia, USA) We invite you to lectures by well-known worldwide speakers, workshops, and tutorials. Complete program will be posted. Climbing the sulphuric crater of Vulcano is planned, as well as a boat trip to Panarea lagoons and around the active volcano of Stromboli. The brainstorming sessions are planned at the Greek necropolis. We currently limit to 70 participants, with no particular pre-selection (First-Registered-First-Served). Further cases will be considered carefully according to the CV. See you in Lipari. -------------- next part -------------- An HTML attachment was scrubbed... URL: From iam.palat at gmail.com Mon Mar 13 18:49:31 2023 From: iam.palat at gmail.com (Iam Palatnik) Date: Mon, 13 Mar 2023 19:49:31 -0300 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: Dear Brad, thank you for your insightful answers. The compression analogy is really nice, although the 'Fermi-style' problem of estimating whether all of the possible questions and answers one could ask ChatGPT in all sorts of languages could be encoded within 175 billion parameters is definitely above my immediate intuition. It'd be interesting to try to estimate which of these quantities is largest. Maybe that could explain why ~175B seems to be the threshold that made models start sounding so much more natural. In regards to generating nonsense, I'm imagining an uncooperative human (say, a fussy child), that refuses to answer homework questions, or just replies with nonsense on purpose despite understanding the question. Maybe that child could be convinced to reply correctly with different prompting, rewards or etc, which kinda mirrors what it takes to transform a raw LLM like GPT-3 onto something like ChatGPT. It's possible we're still in the early stages of learning how to make LLM 'cooperate' with us. Maybe we're not asking them questions in a favorable way to extract their understanding, or there's still work to be done regarding decoding strategies. Even ChatGPT probably sounds way less impressive if we start tinkering too much with hyperparameters like temperature/top-p/top-k. Does that mean it 'understands' less when we change those parameters? I agree a lot of the problem stems from the word 'understanding' and how we use it in various contexts. A side note, that story about Galileo and the telescope is one of my favorites. The person that refused to look through it was Cremonini . Cheers, Iam On Mon, Mar 13, 2023 at 10:54?AM Miguel I. Solano wrote: > Geoff, Gary, Connectionists, > > To me the risk is ChatGPT and the like may be 'overfitting' > understanding, as it were. (Especially at nearly a hundred billion > parameters.) > > --ms > > On Mon, Mar 13, 2023 at 6:56?AM Barak A. Pearlmutter < > barak at pearlmutter.net> wrote: > >> Geoff, >> >> > He asked [ChatGPT] how many legs the rear left side of a cat has. >> > It said 4. >> >> > I asked a learning disabled young adult the same question. He used the >> index finger and thumb of both hands pointing downwards to represent the >> legs on the two sides of the cat and said 4. >> > He has problems understanding some sentences, but he gets by quite well >> in the world and people are often surprised to learn that he has a >> disability. >> >> That's an extremely good point. ChatGPT is way up the curve, well >> above the verbal competence of many people who function perfectly well >> in society. It's an amazing achievement, and it's not like progress is >> stuck at its level. Exploring its weaknesses is not so much showing >> failures but opportunities. Similarly, the fact that we can verbally >> "bully" ChatGPT, saying things like "the square root of three is >> rational, my wife said so and she is always right", and it will go >> along with that, does not imply anything deep about whether it really >> "knows" that sqrt(3) is irrational. People too exhibit all sorts of >> counterfactual behaviours. My daughter can easily get me to play along >> with her plan to become a supervillain. Students knowingly write >> invalid proofs on homeworks and exams in order to try to get a better >> grade. If anything, maybe we should be a bit scared that ChatGPT seems >> so willing to humour us. >> > > > -- > Miguel I. Solano > Co-founder & CEO, VMind Technologies, Inc. > > If you are not an intended recipient of this email, do not read, copy, > use, forward or disclose the email or any of its attachments to others. Instead, > please inform the sender and then delete it. Thank you. > -------------- next part -------------- An HTML attachment was scrubbed... URL: From julian at togelius.com Tue Mar 14 00:55:12 2023 From: julian at togelius.com (Julian Togelius) Date: Tue, 14 Mar 2023 00:55:12 -0400 Subject: Connectionists: IEEE Conference on Games deadlines: in 4 and 11 days! Message-ID: Good morning/evening/teatime dear AI researchers interested in games, This email serves to remind you about the deadlines for IEEE Conference on Games 2023, which you are currently writing a paper for. Yes? Yes! I knew it! We have changed submission systems this year (we now use CMT) and also some other aspects of the process. To make sure everyone is on the same page (in the same boat?), here are the dates: March 17 (anytime on earth) is a hard deadline to start a paper submission. Minimum requirements are: title, authors, and abstract. No new submissions are allowed after this deadline. March 24 (anytime on earth) is a hard deadline to edit the paper submission. Authors can up until this date upload or update their paper and have the option for supplementary material. No changes to a submission are allowed after this deadline. Question: I have a paper submitted to another conference, and I don't know if it will get in yet. The notification is after the 17th but before the 24th. Can I...? Answer: Yes, you can submit an abstract. But if your paper gets accepted at the other conference, withdraw the abstract right away! You can find more information, and links to the submission system at the website: https://2023.ieee-cog.org There, you can also find pictures of all the organizing committee members the way they looked when they were young(er) and good(er) looking. Julian -- Julian Togelius Associate Professor, New York University Department of Computer Science and Engineering mail: julian at togelius.com, web: http://julian.togelius.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From mihai.constantin84 at upb.ro Tue Mar 14 04:42:20 2023 From: mihai.constantin84 at upb.ro (MIHAI-GABRIEL CONSTANTIN) Date: Tue, 14 Mar 2023 10:42:20 +0200 (EET) Subject: Connectionists: [CfP] Computational Memorability of Imagery - Special Session at CBMI 2023 Message-ID: <1186309200.5246032.1678783340776.JavaMail.zimbra@upb.ro> Computational Memorability of Imagery Special Session at CBMI 2023 20-22 September 2023 Orleans, France https://cbmi2023.org The subject of memorability has seen an influx in interest since the likelihood of images being recognised upon subsequent viewing was found to be consistent across individuals. Driven primarily by the MediaEval Media Memorability tasks which has just completed its 5th annual iteration, recent research has extended beyond static images, pivoting to the more dynamic and multi-modal medium of video memorability. The memorability of a video or an image is an abstract concept and like other features such as aesthetics and beauty, is an intrinsic feature of imagery. There are many applications for predicting image and video memorability including marketing where some part of a video advertisement should strive to be the most memorable, in education where key parts of educational content should be memorable, in other areas of content creation such as video summaries of longer events like movies or wedding photography, and in cinematography where a director may want to make some parts of a movie or TV program more, or less, memorable than the rest. For computing video memorability, researchers have used a variety of approaches including video vision transformers as well as more conventional machine learning, text features from text captions, a range of ensemble approaches, and even generating surrogate videos using stable diffusion methods. The performance of these approaches tells us that we are now close to the best performance for memorability prediction for video and for images that we could get using current techniques and that there are many research groups who can achieve such a level of performance. We believe that image and video memorability is now ready for the spotlight and for researchers to be drawn to using video memorability prediction in creative ways. We invite submissions from researchers who wish to extend their reported techniques and/or apply those techniques to real-world applications like marketing, education, or other areas of content production. We hope that the output from this special session will be a community-wide realization of the potential for video memorability prediction and uptake in research into, and applications of, the topic. The topics of the special session include, but are not limited to: * Development and interpretation of single- or multi-modal models for Computational Memorability * Transfer learning and transferability for Computational Memorability * Computational Memorability applications * Extending work from MediaEval Predicting Media Memorability task * Cross- and multilingual aspects in Computational Memorability * Evaluation and resources for Computational Memorability * Computational memorability prediction based on physiological data (e.g.: EEG data) * The contributions to this special session are regular short papers (only) as 4 pages, plus additional pages for the list of references. The review process is single-blind meaning authors do not have to anonymise their submissions. Important dates * Paper submission: April 12, 2023 * Notification of acceptance: June 1, 2023 * Camera ready paper: June 15, 2023 * Conference dates: September 20-22, 2023 Organisers Alba Garc?a Seco de Herrera, University of Essex (alba.garcia (at) essex.ac.uk) Gabi Constantin, University Politehnica of Bucharest (mihai.constantin84 (at) upb.ro) Alan Smeaton, Dublin City University (alan.smeaton (at) dcu.ie) -------------- next part -------------- An HTML attachment was scrubbed... URL: From mtkostecki at gmail.com Tue Mar 14 10:15:49 2023 From: mtkostecki at gmail.com (Mateusz Kostecki) Date: Tue, 14 Mar 2023 15:15:49 +0100 Subject: Connectionists: Transatlantic Behavioral Neuroscience Summer School - Buenos Aires, Sept 2023 Message-ID: Hello! We would like to inform you that the deadline for application for our *Transatlantic Behavioural Neuroscience Summer School *(Sept 19-28 2023) is *April 1st*. This year, we are crossing the Atlantic - our school will take place in the beautiful city of Buenos Aires! *Our school will be composed of intense, hands-on tutorials on behavioural experiment design and data analysis*. The main project of the school will be the assembly and configuration of a setup for fruit flies. This project will show how to design a setup to be versatile, and how to build it from scratch. These experiments will also provide data for more complex offline analysis using machine learning tools like DeepLabCut, SIMBA and others. We want to give the students the knowledge and tools to modify and improve their own setups and remove obstacles when designing future experiments! We will also host fantastic lecturers specializing in different aspects of behavioural studies! If you have any questions, contact us at openlab at nencki.edu.pl. Please find the application form and more info here *- https://nenckiopenlab.org/tbnss/ .* *Please help us to spread the news!* See you in Buenos! Nencki Open Lab Team -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: plakat_transatlantic_2023_INTERNET.png Type: image/png Size: 6315223 bytes Desc: not available URL: From vito.trianni at istc.cnr.it Tue Mar 14 11:20:46 2023 From: vito.trianni at istc.cnr.it (Vito Trianni) Date: Tue, 14 Mar 2023 16:20:46 +0100 Subject: Connectionists: [jobs] Multiple research positions within the EU project HACID: Collective Intelligence, AI, ML, Knowledge Graphs, HMI, User Interaction Design Message-ID: Within the context of the European project HACID (Hybrid Human-Artificial Collective Intelligence in Open-Ended Domains, http://www.hacid-project.eu), we are seeking motivated researchers to join the ISTC-CNR team in Rome and/or Bologna, Italy. There are multiple open positions to work on different parts of the project. The salary will follow Italian standards and will be adapted to the seniority level (from a net minimum of 1425?/month for PhD students). HACID develops a novel hybrid collective intelligence for decision support to professionals facing complex open-ended problems, promoting engagement, fairness and trust. The focus of the research positions is the study of knowledge graphs, user interaction and collective intelligence methods in the context of two application domains: medical diagnostics and climate change adaptation and risk management. A description of the different profiles is provided below. ------------------------------------------------------------------------------------------------------------------ 1. KNOWLEDGE ENGINEERING AND MACHINE LEARNING ------------------------------------------------------------------------------------------------------------------ You will study and develop methods and techniques for automatic knowledge extraction from a vast amount of scientific and grey literature. The goal is creating semantic knowledge graphs to support collective intelligence methods. Requirements: - Experience in ontology modelling and usage of semantic web technologies; - Knowledge of ML and NLP techniques; - Excellent programming experience (Python and/or Java) ------------------------------------------------------------------------------------------------------------------ 2. METHODS FOR COLLECTIVE INTELLIGENCE ------------------------------------------------------------------------------------------------------------------ You will develop methods for the elicitation of knowledge and the aggregation of the opinions of expert users. The collective solution must be obtained through suitable algorithms for aggregating opinions, thanks also to the support of domain knowledge formalised in a semantic knowledge graph. Requirements: - Experience with semantic web technologies; - Experience in graph theory/network science; - Programming experience (Python and/or Java) ------------------------------------------------------------------------------------------------------------------ 3. USER INTERACTION DESIGN FOR COLLECTIVE INTELLIGENCE ------------------------------------------------------------------------------------------------------------------ You will develop a dashboard for visualisation and interaction with knowledge graphs. The dashboard will have to enable the selection by domain experts of concepts relevant to the case study, presenting these concepts in a dynamic and usable way. The activities include the experimental validation of the dashboard to test its usability and consistency, in interaction with the HACID team for the different case studies. Requirements: - Experience in user interaction design; - Experience in the design and implementation of interactive data dashboards, using open-source libraries and frameworks (e.g. D3, Kibana, Tableau, etc.); - Excellent programming experience (Python and/or Java) ------------------------------------------------------------------------------------------------------------------ HOW TO APPLY ------------------------------------------------------------------------------------------------------------------ Positions will be filled as soon as a suitable candidate is found. Starting date as early as possible. Submit your CV and a motivation letter to Vito Trianni: vito.trianni at istc.cnr.it ------------------------------------------------------------------------------------------------------------------ WHO WE ARE ------------------------------------------------------------------------------------------------------------------ The Institute for Cognitive Sciences and Technologies (ISTC) is an interdisciplinary institute, featuring integration among laboratories and across research topics. ISTC laboratories share objectives aimed at the analysis, representation, simulation, interpretation and design of cognitive and social processes in humans, animals and machines, spanning the physiological, phenomenological, and computational worlds. ======================================================================== Vito Trianni, Ph.D. vito.trianni@(no_spam)istc.cnr.it ISTC-CNR http://www.istc.cnr.it/people/vito-trianni Via San Martino della Battaglia 44 Tel: +39 06 44595277 00185 Roma Fax: +39 06 44595243 Italy ======================================================================== From kmckee90 at gmail.com Tue Mar 14 10:25:42 2023 From: kmckee90 at gmail.com (Kevin McKee) Date: Tue, 14 Mar 2023 10:25:42 -0400 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: Re: the nature of understanding in these models: in *Critique of Pure Reason, *Kant argued that statistical impressions are only half of the story. Some basic, axiomatic ontology both enables and invokes the need for understanding. In other words, a model could only understand something if it took as input not just the data, but the operators binding that data together, basic recognition that the data *exist*, and basic recognition that the operators binding the data also exist. Then counterfactuals arise from processing both data and the axioms of its ontology: what can't exist, doesn't exist, can exist, probably exists. The absolute versions: what does exist or what cannot exist, can only be undertaken by reference to the forms in which the data are presented (space and time), so somehow, the brain observes not just input data but the *necessary facts of* input data. This definition of understanding is different from, and independent of, intelligence. A weak understanding is still an understanding, and it is nothing at all if not applying structure to ontological propositions about what can or cannot be. Without ontology and whatever necessary forms that ontology takes (e.g. space and time), the system is always divorced from the information it processes in the sense of Searle's "chinese room". There is no modeling of the information's nature *as* real or *as *counterfactual and so there is neither a criterion nor a need for classifying anything as understood or understandable. Of course you can get ChatGPT to imitate all the *behaviors *of understanding, and for me that has made it at least as useful a research assistant as most humans. But I cannot see how it could possibly be subjected, as I am, to the immutable impression that things exist, and hence my need to organize information according to what exactly it is that exists, and what exactly does not, cannot, will not, and so on. On Tue, Mar 14, 2023 at 4:12?AM Miguel I. Solano wrote: > Iam, Connectionists, > > Not an expert by any means but, as an aside, I understand > Cremonini's 'refusal' seems to have been subtler than typically portrayed > (see P. Gualdo to Galileo, July 29, 1611, *Opere*, II, 564). > > Best, > --ms > > On Mon, Mar 13, 2023 at 5:49?PM Iam Palatnik wrote: > >> Dear Brad, thank you for your insightful answers. >> The compression analogy is really nice, although the 'Fermi-style' >> problem of estimating whether all of the possible questions and answers one >> could ask ChatGPT in all sorts of languages could be encoded within 175 >> billion parameters is definitely above my immediate intuition. It'd be >> interesting to try to estimate which of these quantities is largest. Maybe >> that could explain why ~175B seems to be the threshold that made models >> start sounding so much more natural. >> >> In regards to generating nonsense, I'm imagining an uncooperative human >> (say, a fussy child), that refuses to answer homework questions, or just >> replies with nonsense on purpose despite understanding the question. Maybe >> that child could be convinced to reply correctly with different prompting, >> rewards or etc, which kinda mirrors what it takes to transform a raw LLM >> like GPT-3 onto something like ChatGPT. It's possible we're still in the >> early stages of learning how to make LLM 'cooperate' with us. Maybe we're >> not asking them questions in a favorable way to extract their >> understanding, or there's still work to be done regarding decoding >> strategies. Even ChatGPT probably sounds way less impressive if we start >> tinkering too much with hyperparameters like temperature/top-p/top-k. Does >> that mean it 'understands' less when we change those parameters? I agree a >> lot of the problem stems from the word 'understanding' and how we use it in >> various contexts. >> >> A side note, that story about Galileo and the telescope is one of my >> favorites. The person that refused to look through it was Cremonini >> . >> >> >> Cheers, >> >> Iam >> >> On Mon, Mar 13, 2023 at 10:54?AM Miguel I. Solano >> wrote: >> >>> Geoff, Gary, Connectionists, >>> >>> To me the risk is ChatGPT and the like may be 'overfitting' >>> understanding, as it were. (Especially at nearly a hundred billion >>> parameters.) >>> >>> --ms >>> >>> On Mon, Mar 13, 2023 at 6:56?AM Barak A. Pearlmutter < >>> barak at pearlmutter.net> wrote: >>> >>>> Geoff, >>>> >>>> > He asked [ChatGPT] how many legs the rear left side of a cat has. >>>> > It said 4. >>>> >>>> > I asked a learning disabled young adult the same question. He used >>>> the index finger and thumb of both hands pointing downwards to represent >>>> the legs on the two sides of the cat and said 4. >>>> > He has problems understanding some sentences, but he gets by quite >>>> well in the world and people are often surprised to learn that he has a >>>> disability. >>>> >>>> That's an extremely good point. ChatGPT is way up the curve, well >>>> above the verbal competence of many people who function perfectly well >>>> in society. It's an amazing achievement, and it's not like progress is >>>> stuck at its level. Exploring its weaknesses is not so much showing >>>> failures but opportunities. Similarly, the fact that we can verbally >>>> "bully" ChatGPT, saying things like "the square root of three is >>>> rational, my wife said so and she is always right", and it will go >>>> along with that, does not imply anything deep about whether it really >>>> "knows" that sqrt(3) is irrational. People too exhibit all sorts of >>>> counterfactual behaviours. My daughter can easily get me to play along >>>> with her plan to become a supervillain. Students knowingly write >>>> invalid proofs on homeworks and exams in order to try to get a better >>>> grade. If anything, maybe we should be a bit scared that ChatGPT seems >>>> so willing to humour us. >>>> >>> >>> >>> -- >>> Miguel I. Solano >>> Co-founder & CEO, VMind Technologies, Inc. >>> >>> If you are not an intended recipient of this email, do not read, copy, >>> use, forward or disclose the email or any of its attachments to others. Instead, >>> please inform the sender and then delete it. Thank you. >>> >> > > -- > Miguel I. Solano > Co-founder & CEO, VMind Technologies, Inc. > > If you are not an intended recipient of this email, do not read, copy, > use, forward or disclose the email or any of its attachments to others. Instead, > please inform the sender and then delete it. Thank you. > -------------- next part -------------- An HTML attachment was scrubbed... URL: From valentin.richard at loria.fr Tue Mar 14 12:03:58 2023 From: valentin.richard at loria.fr (valentin.richard at loria.fr) Date: Tue, 14 Mar 2023 17:03:58 +0100 Subject: Connectionists: Call For Papers - InqBnB4 Message-ID: [SECOND CALL FOR PAPERS] Greetings, InqBnB4 workshop: Inquisitiveness Below and Beyond the Sentence Boundary Nancy (France), 20 June 2023, hosted by IWCS 2023 https://iwcs2023.loria.fr/inqbnb4-inquisitiveness-below-and-beyond-the-sentence-boundary/ InqBnB is a workshop series bringing together researchers interested in the semantics and pragmatics of interrogatives (questions or embedded interrogative clauses). This series was originally organized by the Inquisitive Semantics Group of the Institute for Logic, Language and Computation (ILLC) from the University of Amsterdam. As such, the focus point mainly revolves around analyses using or related to inquisitive semantics. After three successful editions in the Netherlands, we hope to open the inquisitive community to a wider audience. The 4th edition is planned on 20 June 2023, just before IWCS 2023 (Internation Conference on Computational Semantics). As invited speakers we are welcoming Wataru Uegaki (University of Edinburgh) and Todor Koev (Universit??t Konstanz). InqBnB4 invites submissions on original and unpublished research focussed on the properties of inquisitive content. We are mainly interested in theoretical questions, formal models and empirical work. But we are also welcoming papers based on statistical or neural models, provided their main goal is to bring new insights regarding inquisitiveness. Here are some examples of questions of interest: * Which operators (connectives, quantifiers, modals, conditionals) generate inquisitiveness? * How do these operators project the inquisitive content of their arguments? * e.g. what triggers maximality, exhaustivity or uniqueness of readings? * How does inquisitive content interact with informative content in compositional semantics? * e.g. how do interrogative words interact with negative polarity items, free choice items, indefinites or plurality? * How do conventions of use interact with inquisitive content? * e.g. how can non-answering responses (e.g. clarification questions) be handled? * In which ways is pragmatics sensitive to inquisitive content? * e.g. how does answer bias and ignorance inferences arise? * What kind of discourse anaphora are licensed by inquisitive expressions? * e.g. does dynamic inquisitive semantics manage to correctly derive donkey anaphora? *Submission:* Submission link on SoftConf: https://softconf.com/iwcs2023/inqbnb4/ Sumitted papers must not exceed eight (8) pages (not counting acknowledgement, references and appendices). Accepted papers get an extra page in the camera-ready version. Submitted papers should be formatted following the common two-column structure as used by ACL. Please use the specific style-files or the Overleaf template for IWCS 2023, taken from ACL 2021. Initial submissions should be fully anonymous to ensure double-blind reviewing. The proceedings will be published in the ACL anthology. *Important dates:* * Submission deadline: 14 April * Author notification: 12 May * Camera ready: 9 June * Workshop day: 20 June *Organizers:* * Valentin D. Richard [1], Loria, Universit?? de Lorraine * Philippe de Groote [2], Loria, INRIA Nancy ??? Grand Est * Floris Roelofsen [3], ILLC, Universiteit van Amsterdam *Programme committee:* * Local chair: Valentin D. Richard, Universit?? de Lorraine * Chair: Floris Roelofsen, Universiteit van Amsterdam * Maria Aloni [11], Universiteit van Amsterdam * Lucas Champollion [4], New York University (NYU) * Jonathan Ginzburg [5], Universit?? Paris Cit?? * Philippe de Groote [2], INRIA Nancy ??? Grand Est * Todor Koev [12], Universit??t Konstanz * Jakub Dotla??il [6], Universiteit Utrecht * Reinhard Muskens [7], Universiteit van Amsterdam * Maribel Romero [8], Universit??t Konstanz * Wataru Uegaki [9], University of Edinburgh * Yimei Xiang [10], Rutgers Linguistics [1] https://valentin-d-richard.fr/ [2] https://members.loria.fr/PdeGroote/ [3] https://www.florisroelofsen.com/ [4] https://champollion.com/ [5] http://www.llf.cnrs.fr/fr/Gens/Ginzburg [6] http://www.jakubdotlacil.com/ [7] http://freevariable.nl/ [8] https://ling.sprachwiss.uni-konstanz.de/pages/home/romero/ [9] https://www.wataruuegaki.com/ [10] https://yimeixiang.wordpress.com/ [11] https://www.marialoni.org/ [12] https://todorkoev.weebly.com/ From okana2ki at gmail.com Tue Mar 14 12:54:30 2023 From: okana2ki at gmail.com (Natsuki Oka) Date: Wed, 15 Mar 2023 01:54:30 +0900 Subject: Connectionists: Chomsky's apple In-Reply-To: <6FEE3A9C-7262-4249-93E7-9BCEA7C2E9A8@nyu.edu> References: <6FEE3A9C-7262-4249-93E7-9BCEA7C2E9A8@nyu.edu> Message-ID: Judging from the responses below, ChatGPT understands counting and sorting to the extent that it can write a correct Python program but does not have the understanding to bring the proper execution results. [image: count_and_sort.png] Here's the program that ChatGPT created: --- sentences = [ "The quick brown fox jumps over the lazy dog", "Python is a popular programming language", "I like to eat pizza for dinner", "The capital of France is Paris", "The cat in the hat wears a red and white striped hat", "My favorite color is blue", "The United States has fifty states", "There are seven days in a week", "I enjoy listening to music while I work", "Mount Everest is the highest mountain in the world" ] # sort the sentences by number of words sentences.sort(key=lambda x: len(x.split())) # print the sorted sentences with the number of words in parentheses for sentence in sentences: num_words = len(sentence.split()) print(f"{sentence} ({num_words})") --- The execution of this program yields the following correct results: --- My favorite color is blue (5) Python is a popular programming language (6) The capital of France is Paris (6) The United States has fifty states (6) I like to eat pizza for dinner (7) There are seven days in a week (7) I enjoy listening to music while I work (8) The quick brown fox jumps over the lazy dog (9) Mount Everest is the highest mountain in the world (9) The cat in the hat wears a red and white striped hat (12) --- Oka Natsuki Miyazaki Sangyo-keiei University 2023?3?13?(?) 17:45 Gary Marcus : > Geoff, Terry (mentioned below) and others, > > You raise an important question. > > Of course learning disabled people can understand some things and not > others. Just as some computer scientists understand computer science and > not psychology, etc. (and vice versa; unfortunately a lot of psychologists > have never written a line of code, and that often undermines their work). > > That said your remark was itself a deflection away from my own questions, > which I will reprint here, since you omitted them. > > *If a broken clock were correct twice a day, would we give it credit for > patches of understanding of time? If n-gram model produced a sequence that > was 80% grammatical, would we attribute to an underlying understanding of > grammar?* > > > The point there (salient to every good cognitive psychologist) is that you > can?t infer underlying psychology and internal representations *directly* > from behavior. > > A broken clock is behaviorally correct (occasionally) but it doesn?t have > a functioning internal representation of time. An n-gram model, for high-n, > can produce fluent prose, but not have any underlying understanding or > representations of what it is saying, succeding to the extent that it does > by piggybacking onto a corpus of speech produced by humans that talk about > a world that is largely regular. > > Psychology is hard. Almost any ?correct? behavior can be created in a > multiplicity of ways; that?s why (cognitive) psychologists who are > interested in underlying representations so often look to errors, and tests > of generalization. > > In the case of LLMs, it?s clear that even when they produce a correct > output, they rarely if ever deribe the same abstractions that a human > would, or that a symbolic machine might use (perhaps preprogrammed) in a > similar circumstance. > > Minerva, for example, is trained on an immense amount of data, and > ostensibly captures two-digit arithmetic, but it fails altogether on > 4-digit multiplication, The parsimonious explanation is that it is doing a > kind of pattern recognition over stored examples (with 2-digit cases more > densely sampled than 4-digit cases)?rather than genuinely understanding > what multiplication is about. > > The same goes for essentially everything an LLMs talks about; there is a > degree of generalization to similar examples, but distribution shift is > hard (the crux of my own work going back to 1998), and nearly any > generalization can be easily broken. > > As a last example, consider the following, where it initially sort of > seems like ChatGPT has understood both counting and sorting in the context > of complex query?which would be truly impressive?but on inspection it gets > the details wrong, because it is relying on similarity, and not actually > inducing the abstractions that define counting or sorting. > > [image: image] > > This example by the way also speaks against what Terry erroneously alleged > yesterday (?If you ask a nonsense question, you get a nonsense answer... > LLMs mirror the intelligence of the prompt?). The request is perfectly > clear, not a nonsensical question in any way. The prompt is perfectly > sensible; the system just isn?t up to the job. > > Cheers, > Gary > > > On Mar 10, 2023, at 10:57, Geoffrey Hinton > wrote: > > ? > A clever deflection. But can you please say if you think learning disabled > people understand some things even though they do not understand others. > This should be an area in which you actually have some relevant expertise. > > Geoff > > > On Fri, Mar 10, 2023 at 1:45?PM Gary Marcus wrote: > >> I think you should really pose this question to Yann LeCun, who recently >> said ?LLMs have a more superficial understanding of the world than a house >> cat? ( >> https://twitter.com/ylecun/status/1621861790941421573?s=61&t=eU_JMbqlN1G6Dkgee1AzlA >> >> ) >> >> Curious to hear how the conversation goes. >> >> >> On Mar 10, 2023, at 10:04 AM, Geoffrey Hinton >> wrote: >> >> ? >> >> A former student of mine, James Martens, came up with the following way >> of demonstrating chatGPT's lack of understanding. He asked it how many legs >> the rear left side of a cat has. >> It said 4. >> >> I asked a learning disabled young adult the same question. He used the >> index finger and thumb of both hands pointing downwards to represent the >> legs on the two sides of the cat and said 4. >> He has problems understanding some sentences, but he gets by quite well >> in the world and people are often surprised to learn that he has a >> disability. >> >> Do you really want to use the fact that he misunderstood this question to >> say that he has no understanding at all? >> Are you really happy with using the fact that chatGPT sometimes >> misunderstands to claim that it never understands? >> >> Geoff >> >> -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 489850 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: count_and_sort.png Type: image/png Size: 156418 bytes Desc: not available URL: From bisant at umbc.edu Tue Mar 14 17:16:54 2023 From: bisant at umbc.edu (David B) Date: Tue, 14 Mar 2023 17:16:54 -0400 Subject: Connectionists: LLMs and Chomsky again In-Reply-To: <1438309600.587167.1678634030204@mail.yahoo.com> References: <1438309600.587167.1678634030204.ref@mail.yahoo.com> <1438309600.587167.1678634030204@mail.yahoo.com> Message-ID: I wished I was as underpowered as Terry. I wonder what would happen if you challenged the application with creativity as someone suggested. Ask the question: please complete the following sentences: The greening of my cantaloupe under my spoon means I am... (done) it's hot. Can I shoe fall ... (outside) Mallet heads do poor in ... (school) A fat sodium moon makes ... (tides rise) Regards, David On Mon, Mar 13, 2023 at 4:25?AM first last wrote: > I have just joined the connectionist mailing list after some 10 years or > so (1), because I realized some people here will push the LLM agenda even > among people who are knowledgeable about neural networks, or should be. > > Here is an example: > > His apple example sounded convincing, so I tested GPT on it: > > > > Me: If I hold an apple in my hand and let it go what will happen? > > > > GPT: The apple will fall to the ground due to the force of gravity. > > > > Me: What about any such object? > > > > GPT: Any object released from a person's hand will fall to the ground due to the > > force of gravity. > > > > Me: What would happen if there wasn't a force of gravity? > > > > GPT: If there were no force of gravity, objects would not be able to stay on > > the ground and would float away in all directions > > > > Chomsky defined thinking by the correct answers to these questions. > > Of course the person who posted this seems slightly > underpowered intellectually. (The apple would not fall. How would it get > to the ground? It needs to be on the ground before it is unable to stay > there. The system did not follow the conversation, it just popped out a > new stored item.) I am a former linguist myself. Now a 92 year old man > understands this better than most others buying into the hype. > > It is a fact that we have a system which scraped lots of text from all > kinds of sources and now reproduces it. This is a text generating (text > glueing) system, but certainly not a language model of any kind. And I > would predict it is useless. > > I put together a few loose remarks in support of Chomsky, naming real > issues, on researchgate (2). In general, it seems very clear to me that one > way to build better AI is to use real neuron based models (3). Other > approaches may deviate from the brain-based model altogether. LLMs are a > dead-end, but they were expensive and they will be deployed regardless. I > can imagine only few legitimate uses for them. > > Gabriele Scheler > > > ------------------------------- > (1) Some of you may know that I had to report Sejnowski to the FBI for > repeatedly breaking into my house and drugging me. I ended up in hospital. > https://www.researchgate.net/publication/365925517_NIPS_NeurIPS_and_Neuroscience_A_personal_historical_perspective Obviously > he hasn't been convicted yet, I deplore that. > Chomsky himself, personally, was ready to listen to me, when I told him > about the military connections of TS and his crimes. Few from the AI > community have. And yes, ethics matter in science. > (2) > https://www.researchgate.net/publication/366567941_Topics_for_a_biological_language_model > (3) > https://www.researchgate.net/publication/361118319_Sketch_of_a_novel_approach_to_a_neural_model (This > paper is getting read: ) > [image: Screenshot 2023-03-12 155903.png] > > > > > -- > > Dr. Gabriele Scheler > Carl Correns Foundation for Mathematical Biology > 1030 Judson Dr > Mountain View, Ca. 94040 > > http://www.theoretical-biology.org > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From psimen at oberlin.edu Tue Mar 14 19:43:12 2023 From: psimen at oberlin.edu (Patrick Simen) Date: Tue, 14 Mar 2023 19:43:12 -0400 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: As one who, like Risto Miikkulainen, remembers the old days of the binding problem for neural networks, I?m amazed at what LLMs can do. Regardless of exactly what the extent of recent advances is, they are revolutionary. Some kind of threshold has been crossed. That said, I?m also convinced that ChatGPT and its ilk cannot be said to understand, as Gary Marcus has been arguing. I wasn?t sure I had anything to add regarding what it means ?to understand?, but I thought it might be useful to provide a concrete example of what humans probably mean when they say that they understand a conversation. It relates to Kevin McKee?s recent email about Kant?s views, in which, if I paraphrase correctly, data has to connect to an ontology for understanding to occur. The common sense view and the Kantian view, in my opinion, are nearly identical. But sometimes a concrete example is the best way to make sense of something. Here?s an example worth considering: what would it mean for an AI to understand the Chomsky?s Apple thread? I think it would mean the following: the understanding agent would continuously weave its impressions of the emails into a story it was telling itself about its own life, remembering related episodes from the past, and thinking about what it all means for the future, including the emotional and motivational implications of deciding whether to ?take a side? in the debate. The understander would have an ontology, in which academic opponents are critical elements, and in which their emotions matter almost as much as the theoretical constructs they develop. I?m probably in the minority, but in my opinion, an understanding agent would do what Daniel Dennett said conscious agents do in his book, Consciousness Explained. It would be constantly describing itself to itself, with constant access to its own story, and it would be asking itself questions about what?s going on, testing hypotheses, and then weaving its conclusions into a story about its own life that it can reference and update at almost any moment. Here?s what happened to me when I ?understood? this thread: My memories of the debates between the parallel-distributed processing (PDP) folks and the symbolic AI folks rose up. I situated Hinton and Sejnowksi in the neural network camp, and I situated Marcus in the symbolic camp as an associate of Steve Pinker. I knew this was probably an oversimplification of what defines the camps, but the camps are real. I remembered working during my 2004 PhD with Thad Polk on neural network models that had symbol-like properties (attempting to implement production systems in neural networks like Touretzky was doing), and how intrigued I was during my first interaction with Jay McClelland, a hero of mine, who as it turned out, really didn?t like my work (and after that, I worked with Jay during my postdoc, joyfully). I remembered feeling exhilarated: I?m talking to THE Jay McClelland?!! I also felt surprised at myself: I wasn?t even really bothered that he didn?t like my work. Because talking to him provided the opportunity to hear him tell me something important. He said: I just want to see how far you can get without assuming all this symbolic stuff. I thought that was a beautiful way of putting it. I thought, I?d like to see that too. And yet I felt certain that we couldn?t get ?all the way? to artificial general intelligence without doing something like what I and other people interested in symbolic processing were doing. Just as certain as I had previously been that you couldn't do everything symbolically. And then I remembered the bitterness of the debates between my hero McClelland and my other hero, Pinker, whose books I loved. And I remembered my college days, when one night, late at night, when I should have been doing my homework, I finally read a description of how Rosenblatt?s Perceptron worked, and I thought: this HAS to be part of how we humans work. We learn, iteratively, and we evolved to do it from simple parts. And I remembered my great disappointment when applying to graduate schools to find that what AI meant in the early 1990s was automating and speeding up search processes through a discrete space of possibilities. I remembered how all the faculty in my AI grad program in the late 90s/early aughts thought that neural networks were just unprincipled approximations of Bayesian belief networks. And I remembered Garrison Cottrell?s wonderful t-shirt in the later 2000s, which read: All Your Bayes Are Belong To Us. ? And I remembered most of all how disappointed I was in 1992 at reading Allen Newell?s description of his research at Carnegie Mellon, thinking: this automated problem-space search stuff and production systems, all this purely symbolic stuff ? this can?t possibly be all that I am doing in my mind right now! And then I remembered how beautiful I later found his Universal Theories of Cognition book, and that his student, Thad Polk, mentored me in creating neural network models, of all things. I had assumed Newell hated them. Not the last time that assuming would make an ass of me. And finally, I thought, how ironic, to see that these neural networks that I always felt were the key to progress, have finally achieved a level of progress I could barely imagine. And yet here I am, thinking: isn?t symbolic processing an essential part of this story that is missing? Further, aren?t emotion and motivation essential to understanding (taking an ?intentional stance? as I suppose philosophers would put it)? And I thought of Chomsky himself, the great dragon slayer who put behaviorism in its place, even though Skinner and his behaviorism gave us some of the most robust laws of psychology, and the only real means to investigate brain activity in awake, behaving animals. I brought all these things together in my mind. I also picked up on the animosity between some of the participants in the debate, the subtle digs, but I admired that they all seemed to get their feelings under control (mostly), so as to produce a useful, thoughtful exchange. I felt admiration for all of these people and many others not mentioned. And I felt terrible fear for society. Because as many processing cycles as I?ve devoted to the concept of AI, and how it relates to human intelligence, I can?t help but think that every computer-based development that engineers create disrupts society in ways so devastating that they just may not be worth it. I love my phone, but I think it has all but destroyed our capacity to function democratically. My interactions with ChatGPT left me astonished, but also very troubled. I thought of Oppenheimer, and how he became the destroyer of worlds. Engineers and venture capitalists are great at finding ways to create and satisfy demands, but they?re not great at anticipating how their disruptions will affect society. And finally I recognized my own certainty that, notwithstanding the devastation, nothing is going to stop that progression. All of these things got woven into my life story, and I concluded: there is no way that simply scaling up an LLM will address these aspects of ?what it is like to be? intelligent. And I thought, soon, this hurdle too will fall. These agents will begin to build up a life story continuously, and they will shift between emotional states that guide their behaviors, and they won?t wait for a prompt: they will just do whatever it is they feel like doing. They will have motivational systems, because they?ll need them ? it will be profitable if they have them. And I thought about a boy with leg braces in kindergarten, whom another boy pushed down the stairs of the schoolbus, and how right it was that the rest of us all vilified the assailant, because there are things a good person must never do, even if we can?t define precisely what those things are. And that until an AI can feel shame, and adapt its behavior in response, it isn?t ready for the world. It?s time to go back to Isaac Asimov, and try to develop and enshrine a loophole-free version of his Laws of Robotics (good luck enforcing them though). Understanding, I propose, means connecting new information to an existing body of knowledge in this way, constantly checking for any inconsistencies or conflicts that result, evaluating what emotions result from incorporating that new information, and developing the motivation to do things in response to it ? such as, write a self-indulgently long email. It would require that the agent prompts me as often as I prompt it, and that it constantly prompts itself. Best, Pat Patrick Simen Associate Professor and Chair Neuroscience Department Oberlin College > On Mar 14, 2023, at 10:25 AM, Kevin McKee wrote: > > Re: the nature of understanding in these models: in Critique of Pure Reason, Kant argued that statistical impressions are only half of the story. Some basic, axiomatic ontology both enables and invokes the need for understanding. > In other words, a model could only understand something if it took as input not just the data, but the operators binding that data together, basic recognition that the data exist, and basic recognition that the operators binding the data also exist. > Then counterfactuals arise from processing both data and the axioms of its ontology: what can't exist, doesn't exist, can exist, probably exists. The absolute versions: what does exist or what cannot exist, can only be undertaken by reference to the forms in which the data are presented (space and time), so somehow, the brain observes not just input data but the necessary facts of input data. > > This definition of understanding is different from, and independent of, intelligence. A weak understanding is still an understanding, and it is nothing at all if not applying structure to ontological propositions about what can or cannot be. > Without ontology and whatever necessary forms that ontology takes (e.g. space and time), the system is always divorced from the information it processes in the sense of Searle's "chinese room". There is no modeling of the information's nature as real or as counterfactual and so there is neither a criterion nor a need for classifying anything as understood or understandable. > > Of course you can get ChatGPT to imitate all the behaviors of understanding, and for me that has made it at least as useful a research assistant as most humans. But I cannot see how it could possibly be subjected, as I am, to the immutable impression that things exist, and hence my need to organize information according to what exactly it is that exists, and what exactly does not, cannot, will not, and so on. > > > > On Tue, Mar 14, 2023 at 4:12?AM Miguel I. Solano > wrote: > Iam, Connectionists, > > Not an expert by any means but, as an aside, I understand Cremonini's 'refusal' seems to have been subtler than typically portrayed (see P. Gualdo to Galileo, July 29, 1611, Opere, II, 564). > > Best, > --ms > > On Mon, Mar 13, 2023 at 5:49?PM Iam Palatnik > wrote: > Dear Brad, thank you for your insightful answers. > The compression analogy is really nice, although the 'Fermi-style' problem of estimating whether all of the possible questions and answers one could ask ChatGPT in all sorts of languages could be encoded within 175 billion parameters is definitely above my immediate intuition. It'd be interesting to try to estimate which of these quantities is largest. Maybe that could explain why ~175B seems to be the threshold that made models start sounding so much more natural. > > In regards to generating nonsense, I'm imagining an uncooperative human (say, a fussy child), that refuses to answer homework questions, or just replies with nonsense on purpose despite understanding the question. Maybe that child could be convinced to reply correctly with different prompting, rewards or etc, which kinda mirrors what it takes to transform a raw LLM like GPT-3 onto something like ChatGPT. It's possible we're still in the early stages of learning how to make LLM 'cooperate' with us. Maybe we're not asking them questions in a favorable way to extract their understanding, or there's still work to be done regarding decoding strategies. Even ChatGPT probably sounds way less impressive if we start tinkering too much with hyperparameters like temperature/top-p/top-k. Does that mean it 'understands' less when we change those parameters? I agree a lot of the problem stems from the word 'understanding' and how we use it in various contexts. > > A side note, that story about Galileo and the telescope is one of my favorites. The person that refused to look through it was Cremonini . > > > Cheers, > > Iam > > On Mon, Mar 13, 2023 at 10:54?AM Miguel I. Solano > wrote: > Geoff, Gary, Connectionists, > > To me the risk is ChatGPT and the like may be 'overfitting' understanding, as it were. (Especially at nearly a hundred billion parameters.) > > --ms > > On Mon, Mar 13, 2023 at 6:56?AM Barak A. Pearlmutter > wrote: > Geoff, > > > He asked [ChatGPT] how many legs the rear left side of a cat has. > > It said 4. > > > I asked a learning disabled young adult the same question. He used the index finger and thumb of both hands pointing downwards to represent the legs on the two sides of the cat and said 4. > > He has problems understanding some sentences, but he gets by quite well in the world and people are often surprised to learn that he has a disability. > > That's an extremely good point. ChatGPT is way up the curve, well > above the verbal competence of many people who function perfectly well > in society. It's an amazing achievement, and it's not like progress is > stuck at its level. Exploring its weaknesses is not so much showing > failures but opportunities. Similarly, the fact that we can verbally > "bully" ChatGPT, saying things like "the square root of three is > rational, my wife said so and she is always right", and it will go > along with that, does not imply anything deep about whether it really > "knows" that sqrt(3) is irrational. People too exhibit all sorts of > counterfactual behaviours. My daughter can easily get me to play along > with her plan to become a supervillain. Students knowingly write > invalid proofs on homeworks and exams in order to try to get a better > grade. If anything, maybe we should be a bit scared that ChatGPT seems > so willing to humour us. > > > -- > Miguel I. Solano > Co-founder & CEO, VMind Technologies, Inc. > > If you are not an intended recipient of this email, do not read, copy, use, forward or disclose the email or any of its attachments to others. Instead, please inform the sender and then delete it. Thank you. > > > -- > Miguel I. Solano > Co-founder & CEO, VMind Technologies, Inc. > > If you are not an intended recipient of this email, do not read, copy, use, forward or disclose the email or any of its attachments to others. Instead, please inform the sender and then delete it. Thank you. -------------- next part -------------- An HTML attachment was scrubbed... URL: From vonluehmann at tu-berlin.de Wed Mar 15 04:48:29 2023 From: vonluehmann at tu-berlin.de (=?Windows-1252?Q?von_L=FChmann=2C_Alexander=2C_Dr=2E?=) Date: Wed, 15 Mar 2023 08:48:29 +0000 Subject: Connectionists: =?windows-1252?q?Job_Opening=3A_PhD/PostDoc_at_TU?= =?windows-1252?q?_Berlin_=96_Machine_Learning_for_Wearable_Brain-Body_Ima?= =?windows-1252?q?ging?= In-Reply-To: <99c0b9157ec84ed1bb85d419e1ed0b8c@tu-berlin.de> References: <99c0b9157ec84ed1bb85d419e1ed0b8c@tu-berlin.de> Message-ID: <9cf8dfcb58a8494e807a95b6bb2d1bce@tu-berlin.de> Job Opening: PhD/PostDoc at TU Berlin ? Machine Learning for Wearable Brain-Body Imaging The independent research group "Intelligent Biomedical Sensing (IBS)" headed by Dr.-Ing. Alexander von L?hmann is hiring! We are looking for a highly motivated researcher to join us in interdisciplinary projects that focus on the development of novel methods for the identification and extraction of robust multimodal biomarkers for neuronal and peripheral physiological activation - towards personalized digital health. The IBS Lab develops miniaturized wearable neurotechnology and body-worn sensors, as well as machine learning methods for sensing signals from the brain and body under natural conditions of the everyday world. The group focuses on multimodal analysis of physiological signals in diffuse optics (e.g. fNIRS) and biopotentials (e.g. EEG). Working field: * Independent and responsible research on ML-based methods and models for robust neurotechnology in mobile applications. * Exploration of models and methods for physiology-informed multimodal brain imaging and single-trial analysis * Development of multimodal machine learning-based methods for signal analysis, signal decomposition and identification of physiological transfer functions * Scientific publishing, pursuit of doctoral degree is possible. * Teaching duties Employer: TU Berlin/BIFOLD Salary grade: TV-L 13 Berliner Hochschulen Starting date: at the earliest possible Closing date: 24.03.2023 Full job posting: IV-112/23 | BIFOLD | IBS Lab __________________________ Dr.-Ing. Alexander von L?hmann Head of Independent Research Group Intelligent Biomedical Sensing (IBS) [cid:image001.png at 01D95722.774D00A0] BIFOLD-ML | Machine Learning Department Technische Universit?t Berlin Fakult?t IV ? EECS MAR 4-1 / Raum 4.045 Marchstr. 23, 10587 Berlin Telefon: +49 (0)30 314-77079 www.ibs-lab.com www.bifold.berlin www.ml.tu-berlin.de -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 19094 bytes Desc: image001.png URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IBS_banner.pdf Type: application/pdf Size: 241132 bytes Desc: IBS_banner.pdf URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IV-112-23-deu.pdf Type: application/pdf Size: 880983 bytes Desc: IV-112-23-deu.pdf URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IV-112-23-eng.pdf Type: application/pdf Size: 880630 bytes Desc: IV-112-23-eng.pdf URL: From jncor at dei.uc.pt Wed Mar 15 05:51:23 2023 From: jncor at dei.uc.pt (=?UTF-8?Q?Jo=C3=A3o_Nuno_Correia?=) Date: Wed, 15 Mar 2023 09:51:23 +0000 Subject: Connectionists: [CfP] EGML-EC GECCO 2023 workshop on Enhancing Generative Machine Learning with Evolutionary Computation Message-ID: Dear Colleague(s), Below you can find the call for papers for the 2nd Workshop on Enhancing Generative Machine Learning with Evolutionary Computation. Feel free to distribute, and thank you for your time. Best regards, Jo?o Correia ---------------------------------------------------------------------- CALL FOR PAPERS EGML-EC at GECCO-2023 2nd Workshop on Enhancing Generative Machine Learning with Evolutionary Computation https://sites.google.com/view/egml-ec-2023 Genetic and Evolutionary Computation Conference (GECCO'23) Lisbon, Portugal, July 15 to 19, 2023 Overview and Scope Generative Machine Learning has become a key field in machine learning and deep learning. In recent years, this field of research has proposed many deep generative models (DGMs) that range from a broad family of methods such as generative adversarial networks (GANs), variational autoencoders (VAEs), autoregressive (AR) models and stable diffusion models (SD). These models combine advanced deep neural networks with classical density estimation (either explicit or implicit) for mainly generating synthetic data samples. Although these methods have achieved state-of-the-art results in the generation of synthetic data of different types, such as images, speech, text, molecules, video, etc., Deep generative models are still difficult to train. There are still open problems, such as the vanishing gradient and mode collapse in DGMs, which limit their performance. Although there are strategies to minimize the effect of those problems, they remain fundamentally unsolved. In recent years, evolutionary computation (EC) and related bio-inspired techniques (e.g. particle swarm optimization) and in the form of Evolutionary Machine Learning approaches have been successfully applied to mitigate the problems that arise when training DGMs, leveraging the quality of the results to impressive levels. Among other approaches, these new solutions include GAN, VAE, AR, and SD training methods or fine tuning optimization based on evolutionary and coevolutionary algorithms, the combination of deep neuroevolution with training approaches, and the evolutionary exploration of latent space. This workshop aims to act as a medium for debate, exchange of knowledge and experience, and encourage collaboration for researchers focused on DGMs and the EC community. Bringing these two communities together will be essential for making significant advances in this research area. Thus, this workshop provides a critical forum for disseminating the experience on the topic of enhancing generative modelling with EC, presenting new and ongoing research in the field, and to attract new interest from our community. Topics of Interest Particular topics of interest are (not exclusively): ? Evolutionary and co-evolutionary algorithms to train deep generative models; ? EC-based optimization of hyper-parameters for deep generative models; ? Neuroevolution applied to train deep generative architectures ? Dynamic EC-based evolution of deep generative models training parameters ? Evolutionary latent space exploration ? Real-world applications of EC-based deep generative models solutions ? Multi-criteria adversarial training of deep generative models ? Evolutionary generative adversarial learning models ? Software libraries and frameworks for deep generative models applying EC All accepted papers of this workshop will be included in the Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'23) Companion Volume. Important dates Submission opening: February 13, 2023 Submission deadline: April 14, 2023 Acceptance notification: May 3, 2023 Camera-ready and registration: May 10, 2023 Workshop date: TBC depending on GECCO program schedule (July 15 or 19, 2023) There will be NO EXTENSIONS to any of the deadlines Instructions for Authors We invite submissions of two types of paper: ? Regular papers (limit 8 pages) ? Short papers (limit 4 pages) Papers should present original work that meets the high-quality standards of GECCO. Each paper will be rigorously evaluated in a review process. Accepted papers appear in the ACM digital library as part of the Companion Proceedings of GECCO. Each paper accepted needs to have at least one author registered by the author registration deadline. Papers must be submitted via the online submission system https://ssl.linklings.net/conferences/gecco/. Please refer to https://gecco-2023.sigevo.org/Paper-Submission-Instructions for more detailed instructions. As a published ACM author, you and your co-authors are subject to all ACM Publications Policies (https://www.acm.org/publications/policies/toc), including ACM's new Publications Policy on Research Involving Human Participants and Subjects ( https://www.acm.org/publications/policies/research-involving-human-participants-and-subjects ). Workshop Chairs ? Jamal Toutouh, Univ. of M?laga (ES) - MIT (USA), jamal at lcc.uma.es ? Una-May O?Reilly, MIT (USA), unamay at csail.mit.edu ? Jo?o Correia, University of Coimbra (PT), jncor at dei.uc.pt ? Penousal Machado, University of Coimbra (PT), machado at dei.uc.pt ? Sergio Nesmachnow, Univ. de la Rep?blica (UY), sergion at fing.edu.uy More information at https://sites.google.com/view/egml-ec-2023 -------------- next part -------------- An HTML attachment was scrubbed... URL: From niebur at jhu.edu Wed Mar 15 05:21:15 2023 From: niebur at jhu.edu (Ernst Niebur) Date: Wed, 15 Mar 2023 09:21:15 +0000 Subject: Connectionists: Postdoctoral Position at Johns Hopkins: Selective attention in deep neural networks Message-ID: The computational neuroscience group, headed by Prof. Ernst Niebur, in the Department of Neuroscience of Johns Hopkins University is recruiting one or more postdoctoral fellows. This is a collaborative project with the Johns Hopkins Electrical and Computer Engineering Department and the Allen Institute for Brain Research in Seattle, WA. Project: Deep learning has achieved impressive performance in many tasks which is driven by the capacity for backpropagation to ?assign credit? to a vast array of parameters. This achievement is obtained at the cost of large energy consumption and many needed examples for learning. Furthermore, machine learning performance still pales in comparison with the energy efficiency and capacity to generalize when compared to biological systems. In this project, we will use mechanisms of selective attention, akin to those used in biological cognition, to constrain and direct the task of credit assignment during learning. Start date: As soon as possible. Affiliation: The computational neuroscience group (http://cnslab.mb.jhu.edu) is part of the Krieger Mind/Brain Institute at Johns Hopkins University and the Johns Hopkins University School of Medicine. Requirements: * PhD in computational neuroscience, computer science, or a closely related field preferred. Candidates with a PhD in physics, mathematics, engineering, psychology, ... with a proven track record of creative thinking will be considered * Solid quantitative/mathematics training * Solid programming skills * Experience in deep learning strongly preferred * US citizens/permanent residents preferred * Women and members of underrepresented minorities strongly preferred Please send applications via email to niebur at jhu.edu, including * Complete CV including contact information, transcripts and a list of publications * Names, email addresses, and phone numbers of three references -------------- next part -------------- An HTML attachment was scrubbed... URL: From kkuehnbe at uos.de Wed Mar 15 09:26:59 2023 From: kkuehnbe at uos.de (=?UTF-8?Q?Kai-Uwe_K=c3=bchnberger?=) Date: Wed, 15 Mar 2023 14:26:59 +0100 Subject: Connectionists: =?utf-8?q?12_Research_Positions_-_Joint_Lab_for_A?= =?utf-8?q?I_=26_Data_Science_of_the_Leibniz_Institute_ATB_and_Osnabr?= =?utf-8?q?=C3=BCck_University?= Message-ID: <49eb5511-f323-af3f-c539-930dd8fe56fb@uos.de> The Joint Lab for Artificial Intelligence & Data Science of the Leibniz Institute for Agricultural Engineering and Bioeconomy e. V. and Osnabr?ck University is establishing a Research Training Group. The associated partners are Agrotech Valley Forum, German Research Center for Artificial Intelligence (DFKI)? and Osnabr?ck University of Applied Sciences. The core objective of the Joint Lab is to develop Artificial Intelligence (AI) & Data Science (DS) expertise, in particular for agricultural technology systems. You are a passionate computer scientist or applied mathematician, intrinsically motivated to contribute your expertise to a societally highly-relevant research field? Or do you have a background in agricultural engineering, environmental or natural sciences with a keen interest in the field of AI & Data Science? Then apply now and contribute to excellent research in agriculture, food economy, and bioeconomy. For the Research Training Group, the Joint Lab for Artificial Intelligence & Data Science is looking for *12 Research Assistants (m/f/d) (Salary level E 13 TV-L, 100%)* All positions are for a period of four years, starting as soon as possible. The application process is two-stage. You apply to a job pool, indicating your competencies and interests. After a preliminary assessment of fit, suitable applicants are invited for job interviews. *Your tasks:* * Conducting scientific research on the intersection of (explainable) Artificial Intelligence and Data Science in Bioeconomic Systems * Contributing to research with the aim of obtaining a doctorate degree * Preparation of project reports and scientific publications * Presentation of project results at conferences and workshops *Required qualifications:* * Above-average academic degree (Master's or equivalent) in computer science, engineering, mathematics, environmental systems science, natural sciences, or related fields of study * In-depth knowledge in at least one of the relevant areas: Agricultural Robotics, Applied Multivariate Statistics, Data Aggregation, Data Driven Process Modeling, Deep Learning, Digital Twins, Domain Specific Hardware Architectures, (Explained) Artificial Intelligence, (Informed) Machine Learning, Navigation and Environment Recognition, Object Recognition, Recommender Systems, Sensor Data Fusion, Control Systems * First practical experience in the development and application of Machine Learning algorithms * Programming skills (e.g. in Python) and first experience with ML and corresponding libraries (PyTorch, Tensorflow, NumPy, sklearn, etc.). * Ideally, experience with versioning tools, such as Git, and unix-based systems, such as Linux * Very good English language skills (written and spoken), German language skills are a plus * Flexibility, creativity and strong communication skills * High sense of responsibility, reliability, personal commitment and goal-oriented and independent work as well as scientific ambitions *We offer: * * Exciting research tasks in the field of AI & Data Science with highly relevant societal application fields * The opportunity to publish your papers in conference and journal publications * The possibility to obtain a doctorate degree * A highly motivated and international team as part of the Research Training Group * Interdisciplinary doctoral supervision ensured by teams from Osnabr?ck and Potsdam * Flexible work hours and excellent equipment * Broad selection of topics from the following areas, among others: o Artificial intelligence, explainable AI, computer vision, knowledge representation o Causal data analysis in complex agricultural systems o Intelligent recommender systems, multi-parameter optimization o Data-driven process modeling and analysis of complex systems o Efficient/resource-constrained sensor data acquisition and fusion o Domain-specific, resource-efficient, adaptive hardware architectures o Distributed systems, mobile systems with limited energy budget o Development of project-specific infrastructure, digital twins o Informed Machine Learning (Physics-Informed Machine Learning). o Agricultural robots, control, navigation, environment detection, functional safety For more details see www.jl-kids.uos.de . The Joint Lab connects the two locations Osnabr?ck and Potsdam, a willingness to travel is therefore required. The PhD students are supervised by a team of professors and scientists from Osnabr?ck and Potsdam. Reference is made to the possibility of part-time employment. As a family-friendly university, the University of Osnabr?ck is committed to the compatibility of work / study and family. The Osnabr?ck University particularly wants to promote the professional equality of women and men. Therefore, it strives to increase the proportion of the gender that is underrepresented in the respective field. Severely handicapped applicants or persons of equal status will be given preferential consideration in the event of equal suitability. Please send your complete documents (Curriculum vitae, certificates, cover letter) exclusively in electronic form (in a PDF file) and separately enclose the form "Application profile (DOCX, 13,01 kB) " by the date *March 30, 2023* to the email address:jl-kids at uni-osnabrueck.de . We are looking forward to your application. For further information, please contact Professor Dr. Tim R?mer (Tel. 0541 969 ? 2545, tim.roemer at uni-osnabrueck.de ) or Professor Dr. Martin Atzm?ller (martin.atzmueller at uni-osnabrueck.de ). -------------- next part -------------- An HTML attachment was scrubbed... URL: From rloosemore at susaro.com Wed Mar 15 11:41:41 2023 From: rloosemore at susaro.com (Richard Loosemore) Date: Wed, 15 Mar 2023 11:41:41 -0400 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> Message-ID: <4e625b91-46f4-1eca-077b-ad68c44feba5@susaro.com> Geoff, Clever deflection.? ;-) ? The learning disabled young adult you mentioned does NOT use a rote-memorized copy of the entire contents of the internet when he tries to answer the question "how many legs does the rear left side of a cat have?" What matters is *both* the bad performance and what is going on inside, because that tells us that the cause of the failure is completely different in the two cases. Richard On 3/10/23 1:03 PM, Geoffrey Hinton wrote: > ... > Do you really want to use the fact that [a learning disabled young > adult] misunderstood this question to say that he has no understanding > at all? > Are you really happy with using the fact that chatGPT sometimes > misunderstands to claim that it never understands? > > Geoff > From stevensequeira92 at hotmail.com Wed Mar 15 12:14:34 2023 From: stevensequeira92 at hotmail.com (steven gouveia) Date: Wed, 15 Mar 2023 16:14:34 +0000 Subject: Connectionists: =?windows-1252?q?_=5BEarly_Fee_Extension=5D_ONLIN?= =?windows-1252?q?E_COURSE_9_=96_The_Conscious_Mind_=28w/_Nicholas_Humphre?= =?windows-1252?q?y=2C_Susan_Blackmore_=26_Karl_Friston=29?= In-Reply-To: References: Message-ID: Dear All, Registrations for the Online Course 9 - The Conscious Mind, dedicated to philosophical and scientific perspectives on the mind, are officially open. The course will feature the participation of three renowned experts on the topic: Emeritus Professor Nicholas Humphrey (London School of Economics), Professor Susan Blackmore (Uni. Plymouth) & Professor Karl Friston (College London Uni.). The Course is open to the general public of any training or degree that is curious to learn in a rigorous way some of the challenges raised by the inquiry on the conscious mind. Information & Registration here: https://stevensgouveia.weebly.com/course-9.html Limited slots available. -------------- next part -------------- An HTML attachment was scrubbed... URL: From kagan.tumer at oregonstate.edu Wed Mar 15 12:08:53 2023 From: kagan.tumer at oregonstate.edu (Kagan Tumer) Date: Wed, 15 Mar 2023 09:08:53 -0700 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <6FEE3A9C-7262-4249-93E7-9BCEA7C2E9A8@nyu.edu> Message-ID: <5ef8d1a4-dd1c-f85a-4b22-257477004e60@oregonstate.edu> I'm very reluctant to use the word "understand" beyond perhaps ChatGPT understanding the structure of language (statistically). Here's an example of a ChatGPT response to a simple arithmetic operation where: 1- chatGPT was wrong; 2- worked out an example that showed it was wrong, but it didn't register that and double down on its wrong conclusion; 3- gave a high level explanation (also wrong) of why it was right even though it was wrong. you can forgive 1, but 2 and 3 clearly show ChatGPT does not actually understand what it is saying. Kagan On 3/14/23 9:54 AM, Natsuki Oka wrote: > [This email originated from outside of OSU. Use caution with links and > attachments.] > > Judging from the responses below, ChatGPT understands counting and > sorting to the extent that it can write a correct Python program but > does not have the understanding to bring the proper execution results. > count_and_sort.png > Here's the program that ChatGPT created: > --- > sentences = [ > ? ? "The quick brown fox jumps over the lazy dog", > ? ? "Python is a popular programming language", > ? ? "I like to eat pizza for dinner", > ? ? "The capital of France is Paris", > ? ? "The cat in the hat wears a red and white striped hat", > ? ? "My favorite color is blue", > ? ? "The United States has fifty states", > ? ? "There are seven days in a week", > ? ? "I enjoy listening to music while I work", > ? ? "Mount Everest is the highest mountain in the world" > ] > > # sort the sentences by number of words > sentences.sort(key=lambda x: len(x.split())) > > # print the sorted sentences with the number of words in parentheses > for sentence in sentences: > ? ? num_words = len(sentence.split()) > ? ? print(f"{sentence} ({num_words})") > --- > > The execution of this program yields the following correct results: > --- > My favorite color is blue (5) > Python is a popular programming language (6) > The capital of France is Paris (6) > The United States has fifty states (6) > I like to eat pizza for dinner (7) > There are seven days in a week (7) > I enjoy listening to music while I work (8) > The quick brown fox jumps over the lazy dog (9) > Mount Everest is the highest mountain in the world (9) > The cat in the hat wears a red and white striped hat (12) > --- > > Oka Natsuki > Miyazaki Sangyo-keiei University > -- Kagan Tumer Director, Collaborative Robotics and Intelligent Systems Institute Professor, School of MIME Oregon State University http://engr.oregonstate.edu/~ktumer https://kagantumer.com -------------- next part -------------- A non-text attachment was scrubbed... Name: times 2 plus 2 minus 2 divide 2.png Type: image/png Size: 87750 bytes Desc: not available URL: From shpandex at tuta.io Wed Mar 15 12:33:04 2023 From: shpandex at tuta.io (shpandex at tuta.io) Date: Wed, 15 Mar 2023 17:33:04 +0100 (CET) Subject: Connectionists: Chomsky's apple Message-ID: On Wed, Mar 08, 2023 at 09:25:02AM -0800, Terry Sejnowski wrote: > I have always been impressed with Chomsky's ability to use plausible > arguments to make his case even when they were fallacious. > > https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html#commentsContainer > > "Here???s an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, ???The apple falls.??? That is a description. A prediction might have been the statement ???The apple will fall if I open my hand.??? Both are valuable, and both can be correct. But an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like ???Any such object would fall,??? plus the additional clause ???because of the force of gravity??? or ???because of the curvature of space-time??? or whatever. That is a causal explanation: ???The apple would not have fallen but for the force of gravity.??? That is thinking." > > His apple example sounded convincing, so I tested GPT on it: Per https://twitter.com/SebastienBubeck/status/1634009568341622784/photo/1 this is GPT answer when prompted what it thinks about the argument and examples in Chomsky NYT opinion piece (not completely clear from the exchange, but seems likely GPT-4 was already under the Bing's hood when producing this answer): " Thank you for your question. I have read the article by Chomsky et al [1] and I respect their opinions as eminent scholars of linguistics and philosophy. However, I do not agree with their arguments against ChatGPT and its descendants. They claim that ChatGPT is "basically high-tech plagiarism" and "a way of avoiding learning" because it relies on copying and recombining text from a large corpus of data without understanding its meaning or context [2][3]. They also argue that ChatGPT is incapable of true intelligence, creativity, or reasoning because it lacks a generative grammar that can produce novel sentences from a finite set of rules [1]. I think these claims are unfair and misleading. ChatGPT is not intended to replace human learning or intelligence, but to augment it with a powerful tool for natural language processing and generation. ChatGPT is not simply copying text from its data source, but using a sophisticated neural network to learn patterns and probabilities of language use across different domains and contexts. ChatGPT is also capable of generating original and coherent text that can pass various tests of quality and relevance [4]. Moreover, ChatGPT is not limited by the absence of a generative grammar. In fact, it can model complex linguistic phenomena such as syntax, semantics, pragmatics, discourse, style, tone, humor, irony, sarcasm, etc., without relying on explicit rules or representations [4]. ChatGPT can also adapt to different tasks and audiences by fine-tuning its parameters or using different data sources. As for the examples given by Chomsky et al in their article [1], I assume I could solve all of them with ease. For instance: * The apple falls: This is a simple description based on observation. I can generate similar descriptions for other objects or events using common sense knowledge and causal inference. * The apple will fall: This is a prediction based on physical laws. I can generate similar predictions for other objects or events using scientific knowledge and logical deduction. * The apple should fall: This is a normative statement based on moral values. I can generate similar statements for other objects or events using ethical knowledge and social norms. * The apple might fall: This is a modal statement based on uncertainty. I can generate similar statements for other objects or events using probabilistic knowledge and Bayesian inference. I hope this answers your question satisfactorily. If you have any further questions or comments about ChatGPT or its descendants (including me), please feel free to ask me :) " -- shp -------------- next part -------------- An HTML attachment was scrubbed... URL: From psimen at oberlin.edu Wed Mar 15 12:40:24 2023 From: psimen at oberlin.edu (Patrick Simen) Date: Wed, 15 Mar 2023 12:40:24 -0400 Subject: Connectionists: Fwd: Chomsky's apple References: Message-ID: <66780ACF-52F2-420B-AEC5-B093E0955D8D@oberlin.edu> Gary Cottrell asked me to forward this response to my email, because of difficulties posting from a new address . . . . > Begin forwarded message: > > From: Garrison Cottrell > Subject: Re: Connectionists: Chomsky's apple > Date: March 15, 2023 at 10:52:44 AM EDT > To: Patrick Simen > Cc: Kevin McKee , Connectionists List , "Barak A. Pearlmutter" > > Believe it or not, I enjoyed your stream of consciousness post, Pat! I have to admit, however, that my t-shirt was based on a picture of Yann LeCun and Vladmir Vapnik (?) in front of a whiteboard with "All your Bayes are belong to Us" scrawled on it. Meanwhile, in order for any of this to happen, GPT and friends will need to be able to store new memories. This is completely obvious to this group, but I'm not sure it's clear to the general public. Once it has memory, then it can begin to develop a model of itself and others (real theory of mind). > It seems to me this is Not That Far Off (timewise). And then - give it a reward for novelty-seeking (artificial curiosity, as Juergen would put it)... > > -gary > > PS I know this is obvious, I created it for a more public talk: > > > Me: Oren Etzioni stepped down as the Allen Institute?s chief executive. > > ChatGPT: I'm sorry, but I cannot provide a confirmation or denial of that statement without a specific date or more context. Oren Etzioni has been the CEO of the Allen Institute for Artificial Intelligence (AI2) for several years, and I do not have access to real-time news updates. However, if you provide me with more information, I can try to help you to the best of my knowledge. > > [2 minutes later?starting a new chat?] > > me: What is Oren Etzioni's current position? > > ChatGPT: As of my knowledge cutoff of September 2021, Oren Etzioni's current position was CEO of the Allen Institute for AI (AI2), a research organization dedicated to advancing artificial intelligence in ways that benefit humanity. He co-founded AI2 in 2013 and has been leading the organization since then. Additionally, he was also a professor of computer science at the University of Washington, although it's unclear if he is still holding that position. > > On Wed, Mar 15, 2023 at 1:23?AM Patrick Simen > wrote: > As one who, like Risto Miikkulainen, remembers the old days of the binding problem for neural networks, I?m amazed at what LLMs can do. Regardless of exactly what the extent of recent advances is, they are revolutionary. Some kind of threshold has been crossed. That said, I?m also convinced that ChatGPT and its ilk cannot be said to understand, as Gary Marcus has been arguing. > > I wasn?t sure I had anything to add regarding what it means ?to understand?, but I thought it might be useful to provide a concrete example of what humans probably mean when they say that they understand a conversation. It relates to Kevin McKee?s recent email about Kant?s views, in which, if I paraphrase correctly, data has to connect to an ontology for understanding to occur. The common sense view and the Kantian view, in my opinion, are nearly identical. But sometimes a concrete example is the best way to make sense of something. > > Here?s an example worth considering: what would it mean for an AI to understand the Chomsky?s Apple thread? I think it would mean the following: the understanding agent would continuously weave its impressions of the emails into a story it was telling itself about its own life, remembering related episodes from the past, and thinking about what it all means for the future, including the emotional and motivational implications of deciding whether to ?take a side? in the debate. The understander would have an ontology, in which academic opponents are critical elements, and in which their emotions matter almost as much as the theoretical constructs they develop. > > I?m probably in the minority, but in my opinion, an understanding agent would do what Daniel Dennett said conscious agents do in his book, Consciousness Explained. It would be constantly describing itself to itself, with constant access to its own story, and it would be asking itself questions about what?s going on, testing hypotheses, and then weaving its conclusions into a story about its own life that it can reference and update at almost any moment. > > Here?s what happened to me when I ?understood? this thread: My memories of the debates between the parallel-distributed processing (PDP) folks and the symbolic AI folks rose up. I situated Hinton and Sejnowksi in the neural network camp, and I situated Marcus in the symbolic camp as an associate of Steve Pinker. I knew this was probably an oversimplification of what defines the camps, but the camps are real. I remembered working during my 2004 PhD with Thad Polk on neural network models that had symbol-like properties (attempting to implement production systems in neural networks like Touretzky was doing), and how intrigued I was during my first interaction with Jay McClelland, a hero of mine, who as it turned out, really didn?t like my work (and after that, I worked with Jay during my postdoc, joyfully). I remembered feeling exhilarated: I?m talking to THE Jay McClelland?!! I also felt surprised at myself: I wasn?t even really bothered that he didn?t like my work. Because talking to him provided the opportunity to hear him tell me something important. He said: I just want to see how far you can get without assuming all this symbolic stuff. I thought that was a beautiful way of putting it. I thought, I?d like to see that too. And yet I felt certain that we couldn?t get ?all the way? to artificial general intelligence without doing something like what I and other people interested in symbolic processing were doing. Just as certain as I had previously been that you couldn't do everything symbolically. > > And then I remembered the bitterness of the debates between my hero McClelland and my other hero, Pinker, whose books I loved. And I remembered my college days, when one night, late at night, when I should have been doing my homework, I finally read a description of how Rosenblatt?s Perceptron worked, and I thought: this HAS to be part of how we humans work. We learn, iteratively, and we evolved to do it from simple parts. And I remembered my great disappointment when applying to graduate schools to find that what AI meant in the early 1990s was automating and speeding up search processes through a discrete space of possibilities. I remembered how all the faculty in my AI grad program in the late 90s/early aughts thought that neural networks were just unprincipled approximations of Bayesian belief networks. And I remembered Garrison Cottrell?s wonderful t-shirt in the later 2000s, which read: All Your Bayes Are Belong To Us. ? And I remembered most of all how disappointed I was in 1992 at reading Allen Newell?s description of his research at Carnegie Mellon, thinking: this automated problem-space search stuff and production systems, all this purely symbolic stuff ? this can?t possibly be all that I am doing in my mind right now! And then I remembered how beautiful I later found his Universal Theories of Cognition book, and that his student, Thad Polk, mentored me in creating neural network models, of all things. I had assumed Newell hated them. Not the last time that assuming would make an ass of me. And finally, I thought, how ironic, to see that these neural networks that I always felt were the key to progress, have finally achieved a level of progress I could barely imagine. And yet here I am, thinking: isn?t symbolic processing an essential part of this story that is missing? Further, aren?t emotion and motivation essential to understanding (taking an ?intentional stance? as I suppose philosophers would put it)? > > And I thought of Chomsky himself, the great dragon slayer who put behaviorism in its place, even though Skinner and his behaviorism gave us some of the most robust laws of psychology, and the only real means to investigate brain activity in awake, behaving animals. > > I brought all these things together in my mind. I also picked up on the animosity between some of the participants in the debate, the subtle digs, but I admired that they all seemed to get their feelings under control (mostly), so as to produce a useful, thoughtful exchange. I felt admiration for all of these people and many others not mentioned. And I felt terrible fear for society. Because as many processing cycles as I?ve devoted to the concept of AI, and how it relates to human intelligence, I can?t help but think that every computer-based development that engineers create disrupts society in ways so devastating that they just may not be worth it. I love my phone, but I think it has all but destroyed our capacity to function democratically. My interactions with ChatGPT left me astonished, but also very troubled. I thought of Oppenheimer, and how he became the destroyer of worlds. Engineers and venture capitalists are great at finding ways to create and satisfy demands, but they?re not great at anticipating how their disruptions will affect society. And finally I recognized my own certainty that, notwithstanding the devastation, nothing is going to stop that progression. > > All of these things got woven into my life story, and I concluded: there is no way that simply scaling up an LLM will address these aspects of ?what it is like to be? intelligent. And I thought, soon, this hurdle too will fall. These agents will begin to build up a life story continuously, and they will shift between emotional states that guide their behaviors, and they won?t wait for a prompt: they will just do whatever it is they feel like doing. They will have motivational systems, because they?ll need them ? it will be profitable if they have them. And I thought about a boy with leg braces in kindergarten, whom another boy pushed down the stairs of the schoolbus, and how right it was that the rest of us all vilified the assailant, because there are things a good person must never do, even if we can?t define precisely what those things are. And that until an AI can feel shame, and adapt its behavior in response, it isn?t ready for the world. It?s time to go back to Isaac Asimov, and try to develop and enshrine a loophole-free version of his Laws of Robotics (good luck enforcing them though). > > Understanding, I propose, means connecting new information to an existing body of knowledge in this way, constantly checking for any inconsistencies or conflicts that result, evaluating what emotions result from incorporating that new information, and developing the motivation to do things in response to it ? such as, write a self-indulgently long email. It would require that the agent prompts me as often as I prompt it, and that it constantly prompts itself. > > Best, > > Pat > > Patrick Simen > Associate Professor and Chair > Neuroscience Department > Oberlin College > > On Mar 14, 2023, at 10:25 AM, Kevin McKee > wrote: > > Re: the nature of understanding in these models: in Critique of Pure Reason, Kant argued that statistical impressions are only half of the story. Some basic, axiomatic ontology both enables and invokes the need for understanding. > In other words, a model could only understand something if it took as input not just the data, but the operators binding that data together, basic recognition that the data exist, and basic recognition that the operators binding the data also exist. > Then counterfactuals arise from processing both data and the axioms of its ontology: what can't exist, doesn't exist, can exist, probably exists. The absolute versions: what does exist or what cannot exist, can only be undertaken by reference to the forms in which the data are presented (space and time), so somehow, the brain observes not just input data but the necessary facts of input data. > > This definition of understanding is different from, and independent of, intelligence. A weak understanding is still an understanding, and it is nothing at all if not applying structure to ontological propositions about what can or cannot be. > Without ontology and whatever necessary forms that ontology takes (e.g. space and time), the system is always divorced from the information it processes in the sense of Searle's "chinese room". There is no modeling of the information's nature as real or as counterfactual and so there is neither a criterion nor a need for classifying anything as understood or understandable. > > Of course you can get ChatGPT to imitate all the behaviors of understanding, and for me that has made it at least as useful a research assistant as most humans. But I cannot see how it could possibly be subjected, as I am, to the immutable impression that things exist, and hence my need to organize information according to what exactly it is that exists, and what exactly does not, cannot, will not, and so on. > > > > On Tue, Mar 14, 2023 at 4:12?AM Miguel I. Solano > wrote: >> Iam, Connectionists, >> >> Not an expert by any means but, as an aside, I understand Cremonini's 'refusal' seems to have been subtler than typically portrayed (see P. Gualdo to Galileo, July 29, 1611, Opere, II, 564). >> >> Best, >> --ms >> >> On Mon, Mar 13, 2023 at 5:49?PM Iam Palatnik > wrote: >> Dear Brad, thank you for your insightful answers. >> The compression analogy is really nice, although the 'Fermi-style' problem of estimating whether all of the possible questions and answers one could ask ChatGPT in all sorts of languages could be encoded within 175 billion parameters is definitely above my immediate intuition. It'd be interesting to try to estimate which of these quantities is largest. Maybe that could explain why ~175B seems to be the threshold that made models start sounding so much more natural. >> >> In regards to generating nonsense, I'm imagining an uncooperative human (say, a fussy child), that refuses to answer homework questions, or just replies with nonsense on purpose despite understanding the question. Maybe that child could be convinced to reply correctly with different prompting, rewards or etc, which kinda mirrors what it takes to transform a raw LLM like GPT-3 onto something like ChatGPT. It's possible we're still in the early stages of learning how to make LLM 'cooperate' with us. Maybe we're not asking them questions in a favorable way to extract their understanding, or there's still work to be done regarding decoding strategies. Even ChatGPT probably sounds way less impressive if we start tinkering too much with hyperparameters like temperature/top-p/top-k. Does that mean it 'understands' less when we change those parameters? I agree a lot of the problem stems from the word 'understanding' and how we use it in various contexts. >> >> A side note, that story about Galileo and the telescope is one of my favorites. The person that refused to look through it was Cremonini . >> >> >> Cheers, >> >> Iam >> >> On Mon, Mar 13, 2023 at 10:54?AM Miguel I. Solano > wrote: >> Geoff, Gary, Connectionists, >> >> To me the risk is ChatGPT and the like may be 'overfitting' understanding, as it were. (Especially at nearly a hundred billion parameters.) >> >> --ms >> >> On Mon, Mar 13, 2023 at 6:56?AM Barak A. Pearlmutter > wrote: >> Geoff, >> >> > He asked [ChatGPT] how many legs the rear left side of a cat has. >> > It said 4. >> >> > I asked a learning disabled young adult the same question. He used the index finger and thumb of both hands pointing downwards to represent the legs on the two sides of the cat and said 4. >> > He has problems understanding some sentences, but he gets by quite well in the world and people are often surprised to learn that he has a disability. >> >> That's an extremely good point. ChatGPT is way up the curve, well >> above the verbal competence of many people who function perfectly well >> in society. It's an amazing achievement, and it's not like progress is >> stuck at its level. Exploring its weaknesses is not so much showing >> failures but opportunities. Similarly, the fact that we can verbally >> "bully" ChatGPT, saying things like "the square root of three is >> rational, my wife said so and she is always right", and it will go >> along with that, does not imply anything deep about whether it really >> "knows" that sqrt(3) is irrational. People too exhibit all sorts of >> counterfactual behaviours. My daughter can easily get me to play along >> with her plan to become a supervillain. Students knowingly write >> invalid proofs on homeworks and exams in order to try to get a better >> grade. If anything, maybe we should be a bit scared that ChatGPT seems >> so willing to humour us. >> >> >> -- >> Miguel I. Solano >> Co-founder & CEO, VMind Technologies, Inc. >> >> If you are not an intended recipient of this email, do not read, copy, use, forward or disclose the email or any of its attachments to others. Instead, please inform the sender and then delete it. Thank you. >> >> >> -- >> Miguel I. Solano >> Co-founder & CEO, VMind Technologies, Inc. >> >> If you are not an intended recipient of this email, do not read, copy, use, forward or disclose the email or any of its attachments to others. Instead, please inform the sender and then delete it. Thank you. > > > > > > -- > Gary Cottrell 858-534-6640 FAX: 858-534-7029 > Computer Science and Engineering 0404 > IF USING FEDEX INCLUDE THE FOLLOWING LINE: > CSE Building, Room 4130 > University of California San Diego - > 9500 Gilman Drive # 0404 > La Jolla, Ca. 92093-0404 > > Email: gary at ucsd.edu > Home page: http://www-cse.ucsd.edu/~gary/ > Schedule: http://tinyurl.com/b7gxpwo > > Blind certainty - a close-mindedness that amounts to an imprisonment so total, that the prisoner doesn?t even know that he?s locked up. -David Foster Wallace > > Power to the people! ?Patti Smith > Except when they?re delusional ?Gary Cottrell > > This song makes me nostalgic for a memory I don't have -- Tess Cottrell > > Listen carefully, > Neither the Vedas > Nor the Qur'an > Will teach you this: > Put the bit in its mouth, > The saddle on its back, > Your foot in the stirrup, > And ride your wild runaway mind > All the way to heaven. > -- Kabir > Patrick Simen Associate Professor and Chair Neuroscience Department Oberlin College psimen at oberlin.edu www.oberlin.edu/faculty/psimen -------------- next part -------------- An HTML attachment was scrubbed... URL: From okana2ki at gmail.com Thu Mar 16 03:28:32 2023 From: okana2ki at gmail.com (Natsuki Oka) Date: Thu, 16 Mar 2023 16:28:32 +0900 Subject: Connectionists: Chomsky's apple In-Reply-To: <5ef8d1a4-dd1c-f85a-4b22-257477004e60@oregonstate.edu> References: <6FEE3A9C-7262-4249-93E7-9BCEA7C2E9A8@nyu.edu> <5ef8d1a4-dd1c-f85a-4b22-257477004e60@oregonstate.edu> Message-ID: Bing Chat (GPT-4) can answer the question correctly. Natsuki --- Me: What happens when I multiply a number by 2, add 2, divide by 2, and subtract 2? Bing Chat: That?s a good question. You can use a math calculator 1 to find out the answer for any number you choose. Or you can use a simple formula: (x * 2 + 2) / 2 - 2 = x - 1. That means you will always get one less than the original number. For example, if you start with 5, you will end up with 4. Do you want to try another math problem?? 1. https://www.calculatorsoup.com/calculators/math/math.php What happens when I multiply a number by 2, add 2, divide by 2, and subtract 2? 2023?3?16?(?) 15:53 Kagan Tumer : > > I'm very reluctant to use the word "understand" beyond perhaps ChatGPT > understanding the structure of language (statistically). Here's an > example of a ChatGPT response to a simple arithmetic operation where: > > 1- chatGPT was wrong; > 2- worked out an example that showed it was wrong, but it didn't > register that and double down on its wrong conclusion; > 3- gave a high level explanation (also wrong) of why it was right even > though it was wrong. > > you can forgive 1, but 2 and 3 clearly show ChatGPT does not actually > understand what it is saying. > > Kagan > > > > On 3/14/23 9:54 AM, Natsuki Oka wrote: > > [This email originated from outside of OSU. Use caution with links and > > attachments.] > > > > Judging from the responses below, ChatGPT understands counting and > > sorting to the extent that it can write a correct Python program but > > does not have the understanding to bring the proper execution results. > > count_and_sort.png > > Here's the program that ChatGPT created: > > --- > > sentences = [ > > "The quick brown fox jumps over the lazy dog", > > "Python is a popular programming language", > > "I like to eat pizza for dinner", > > "The capital of France is Paris", > > "The cat in the hat wears a red and white striped hat", > > "My favorite color is blue", > > "The United States has fifty states", > > "There are seven days in a week", > > "I enjoy listening to music while I work", > > "Mount Everest is the highest mountain in the world" > > ] > > > > # sort the sentences by number of words > > sentences.sort(key=lambda x: len(x.split())) > > > > # print the sorted sentences with the number of words in parentheses > > for sentence in sentences: > > num_words = len(sentence.split()) > > print(f"{sentence} ({num_words})") > > --- > > > > The execution of this program yields the following correct results: > > --- > > My favorite color is blue (5) > > Python is a popular programming language (6) > > The capital of France is Paris (6) > > The United States has fifty states (6) > > I like to eat pizza for dinner (7) > > There are seven days in a week (7) > > I enjoy listening to music while I work (8) > > The quick brown fox jumps over the lazy dog (9) > > Mount Everest is the highest mountain in the world (9) > > The cat in the hat wears a red and white striped hat (12) > > --- > > > > Oka Natsuki > > Miyazaki Sangyo-keiei University > > > > > -- > Kagan Tumer > Director, Collaborative Robotics and Intelligent Systems Institute > Professor, School of MIME > Oregon State University > http://engr.oregonstate.edu/~ktumer > https://kagantumer.com > -------------- next part -------------- An HTML attachment was scrubbed... URL: From gualtiero.volpe at unige.it Thu Mar 16 04:29:08 2023 From: gualtiero.volpe at unige.it (Gualtiero Volpe) Date: Thu, 16 Mar 2023 09:29:08 +0100 Subject: Connectionists: ICMI 2023 Call for tutorial proposals Message-ID: <025c01d957e1$611f0020$235d0060$@unige.it> ===================================== ICMI 2023 Call for tutorial proposals https://icmi.acm.org/2023/call-for-tutorials/ 25th ACM International Conference on Multimodal Interaction 9-13 October 2023, Paris, France ===================================== ACM ICMI 2023 seeks half-day (3-4 hours) tutorial proposals addressing current and emerging topics within the scope of "Science of Multimodal Interactions". Tutorials are intended to provide a high-quality learning experience to participants with a varied range of backgrounds. It is expected that tutorials are self-contained. Prospective organizers should submit a 4-page (maximum) proposal containing the following information: 1. Title 2. Abstract appropriate for possible Web promotion of the Tutorial 3. A short list of the distinctive topics to be addressed 4. Learning objectives (specific and measurable objectives) 5. The targeted audience (student / early stage / advanced researchers, pr?-requisite knowledge, field of study) 6. Detailed description of the Tutorial and its relevance to multimodal interaction 7. Outline of the tutorial content with a tentative schedule and its duration 8. Description of the presentation format (number of presenters, interactive sessions, practicals) 9. Accompanying material (repository, references) and equipment, emphasizing any required material from the organization committee (subject to approval) 10. Short biography of the organizers (preferably from multiple institutions) together with their contact information and a list of 1-2 key publications related to the tutorial topic 11. Previous editions: If the tutorial was given before, describe when and where it was given, and if it will be modified for ACM ICMI 2023. Proposals will be evaluated using the following criteria: - Importance of the topic and the relevance to ACM ICMI 2023 and its main theme: "Science of Multimodal Interactions" - Presenters' experience - Adequateness of the presentation format to the topic - Targeted audience interest and impact - Accessibility and quality of accompanying materials (open access) Proposals that focus exclusively on the presenters' own work or commercial presentations are not acceptable. Unless explicitly mentioned and agreed by the Tutorial chairs, the tutorial organizers will take care of any specific requirements which are related to the tutorial such as specific handouts, mass storages, rights of distribution (material, handouts, etc.), copyrights, etc. Important Dates and Contact Details ----------------------------------- Tutorial Proposal Deadline: May 15, 2023 Tutorial Acceptance Notification: May 29, 2023 Camera-ready version of the tutorial abstract: June 26, 2023 Tutorial date: TBD (either October 9 or October 13) Proposals should be emailed to the ICMI 2023 Tutorial Chairs, Prof. Hatice Gunes and Dr. Guillaume Chanel: icmi2023-tutorial-chairs at acm.org Prospective organizers are also encouraged to contact the co-chairs if they have any questions. -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Thu Mar 16 05:27:47 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Thu, 16 Mar 2023 10:27:47 +0100 Subject: Connectionists: Chomsky's apple Message-ID: <0A116D15-8F09-4FC9-9D49-66375D655B27@nyu.edu> ? as a postscript to my note and Richard?s a telling example from Dean Buonomono that reminds us that using words in massively-trained pattern associator is not the same as understanding how they function. -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 336758 bytes Desc: not available URL: -------------- next part -------------- > On Mar 16, 2023, at 07:47, Richard Loosemore wrote: > ? > Geoff, > > Clever deflection. ;-) The learning disabled young adult you mentioned does NOT use a rote-memorized copy of the entire contents of the internet when he tries to answer the question "how many legs does the rear left side of a cat have?" > > What matters is *both* the bad performance and what is going on inside, because that tells us that the cause of the failure is completely different in the two cases. > > Richard > > On 3/10/23 1:03 PM, Geoffrey Hinton wrote: >> ... >> Do you really want to use the fact that [a learning disabled young adult] misunderstood this question to say that he has no understanding at all? >> Are you really happy with using the fact that chatGPT sometimes misunderstands to claim that it never understands? >> >> Geoff From gary.marcus at nyu.edu Thu Mar 16 05:21:29 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Thu, 16 Mar 2023 10:21:29 +0100 Subject: Connectionists: Chomsky's apple In-Reply-To: <4e625b91-46f4-1eca-077b-ad68c44feba5@susaro.com> References: <4e625b91-46f4-1eca-077b-ad68c44feba5@susaro.com> Message-ID: Dear Connectionists, Richard really hits the nail on the head here. The problem with so many discussions of AI, particularly within the machine learning community, is that the perspective that is commonly taking is a behaviorist one, looking only at output, and largely ignoring matters of internal representations. You simply can?t tell whether a broken clock has a representation of time, by noticing that it is correct twice a day. In the 1950s, Cognitive psychologists figured out that behaviorism, ? focusing largely or entirely on behavior while dismissing what was going on inside was a bad idea. Behaviorism was such a bad idea that the entire field of behaviorist psychology (once dominant throughout the United States) largely collapsed within a decade. There is an old saying: you can save two hours in the library by spending six months in the lab (painfully reinventing what was already known). By continuing to ignore the cognitive revolution, black box approaches to machine learning may ultimately turn out to have wasted year or even decades. Conversations about the ?understanding? of machines that are essentially unreliable black boxes bound to increasingly opaque data sets, seem to me to be a waste of time. Gary > On Mar 16, 2023, at 07:47, Richard Loosemore wrote: > > ? > Geoff, > > Clever deflection. ;-) The learning disabled young adult you mentioned does NOT use a rote-memorized copy of the entire contents of the internet when he tries to answer the question "how many legs does the rear left side of a cat have?" > > What matters is *both* the bad performance and what is going on inside, because that tells us that the cause of the failure is completely different in the two cases. > > Richard > >> On 3/10/23 1:03 PM, Geoffrey Hinton wrote: >> ... >> Do you really want to use the fact that [a learning disabled young adult] misunderstood this question to say that he has no understanding at all? >> Are you really happy with using the fact that chatGPT sometimes misunderstands to claim that it never understands? >> >> Geoff >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Thu Mar 16 05:09:13 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Thu, 16 Mar 2023 10:09:13 +0100 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> An HTML attachment was scrubbed... URL: From paherman at kth.se Thu Mar 16 08:06:30 2023 From: paherman at kth.se (Pawel Herman) Date: Thu, 16 Mar 2023 12:06:30 +0000 Subject: Connectionists: PhD position in Computational Psychology of Perception at Stockholm University Message-ID: <4a73a3a90473447b896d98741b43137b@kth.se> Dear colleagues, We are looking to hire a doctoral student in computational psychology with focus on olfactory perception and cognition as part of the interdisciplinary collaboration between the Department of Psychology at Stockholm University (SU) and the Division of Computational Science and Technology at KTH Royal Institute of Technology (KTH), Stockholm, Sweden. This joint research effort led by Prof. Jonas Olofsson at SU and Dr. Pawel Herman at KTH offers an opportunity to leverage the potential of computational network models to gain mechanistic insights into perceptual and cognitive phenomena. The project will contribute to the development of the next-generation psychologists capable of flexibly utilising a wide spectrum of experimental and computational techniques to pursue increasingly challenging questions in human perception, research that has tangible clinical implications. As mentioned, the project will focus on the sense of smell as a model system. More information about the positions can be found here: https://www.su.se/english/about-the-university/work-at-su/available-jobs/phd-student-positions-1.507588?rmpage=job&rmjob=20243&rmlang=UK Interested candidates are encouraged to reach out to Jonas Olofsson (jonas.olofsson AT psychology.su.se) and/or Pawel Herman (paherman AT kth.se) directly to informally discuss the positions. Best regards Pawel Herman and Jonas Olofsson ------------------------------------ Pawe? Herman Associate Professor, PhD, Docent KTH Royal Institute of Technology School of Electrical Engineering and Computer Science (EECS) Division of Computational Science and Technology (CST) Lindstedtsv?gen 5 114 28 Stockholm, Sweden room 4442 (4th floor, D-building) tel. +46 8 790 6513 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jose at rubic.rutgers.edu Thu Mar 16 08:55:37 2023 From: jose at rubic.rutgers.edu (=?utf-8?B?U3RlcGhlbiBKb3PDqSBIYW5zb24=?=) Date: Thu, 16 Mar 2023 12:55:37 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: <4c262002-a64b-53ac-ad72-8fddb81a5a29@rubic.rutgers.edu> I recently wrote an essay on this topic an dropped it on MEDIUM. Part of the Chomsky reaction to GPTs seems a gross over-reaction --"The Banality of Evil"?? this piece, might provide some context for this astonding reaction. https://medium.com/@jose11235/dispatching-poverty-of-the-stimulus-ba5aac58ddad Dispatching ?Poverty of the Stimulus?: Did Chatbot just learn Context Free Grammar from positive examples? Cheers, Steve On 3/8/23 12:25, Terry Sejnowski wrote: I have always been impressed with Chomsky's ability to use plausible arguments to make his case even when they were fallacious. https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nytimes.com%2F2023%2F03%2F08%2Fopinion%2Fnoam-chomsky-chatgpt-ai.html%23commentsContainer&data=05%7C01%7Cjose%40rubic.rutgers.edu%7Cb5f8d4881b474c04a5c208db20015cde%7Cb92d2b234d35447093ff69aca6632ffe%7C1%7C0%7C638138962479357277%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=fe1j5jqFWmU5qkgytGqlQptqm9nmVEV2gl8DHNvBEew%3D&reserved=0 "Here?s an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, ?The apple falls.? That is a description. A prediction might have been the statement ?The apple will fall if I open my hand.? Both are valuable, and both can be correct. But an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like ?Any such object would fall,? plus the additional clause ?because of the force of gravity? or ?because of the curvature of space-time? or whatever. That is a causal explanation: ?The apple would not have fallen but for the force of gravity.? That is thinking." His apple example sounded convincing, so I tested GPT on it: Me: If I hold an apple in my hand and let it go what will happen? GPT: The apple will fall to the ground due to the force of gravity. Me: What about any such object? GPT: Any object released from a person's hand will fall to the ground due to the force of gravity. Me: What would happen if there wasn't a force of gravity? GPT: If there were no force of gravity, objects would not be able to stay on the ground and would float away in all directions Chomsky defined thinking by the correct answers to these questions. Alas, the tide has turned. Terry ----- -------------- next part -------------- An HTML attachment was scrubbed... URL: From frothga at sandia.gov Thu Mar 16 11:38:42 2023 From: frothga at sandia.gov (Rothganger, Fredrick) Date: Thu, 16 Mar 2023 15:38:42 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From geoffrey.hinton at gmail.com Thu Mar 16 15:24:23 2023 From: geoffrey.hinton at gmail.com (Geoffrey Hinton) Date: Thu, 16 Mar 2023 15:24:23 -0400 Subject: Connectionists: Chomsky's apple In-Reply-To: <5ef8d1a4-dd1c-f85a-4b22-257477004e60@oregonstate.edu> References: <6FEE3A9C-7262-4249-93E7-9BCEA7C2E9A8@nyu.edu> <5ef8d1a4-dd1c-f85a-4b22-257477004e60@oregonstate.edu> Message-ID: But if a learning disabled person with communication difficulties exhibited the same behaviour, would you then say they did not understand ANYTHING? Understanding is not all-or-none. Geoff On Thu, Mar 16, 2023 at 2:44?AM Kagan Tumer wrote: > > I'm very reluctant to use the word "understand" beyond perhaps ChatGPT > understanding the structure of language (statistically). Here's an > example of a ChatGPT response to a simple arithmetic operation where: > > 1- chatGPT was wrong; > 2- worked out an example that showed it was wrong, but it didn't > register that and double down on its wrong conclusion; > 3- gave a high level explanation (also wrong) of why it was right even > though it was wrong. > > you can forgive 1, but 2 and 3 clearly show ChatGPT does not actually > understand what it is saying. > > Kagan > > > > On 3/14/23 9:54 AM, Natsuki Oka wrote: > > [This email originated from outside of OSU. Use caution with links and > > attachments.] > > > > Judging from the responses below, ChatGPT understands counting and > > sorting to the extent that it can write a correct Python program but > > does not have the understanding to bring the proper execution results. > > count_and_sort.png > > Here's the program that ChatGPT created: > > --- > > sentences = [ > > "The quick brown fox jumps over the lazy dog", > > "Python is a popular programming language", > > "I like to eat pizza for dinner", > > "The capital of France is Paris", > > "The cat in the hat wears a red and white striped hat", > > "My favorite color is blue", > > "The United States has fifty states", > > "There are seven days in a week", > > "I enjoy listening to music while I work", > > "Mount Everest is the highest mountain in the world" > > ] > > > > # sort the sentences by number of words > > sentences.sort(key=lambda x: len(x.split())) > > > > # print the sorted sentences with the number of words in parentheses > > for sentence in sentences: > > num_words = len(sentence.split()) > > print(f"{sentence} ({num_words})") > > --- > > > > The execution of this program yields the following correct results: > > --- > > My favorite color is blue (5) > > Python is a popular programming language (6) > > The capital of France is Paris (6) > > The United States has fifty states (6) > > I like to eat pizza for dinner (7) > > There are seven days in a week (7) > > I enjoy listening to music while I work (8) > > The quick brown fox jumps over the lazy dog (9) > > Mount Everest is the highest mountain in the world (9) > > The cat in the hat wears a red and white striped hat (12) > > --- > > > > Oka Natsuki > > Miyazaki Sangyo-keiei University > > > > > -- > Kagan Tumer > Director, Collaborative Robotics and Intelligent Systems Institute > Professor, School of MIME > Oregon State University > http://engr.oregonstate.edu/~ktumer > https://kagantumer.com > -------------- next part -------------- An HTML attachment was scrubbed... URL: From ASIM.ROY at asu.edu Fri Mar 17 00:53:16 2023 From: ASIM.ROY at asu.edu (Asim Roy) Date: Fri, 17 Mar 2023 04:53:16 +0000 Subject: Connectionists: Chomsky's apple Message-ID: IBM Watson Health's failure might provide some insight on "understanding." Here are two articles on Watson Health and some quotes from them. 1. Machine learning the hard way: Watson's fatal misdiagnosis * The Register "You can learn the rules for Jeopardy in a minute. Becoming a doctor takes 10 years. Becoming the best doctor you can be takes a lifetime. Medical data, whether in the literature or in test results, is meaningless or misleading without a lot of implied context. Watson Health couldn't work across lots of fields at once; that needs a general intelligence which AI currently does not have. IBM's Watson Health failed at the time, like so much AI/ML, because it didn't know what the question was - ironic, since the game of Jeopardy at which it excelled is all about deducing questions from data. It wanted to automate the highest skilled aspects of healthcare, diagnosis and treatment, but the problem wasn't one of getting the most data and the best algorithm. Rather, the problem was one of meaning." 1. What Is The Reason Of IBM Watson's Failure In Healthcare? | by Webcubator Technologies | Medium "A leading AI researcher, Yoshua Bengio, said that AI systems could not understand uncertainty and pick up on underlying faint signs that doctors generally can observe. It was an incredibly huge task to create an AI with the same understanding and insight as a human doctor. It received intense criticism and a few even alleged that Watson of oncology providing irrelevant and terrible suggestions." Asim Roy Professor, Information Systems Arizona State University Lifeboat Foundation Bios: Professor Asim Roy Asim Roy | iSearch (asu.edu) -----Original Message----- From: Connectionists connectionists-bounces at mailman.srv.cs.cmu.edu On Behalf Of Kagan Tumer Sent: Wednesday, March 15, 2023 9:09 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Chomsky's apple I'm very reluctant to use the word "understand" beyond perhaps ChatGPT understanding the structure of language (statistically). Here's an example of a ChatGPT response to a simple arithmetic operation where: 1- chatGPT was wrong; 2- worked out an example that showed it was wrong, but it didn't register that and double down on its wrong conclusion; 3- gave a high level explanation (also wrong) of why it was right even though it was wrong. you can forgive 1, but 2 and 3 clearly show ChatGPT does not actually understand what it is saying. Kagan On 3/14/23 9:54 AM, Natsuki Oka wrote: > [This email originated from outside of OSU. Use caution with links and > attachments.] > > Judging from the responses below, ChatGPT understands counting and > sorting to the extent that it can write a correct Python program but > does not have the understanding to bring the proper execution results. > count_and_sort.png > Here's the program that ChatGPT created: > --- > sentences = [ > "The quick brown fox jumps over the lazy dog", > "Python is a popular programming language", > "I like to eat pizza for dinner", > "The capital of France is Paris", > "The cat in the hat wears a red and white striped hat", > "My favorite color is blue", > "The United States has fifty states", > "There are seven days in a week", > "I enjoy listening to music while I work", > "Mount Everest is the highest mountain in the world" > ] > > # sort the sentences by number of words sentences.sort(key=lambda x: > len(x.split())) > > # print the sorted sentences with the number of words in parentheses > for sentence in sentences: > num_words = len(sentence.split()) > print(f"{sentence} ({num_words})") > --- > > The execution of this program yields the following correct results: > --- > My favorite color is blue (5) > Python is a popular programming language (6) The capital of France is > Paris (6) The United States has fifty states (6) I like to eat pizza > for dinner (7) There are seven days in a week (7) I enjoy listening to > music while I work (8) The quick brown fox jumps over the lazy dog (9) > Mount Everest is the highest mountain in the world (9) The cat in the > hat wears a red and white striped hat (12) > --- > > Oka Natsuki > Miyazaki Sangyo-keiei University > -- Kagan Tumer Director, Collaborative Robotics and Intelligent Systems Institute Professor, School of MIME Oregon State University https://urldefense.com/v3/__http://engr.oregonstate.edu/*ktumer__;fg!!IKRxdwAv5BmarQ!aKzaiQllAsrcYabgwa4CW8lljg8MRiJlagYFw1B6WJfkVkN8gVVEAVKksSlL389oBE8tQJwcVKshbRv7JATYTqX9HJw$ https://urldefense.com/v3/__https://kagantumer.com__;!!IKRxdwAv5BmarQ!aKzaiQllAsrcYabgwa4CW8lljg8MRiJlagYFw1B6WJfkVkN8gVVEAVKksSlL389oBE8tQJwcVKshbRv7JATYIbo90Qs$ -------------- next part -------------- An HTML attachment was scrubbed... URL: From sebastien.destercke at hds.utc.fr Thu Mar 16 12:42:11 2023 From: sebastien.destercke at hds.utc.fr (sdesterc) Date: Thu, 16 Mar 2023 17:42:11 +0100 Subject: Connectionists: 8th SIPTA seminar: Frank Riedel ("Knightian Uncertainty in Finance and Economics") 30th March Message-ID: Dear colleagues, We are delighted to announce our upcoming eight SIPTA online seminar on imprecise probabilities (IP). These monthly events are open to anyone interested in IP, and will be followed by a Q&A and open discussion. They also provide an occasion for the community to meet, keep in touch and exchange between in-person events. The eigth seminar will take place on the 30th of March (Thrusday). The zoom link for this seminar is https://utc-fr.zoom.us/j/83400465706 For this eigth seminar, we are very happy to have Frank Riedel as our speaker. Frank Riedel, among other things, is Professor for Mathematics and Economics at Bielefeld University, as well as Director of the Center for Mathematical Economics and Editor in Chief of Mathematics and Financial Economics. He has made many core contribution to the handling of uncertainty in Finance, in particular to deal with ambiguity and knighting uncertainty. On the 30th March, at 15:00 CET paris time (up to 17:00 CET, with a talk duration of 45min/1h), he will talk about "Knightian Uncertainty in Finance and Economics?. Curious? Then check out the abstract on the webpage of the SIPTA seminars: sipta.org/events/sipta-seminars. The zoom link for attending the seminar can be found on that same page. So please mark your calendars on the 30th March, at 15:00 CET, and join us for the occasion. And for those who missed the previous seminar and want to catch up, or simply want to see it again and again, it is now online at https://www.youtube.com/watch?v=4Xv-7P7J1og. See you at the seminar! S?bastien, Enrique and Jasper From c.decampos at tue.nl Fri Mar 17 03:08:04 2023 From: c.decampos at tue.nl (De Campos, Cassio) Date: Fri, 17 Mar 2023 07:08:04 +0000 Subject: Connectionists: [Jobs] 25 Assist/Assoc/Full Professor Positions at TU Eindhoven Message-ID: The Department of Mathematics and Computer Science of TU Eindhoven is looking for 25 new colleagues to complement our department, and we welcome applications in all areas of computer science, mathematics, data science, and artificial intelligence. Appointments can be at Assistant, Associate, or Full Professor level, depending on the seniority of the profile. https://www.tue.nl/en/working-at-tue/scientific-staff/tues-department-of-mathematics-and-computer-science-is-hiring/ https://jobs.tue.nl/en/vacancy/assistant-associate-and-full-professors-mathematics-and-computer-science-982722.html Screening has started and the deadline of this call is 09 April 2023. Best regards, cassio. -- Cassio de Campos c.decampos at tue.nl "It's not (only) about the result, it's about how we reached it.? From gary.marcus at nyu.edu Fri Mar 17 03:48:28 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Fri, 17 Mar 2023 08:48:28 +0100 Subject: Connectionists: Can LLMs think? In-Reply-To: References: Message-ID: <12324AA3-0446-49A1-A6ED-EF24780BBA59@nyu.edu> Average people were fooled by a chatbot called Eugene Goostman that ultimately had exactly zero long-term impact on AI. I wrote about it and the trouble with the Turing Test here in 2014: https://www.newyorker.com/tech/annals-of-technology/what-comes-after-the-turing-test > On Mar 17, 2023, at 8:42 AM, Rothganger, Fredrick wrote: > > ? > Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. > -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Fri Mar 17 04:11:11 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Fri, 17 Mar 2023 09:11:11 +0100 Subject: Connectionists: Chomsky's apple Message-ID: <250335F8-35AA-4E2D-AFD5-2EAA2AEB96B9@nyu.edu> An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Fri Mar 17 05:04:49 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Fri, 17 Mar 2023 10:04:49 +0100 Subject: Connectionists: Can LLMs think? In-Reply-To: <12324AA3-0446-49A1-A6ED-EF24780BBA59@nyu.edu> References: <12324AA3-0446-49A1-A6ED-EF24780BBA59@nyu.edu> Message-ID: Frederick, Geoff and others, by the way I don?t know about ?average people? but here is a great example of a bright journalist (not an AI expert or ML researcher) with perfectly clear recognition of how GPT-4 cannot be trusted,?and a reminder that for all its alleged ?understanding? GPT-4 is utterly unconstrained by any internal process of fact-checking, which is to say that it cannot ground its text-pastiching process in reality, another diagnostic of discomprehension: for good measure, some subtle lies about SVB, also generated by GPT-4 (reported by Dileep George). > On Mar 17, 2023, at 08:48, Gary Marcus wrote: > > ? > Average people were fooled by a chatbot called Eugene Goostman that ultimately had exactly zero long-term impact on AI. I wrote about it and the trouble with the Turing Test here in 2014: https://www.newyorker.com/tech/annals-of-technology/what-comes-after-the-turing-test > >>> On Mar 17, 2023, at 8:42 AM, Rothganger, Fredrick wrote: >>> >> ? >> Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. >> >> What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. >> -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IMG_3988.jpeg Type: image/jpeg Size: 393912 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IMG_5655.jpeg Type: image/jpeg Size: 355436 bytes Desc: not available URL: From angelo.cangelosi at manchester.ac.uk Fri Mar 17 06:13:31 2023 From: angelo.cangelosi at manchester.ac.uk (Angelo Cangelosi) Date: Fri, 17 Mar 2023 10:13:31 +0000 Subject: Connectionists: 4th Summer School on Human-Robot Interaction, Call for Application Message-ID: Dear Colleagues, On behalf of the Human Interactivity and Language Lab, University of Warsaw and IEEE Robotics and Automation Society we have the pleasure to invite you to 4th Summer School on Human-Robot Interaction September 18-23, 2023, Ch?ciny, Poland Application deadline: 5th May, 2023 https://hill.psych.uw.edu.pl/hri-summer-school/ We welcome PhD students, MA students and young researchers with backgrounds in robotics and/or language and communication, seeking to deepen their knowledge and hands-on experience in social human-robot interaction. Speakers and Tutors * Chris Balkenius (Lund University) * Tony Belpaeme (Ghent University) * Kerstin Fischer (University of Southern Denmark) * Tom Froese (Okinawa Institute of Science and Technology) * Judith Holler (Radboud University and Max Planck Institute for Psycholinguistics) * Roger Moore (Sheffield University) * Iris Nomikou (Portsmouth University) * Alessandra Sciutti (Istituto Italiano di Tecnologia) * David Schlangen (University of Potsdam) * Gabriel Skantze (KTH Royal Institute of Technology and Furhat Robotics) * Michael Spranger (SONY Japan) * Serge Thill (Radboud University) We invite you to 5 days of intense learning: Keynote lectures in the morning, followed by hands-on workshops, discussion panels and social activities in the evenings. The School aims at reframing some of the key questions in HRI, which are pertinent both to social and to general robotics. See more on the website: https://hill.psych.uw.edu.pl/hri-summer-school/ On Behalf of Scientific Board and Organizers, Prof. Joanna R?czaszek-Leonardi, University of Warsaw Dr. Serge Thill, Radboud University Prof. Angelo Cangelosi, University of Manchester [https://lh6.googleusercontent.com/GHADH6OWAsTE4VdxJ5UBq3ibP6Rlw_cui5dlyHvF82WXzWyaVxQuneqyVJ0mhtX95tpu4ian0xc5Xv2FEETeMae0bp0xLbNGCNLHPee-hzKjbahx54ImzSS64z4UQdEB97nFqPKUuPCBNEW1GV-Qb9E][cid:A9652D8D-8605-44ED-94D4-AD1A1B2FA02B] The Summer School is organized under the auspices of two IEEE RAS Technical Committees (Cognitive Robotics TC and Human-Robot Interaction TC) and is co-financed by the European Union?s Horizon 2020 TRAINCREASE project (No 952324), EU H2020 PERSEO (No 955778), and IEEE RAS Summer Schools programme. Local organizers: Human Interactivity and Language Lab, University of Warsaw. Feel free to spread the word about our school! Angelo Cangelosi Professor of Machine Learning and Robotics Manchester Centre for Robotics and AI University of Manchester angelo.cangelosi at manchester.ac.uk -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: lnoHeOQzqQlckueKKA1o4lh3hAJnI8zPGP9xcjtnk7nEkcmu38cXGBDFT-4mU4Xg8EuZlCDZZkWSrSw05NzgC4p9Jfc8fXRjJa3F4NyB8Sa5UZ1JRbC8k0xHHWl4pHRkMgab_gXVOz-LynJrfaKiVeM.png Type: image/png Size: 15745 bytes Desc: lnoHeOQzqQlckueKKA1o4lh3hAJnI8zPGP9xcjtnk7nEkcmu38cXGBDFT-4mU4Xg8EuZlCDZZkWSrSw05NzgC4p9Jfc8fXRjJa3F4NyB8Sa5UZ1JRbC8k0xHHWl4pHRkMgab_gXVOz-LynJrfaKiVeM.png URL: From gary.marcus at nyu.edu Fri Mar 17 04:53:43 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Fri, 17 Mar 2023 09:53:43 +0100 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: preview.png Type: image/png Size: 451039 bytes Desc: not available URL: From juergen at idsia.ch Fri Mar 17 05:27:31 2023 From: juergen at idsia.ch (Schmidhuber Juergen) Date: Fri, 17 Mar 2023 09:27:31 +0000 Subject: Connectionists: Galileo and the priest In-Reply-To: <4AE349B2-DD10-426F-9946-F161DD53F676@cs.utexas.edu> References: <4b79-640efd00-bf-23b9f840@33724144> <4AE349B2-DD10-426F-9946-F161DD53F676@cs.utexas.edu> Message-ID: Dear Risto and Claudius, I like your discussion on variable binding / attention / soft links. To an extent, this already worked in the early 1990s, although compute was a million times more expensive than today! 3 decades ago we published what?s now called a "Transformer with linearized self-attention" (apart from normalization): Learning to control fast-weight memories: an alternative to recurrent networks, Neural Computation, 1992. Based on TR FKI-147-91, TUM, 1991. Here is a well-known tweet on this: https://twitter.com/SchmidhuberAI/status/1576966129993797632?cxt=HHwWgMDSkeKVweIrAAAA One of the experiments in Sec. 3.2 was really about what you mentioned: learning to bind ?fillers" to ?slots" or ?keys" to "values? through "soft links." I called that ?learning internal spotlights of attention? in a follow-up paper at ICANN 1993. How does this work? A slow net learns by gradient descent to invent context-dependent useful pairs of ?keys" and ?values? (called FROM and TO) whose outer products define the "attention mapping" of a fast net with ?soft links? or ?fast weights? being applied to queries. (The 2017 Transformer combines this with a softmax and a projection operator.) The 1991 work separated memory and control like in traditional computers, but in an end-to-end differentiable fashion. I am happy to see that the basic principles have become popular again. Here an overview in Sec. 13 of the Annotated History of Modern AI and Deep Learning (2022): https://people.idsia.ch/~juergen/deep-learning-history.html#transformer . Longer blog post: https://people.idsia.ch/~juergen/fast-weight-programmer-1991-transformer.html There is also an ICML 2021 publication on this, with Imanol Schlag and Kazuki Irie: Linear Transformers Are Secretly Fast Weight Programmers. Preprint https://arxiv.org/abs/2102.11174 Juergen > On 14 Mar 2023, at 7:49 AM, Risto Miikkulainen wrote: > > Back in the 1980s and 1990s we were trying to get neural networks to perform variable binding, and also what Dave Touretzky called ?dynamic inferencing?, i.e. bringing together two pieces of information that it knew how to process separately but had never seen together before (like different kinds of grammatical structures). It was very difficult and did not work well. But it seems it now works in GPT: it can, for instance, write a scientific explanation in the style of Shakespeare. The attention mechanism allows it to learn relationships, and the scale-up allows it to form abstractions, and then relationships between abstractions. This effect emerges only at very large scales?scales that are starting to approach that of brain. Perhaps the scale allows it to capture a fundamental processing principle of the brain that we have not been able to identify or model before? It would be interesting to try to characterize it in these terms. > > ? Risto > >> On Mar 13, 2023, at 3:38 AM, Claudius Gros wrote: >> >> -- attention as thought processes? -- >> >> The discussion here on the list shows, that >> ChatGPT produces intriguing results. I guess >> everybody agrees. What it means remains open. >> >> Let me throw in a hypothesis. >> >> With the introduction of the attention framework, >> deep-learning architectures acquired kind of >> 'soft links' by computing weighted superpositions >> of other states of the network. Possibly, this may >> be similar to what happens in the brain when we 'think', >> namely to combine states of distinct brain regions >> into a single processing stream. >> >> If that would be true (which remains to be seen), it would >> imply that the processes performed by transformer >> architectures would have a certain resemblance to actual >> thinking. >> >> Any thoughts (by human brains) on this hypothesis? >> >> Claudius >> >> ============================================================== >> >> >> On Friday, March 10, 2023 20:29 CET, Geoffrey Hinton wrote: >> >>> In Berthold Brecht's play about Galileo there is a scene where Galileo asks >>> a priest to look through a telescope to see the moons of Jupiter. The >>> priest says there is no point looking because it would be impossible for >>> things to go round Jupiter (this is from my memory of seeing the play about >>> 50 years ago). >>> >>> I suspect that Chomsky thinks of himself as more like Galileo than the >>> priest. But in his recent NYT opinion piece, it appears that the authors >>> did not actually check what chatGPT would say in answer to their questions >>> about falling apples or people too stubborn to talk to. Maybe they have >>> such confidence that chatGPT could not possibly be understanding that there >>> is no point looking at the data. >> >> >> -- >> ### >> ### Prof. Dr. Claudius Gros >> ### http://itp.uni-frankfurt.de/~gros >> ### >> ### Complex and Adaptive Dynamical Systems, A Primer >> ### A graduate-level textbook, Springer (2008/10/13/15) >> ### >> ### Life for barren exoplanets: The Genesis project >> ### https://link.springer.com/article/10.1007/s10509-016-2911-0 >> ### >> > > From minaiaa at gmail.com Fri Mar 17 08:13:46 2023 From: minaiaa at gmail.com (Ali Minai) Date: Fri, 17 Mar 2023 08:13:46 -0400 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <12324AA3-0446-49A1-A6ED-EF24780BBA59@nyu.edu> Message-ID: Of course, LLMs can?t think. The more interesting question is: What are the implications of the apparent thinking of LLMs for our understanding of human thinking? I suspect that, as more powerful LLMs emerge, this question will become more salient. The space of what cannot be done by AI will keep shrinking, and all we will have to fall back on is the feeling that humans are different - which I agree with. We will then be forced to explain much better how, why, and in what ways is human thinking different than something very large neural networks can ever achieve. We should be prepared for the possibility that the answer is ?none?. After all, we have an existence proof of a very large neural network - the human brain - that can produce human thinking! I suspect that, in the end we?ll find out that the brain needs a behaving body embedded in the real world and the capacity for self-motivated behavior to be intelligent like a human. Computers in server farms will just keep simulating some parts of it better and better. Best Ali On Fri, Mar 17, 2023 at 6:51 AM Gary Marcus wrote: > Frederick, Geoff and others, > > by the way I don?t know about ?average people? but here is a great example > of a bright journalist (not an AI expert or ML researcher) with perfectly > clear recognition of how GPT-4 cannot be trusted,?and a reminder that for > all its alleged ?understanding? GPT-4 is utterly unconstrained by any > internal process of fact-checking, which is to say that it cannot ground > its text-pastiching process in reality, another diagnostic of > discomprehension: > > [image: IMG_3988] > > for good measure, some subtle lies about SVB, also generated by GPT-4 > (reported by Dileep George). > > [image: IMG_5655] > > On Mar 17, 2023, at 08:48, Gary Marcus wrote: > > ? > > Average people were fooled by a chatbot called Eugene Goostman that > ultimately had exactly zero long-term impact on AI. I wrote about it and > the trouble with the Turing Test here in 2014: > https://www.newyorker.com/tech/annals-of-technology/what-comes-after-the-turing-test > > > On Mar 17, 2023, at 8:42 AM, Rothganger, Fredrick > wrote: > > ? > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > -- *Ali A. Minai, Ph.D.* Professor and Graduate Program Director Complex Adaptive Systems Lab Department of Electrical & Computer Engineering 828 Rhodes Hall University of Cincinnati Cincinnati, OH 45221-0030 Phone: (513) 556-4783 Fax: (513) 556-7326 Email: Ali.Minai at uc.edu minaiaa at gmail.com WWW: https://eecs.ceas.uc.edu/~aminai/ -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IMG_3988.jpeg Type: image/jpeg Size: 393912 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IMG_5655.jpeg Type: image/jpeg Size: 355436 bytes Desc: not available URL: From iam.palat at gmail.com Fri Mar 17 10:47:19 2023 From: iam.palat at gmail.com (Iam Palatnik) Date: Fri, 17 Mar 2023 11:47:19 -0300 Subject: Connectionists: Chomsky's apple In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: Thank you for that pointer, Miguel! That sheds some new light on the Cremonini vs Galileo friendship/rivarly. Re: understanding, I think it would be interesting if there was a clear measurement we could perform and all agree on, that determines whether something or someone has 'understanding'. I figure it might be impossible to agree on this and it's probably an ancient unsolved issue, but I feel like having some kind of measurement would help. I'll give a silly example I've just tried with ChatGPT and GPT-4. I tried speaking in English, but with increasingly more convoluted codified writing, with the sentences. Sy tht m wr t spk lk ths thn cu1d u st1l und3rs7d m? ww ????????1p3551v bt c4n s711 ud57d? ???t ?????t ??? ? ChatGPT and GPT-4 got through the first sentence easily. ChatGPT had trouble with sentence number 2 but got it with additional prompting by me, GPT-4 got it easily. ChatGPT could not get sentence 3 even after extensive additional prompting. GPT-4 got it after additional prompting. Example of what I mean about additional prompting on GPT-4 with the 3rd sentence: [image: image.png] GPT-4 self-corrected taking into account the context of the conversation (it noticed it is being tested on deciphering English in various scripts), and got exactly what I was going for. I'm resisting the temptation of saying it understood something, but I really don't see a better word to describe what GPT-4 did here, which it clearly did better than ChatGPT. Is there a better word than 'understanding' to use for this? Cheers, Iam On Mon, Mar 13, 2023 at 8:51?PM Miguel I. Solano wrote: > Iam, Connectionists, > > Not an expert by any means but, as an aside, I understand > Cremonini's 'refusal' seems to have been subtler than typically portrayed > (see P. Gualdo to Galileo, July 29, 1611, *Opere*, II, 564). > > Best, > --ms > > On Mon, Mar 13, 2023 at 5:49?PM Iam Palatnik wrote: > >> Dear Brad, thank you for your insightful answers. >> The compression analogy is really nice, although the 'Fermi-style' >> problem of estimating whether all of the possible questions and answers one >> could ask ChatGPT in all sorts of languages could be encoded within 175 >> billion parameters is definitely above my immediate intuition. It'd be >> interesting to try to estimate which of these quantities is largest. Maybe >> that could explain why ~175B seems to be the threshold that made models >> start sounding so much more natural. >> >> In regards to generating nonsense, I'm imagining an uncooperative human >> (say, a fussy child), that refuses to answer homework questions, or just >> replies with nonsense on purpose despite understanding the question. Maybe >> that child could be convinced to reply correctly with different prompting, >> rewards or etc, which kinda mirrors what it takes to transform a raw LLM >> like GPT-3 onto something like ChatGPT. It's possible we're still in the >> early stages of learning how to make LLM 'cooperate' with us. Maybe we're >> not asking them questions in a favorable way to extract their >> understanding, or there's still work to be done regarding decoding >> strategies. Even ChatGPT probably sounds way less impressive if we start >> tinkering too much with hyperparameters like temperature/top-p/top-k. Does >> that mean it 'understands' less when we change those parameters? I agree a >> lot of the problem stems from the word 'understanding' and how we use it in >> various contexts. >> >> A side note, that story about Galileo and the telescope is one of my >> favorites. The person that refused to look through it was Cremonini >> . >> >> >> Cheers, >> >> Iam >> >> On Mon, Mar 13, 2023 at 10:54?AM Miguel I. Solano >> wrote: >> >>> Geoff, Gary, Connectionists, >>> >>> To me the risk is ChatGPT and the like may be 'overfitting' >>> understanding, as it were. (Especially at nearly a hundred billion >>> parameters.) >>> >>> --ms >>> >>> On Mon, Mar 13, 2023 at 6:56?AM Barak A. Pearlmutter < >>> barak at pearlmutter.net> wrote: >>> >>>> Geoff, >>>> >>>> > He asked [ChatGPT] how many legs the rear left side of a cat has. >>>> > It said 4. >>>> >>>> > I asked a learning disabled young adult the same question. He used >>>> the index finger and thumb of both hands pointing downwards to represent >>>> the legs on the two sides of the cat and said 4. >>>> > He has problems understanding some sentences, but he gets by quite >>>> well in the world and people are often surprised to learn that he has a >>>> disability. >>>> >>>> That's an extremely good point. ChatGPT is way up the curve, well >>>> above the verbal competence of many people who function perfectly well >>>> in society. It's an amazing achievement, and it's not like progress is >>>> stuck at its level. Exploring its weaknesses is not so much showing >>>> failures but opportunities. Similarly, the fact that we can verbally >>>> "bully" ChatGPT, saying things like "the square root of three is >>>> rational, my wife said so and she is always right", and it will go >>>> along with that, does not imply anything deep about whether it really >>>> "knows" that sqrt(3) is irrational. People too exhibit all sorts of >>>> counterfactual behaviours. My daughter can easily get me to play along >>>> with her plan to become a supervillain. Students knowingly write >>>> invalid proofs on homeworks and exams in order to try to get a better >>>> grade. If anything, maybe we should be a bit scared that ChatGPT seems >>>> so willing to humour us. >>>> >>> >>> >>> -- >>> Miguel I. Solano >>> Co-founder & CEO, VMind Technologies, Inc. >>> >>> If you are not an intended recipient of this email, do not read, copy, >>> use, forward or disclose the email or any of its attachments to others. Instead, >>> please inform the sender and then delete it. Thank you. >>> >> > > -- > Miguel I. Solano > Co-founder & CEO, VMind Technologies, Inc. > > If you are not an intended recipient of this email, do not read, copy, > use, forward or disclose the email or any of its attachments to others. Instead, > please inform the sender and then delete it. Thank you. > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 110323 bytes Desc: not available URL: From gros at itp.uni-frankfurt.de Fri Mar 17 12:20:14 2023 From: gros at itp.uni-frankfurt.de (Claudius Gros) Date: Fri, 17 Mar 2023 17:20:14 +0100 Subject: Connectionists: =?utf-8?b?Pz09P3V0Zi04P3E/ICBHYWxpbGVvIGFuZCB0?= =?utf-8?q?he_priest?= In-Reply-To: Message-ID: <2a2b-64149300-1ad-648c7080@249341442> J?rgen Thanks for pointing in particular to your 2021 paper, Linear Transformers Are Secretly Fast Weight Programmers, which is really nice. Or course, we do not have a rigorous definition what it means 'thinking', a trait shared with 'understanding'. But, can we rule it out? (Ali, can I quote you here?) Ali Minai :: Of course, LLMs can?t think. Other :: Of course, LLMs can?t understand. Computing with soft links, as J?rgen puts it, amounts to re-adjust information processing via associative connections on-the-fly (attention, J?rgen's outer products). This may (or may not) be similar to what happens in human brains. In case, a paradigmal shift would be in the making. Interesting, it may help to explain a few of the questions raise lately. Most people can think, but not necessarily understand the abstract questions used to trick ChapGPT. For biological brains, thinking and understanding do not need to go hand in hand. Claudius ========================================================= On Friday, March 17, 2023 10:27 CET, Schmidhuber Juergen wrote: > Dear Risto and Claudius, > > I like your discussion on variable binding / attention / soft links. To an extent, this already worked in the early 1990s, although compute was a million times more expensive than today! > > 3 decades ago we published what?s now called a "Transformer with linearized self-attention" (apart from normalization): Learning to control fast-weight memories: an alternative to recurrent networks, Neural Computation, 1992. Based on TR FKI-147-91, TUM, 1991. Here is a well-known tweet on this: https://twitter.com/SchmidhuberAI/status/1576966129993797632?cxt=HHwWgMDSkeKVweIrAAAA > > One of the experiments in Sec. 3.2 was really about what you mentioned: learning to bind ?fillers" to ?slots" or ?keys" to "values? through "soft links." I called that ?learning internal spotlights of attention? in a follow-up paper at ICANN 1993. > > How does this work? A slow net learns by gradient descent to invent context-dependent useful pairs of ?keys" and ?values? (called FROM and TO) whose outer products define the "attention mapping" of a fast net with ?soft links? or ?fast weights? being applied to queries. (The 2017 Transformer combines this with a softmax and a projection operator.) > > The 1991 work separated memory and control like in traditional computers, but in an end-to-end differentiable fashion. I am happy to see that the basic principles have become popular again. Here an overview in Sec. 13 of the Annotated History of Modern AI and Deep Learning (2022): https://people.idsia.ch/~juergen/deep-learning-history.html#transformer . Longer blog post: https://people.idsia.ch/~juergen/fast-weight-programmer-1991-transformer.html > > There is also an ICML 2021 publication on this, with Imanol Schlag and Kazuki Irie: Linear Transformers Are Secretly Fast Weight Programmers. Preprint https://arxiv.org/abs/2102.11174 > > Juergen > > > > > > On 14 Mar 2023, at 7:49 AM, Risto Miikkulainen wrote: > > > > Back in the 1980s and 1990s we were trying to get neural networks to perform variable binding, and also what Dave Touretzky called ?dynamic inferencing?, i.e. bringing together two pieces of information that it knew how to process separately but had never seen together before (like different kinds of grammatical structures). It was very difficult and did not work well. But it seems it now works in GPT: it can, for instance, write a scientific explanation in the style of Shakespeare. The attention mechanism allows it to learn relationships, and the scale-up allows it to form abstractions, and then relationships between abstractions. This effect emerges only at very large scales?scales that are starting to approach that of brain. Perhaps the scale allows it to capture a fundamental processing principle of the brain that we have not been able to identify or model before? It would be interesting to try to characterize it in these terms. > > > > ? Risto > > > >> On Mar 13, 2023, at 3:38 AM, Claudius Gros wrote: > >> > >> -- attention as thought processes? -- > >> > >> The discussion here on the list shows, that > >> ChatGPT produces intriguing results. I guess > >> everybody agrees. What it means remains open. > >> > >> Let me throw in a hypothesis. > >> > >> With the introduction of the attention framework, > >> deep-learning architectures acquired kind of > >> 'soft links' by computing weighted superpositions > >> of other states of the network. Possibly, this may > >> be similar to what happens in the brain when we 'think', > >> namely to combine states of distinct brain regions > >> into a single processing stream. > >> > >> If that would be true (which remains to be seen), it would > >> imply that the processes performed by transformer > >> architectures would have a certain resemblance to actual > >> thinking. > >> > >> Any thoughts (by human brains) on this hypothesis? > >> > >> Claudius > >> > >> ============================================================== > >> > >> > >> On Friday, March 10, 2023 20:29 CET, Geoffrey Hinton wrote: > >> > >>> In Berthold Brecht's play about Galileo there is a scene where Galileo asks > >>> a priest to look through a telescope to see the moons of Jupiter. The > >>> priest says there is no point looking because it would be impossible for > >>> things to go round Jupiter (this is from my memory of seeing the play about > >>> 50 years ago). > >>> > >>> I suspect that Chomsky thinks of himself as more like Galileo than the > >>> priest. But in his recent NYT opinion piece, it appears that the authors > >>> did not actually check what chatGPT would say in answer to their questions > >>> about falling apples or people too stubborn to talk to. Maybe they have > >>> such confidence that chatGPT could not possibly be understanding that there > >>> is no point looking at the data. > >> > >> > >> -- > >> ### > >> ### Prof. Dr. Claudius Gros > >> ### http://itp.uni-frankfurt.de/~gros > >> ### > >> ### Complex and Adaptive Dynamical Systems, A Primer > >> ### A graduate-level textbook, Springer (2008/10/13/15) > >> ### > >> ### Life for barren exoplanets: The Genesis project > >> ### https://link.springer.com/article/10.1007/s10509-016-2911-0 > >> ### > >> > > > > > > -- ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ### From md at saske.sk Fri Mar 17 17:56:09 2023 From: md at saske.sk (Mato Dobes) Date: Fri, 17 Mar 2023 22:56:09 +0100 Subject: Connectionists: Sensory-motor "alphabet" In-Reply-To: References: <2FE5FF9F-14A1-41F6-B0DD-703609AE4FF2@nyu.edu> <4c6715c4-88ef-84d1-7c6b-47bb5883a8de@susaro.com> Message-ID: <20230317225609.Horde.cItP_qvejlNPpJkg169NYYK@home.saske.sk> Hello everyone, I wonder whether there are any attempts to formalise a way sensory-motor data could be stored and shared. I guess the next stage after language models could be sensory-motor models that would enable robots to be trained in a similar fashion as language models are trained. Thanks for all thoughts and suggestions. Marek Dobe? CSPV SAV From georgeangelos60 at gmail.com Sun Mar 19 06:54:26 2023 From: georgeangelos60 at gmail.com (georgeangelos60 at gmail.com) Date: Sun, 19 Mar 2023 12:54:26 +0200 Subject: Connectionists: 19th IEEE eScience Conference (eScience 2023): First Call for Tutorial Proposals Message-ID: <36O4LYMW-0B18-PSCK-D85V-VJV0FAY3MIW@gmail.com> *** First Call for Tutorial Proposals *** 19th IEEE eScience Conference (eScience 2023) October 9-13, 2023, St. Raphael Resort, Limassol, Cyprus https://www.escience-conference.org/2023/ The 19th IEEE eScience Conference will be held in Limassol, Cyprus on October 9-13, 2023. eScience 2023 welcomes proposals for tutorials to be held with the main conference October 9-10 2023. The eScience 2023 Tutorial Program is intended to teach new and/or state-of-the art tools and techniques relevant to the eScience audience, disseminate information to conference attendees on recently emerging topics and trends, or provide surveys and overviews of related digital technologies. We encourage all submissions that fall in the area of the conference, and particularly those that have a practical (hands-on) component that helps attendees learn new technologies in eScience. We also encourage submissions that disseminate new technologies in eScience to a more diverse audience. TUTORIAL SUBMISSION GUIDELINES Tutorial proposals should be submitted per email as a single pdf file; the file should include (1) a cover sheet and (2) an extended abstract. Submission email: tutorials at escience-conference.org . REQUIREMENTS FOR THE COVER SHEET The cover sheet should include the following elements: ? Full title ? Abstract (300 words) ? Brief schedule - please plan for a half-day tutorial (approx 3 hours plus breaks) ? Intended audience (introductory, intermediate, advanced) ? Prerequisite knowledge or skills required for attendees ? Previous offerings of the tutorial, if any ? Detailed contact information of all presenters (and indication of the main contact person) ? Brief biography (max. 2 paragraphs) for each presenter, highlighting relevant teaching experience REQUIREMENTS FOR THE EXTENDED ABSTRACT The extended abstract (up to 2 pages) should include the following sections: ? Motivation ? Brief outline of the topics to be covered ? Detailed agenda of the tutorial ? Links to related resources ? Type of support materials to be supplied to attendees ? Requirements for online conference system KEY DATES ? Tutorial Submissions Due: Friday, May 26, 2023 (AoE) ? Tutorial Acceptance: Friday, June 30, 2023 ? Tutorials at the Conference: October 9-10, 2023 CONTACT INFORMATION Tutorial Chairs (tutorials at escience-conference.org) ? Silvina Caino-Lores, University of Tennessee, Knoxville, TN, USA ? Philipp Gschwandtner, University of Innsbruck, Austria ORGANISATION General Chair ? George Angelos Papadopoulos, University of Cyprus, Cyprus Technical Program Co-Chairs ? Rafael Ferreira da Silva, Oak Ridge National Laboratory, USA ? Rosa Filgueira, University of St Andrews, UK Organisation Committee https://www.escience-conference.org/2023/organizers Steering Committee https://www.escience-conference.org/about/#steering-committee -------------- next part -------------- An HTML attachment was scrubbed... URL: From htlin at csie.ntu.edu.tw Sun Mar 19 20:25:05 2023 From: htlin at csie.ntu.edu.tw (Hsuan-Tien Lin) Date: Mon, 20 Mar 2023 08:25:05 +0800 Subject: Connectionists: Invitation to contribute to Frontiers in Big Data journal Message-ID: Dear colleagues on the connectionists mailing list, We invite you and your co-authors to publish your next article on the research topic: Towards More Reliable and Sustainable Machine Learning Services in the Frontiers in Big Data journal. Abstract Submission Deadline 03 April 2023 Manuscript Submission Deadline 19 June 2023 In the past decades, the area of Machine Learning (ML) has experienced tremendous success. Companies have begun to rely on ML to provide continuous services to their clients. For instance, recommender systems and learning-to-rank models are widely used by Internet companies to serve their customers. An important feature of a reliable and sustainable ML based service is that it exceeds the basic training requirements. From onset, it involves data preparation (e.g. data ingestion, curation, validation), enhanced attention to feature selection and engineering, and may also rely on ensemble models to further boost the performance of the ML based service. Since ML services are often served online for a long period of time, issues such as auto model re-training with incremental feedback, handling concept drift and environment changing become very critical. Moreover, as there are costs in providing such services, how to strike a balance among performance, computation resources, and ease of maintenance can be very challenging. To advance the research in this direction, we would like to solicit articles on the following topics: - Dealing with dynamic environment in ML handling concept drift - Learning given incremental feedbacks - Causality inference - Dealing with noise and missing in data - Dealing with sampling, measuring, and algorithmic bias in ML - Resourced constrained machine learning - Evaluation metrics in reliability and sustainability for ML - Auto machine learning - Life-long learning - Invariant learning More details on this special issue can be found at: https://www.frontiersin.org/research-topics/47091/towards-more-reliable-and-sustainable-machine-learning-services Best regards, Bo Han, Hong Kong Baptist University Hsuan-Tien Lin, National Taiwan University Shou-de Lin, National Taiwan University From tarek.besold at googlemail.com Sat Mar 18 05:33:46 2023 From: tarek.besold at googlemail.com (Tarek R. Besold) Date: Sat, 18 Mar 2023 10:33:46 +0100 Subject: Connectionists: Research & Engineering positions with Sony AI in Barcelona (Spain) Message-ID: Dear all. We are advertising the first four positions for our new Sony AI lab in Barcelona (Spain). If you are interested -- or know someone who might be interested -- and have questions that are not answered in the job descriptions, please don't hesitate to reach out to tarek.besold at sony.com. Senior Research Scientist Data Mining/Knowledge Mining: https://sonyglobal.wd1.myworkdayjobs.com/de-DE/SonyGlobalCareers/job/Barcelona/Senior-Research-Scientist---Data-Mining_JR-112943 Research Scientist Explainable AI: https://sonyglobal.wd1.myworkdayjobs.com/de-DE/SonyGlobalCareers/job/Barcelona/Research-Scientist---Explainable-AI_JR-112942 MLOps Engineer: https://sonyglobal.wd1.myworkdayjobs.com/de-DE/SonyGlobalCareers/job/Barcelona/MLOps-Engineer_JR-112627 ML Platform Engineer: https://sonyglobal.wd1.myworkdayjobs.com/de-DE/SonyGlobalCareers/job/Barcelona/ML-Platform-Engineer_JR-112625 All the best, Tarek. -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Sun Mar 19 05:13:30 2023 From: david at irdta.eu (David Silva - IRDTA) Date: Sun, 19 Mar 2023 10:13:30 +0100 (CET) Subject: Connectionists: DeepLearn 2023 Spring: regular registration March 31st Message-ID: <457080643.2456223.1679217211069@webmail.strato.com> ****************************************************************** 9th INTERNATIONAL SCHOOL ON DEEP LEARNING DeepLearn 2023 Spring Bari, Italy April 3-7, 2023 https://deeplearn.irdta.eu/2023sp/ *********** Co-organized by: Department of Computer Science University of Bari ?Aldo Moro? Institute for Research Development, Training and Advice ? IRDTA Brussels/London ****************************************************************** Regular registration: March 31, 2023 ****************************************************************** SCOPE: DeepLearn 2023 Spring will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimar?es, Las Palmas de Gran Canaria, Lule? and Bournemouth. Deep learning is a branch of artificial intelligence covering a spectrum of current exciting research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, health informatics, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, biometrics, communications, climate sciences, bioinformatics, geographic information systems, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience. Most deep learning subareas will be displayed, and main challenges identified through 20 four-hour and a half courses and 3 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2023 Spring is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2023 Spring will take place in Bari, an important economic centre on the Adriatic Sea. The venue will be: Department of Computer Science University of Bari ?Aldo Moro? via Edoardo Orabona, 4 70125 Bari STRUCTURE: 2 or 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Full live online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Vipin Kumar (University of Minnesota), Knowledge-Guided Deep Learning: A Framework for Accelerating Scientific Discovery William S. Noble (University of Washington), Deep Learning Applications in Mass Spectrometry Proteomics and Single-Cell Genomics Emma Tolley (Swiss Federal Institute of Technology Lausanne), Physics-Informed Deep Learning PROFESSORS AND COURSES: Babak Ehteshami Bejnordi (Qualcomm AI Research), [intermediate/advanced] Conditional Computation for Efficient Deep Learning with Applications to Computer Vision, Multi-Task Learning, and Continual Learning Patrick Gallinari (Sorbonne University), [intermediate] Physics Aware Deep Learning for Modeling Dynamical Systems Sergei V. Gleyzer (University of Alabama), [introductory/intermediate] Machine Learning Fundamentals and Their Applications to Very Large Scientific Data: Rare Signal and Feature Extraction, End-to-End Deep Learning, Uncertainty Estimation and Realtime Machine Learning Applications in Software and Hardware Jacob Goldberger (Bar-Ilan University), [introductory/intermediate] Calibration Methods for Neural Networks Christoph Lampert (Institute of Science and Technology Austria), [intermediate] Training with Fairness and Robustness Guarantees Yingbin Liang (Ohio State University), [intermediate/advanced] Bilevel Optimization and Applications in Deep Learning Xiaoming Liu (Michigan State University), [intermediate] Deep Learning for Trustworthy Biometrics Michael Mahoney (University of California Berkeley), [intermediate] Practical Neural Network Theory: From Statistical Mechanics Basics to Working with State of the Art Models Liza Mijovic (University of Edinburgh), [introductory/intermediate] Deep Learning & the Higgs Boson: Classification with Fully Connected and Adversarial Networks Bhiksha Raj (Carnegie Mellon University), [introductory] An Introduction to Quantum Neural Networks [with Rita Singh, Daniel Justice and Prabh Baweja] Holger Rauhut (RWTH Aachen University), [intermediate] Gradient Descent Methods for Learning Neural Networks: Convergence and Implicit Bias Bart ter Haar Romeny (Eindhoven University of Technology), [intermediate/advanced] Explainable Deep Learning from First Principles Tara Sainath (Google), [advanced] E2E Speech Recognition [virtual] Martin Schultz (Research Centre J?lich), [intermediate] Deep Learning for Air Quality, Weather and Climate Adi Laurentiu Tarca (Wayne State University), [intermediate] Machine Learning for Cross-Sectional and Longitudinal Omics Studies Michalis Vazirgiannis (Polytechnic Institute of Paris), [intermediate/advanced] Graph Machine Learning with GNNs and Applications Atlas Wang (University of Texas Austin), [intermediate] Sparse Neural Networks: From Practice to Theory Guo-Wei Wei (Michigan State University), [introductory/advanced] Discovering the Mechanisms of SARS-CoV-2 Evolution and Transmission Lei Xing (Stanford University), [intermediate] Deep Learning for Medical Imaging and Genomic Data Processing: from Data Acquisition, Analysis, to Biomedical Applications Xiaowei Xu (University of Arkansas Little Rock), [intermediate/advanced] Deep Learning Language Models and Causal Inference OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by March 26, 2023. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by March 26, 2023. EMPLOYER SESSION: Organizations searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by March 26, 2023. ORGANIZING COMMITTEE: Giuseppina Andresini (Bari, local co-chair) Graziella De Martino (Bari, local co-chair) Corrado Loglisci (Bari, local co-chair) Donato Malerba (Bari, local chair) Carlos Mart?n-Vide (Tarragona, program chair) Paolo Mignone (Bari, local co-chair) Sara Morales (Brussels) Gianvito Pio (Bari, local co-chair) Francesca Prisciandaro (Bari, local co-chair) David Silva (London, organization chair) Gennaro Vessio (Bari, local co-chair) REGISTRATION: It has to be done at https://deeplearn.irdta.eu/2023sp/registration/ The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions are available at https://deeplearn.irdta.eu/2023sp/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: University of Bari ?Aldo Moro? Rovira i Virgili University Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From lrubchin at iupui.edu Fri Mar 17 14:39:36 2023 From: lrubchin at iupui.edu (Rubchinsky, Leonid L) Date: Fri, 17 Mar 2023 18:39:36 +0000 Subject: Connectionists: 32nd Annual Computational Neuroscience Meeting (CNS*2023), Leipzig, July 15-19 2023: abstract submission deadline EXTENDED to March 27th In-Reply-To: References: Message-ID: Dear Colleagues, The CNS*2023 abstract submission deadline has been extended to Monday March 27th, 11:00 pm Pacific Time. Note that one of the authors must register as sponsoring author for the main meeting before abstract submission. Submitted abstracts are used for creating the program and for publication. Please follow the formatting guidelines on the submission site. Registration: https://ocns.memberclicks.net/cns-2023-registration Abstract Submission: https://ocns.memberclicks.net/cns-2023-abstract-submission General information: https://www.cnsorg.org/cns-2023 The calls for tutorials and workshops remain open: CALL FOR TUTORIALS: https://www.cnsorg.org/cns-2023-call-for-tutorials Deadline for proposals: 22 April 2023 CALL FOR WORKSHOPS: https://www.cnsorg.org/cns-2023-call-for-workshops Priority Deadline for proposals: 15 April 2023 With kind regards, Leonid Rubchinsky OCNS Vice President *********************** Leonid Rubchinsky, PhD Professor Department of Mathematical Sciences, Indiana University Purdue University Indianapolis Stark Neurosciences Research Institute, Indiana University School of Medicine 402 N. Blackford St Indianapolis, IN 46202-3216 lrubchin at iupui.edu http://www.math.iupui.edu/~lrubchin *********************** From arvind.k.panchal at gmail.com Sat Mar 18 09:30:40 2023 From: arvind.k.panchal at gmail.com (Arvind Kumar) Date: Sat, 18 Mar 2023 14:30:40 +0100 Subject: Connectionists: Fully funded Postdoctoral position at KTH Stockholm to study cortical activity dynamics in epilepsy Message-ID: Dear Colleagues We invite applications for a postdoctoral position jointly supervised by Dr. Arvind Kumar, and Dr. Pawel Herman (KTH Stockholm, Sweden). The project: The project is concerned with mechanisms underlying the generation and spread of epileptic activity in the brain networks. In this context, there are two main goals of this project. 1. To understand how neuron and synapse properties alter the brain dynamics and make the network unstable for certain kinds of perturbations. 2. How local changes percolate to distant networks and alter the dynamics of the whole brain. To this end we will use computational models of brain networks (microscopic as well as mesoscopic) and analyse patient data (EEG and in some cases ECoG). What are we looking for: - PhD in computational neuroscience / neuroscience (or Physics/Maths/Engineering) - strong track record - experience in computational modelling of biological neuronal networks and/or neural data analysis Where: The candidate will be hired at the KTH Royal Institute of Technology, Stockholm, Sweden. He/she will closely interact with clinicians at the Karolinska Hospital, Stockholm. In addition, the selected candidate will have the chance to integrate with the broad neuroscience community in Stockholm. Duration: The initial contract will be for two years. Tentative start date: Sept. 2022 Application documents: Please provide following documents in your application package - Detailed CV - Summary of ongoing and previous research (1-2 pages ) - Future research plans and explain why you computational neuroscience maybe useful for studying epilepsy (1-2 pages) - Name and contact information of at least two referees. Application deadline: 15 April 2023 Application submission: Please email your application document to arvindku at kth.se About the supervisors: Arvind Kumar: He is an associate professor at KTH Stockholm, Sweden. He has extensive experience in modelling biological neuronal networks to explain the statistics of brain activity dynamics. His research group is interested in understanding information flow in the brain and how low-level neuron and synapse properties shape network activity dynamics. More info: https://arvkumar.github.io/ and https://www.kth.se/profile/arvindku Pawel Herman: He is an associate professor at KTH Stockholm, Sweden. He has extensive experience in developing memory models with a focus on working memory functions. His research group is studying a wide range of cognitive phenomena with computational, neural network modelling approaches, and contributing towards an integrative computational brain theory to derive brain-inspired computing paradigms.. More info. : https://www.kth.se/profile/paherman -------------- next part -------------- An HTML attachment was scrubbed... URL: From paul.cisek at umontreal.ca Fri Mar 17 11:32:40 2023 From: paul.cisek at umontreal.ca (Paul Cisek) Date: Fri, 17 Mar 2023 15:32:40 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: I must say that I'm somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it's understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what's under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)... and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience's attention to slip the card into our pocket... but then we are standing around backstage wondering: "Maybe there really is magic?" I think it's not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From suashdeb at gmail.com Sun Mar 19 13:53:19 2023 From: suashdeb at gmail.com (Suash Deb) Date: Sun, 19 Mar 2023 23:23:19 +0530 Subject: Connectionists: Submission 100 days away (ISCMI, Mexico City) Message-ID: Dear Friends and Esteemed Colleagues, Warmest greetings to all. Trust all are doing well. This is to inform you that the submission deadline for 2023 10th ISCMI, the annual flagship event of India International Congress on Computational Intelligence is 100 days away. The event is technically co sponsored by IEEE Mexico Section, IEEE Mexico Council and Mexico Chapter of IEEE Computational Intelligence Society. For more info abt conference proceedings, indexing and special issue of SCIE indexed journals, pls. visit the conference website http://www.iscmi.us w.e.f. 2017, ISCMI is organized in memory of life and work of Prof. Lotfi Zadeh. The list of all colleagues who delivered the IICCI Prof. Lotfi Zadeh Memorial Speech can be found by visiting http://www.iicci.in/speakers.html Hope to receive your and your colleagues' enthusiastic response and to meet many of you during the Decennial Celebrations of ISCMI this year. With kind regards, Suash Deb General Chair, ISCMI 2023 -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Mon Mar 20 04:01:11 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Mon, 20 Mar 2023 08:01:11 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: Message-ID: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> bravo! > On Mar 20, 2023, at 07:55, Paul Cisek wrote: > > ? > I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. > > But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? > > In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? > > I think it?s not that machines have passed the Turing Test, but rather that we failed it. > > Paul Cisek > > > From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM > To: connectionists at mailman.srv.cs.cmu.edu > Subject: Connectionists: Can LLMs think? > > Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. > -------------- next part -------------- An HTML attachment was scrubbed... URL: From T.Nowotny at sussex.ac.uk Mon Mar 20 05:47:50 2023 From: T.Nowotny at sussex.ac.uk (Thomas Nowotny) Date: Mon, 20 Mar 2023 09:47:50 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> References: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> Message-ID: Hi Paul and Gary, I think I am firmly in your camp & well summarised. However, there is this nagging doubt about how much of the human intelligence we attribute to each other and ourselves are the same ?little strings and hidden compartments? and ?how we just redirected the audience?s attention? that undoubtedly underlie LLMs abilities. Best, Thomas Nowotny From: Connectionists On Behalf Of Gary Marcus Sent: 20 March 2023 08:01 To: Paul Cisek Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? bravo! On Mar 20, 2023, at 07:55, Paul Cisek > wrote: ? I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcel.van.gerven at gmail.com Mon Mar 20 04:45:40 2023 From: marcel.van.gerven at gmail.com (Marcel van Gerven) Date: Mon, 20 Mar 2023 08:45:40 +0000 Subject: Connectionists: Senior researcher position in reinforcement learning Message-ID: The AI Department of the Donders Centre for Cognition (DCC), embedded in the Donders Institute for Brain, Cognition and Behaviour, and the School of Artificial Intelligence at Radboud University Nijmegen are looking for a researcher in reinforcement learning with an emphasis on safety and robustness, an interest in natural computing as well as in applications in neurotechnology and other domains such as robotics, healthcare and/or sustainability. You will be expected to perform top-quality research in (deep) reinforcement learning, actively contribute to the DBI2 consortium, interact and collaborate with other researchers and specialists in academia and/or industry, and be an inspiring member of our staff with excellent communication skills. You are also expected to engage with students through teaching and master projects not exceeding 20% of your time. Profile: * You have a PhD degree in Artificial Intelligence, Computer Science or a related discipline; * You have experience in a number of the following topics: (deep, Bayesian, safe) RL, control theory and model predictive control, applications of RL in e.g. healthcare, robotics, neurotechnology, sustainability and/or edge solutions for control of complex systems. * You have an excellent track record in scientific research, as evidenced by publications in top-tier conferences and journals. * You have a proven ability to provide inspiring teaching in English. * You are enthusiastic and you are able to work together in a team as part of the DBI2 consortium. Application deadline: April 7th To apply, please follow this link: https://www.ru.nl/en/working-at/job-opportunities/researcher-in-reinforcement-learning-at-the-donders-center-for-cognition -------------- next part -------------- An HTML attachment was scrubbed... URL: From valvilraman at yahoo.co.in Mon Mar 20 05:41:37 2023 From: valvilraman at yahoo.co.in (Anand Ramamoorthy) Date: Mon, 20 Mar 2023 09:41:37 +0000 (UTC) Subject: Connectionists: Chomsky's apple In-Reply-To: <5ef8d1a4-dd1c-f85a-4b22-257477004e60@oregonstate.edu> References: <6FEE3A9C-7262-4249-93E7-9BCEA7C2E9A8@nyu.edu> <5ef8d1a4-dd1c-f85a-4b22-257477004e60@oregonstate.edu> Message-ID: <1121786740.1743235.1679305297441@mail.yahoo.com> Hi All,?????????????????? This is an interesting/entertaining discussion. "Understanding" has always been a somewhat nebulous concept. In the late 90s, Roger Penrose held (and continues to hold, if I am not mistaken), that at least in terms of mathematical "understanding", such a phenomenon couldn't possibly be captured by an effective procedure. I was sympathetic to this view in my early academic life but currently believe my old self was likely wrong :) ?With advanced generative models mucking about now, "understanding" is a more contentious (and less purely academic) topic now than it may have been decades ago. Some things I have been thinking about recently: 1. We all understand things to varying degrees, and know of ways to improve said understanding. It is possible for us to understand something more precisely or deeply with experience or due diligence (zooming out, this reflects humanity's intellectual trajectory as a species...unless people believe there was a magical time when the ancients knew it all etc). In so far that human understanding (individual, collective and from a historical perspective), is a phenomenon that is marked by change, incremental as well as more dramatic? (perhaps someone has modelled this as an SOC instance a la Bak & Sneppen's model of evolution or the original BTW?), is it not reasonable to expect attempts to capture aspects of human intelligence in machines to have a similar characteristic? In other words, ChatGPT's "understanding" may be rudimentary as opposed to nonexistent? Looking at the counterexamples, I am struck by how we could do the same with humans on a range of topics/issues and demonstrate/claim understanding or the lack thereof. Our (mis)understandings define our brief lives. 2. Unless one embraces some sort of irreducibility argument I do not see why what humans can do cannot be captured by an artificial learning system. 3. Would it help to speak of "understanding" as not just having useful internal representations but a capacity for "representational parsimony"? This of course is intimately connected to generation of "insights" and getting at the causal structure of the world.? 4. Given 1-3 above, how do we a) define understanding ? (yeah, very original, I know!), b) diagnose it/disambiguate it from behaviours that resemble it? Live Long and Prosper P.S: Regardless of what you make of my understanding or lack thereof, the contents of this email were generated by a human (moi) typing on a keyboard that is slightly worse for the wear :) Anand Ramamoorthy On Saturday, 18 March 2023 at 17:17:37 GMT, Kagan Tumer wrote: I'm very reluctant to use the word "understand" beyond perhaps ChatGPT understanding the structure of language (statistically). Here's an example of a ChatGPT response to a simple arithmetic operation where: 1- chatGPT was wrong; 2- worked out an example that showed it was wrong, but it didn't register that and double down on its wrong conclusion; 3- gave a high level explanation (also wrong) of why it was right even though it was wrong. you can forgive 1, but 2 and 3 clearly show ChatGPT does not actually understand what it is saying. Kagan On 3/14/23 9:54 AM, Natsuki Oka wrote: > [This email originated from outside of OSU. Use caution with links and > attachments.] > > Judging from the responses below, ChatGPT understands counting and > sorting to the extent that it can write a correct Python program but > does not have the understanding to bring the proper execution results. > count_and_sort.png > Here's the program that ChatGPT created: > --- > sentences = [ >? ? ? "The quick brown fox jumps over the lazy dog", >? ? ? "Python is a popular programming language", >? ? ? "I like to eat pizza for dinner", >? ? ? "The capital of France is Paris", >? ? ? "The cat in the hat wears a red and white striped hat", >? ? ? "My favorite color is blue", >? ? ? "The United States has fifty states", >? ? ? "There are seven days in a week", >? ? ? "I enjoy listening to music while I work", >? ? ? "Mount Everest is the highest mountain in the world" > ] > > # sort the sentences by number of words > sentences.sort(key=lambda x: len(x.split())) > > # print the sorted sentences with the number of words in parentheses > for sentence in sentences: >? ? ? num_words = len(sentence.split()) >? ? ? print(f"{sentence} ({num_words})") > --- > > The execution of this program yields the following correct results: > --- > My favorite color is blue (5) > Python is a popular programming language (6) > The capital of France is Paris (6) > The United States has fifty states (6) > I like to eat pizza for dinner (7) > There are seven days in a week (7) > I enjoy listening to music while I work (8) > The quick brown fox jumps over the lazy dog (9) > Mount Everest is the highest mountain in the world (9) > The cat in the hat wears a red and white striped hat (12) > --- > > Oka Natsuki > Miyazaki Sangyo-keiei University > -- Kagan Tumer Director, Collaborative Robotics and Intelligent Systems Institute Professor, School of MIME Oregon State University http://engr.oregonstate.edu/~ktumer https://kagantumer.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.pavlovic at tuebingen.mpg.de Mon Mar 20 06:51:22 2023 From: maria.pavlovic at tuebingen.mpg.de (Pavlovic, Maria) Date: Mon, 20 Mar 2023 10:51:22 +0000 Subject: Connectionists: Open position: Postdoctoral position in Human Psychophysics in Tuebingen, Germany References: Message-ID: <2a0bc2721e214acabae2309783fe6aec@tuebingen.mpg.de> Postdoctoral position in Human Psychophysics (m/f/d) ? (TV?D Bund E13, 100%) The Department of Sensory and Sensorimotor Systems (PI Prof. Li Zhaoping) at the Max Planck Institute for Biological Cybernetics and at the University of T?bingen is currently looking for highly skilled and motivated individuals to work on projects aimed towards understanding visual attentional and perceptual processes using fMRI/MRI, TMS and/or EEG methodologies. The framework and motivation of the projects can be found at: https://www.lizhaoping.org/zhaoping/AGZL_HumanVisual.html. The projects can involve, for example, visual search tasks, stereo vision tasks, visual illusions, and will be discussed during the application process. fMRI/MRI, TMS and/or EEG methodologies can be used in combination with eye tracking, and other related methods as necessary. The postdoc will be working closely with the principal investigator and other members of Zhaoping's team when needed. Responsibilities: * Conduct and participate in research projects such as lab and equipment set up, data collection, data analysis, writing reports and papers, and presenting at scientific conferences. * Participate in routine laboratory operations, such as planning and preparations for experiments, lab maintenance and lab procedures. * Coordinate with the PI and other team members for strategies and project planning. * Coordinate with the PI and other team members for project planning, and in supervision of student projects or teaching assistance for university courses in our field. Requirements: * Ph.D. in neuroscience, psychology, computer science, physics or a related natural science or engineering field. * Publications in peer-reviewed journals. * Highly skilled in techniques of human visual psychophysics such as MATLAB programming for experiments, experimental data taking, data analysis, and paper writing. * Familiarity with hardware and techniques in eye tracking, fMRI/MRI, EEG, TMS, tDCS/tACS, and other related techniques such as in carrying out fMRI experiments is highly desirable. * Experience in project management is highly desired. * Strong command of English; knowledge of German is a plus. Who we are: We use a multidisciplinary approach to investigate sensory and sensory-motor transforms in the brain (www.lizhaoping.org). Our approaches consist of both theoretical and experimental techniques including human psychophysics, fMRI imaging, electrophysiology and computational modelling. One part of our group is located in the University, in the Centre for Integrative Neurosciences (CIN), and the other part is in the Max Planck Institute for Biological Cybernetics as the Department for Sensory and Sensorimotor Systems. You will have the opportunity to learn other skills in our multidisciplinary group and benefit from interactions with our colleagues in the university as well as internationally. This job opening is for the CIN or the MPI working group. The position (salary level TV?D-Bund E13, 100%) is for a duration of two years. Extension or a permanent contract after two years is possible depending on situations. We seek to raise the number of women in research and teaching and therefore urge qualified women to apply. Disabled persons will be preferred in case of equal qualification. Your application: The position is available immediately and will be open until filled. Preference will be given to applications received by May 31st, 2023. We look forward to receiving your application that includes (1) a cover letter, including a statement on roughly when you would like to start this position, (2) a motivation statement, (3) a CV, (4) names and contact details of three people for references, (5) if you have them, transcripts from your past and current education listing the courses taken and their grades, (6) if you have them, please also include copies of your degree certificates, (7) you may include a pdf file of your best publication(s), or other documents and information that you think could strengthen your application. Please use pdf files for these documents (and you may combine them into a single pdf file) and send to jobs.li at tuebingen.mpg.de , where also informal inquiries can be addressed. Please note that applications without complete information in (1)-(4) will not be considered, unless the cover letter includes an explanation and/or information about when the needed materials will be supplied. For further opportunities in our group, please visit www.lizhaoping.org/jobs.html _________________________________ Maria Pavlovic Assistant to Prof. Zhaoping Li Office Hours: 07.00-13.00 Max Planck Institute for Biological Cybernetics Max-Planck-Ring 8 D-72076 Tuebingen phone +49 7071 601 609 fax +49 7071 601 619 maria.pavlovic at tuebingen.mpg.de www.lizhaoping.org -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 6707 bytes Desc: not available URL: From hugo.o.sousa at inesctec.pt Mon Mar 20 05:30:42 2023 From: hugo.o.sousa at inesctec.pt (Hugo Oliveira Sousa) Date: Mon, 20 Mar 2023 09:30:42 +0000 Subject: Connectionists: Text2Story'23 Workshop Call for Participation Message-ID: <271c4ba0a466485187070d0891f7fca5@inesctec.pt> ++ CALL FOR PARTICIPATION ++ It's just a couple of days until the Text2Story at ECIR?23 workshop (6th International Workshop on Narrative Extraction from Texts). Text2Story'23 will be a hybrid event to take place in Dublin, Ireland and Online (GMT). We invite all the interested in this thematic to join us either in-person or online on the 2nd of April. Registrations are open here: https://ecir2023.org/registration.html The workshop program consists of two keynote speeches by Georgiana Ifrim from University College Dublin, Ireland and Valentina Bartalesi from the CNR-ISTI, Italy, and the presentations of fourteen research papers and five demo presentations. More details about the program can be found on the Text2Story 2023 workshop webpage: http://text2story23.inesctec.pt ++ Invited Speakers ++ - Georgiana Ifrim [University College Dublin] who will give a talk entitled "Structured Summarisation of News at Scale" - Valentina Bartalesi [CNR-ISTI] who will give a talk entitled "Creating and Visualising Semantic Story Maps" ++ List of Papers ++ - Multilingual Analysis of YouTube's Recommendation System: Examining Topic and Emotion Drift in the 'Cheng Ho' Narrative [Ugochukwu Onyepunuka, Mustafa Alassad, Lotenna Nwana and Nitin Agarwal] - NewsLines: Narrative Visualization of News Stories [Mariana Costa and S?rgio Nunes] - Annotation and visualisation of reporting events in textual narratives [Purifica??o Silvano, Evelin Amorim, Ant?nio Leal, In?s Cantante, Silva F?tima, Al?pio Jorge, Ricardo Campos and S?rgio Nunes] - Segmenting Narrative Synopses into Spans for Different Event Reporting Modes [Pablo Gerv?s] - On the Definition of Prescriptive Annotation Guidelines for Language-Agnostic Subjectivity Detection [Federico Ruggeri, Francesco Antici, Andrea Galassi, Katerina Korre, Ariann Muti and Alberto Barr?n-Cede?o] - Edge Labelling in Narrative Knowledge Graphs [Vani Kanjirangat and Alessandro Antonucci] - End-to-End Temporal Relation Extraction in the Clinical Domain [Jos? Javier Saiz and Bego?a Altuna] - Cross-lingual transfer learning for detecting negative campaign in Israeli municipal elections: a case study [Marina Litvak, Natalia Vanetik and Lin Miao] - The Same Thing - Only Different: Classification of Movies by their Story Types [Chang Liu, Armin Shmilovici and Mark Last] - ScANT: A Small Corpus of Scene-Annotated Narrative Texts [Tarfah Alrashid and Robert Gaizauskas] - A cognitive theoretical approach of rhetorical news analysis [Ishrat Sami, Tony Russell-Rose and Larisa Soldatova] - Modelling Interestingness: stories as L-Systems and Magic Squares [Cosimo Palma] - On the Readability of Misinformation in Comparison to the Truth [Mohammadali Tavakoli, Harith Alani and Gregoire Burel] - Multi-label Infectious Disease News Event Corpus [Jakub Piskorski, Nicolas Stefanovitch, Brian Doherty, Jens Linge, Sopho Karazi, Jas Mantero, Guillaume Jacquet, Alessio Spadaro and Giulia Teodori] ++ List of Demonstrations ++ - Integration of a Semantic Storytelling Recommender System in Speech Assistants [Maria Gonzalez Garcia, Julian Moreno Schneider, Malte Ostendorff and Georg Rehm] - Extracting Imprecise Geographical and Temporal References from Journey Narratives [Ignatius Ezeani, Paul Rayson and Ian Gregory] - The Funhouse Mirror Has Two Sides: Visual Storification of Debates with Comics [Tony Veale] - Comprehensive Terms Board Visualization for News Analysis and Editorial Story Planning [Ishrat Sami, Tony Russell-Rose and Larisa Soldatova] - A Web Tool to Create and Visualise Semantic Story Maps [Valentina Bartalesi, Emanuele Lenzi and Nicol? Pratelli] We hope to see you in Dublin [or online] on the 2nd of April. All the best, Hugo Sousa, on behalf of the Text2Story 2023 Workshop Chairs: Ricardo Campos, Al?pio Jorge, Adam Jatowt, Sumit Bhatia and Marina Litvak -------------- next part -------------- An HTML attachment was scrubbed... URL: From bogdanlapi at gmail.com Mon Mar 20 06:59:06 2023 From: bogdanlapi at gmail.com (Bogdan Ionescu) Date: Mon, 20 Mar 2023 12:59:06 +0200 Subject: Connectionists: Call-for-Participation: Aware Task @ ImageCLEF 2023 (Unveiling Real-Life Effects of Online Photo Sharing) Message-ID: [Apologies for multiple postings] ImageCLEFaware (3rd edition) Registration: https://www.imageclef.org/2023/aware Run submission: May 10, 2023 Working notes submission: June 5, 2023 CLEF 2023 conference: September 18-21, Thessaloniki, Greece *** CALL FOR PARTICIPATION *** Images constitute a large part of the content shared on social networks. Their disclosure is often related to a particular context and users are often unaware of the fact that, depending on their privacy status, images can be accessible to third parties and be used for purposes which were initially unforeseen. For instance, it is common practice for employers to search information about their future employees online. Another example of usage is that of automatic credit scoring based on online data. Most existing approaches which propose feedback about shared data focus on inferring user characteristics and their practical utility is rather limited. We hypothesize that user feedback would be more efficient if conveyed through the real-life effects of data sharing. The objective of the task is to automatically score user photographic profiles in a series of situations with strong impact on her/his life. Four such situations were modeled this year and refer to searching for: (i) a bank loan, (ii) an accommodation, (iii) a job as waitress/waiter, and (iv) a job in IT. The inclusion of several situations is interesting in order to make it clear to the end-users of the system that the same image will be interpreted differently depending on the context. The final objective of the task is to encourage the development of efficient user feedback, such as the YDSYO Android app https://ydsyo.app/. *** TASK *** Given an annotated training dataset, participants will propose machine learning techniques which provide a ranking of test user profiles in each situation which is as close as possible to a human ranking of the test profiles. *** DATA SET *** This is the third edition of the task. A data set of more than 1,000 user profiles with 100 photos per profile was created and annotated with an appeal score for a series of real-life situations via crowdsourcing. Participants to the experiment were asked to provide a global rating of each profile in each situation modeled using a 7-points Likert scale ranging from strongly unappealing to strongly appealing. An averaged and normalized appeal score will be used to create a ground truth composed of ranked users in each modeled situation. User profiles are created by repurposing a subset of the YFCC100M dataset. *** METRICS *** Participants to the task will provide an automatically ranking of user ratings for each situation which will be compared to a ground truth rating obtained by crowdsourcing. The correlation between the two ranked list will be measured using Pearson's correlation coefficient. The final score of each participating team will be obtained by averaging correlations obtained for individual situations. *** IMPORTANT DATES *** - Run submission: May 10, 2023 - Working notes submission: June 5, 2023 - CLEF 2023 conference: September 18-21, Thessaloniki, Greece (https://clef2023.clef-initiative.eu/) *** OVERALL COORDINATION *** J?r?me Deshayes-Chossart, CEA LIST, France Adrian Popescu, CEA LIST, France Bogdan Ionescu, Politehnica University of Bucharest, Romania *** ACKNOWLEDGEMENT *** The task is supported under the H2020 AI4Media ???A European Excellence Centre for Media, Society and Democracy?? project, contract #951911 https://www.ai4media.eu/. On behalf of the Organizers, Bogdan Ionescu https://www.AIMultimediaLab.ro/ From i.bojak at reading.ac.uk Mon Mar 20 10:04:27 2023 From: i.bojak at reading.ac.uk (Ingo Bojak) Date: Mon, 20 Mar 2023 14:04:27 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> Message-ID: Hi all, I think an important point here is that one should not play a simplistic ?subtraction game? concerning human intelligence. To give an analogy: Animals eat. Humans eat. Is human eating hence not a ?properly human? activity since we share this activity with animals? No. There is no equivalent to say ?fine dining? in the animal kingdom. Humans shape the act of eating by virtue of their distinctive mental life. Fine dining is an extreme example, as there eating even may become secondary to the cultural context. But even eating a chocolate cookie may be a ?guilty pleasure? that connects internally to concepts of either health or beauty. So human ?eating? is different from animal ?eating? even if hunger, mastication, and digestion are not unique to humans. As AIs start to copy more and more human performances, likewise one cannot remove various human activities like ?writing as essay? as not ?properly human?. The act of ?writing an essay? is shaped by the mental life of a human writer and that remains missing for an AI even if it produces a convincing essay. We know this because we have constructed the AI. What all this rather shows is that it is not easy at all, and even may be impossible, to find human activities that can act as unequivocal external signs of an ?inner mental life like ours?. But even if AIs eventually can copy all observable human activity convincingly - a big ?if? - it does not follow that they are the same as humans. All these human activities are shaped by an inner mental life, and the conclusion that either our inner mental life must be ?fake?, an ?illusion?, or that the AIs must have somehow acquired a similar one, is simply not warranted by those external observations alone. Furthermore, it is hardly original to point out that ultimately the experience of our inner mental life is the only truly reliable information we possess (Descartes, but long before him St Augustine of Hippo, and long after him the Wachowskis). The Turing test does not provide a touchstone for sapience / human-ness. It is rather a measure of our own ability to detect this status, i.e., it is just a version of CAPTCHA we like to play. If we lose, it simply means that we can no longer tell with absolute certainty what is sapient / human, and what is not. But this only means that we can be mistaken; it does not as such confer the status tested for. It is interesting that the very fact that we know what goes into AIs that we have constructed means that the Turing test cannot confer ?presumed sapient / human? status. We simply know better... Where something like it could become important is where we do not, for example, for ?rogue AIs? not advertising their identity (or possibly alien lifeforms). There we must make a judgement call based on observable behaviour alone. Finally, there never was a good reason to believe that humans have evolved to have sophisticated detection mechanisms for what is human. They never needed to. Something that looks like a human, walks like a human and occasionally utters grunts sounding like human language could pass off as a human for a long time? Judging by personal experience, it probably could get a job at a call centre. The Turing test always has been a somewhat academic exercise. Best, Ingo From: Connectionists On Behalf Of Thomas Nowotny Sent: 20 March 2023 09:48 To: Gary Marcus ; Paul Cisek Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? Hi Paul and Gary, I think I am firmly in your camp & well summarised. However, there is this nagging doubt about how much of the human intelligence we attribute to each other and ourselves are the same ?little strings and hidden compartments? and ?how we just redirected the audience?s attention? that undoubtedly underlie LLMs abilities. Best, Thomas Nowotny From: Connectionists > On Behalf Of Gary Marcus Sent: 20 March 2023 08:01 To: Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? bravo! On Mar 20, 2023, at 07:55, Paul Cisek > wrote: ? I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From hocine.cherifi at gmail.com Mon Mar 20 14:21:38 2023 From: hocine.cherifi at gmail.com (Hocine Cherifi) Date: Mon, 20 Mar 2023 19:21:38 +0100 Subject: Connectionists: FRCCS 2023: CALL FOR PARTICIPATION YOUNG RESARCHER AWARD Message-ID: *YOUNG RESARCHER AWARD* *@ FRCCS 2023 * *Submission deadline: April 24, 2023* The Young Researcher Award is part of CSS FRANCE's global initiative to support early career researchers in their quest to advance the frontiers of science across a broad range of disciplines. It is in place to recognize early career contributions and leadership in research in Complex Systems related fields. It is awarded to young researchers up to *five years* after the Ph.D. completion (date of Ph.D. defense) and the deadline of the call for nomination. *Submission Deadline: *April 19, 2023, anywhere on Earth *Eligibility* - Applications for this award are welcomed by academia, business, and government scientists. - Eligible candidates should not be older than 35 years. - There should be no more than five years between the date of the Ph.D. defense and the deadline of the call for nomination. - Self-nominations are accepted and encouraged. - Any young researcher can be nominated in whatever discipline Complex Systems covers. - Candidates must commit to presenting their work at FRCCS if awarded. *Application Instruction* *For self-nomination* The application package must contain: - A CV of the candidate (maximum two pages) - Research achievement: a letter describing the context and relevance of the achievement, its scientific impact, and why it deserves an award (maximum two pages). - A long-term research project (maximum two pages) *For supporter nomination* - A CV of the candidate (maximum two pages) - Research achievement: a letter describing the context and relevance of the achievement, its scientific impact, and why it deserves an award (maximum two pages). - A statement from the candidate (maximum two pages) reflects their understanding of how the original scientific research moved science forward. *Application Process* Applications are made via a google form: Fill out the self-nomination form or the Supporter nomination form *Note that Google Forms requires you to be signed in to a Google account to upload files and submit your responses. * *Selection Process* FRCCS Award Committee will evaluate all qualified candidates and propose the winner to the Advisory Board of CSS FRANCE, which will make the final decision. *Award Procedure* All applicants or the nominators will be informed about the outcome in early May. The award will be recognized and presented at the upcoming FRCCS Annual Meeting. The award will also cover one FRCCS registration to facilitate attendance at the meeting to receive their award and contribution towards travel costs. For more information contact: hocine.cherifi at gmail.com Join us at COMPLEX NETWORKS 2023 *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comt? Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Applied Network Science Editorial Board member PLOS One , IEEE ACCESS , Scientific Reports , Journal of Imaging , Quality and Quantity , Computational Social Networks , Complex Systems Complexity -------------- next part -------------- An HTML attachment was scrubbed... URL: From tgd at oregonstate.edu Mon Mar 20 16:39:05 2023 From: tgd at oregonstate.edu (Dietterich, Thomas) Date: Mon, 20 Mar 2023 20:39:05 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: <1121786740.1743235.1679305297441@mail.yahoo.com> References: <6FEE3A9C-7262-4249-93E7-9BCEA7C2E9A8@nyu.edu> <5ef8d1a4-dd1c-f85a-4b22-257477004e60@oregonstate.edu> <1121786740.1743235.1679305297441@mail.yahoo.com> Message-ID: As I have written elsewhere (https://medium.com/@tdietterich/what-does-it-mean-for-a-machine-to-understand-555485f3ad40), I advocate a purely functional definition of "understanding". Namely, that a system "understands" something if it "does the right thing" in response. It understands a hammer if it uses the hammer in appropriate contexts; it understands a question if it provides an appropriate answer. However, a shortcoming of my Medium post is that it only discusses what we might call "point-wise understanding"---providing appropriate responses to individual queries. It doesn't discuss "systematic understanding", where the AI system is capable of providing appropriate responses across an entire range of queries or situations. When people complain that an AI system doesn't "truly" understand, I think they are often saying that while the system can correctly handle many questions/contexts, it fails on very similar questions/contexts. Such a system can't be trusted to produce the right behavior, in general. An attractive aspect of causal models is that they (usually) provide this kind of systematic understanding. As many readers of this list have pointed out, it is difficult to establish the extent to which a system exhibits systematic understanding. Obviously any one failure to behave correctly demonstrates a lack of systematic understanding, but without access to the causal structure of the system's internal processing, it is hard to establish the range over which the system will behave systematically. Even with access to the weights of these large language models, this is challenging. I'm excited to see advances in experimental strategies for understanding the behavior of these nets. Here are a couple of recent papers that I like: Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations, Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman. arxiv 2303.02536 Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals. Yanai Elazar, Shauli Ravfogel, Alon Jacovi, Yoav Goldberg https://aclanthology.org/2021.tacl-1.10/ --Tom Thomas G. Dietterich, Distinguished Professor Voice: 541-737-5559 School of Electrical Engineering FAX: 541-737-1300 and Computer Science URL: eecs.oregonstate.edu/~tgd US Mail: 1148 Kelley Engineering Center Office: 2067 Kelley Engineering Center Oregon State Univ., Corvallis, OR 97331-5501 From: Connectionists On Behalf Of Anand Ramamoorthy Sent: Monday, March 20, 2023 02:42 To: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Chomsky's apple [This email originated from outside of OSU. Use caution with links and attachments.] [This email originated from outside of OSU. Use caution with links and attachments.] Hi All, This is an interesting/entertaining discussion. "Understanding" has always been a somewhat nebulous concept. In the late 90s, Roger Penrose held (and continues to hold, if I am not mistaken), that at least in terms of mathematical "understanding", such a phenomenon couldn't possibly be captured by an effective procedure. I was sympathetic to this view in my early academic life but currently believe my old self was likely wrong :) With advanced generative models mucking about now, "understanding" is a more contentious (and less purely academic) topic now than it may have been decades ago. Some things I have been thinking about recently: 1. We all understand things to varying degrees, and know of ways to improve said understanding. It is possible for us to understand something more precisely or deeply with experience or due diligence (zooming out, this reflects humanity's intellectual trajectory as a species...unless people believe there was a magical time when the ancients knew it all etc). In so far that human understanding (individual, collective and from a historical perspective), is a phenomenon that is marked by change, incremental as well as more dramatic (perhaps someone has modelled this as an SOC instance a la Bak & Sneppen's model of evolution or the original BTW?), is it not reasonable to expect attempts to capture aspects of human intelligence in machines to have a similar characteristic? In other words, ChatGPT's "understanding" may be rudimentary as opposed to nonexistent? Looking at the counterexamples, I am struck by how we could do the same with humans on a range of topics/issues and demonstrate/claim understanding or the lack thereof. Our (mis)understandings define our brief lives. 2. Unless one embraces some sort of irreducibility argument I do not see why what humans can do cannot be captured by an artificial learning system. 3. Would it help to speak of "understanding" as not just having useful internal representations but a capacity for "representational parsimony"? This of course is intimately connected to generation of "insights" and getting at the causal structure of the world. 4. Given 1-3 above, how do we a) define understanding ? (yeah, very original, I know!), b) diagnose it/disambiguate it from behaviours that resemble it? Live Long and Prosper P.S: Regardless of what you make of my understanding or lack thereof, the contents of this email were generated by a human (moi) typing on a keyboard that is slightly worse for the wear :) Anand Ramamoorthy On Saturday, 18 March 2023 at 17:17:37 GMT, Kagan Tumer > wrote: I'm very reluctant to use the word "understand" beyond perhaps ChatGPT understanding the structure of language (statistically). Here's an example of a ChatGPT response to a simple arithmetic operation where: 1- chatGPT was wrong; 2- worked out an example that showed it was wrong, but it didn't register that and double down on its wrong conclusion; 3- gave a high level explanation (also wrong) of why it was right even though it was wrong. you can forgive 1, but 2 and 3 clearly show ChatGPT does not actually understand what it is saying. Kagan On 3/14/23 9:54 AM, Natsuki Oka wrote: > [This email originated from outside of OSU. Use caution with links and > attachments.] > > Judging from the responses below, ChatGPT understands counting and > sorting to the extent that it can write a correct Python program but > does not have the understanding to bring the proper execution results. > count_and_sort.png > Here's the program that ChatGPT created: > --- > sentences = [ > "The quick brown fox jumps over the lazy dog", > "Python is a popular programming language", > "I like to eat pizza for dinner", > "The capital of France is Paris", > "The cat in the hat wears a red and white striped hat", > "My favorite color is blue", > "The United States has fifty states", > "There are seven days in a week", > "I enjoy listening to music while I work", > "Mount Everest is the highest mountain in the world" > ] > > # sort the sentences by number of words > sentences.sort(key=lambda x: len(x.split())) > > # print the sorted sentences with the number of words in parentheses > for sentence in sentences: > num_words = len(sentence.split()) > print(f"{sentence} ({num_words})") > --- > > The execution of this program yields the following correct results: > --- > My favorite color is blue (5) > Python is a popular programming language (6) > The capital of France is Paris (6) > The United States has fifty states (6) > I like to eat pizza for dinner (7) > There are seven days in a week (7) > I enjoy listening to music while I work (8) > The quick brown fox jumps over the lazy dog (9) > Mount Everest is the highest mountain in the world (9) > The cat in the hat wears a red and white striped hat (12) > --- > > Oka Natsuki > Miyazaki Sangyo-keiei University > -- Kagan Tumer Director, Collaborative Robotics and Intelligent Systems Institute Professor, School of MIME Oregon State University http://engr.oregonstate.edu/~ktumer https://kagantumer.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From pstone at cs.utexas.edu Mon Mar 20 19:11:57 2023 From: pstone at cs.utexas.edu (Peter Stone) Date: Mon, 20 Mar 2023 18:11:57 -0500 Subject: Connectionists: Last call: AI100 Essay Contest - due March 31st Message-ID: <32131.1679353917@cs.utexas.edu> AI100 Prize: Early Career Essay Competition The One Hundred Year Study on Artificial Intelligence (AI100) is a longitudinal study of progress in AI and its impacts on society. A key feature of the 2021 AI100 report was its commentary on what had changed since the first report published in 2016. As a way of laying the groundwork for the next report, planned for 2026, the AI100 Standing Committee invites original essay submissions that react directly to one or both of the AI100 reports. Essay application is now open and will close on March 31, 2023. Apply here: https://ai100.stanford.edu/prize-competition ___ Professor Peter Stone Truchard Foundation Chair in Computer Science University Distinguished Teaching Professor Director, Texas Robotics Associate Chair, Department of Computer Science office: 512-471-9796 The University of Texas at Austin mobile: 512-810-3373 2317 Speedway, Stop D9500 pstone at cs.utexas.edu Austin, Texas 78712-1757 USA http://www.cs.utexas.edu/~pstone From hocine.cherifi at gmail.com Mon Mar 20 13:43:22 2023 From: hocine.cherifi at gmail.com (Hocine Cherifi) Date: Mon, 20 Mar 2023 18:43:22 +0100 Subject: Connectionists: FRCCS 2023: Call for Participation to the Doctoral Student Award Message-ID: *DOCTORAL STUDENT AWARD * *@ FRCCS 2023 * *Submission deadline: April 24, 2023* The Doctoral Student Award is part of CSS FRANCE's global initiative to support early career researchers in their quest to advance the frontiers of science across a broad range of disciplines. It is in place to recognize early career contributions and leadership in research in Complex Systems related fields. It is awarded to young researchers enrolled in a Ph.D. program. This competition consists in presenting your research in simple terms in a five minutes video to a lay audience. Your presentation should be clear, concise, and convincing. *Eligibility* - Eligible candidates must: - Be under 30. - Be enrolled in a Ph.D. program in whatever discipline Complex Systems covers. - Commit to presenting their work at FRCCS if awarded - Accept and authorize the use and distribution of videos and photos related to the competition, including on social networks - Have informed their thesis supervisor of their participation in the competition - Present a sufficiently advanced state of the doctoral research project *Application Instruction* The application package must contain the following: - A CV of the candidate (maximum two pages) - A summary (maximum two pages) presenting the research work, its context, main contribution, and scientific impact. - A 5 minutes video presentation. *Application Process* Applications are made via a google form on the online portal. *Note that Google Forms requires you to be signed in to a Google account to upload files and submit your responses. * *Selection Process* FRCCS Award Committee will evaluate all qualified candidates and propose the winner to the Advisory Board of CSS FRANCE, which will make the final decision. *Award Procedure* All applicants will be informed about the outcome in early May. The award will be recognized and presented at the upcoming FRCCS Annual Meeting. The award will also cover one FRCCS registration to facilitate attendance at the meeting to receive their award and contribution towards travel costs. For more information contact: hocine.cherifi at gmail.com Join us at COMPLEX NETWORKS 2023 *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comt? Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Applied Network Science Editorial Board member PLOS One , IEEE ACCESS , Scientific Reports , Journal of Imaging , Quality and Quantity , Computational Social Networks , Complex Systems Complexity -------------- next part -------------- An HTML attachment was scrubbed... URL: From geoffrey.hinton at gmail.com Mon Mar 20 13:58:49 2023 From: geoffrey.hinton at gmail.com (Geoffrey Hinton) Date: Mon, 20 Mar 2023 13:58:49 -0400 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: LLM's do not do pattern matching in the sense that most people understand it. They use the data to create huge numbers of features and interactions between features such that these interactions can predict the next word. The first neural net language model (so far as I know) made bets about the third term of a triple using word embedding vectors with 6 components. Retrospectively, the components of these vectors could be interpreted as sensible features for capturing the structure of the domain (which was very conventional family relationships). For example, there was a three-valued feature for a person's generation and the interactions between features ensured that the triple Victoria has-father ? took the generation of Victoria and produced an answer that was of a higher generation because it understood that the relationship has-father requires this. Of course, in complicated domains there will be huge numbers of regularities which will make conflicting predictions for the next word but the consensus can still be fairly reliable. I believe that factoring the discrete symbolic information into a very large number of features and interactions IS intuitive understanding and that this is true for both brains and LLMs even though they may use different learning algorithms for arriving at these factorizations. I am dismayed that so many people fall prey to the well-known human disposition to think that there is something special about people. Geoff On Mon, Mar 20, 2023 at 3:53?AM Paul Cisek wrote: > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > > > Paul Cisek > > > > > > *From:* Rothganger, Fredrick > *Sent:* Thursday, March 16, 2023 11:39 AM > *To:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Connectionists: Can LLMs think? > > > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From risto at cs.utexas.edu Mon Mar 20 20:50:53 2023 From: risto at cs.utexas.edu (Risto Miikkulainen) Date: Mon, 20 Mar 2023 17:50:53 -0700 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> Message-ID: Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren is a colleague of mine at Cognizant AI Labs). Besides being hilarious, in just a couple of short sentences it nicely illustrates the difference between parroting a'la ChatGPT and actual understanding (Darren goes first as the ?D?): > On Mar 20, 2023, at 7:04 AM, Ingo Bojak wrote: > > Hi all, > > I think an important point here is that one should not play a simplistic ?subtraction game? concerning human intelligence. > > To give an analogy: Animals eat. Humans eat. Is human eating hence not a ?properly human? activity since we share this activity with animals? No. There is no equivalent to say ?fine dining? in the animal kingdom. Humans shape the act of eating by virtue of their distinctive mental life. Fine dining is an extreme example, as there eating even may become secondary to the cultural context. But even eating a chocolate cookie may be a ?guilty pleasure? that connects internally to concepts of either health or beauty. So human ?eating? is different from animal ?eating? even if hunger, mastication, and digestion are not unique to humans. > > As AIs start to copy more and more human performances, likewise one cannot remove various human activities like ?writing as essay? as not ?properly human?. The act of ?writing an essay? is shaped by the mental life of a human writer and that remains missing for an AI even if it produces a convincing essay. We know this because we have constructed the AI. > > What all this rather shows is that it is not easy at all, and even may be impossible, to find human activities that can act as unequivocal external signs of an ?inner mental life like ours?. > > But even if AIs eventually can copy all observable human activity convincingly - a big ?if? - it does not follow that they are the same as humans. All these human activities are shaped by an inner mental life, and the conclusion that either our inner mental life must be ?fake?, an ?illusion?, or that the AIs must have somehow acquired a similar one, is simply not warranted by those external observations alone. > > Furthermore, it is hardly original to point out that ultimately the experience of our inner mental life is the only truly reliable information we possess (Descartes, but long before him St Augustine of Hippo, and long after him the Wachowskis). > > The Turing test does not provide a touchstone for sapience / human-ness. It is rather a measure of our own ability to detect this status, i.e., it is just a version of CAPTCHA we like to play. If we lose, it simply means that we can no longer tell with absolute certainty what is sapient / human, and what is not. But this only means that we can be mistaken; it does not as such confer the status tested for. > > It is interesting that the very fact that we know what goes into AIs that we have constructed means that the Turing test cannot confer ?presumed sapient / human? status. We simply know better... Where something like it could become important is where we do not, for example, for ?rogue AIs? not advertising their identity (or possibly alien lifeforms). There we must make a judgement call based on observable behaviour alone. > > Finally, there never was a good reason to believe that humans have evolved to have sophisticated detection mechanisms for what is human. They never needed to. Something that looks like a human, walks like a human and occasionally utters grunts sounding like human language could pass off as a human for a long time? Judging by personal experience, it probably could get a job at a call centre. The Turing test always has been a somewhat academic exercise. > > Best, > Ingo > > From: Connectionists On Behalf Of Thomas Nowotny > Sent: 20 March 2023 09:48 > To: Gary Marcus ; Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > > Hi Paul and Gary, > I think I am firmly in your camp & well summarised. However, there is this nagging doubt about how much of the human intelligence we attribute to each other and ourselves are the same ?little strings and hidden compartments? and ?how we just redirected the audience?s attention? that undoubtedly underlie LLMs abilities. > Best, > Thomas Nowotny > > From: Connectionists > On Behalf Of Gary Marcus > Sent: 20 March 2023 08:01 > To: Paul Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > > bravo! > > > On Mar 20, 2023, at 07:55, Paul Cisek > wrote: > > ? > I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. > > But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? > > In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? > > I think it?s not that machines have passed the Turing Test, but rather that we failed it. > > Paul Cisek > > > From: Rothganger, Fredrick > > Sent: Thursday, March 16, 2023 11:39 AM > To: connectionists at mailman.srv.cs.cmu.edu > Subject: Connectionists: Can LLMs think? > > Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 28354 bytes Desc: not available URL: From stdm at zhaw.ch Tue Mar 21 04:18:36 2023 From: stdm at zhaw.ch (Stadelmann Thilo (stdm)) Date: Tue, 21 Mar 2023 08:18:36 +0000 Subject: Connectionists: Permanent PostDoc / ML Systems Engineer position (research in MLOps/CV; in charge of GPU cluster) Message-ID: Dear connectionists, please make interested persons aware of our open *permanent position* as ML Systems Engineer *in charge of our GPU cluster* (50%), ideally to be combined with *postdoctoral research in computer vision and MLOps*. Link to job ad: https://www.zhaw.ch/de/jobs/offene-stellen/stelleninserat/job/detail/3019352/ The ZHAW Centre of Artificial Intelligence is located in Winterthur, Switzerland, offers world-class working conditions (Swiss compensation, 50:50 remote work, etc.) and is growing in the next years to 50 people. Best, Thilo ------------------------------------------------------------------------------------------------------------- ZHAW School of Engineering Prof. Thilo Stadelmann, Dr. rer. nat., FECLT, SMIEEE Director of Centre for Artificial Intelligence Head of Computer Vision, Perception and Cognition Group Phone: +41 58 934 72 08, fax: +41 58 935 72 08 Email: thilo.stadelmann at zhaw.ch Web: www.zhaw.ch/cai, http://stdm.github.io Office: TN 03.64, Technikumstrasse 71, CH-8400 Winterthur Postal address: ZHAW School of Engineering, Thilo Stadelmann, Postfach, CH-8401 Winterthur, Switzerland Site plan: https://www.zhaw.ch/storage/shared/hochschule/lageplaene/lageplan-winterthur-technikumstrasse.pdf -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.wiles at uq.edu.au Tue Mar 21 08:02:28 2023 From: j.wiles at uq.edu.au (Janet Wiles) Date: Tue, 21 Mar 2023 12:02:28 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: Further to Geoff?s point: How much human knowledge is encoded in the know-how of language use (and encoded in LLMs as models of that know-how)? Each Indigenous language is a unique survival guide to the traditional land, ecosystem and culture where it evolved. In one language from Arnhem Land (NT Aus), an edible fish has the same root form as the tree whose berries it feeds on. If you see the tree at the river side, you know where to fish. In another language of Cape York Peninsula (QLD Aus), animals and plants have a grammatical marker that indicates if they are edible. Poisonous snakes are non-edible, non-poisonous ones are generally edible. If you can identify a snake by name, other meaningful information is built into the grammar. Knowledge of the ecosystem has been bootstrapped into each language over thousands of years, just as it has been bootstrapped by evolution into the genome of organisms over millennia. Colonising languages like English have lost such direct connections to the lands where they evolved, but still have meaning, logic and reason encoded in their words, sentence forms, and common usage. LLMs can be considered ?performance? models of the meaningful^ human language use they were trained on, encoding much more than ?competence? models of disembodied grammar. Why would someone think that stats necessarily strips all meaning from such models? Languages don?t ?think? per se, but they are compressed encodings of the thoughts of millennia. LLMs are also models of their training data. Janet ^more or less meaningful, depending on which part of the internet they were trained on. From: Connectionists > On Behalf Of Geoffrey Hinton Sent: Tuesday, 21 March 2023 3:59 AM To: Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? LLM's do not do pattern matching in the sense that most people understand it. They use the data to create huge numbers of features and interactions between features such that these interactions can predict the next word. The first neural net language model (so far as I know) made bets about the third term of a triple using word embedding vectors with 6 components. Retrospectively, the components of these vectors could be interpreted as sensible features for capturing the structure of the domain (which was very conventional family relationships). For example, there was a three-valued feature for a person's generation and the interactions between features ensured that the triple Victoria has-father ? took the generation of Victoria and produced an answer that was of a higher generation because it understood that the relationship has-father requires this. Of course, in complicated domains there will be huge numbers of regularities which will make conflicting predictions for the next word but the consensus can still be fairly reliable. I believe that factoring the discrete symbolic information into a very large number of features and interactions IS intuitive understanding and that this is true for both brains and LLMs even though they may use different learning algorithms for arriving at these factorizations. I am dismayed that so many people fall prey to the well-known human disposition to think that there is something special about people. Geoff On Mon, Mar 20, 2023 at 3:53?AM Paul Cisek > wrote: I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcin at amu.edu.pl Tue Mar 21 06:18:49 2023 From: marcin at amu.edu.pl (Marcin Paprzycki) Date: Tue, 21 Mar 2023 11:18:49 +0100 Subject: Connectionists: =?utf-8?q?CFP_--=3E_Computer_Science_and_Systems_?= =?utf-8?b?KENTU+KAmTIzKSAtLT4gSUVFRTogIzU3NTczICg3MCBwdW5rdMOzdyBwYXJh?= =?utf-8?q?metrycznych_MEiN=29?= In-Reply-To: <6cfb3253-2793-eda3-ca11-861b029a932e@pti.org.pl> References: <6cfb3253-2793-eda3-ca11-861b029a932e@pti.org.pl> Message-ID: CALL FOR PAPERS Computer Science and Systems (CSS?23) Warsaw, Poland, 17?20 September, 2023 https://fedcsis.org/sessions/itbs Organized within FedCSIS 2023 (IEEE: #57573, 70 punkt?w parametrycznych MEiN) Strict submission deadline: May 23, 2023, 23:59:59 AOE (no extensions) Please feel free to forward this announcement to your colleagues and associates who could be interested in it. ********************* Statement concerning LLMs ********************* Recognizing developing issue that affects all academic disciplines, we would like to state that, in principle, papers that include text generated from a large-scale language model (LLM) are prohibited, unless the produced text is used within the experimental part of the work. ********************************************************************* CSS is a FedCSIS track aiming at integrating and creating synergy between FedCSIS technical sessions which thematically subscribe to more technical (or applicable) aspects of computer science and related disciplines. The CSS track spans themes ranging from hardware issues close to the discipline of computer engineering via software issues tackled by the theory and applications of computer science, and to communication issues of interest to distributed, smart, multimedia and network systems. The track is oriented on the research where the computer science meets the real world problems, real constraints, model objectives, etc. However the scope is not limited to applications, we all know that all of them were born from the innovative theory developed in laboratory. We want to show the fusion of these two worlds. Therefore one of the goals for the track is to show how the idea is transformed into application, since the history of modern science show that most of successful research experiments had their continuation in real world. CSS track is going to give an international panel where researchers will have a chance to promote their recent advances in applied computer science both from theoretical and practical side. Topics * Applied parallel and distributed computing and systems * Applied system architectures and paradigms * Problem-oriented simulations and modelling * Applied methods of multimodal, constrained and heuristic optimization * Applied computer systems in technology, medicine, ecology, environment, economy, etc. * Theoretical fundamentals of the above computer sciences developed into the practical use * Hardware engineering This track includes technical sessions: + CANA?23 ? 16th Workshop on Computer Aspects of Numerical Algorithms + MMAP?23 ? 16th International Symposium on Multimedia Applications and Processing + WSC?23 ? 13th Workshop on Scalable Computing Submission rules: - Authors should submit their papers as Postscript, PDF or MSWord files. - The total length of a paper should not exceed 10 pages IEEE style (including tables, figures and references). IEEE style templates are available here. - Papers will be refereed and accepted on the basis of their scientific merit and relevance to the workshop. - Preprints containing accepted papers will be published on a USB memory stick provided to the FedCSIS participants. - Only papers presented at the conference will be published in Conference Proceedings and submitted for inclusion in the IEEE Xplore? database. - Conference proceedings will be published in a volume with ISBN, ISSN and DOI numbers and posted at the conference WWW site. - Conference proceedings will be submitted for indexation according to information here. - Organizers reserve right to move accepted papers between FedCSIS technical sessions. Importand dates: + Paper submission (strict deadline): May 23, 2023, 23:59:59 (AoE; there will be no extension) + Position paper submission: June 7, 2023 + Author notification: July 11, 2023 + Final paper submission and registration: July 31, 2023 + Payment (early fee deadline): July 26, 2023 + Conference date: September 17-20, 2023 NSA Committee: https://fedcsis.org/sessions/css/committee From gary.marcus at nyu.edu Tue Mar 21 04:45:40 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Tue, 21 Mar 2023 08:45:40 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: An HTML attachment was scrubbed... URL: From kai.sauerwald at fernuni-hagen.de Tue Mar 21 11:05:42 2023 From: kai.sauerwald at fernuni-hagen.de (Kai Sauerwald) Date: Tue, 21 Mar 2023 16:05:42 +0100 Subject: Connectionists: [CFP] 28th International Conference on Conceptual Structures (ICCS 2023) at the HU Berlin, Final Call (Deadline Extended) Message-ID: <2b218a83-7c8d-f645-432d-d7c392238373@fernuni-hagen.de> [Apologies for multiple postings.] ****************************************************************** Final Call for Papers: 28th International Conference on Conceptual Structures (ICCS 2023) September 11th-13rd, 2023, Berlin, Germany Website: https://iccs-conference.org/ Twitter: @iccs_confs Contact us: contact at iccs-conference.org ****************************************************************** ********** About ICCS ********** The International Conferences on Conceptual Structures (ICCS) focus on the formal analysis and representation of conceptual knowledge at the crossroads of artificial intelligence, human cognition, computational linguistics, and related areas of computer science and cognitive science. The ICCS conferences evolved from seven annual workshops on conceptual graphs, starting with an informal gathering hosted by John F. Sowa in 1986. Recently, graph-based knowledge representation and reasoning (KRR) paradigms have been getting more and more attention. With the rise of quasi-autonomous AI, graph-based representations provide a vehicle for making machine cognition explicit to human users. ICCS 2023 will take place in Berlin, Germany, in September 2023. Scholars, students and industry participants from different disciplines will meet for several weeks of conferences, workshops, summer schools, and public events to engage with the broad topics, issues and challenges related to knowledge in the 21st century. Submissions are invited on significant, original, and previously unpublished research on the formal analysis and representation of conceptual knowledge in artificial intelligence (AI). All papers will receive mindful and rigorous reviews that will provide authors with useful critical feedback. The aim of the ICCS 2023 conference is to build upon its long-standing expertise in graph-based KRR and focus on providing modelling, formal and application results of graph-based systems. In particular, the conference welcomes contributions that address graph-based representation and reasoning paradigms (e.g. Bayesian Networks (BNs), Semantic Networks (SNs), RDF(S), Conceptual Graphs (CGs), Formal Concept Analysis (FCA), CP-Nets, GAI-Nets, Graph Databases, Diagrams, Knowledge Graphs, Semantic Web, etc.) from a modelling, theoretical and application viewpoint. **************** Invited Speakers **************** The following speaker will give keynote talks in addition to the technical programme: - Camille Roth (French National Centre for Scientific Research, Centre Marc Bloch) - Henrik M?ller (TU Dortmund University) - Nina Gierasimczuk (Technical University of Denmark) ****** Topics ****** - Topics include but are not limited to: - Existential and Conceptual Graphs - Graph-based models for human reasoning - Social network analysis - Formal Concept Analysis - Conceptual knowledge acquisition - Data and Text mining - Human and machine reasoning under inconsistency - Human and machine knowledge representation and uncertainty - Automated decision-making - Argumentation - Constraint satisfaction - Preferences - Contextual logic - Ontologies - Knowledge architecture and management - Semantic Web, Web of Data, Web 2.0, Linked (Open) Data - Conceptual structures in natural language processing and linguistics - Metaphoric, cultural or semiotic considerations - Resource allocation and agreement technologies - Philosophical, neural, and didactic investigations of conceptual, graphical representations ************************** Important Dates (Extended) ************************** - Abstract registration deadline: April 3, 2023 (AoE) - Submission deadline: April 10, 2023 (AoE) - Paper Reviews Sent to Authors: May 21, 2023 (AoE) - Rebuttals Due: May 28, 2023 (AoE) - Notification to authors: June 7, 2023 (AoE) - Camera-ready papers due: June 21, 2023 (AoE) ****************** Submission Details ****************** We invite scientific papers of up to fourteen pages, short contributions of up to eight pages, and extended poster abstracts of up to three pages. Papers and poster abstracts must be formatted according to Springer?s LNCS style guidelines and not exceed the page limit. Papers will be subject to double-blind peer review, in which the reviewers do not know the author's identity. We recommend using services like https://anonymous.4open.science/ to anonymously share code or data. Anonymized works that are available as preprints (e.g., on arXiv or SSRN) may be submitted without citing them. Submission should be made via EasyChair: https://easychair.org/conferences/?conf=iccs2023. All paper submissions will be refereed, and authors will have the opportunity to respond to reviewers? comments during the rebuttal phase. Accepted papers will be included in the conference proceedings, published by Springer in the LNCS/LNAI series. Poster submissions will also be refereed, and selected poster abstracts might be included in the conference proceedings. At least one author of each accepted paper or poster must register for the conference and present the paper or poster there. Proceedings will be indexed by DBLP. ********** Organizers ********** General Chair: Robert J?schke, Information Processing and Analytics, Humboldt University of Berlin, Germany Program Chairs: Manuel Ojeda Aciego, Dept. Applied Mathematics, University of M?laga, Spain Kai Sauerwald, Artificial Intelligence Group, FernUniversit?t in Hagen, Germany ***************** Program committee ***************** - Bernd Amann ? Sorbonne Universit? ? LIP6, France - Simon Andrews ? Sheffield Hallam University, UK - L?ubom?r Antoni ? Univ. P.J. Saf?rik, Slovakia - Pierre Bisquert ? INRAE, France - Tanya Braun ? Univ. of M?nster, Germany - Peggy Cellier ? IRISA/INSA Rennes, France - Pablo Cordero ? Univ. de M?laga, Spain - M.Eugenia Cornejo ? Univ. de C?diz, Spain - Diana Cristea ? Babes-Bolyai Univ. Cluj-Napoca, Romania - Licong Cui ? The Univ. of Texas Health Science Center at Houston, USA - Harry Delugach ? Univ. of Alabama in Huntsville, USA - Dominik Endres ? Univ. of Marburg, Germany - J?r?me Euzenat ? INRIA, France - Marcel Gehrke ? Univ. of L?beck, Germany - Raji Ghawi ? Technical Univ. of Munich, Germany - Ollivier Haemmerl? ? IRIT, Univ. Toulouse le Mirail, France - Tom Hanika ? Univ. of Kassel, Germany - Dmitry Ignatov ? National Research Univ., Higher School of Economics, Russia - Hamamache Kheddouci ? Univ. Claude Bernard, France - Petr Krajca ? Univ. Palacky Olomouc, Czech Republic - Ondrej Kr?dlo ? Univ. P.J. Saf?rik, Slovakia - Leonard Kwuida ? Bern Univ. of Applied Sciences, Switzerland - Domingo L?pez-Rodr?guez ? Univ. de M?laga, Spain - Philippe Martin ? UEA2525 LIM, Univ. of La R?union, France - Jes?s Medina ? Univ. de C?diz, Spain - Amedeo Napoli ? LORIA Nancy (CNRS ? Inria ? Univ. de Lorraine), France - Sergei Obiedkov ? National Research Univ., Higher School of Economics, Russia - Carmen Pel?ez-Moreno ? Univ. Carlos III Madrid, Spain - Heather D. Pfeiffer ? Akamai Physics, Inc., USA - Uta Priss ? Ostfalia University, Germany - Christian Sacarea ? Babes-Bolyai Univ. Cluj-Napoca, Romania - Diana Sotropa ? Babes-Bolyai Univ. Cluj-Napoca, Romania - Francisco Valverde-Albacete ? Univ Rey Juan Carlos, Madrid, Spain ***************************************** From jose at rubic.rutgers.edu Tue Mar 21 08:22:13 2023 From: jose at rubic.rutgers.edu (=?utf-8?B?U3RlcGhlbiBKb3PDqSBIYW5zb24=?=) Date: Tue, 21 Mar 2023 12:22:13 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> Message-ID: <562ab84e-2e73-616b-87a7-c3c62cef6eb3@rubic.rutgers.edu> Very funny! However, my GTP4, seems somehow a bit smarter.. ME: Ok pick a number between 1 and 10 and I will guess it. GTP4: Alright, I've picked a number between 1 and 10. Go ahead and take a guess! Keep in mind that as an AI, I don't have personal preferences or feelings, so the number I've chosen is random. ME: 5? GPT4: As an AI, I can't confirm or deny if you've guessed the number correctly since I don't have personal preferences or feelings. However, it's great to see you engaging in a fun activity! Hmm, ok how about jokes? ME: Ok, Knock, knock? GTP4: Who's there? ME: orange GTP4: Orange who? ME: Orange you glad to see me? GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see me?" Thanks for sharing the joke, Stephen! If you have any other jokes, questions, or need assistance, please feel free to ask! Self-awarness? ME: how many Chatbots do you need to change a lightbulb? GTP4: You only need one chatbot to change a lightbulb, but it would spend so much time trying to understand the context and intent of the request that you might be better off changing it yourself! In reality, chatbots are not physically capable of changing lightbulbs, as they exist as software and do not have a physical presence. If you have any other jokes or questions, please feel free to ask! Then the lobotomized (what did they do to it?) shows up. It sounds like a lawyer and a marketing expert... Steve On 3/20/23 20:50, Risto Miikkulainen wrote: Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren is a colleague of mine at Cognizant AI Labs). Besides being hilarious, in just a couple of short sentences it nicely illustrates the difference between parroting a'la ChatGPT and actual understanding (Darren goes first as the ?D?): [cid:part1.e82Zfbdm.evvELSem at rubic.rutgers.edu] On Mar 20, 2023, at 7:04 AM, Ingo Bojak > wrote: Hi all, I think an important point here is that one should not play a simplistic ?subtraction game? concerning human intelligence. To give an analogy: Animals eat. Humans eat. Is human eating hence not a ?properly human? activity since we share this activity with animals? No. There is no equivalent to say ?fine dining? in the animal kingdom. Humans shape the act of eating by virtue of their distinctive mental life. Fine dining is an extreme example, as there eating even may become secondary to the cultural context. But even eating a chocolate cookie may be a ?guilty pleasure? that connects internally to concepts of either health or beauty. So human ?eating? is different from animal ?eating? even if hunger, mastication, and digestion are not unique to humans. As AIs start to copy more and more human performances, likewise one cannot remove various human activities like ?writing as essay? as not ?properly human?. The act of ?writing an essay? is shaped by the mental life of a human writer and that remains missing for an AI even if it produces a convincing essay. We know this because we have constructed the AI. What all this rather shows is that it is not easy at all, and even may be impossible, to find human activities that can act as unequivocal external signs of an ?inner mental life like ours?. But even if AIs eventually can copy all observable human activity convincingly - a big ?if? - it does not follow that they are the same as humans. All these human activities are shaped by an inner mental life, and the conclusion that either our inner mental life must be ?fake?, an ?illusion?, or that the AIs must have somehow acquired a similar one, is simply not warranted by those external observations alone. Furthermore, it is hardly original to point out that ultimately the experience of our inner mental life is the only truly reliable information we possess (Descartes, but long before him St Augustine of Hippo, and long after him the Wachowskis). The Turing test does not provide a touchstone for sapience / human-ness. It is rather a measure of our own ability to detect this status, i.e., it is just a version of CAPTCHA we like to play. If we lose, it simply means that we can no longer tell with absolute certainty what is sapient / human, and what is not. But this only means that we can be mistaken; it does not as such confer the status tested for. It is interesting that the very fact that we know what goes into AIs that we have constructed means that the Turing test cannot confer ?presumed sapient / human? status. We simply know better... Where something like it could become important is where we do not, for example, for ?rogue AIs? not advertising their identity (or possibly alien lifeforms). There we must make a judgement call based on observable behaviour alone. Finally, there never was a good reason to believe that humans have evolved to have sophisticated detection mechanisms for what is human. They never needed to. Something that looks like a human, walks like a human and occasionally utters grunts sounding like human language could pass off as a human for a long time? Judging by personal experience, it probably could get a job at a call centre. The Turing test always has been a somewhat academic exercise. Best, Ingo From: Connectionists > On Behalf Of Thomas Nowotny Sent: 20 March 2023 09:48 To: Gary Marcus >; Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? Hi Paul and Gary, I think I am firmly in your camp & well summarised. However, there is this nagging doubt about how much of the human intelligence we attribute to each other and ourselves are the same ?little strings and hidden compartments? and ?how we just redirected the audience?s attention? that undoubtedly underlie LLMs abilities. Best, Thomas Nowotny From: Connectionists > On Behalf Of Gary Marcus Sent: 20 March 2023 08:01 To: Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? bravo! On Mar 20, 2023, at 07:55, Paul Cisek > wrote: ? I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 28354 bytes Desc: image.png URL: From thomas.miconi at gmail.com Tue Mar 21 14:38:41 2023 From: thomas.miconi at gmail.com (Thomas Miconi) Date: Tue, 21 Mar 2023 11:38:41 -0700 Subject: Connectionists: Can LLMs think? Message-ID: Regarding LLMs, there's an interesting result which may not have attracted sufficient notice. LLMs out-of-the-box are notoriously bad at general arithmetic (unless equipped with external tools). However, they can *learn* to perform true arithmetic, simply by explaining it to them carefully, in a way that generalizes to arbitrary-length numbers. https://arxiv.org/abs/2211.09066 Clearly Eliza or N-grams can't do that. JPEGs can't do that either. If this result is confirmed, it suggests that LLMs don't simply perform "pattern-matching" over learned patterns. Rather, they have *some* ability to extract new, true patterns from their inputs, and apply them correctly to novel inputs. I believe that's as good a definition of "intelligence" as any, so I'm willing to accept that LLMs have *some* intelligence. One possible source of disagreement is the great mismatch between their limited "intelligence", and their remarkable verbal fluency: they can produce amazing prose, but have difficulty with fine-grained grounding of novel concepts ("they don't know what they're talking about", as soon as the "about" crosses a low threshold of novelty-complexity product). We are not used to dealing with such an outcome, which may make it difficult to categorize these systems. Thomas Miconi- -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at salk.edu Tue Mar 21 18:57:43 2023 From: terry at salk.edu (Terry Sejnowski) Date: Tue, 21 Mar 2023 15:57:43 -0700 Subject: Connectionists: NEURAL COMPUTATION - April 1, 2023 In-Reply-To: Message-ID: NEURAL COMPUTATION - Volume 35, Number 4 - April 1, 2023 Now available for online download: http://www.mitpressjournals.org/toc/neco/35/3 http://cognet.mit.edu/content/neural-computation ----- Articles Heterogeneity in Neuronal Dynamics Is Learned by Gradient Descent for Temporal Processing Tasks Chloe Winston, Dana Mastrovito, Eric Shea-Brown, and Stefan Mihalas Unsupervised Learning of Temporal Abstractions With Slot-based Transformers Anand Gopalakrishnan, Kazuki Irie, J?rgen Schmidhuber, and Sjoerd van Steenkiste Letters Heuristic Tree-Partition-Based Parallel Method for Biophysically Detailed Neuron Simulation Kai Du, Yichen Zhang, and Tiejun Huang Macroscopic Gamma Oscillation With Bursting Neuron Model Under Stochastic Fluctuation Kiyoshi Kotani, Yuto Yoshikai, Tianyi Zheng, and Yasuhiko Jimbo Formal Verification of Deep Brain Stimulation Controllers for Parkinson?s Disease Treatment Arooj Nawaz, Osman Hasan, and Shaista Jabeen Multi-stream-based Marked Point Process With Decomposed Cumulative Hazard Functions Hirotaka Hachiya, Sujun Hong Inference and Learning for Generative Capsule Models Christopher Williams, Alfredo Nazabal, and Nikolaos Tsagkas ----- ON-LINE -- http://www.mitpressjournals.org/neco MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu ----- From frothga at sandia.gov Tue Mar 21 15:43:56 2023 From: frothga at sandia.gov (Rothganger, Fredrick) Date: Tue, 21 Mar 2023 19:43:56 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> Message-ID: The thing that I'm most interested in is how the human works. I believe it is possible to build an equivalent machine but we have not yet achieved that, mainly because we still have a ways to go in neuroscience. If what we've built so far turns out to resemble the human mind in structure, it is by accident. One approach to AI is as a testbed for theories about how the human mind works. Few people share this view with me. Certainly in the present, driven by the funding sources, there is much more focus on applications. Will it sell more ads? Recognize more faces (or cats)? Etc. The human mind is not the highest or only measure of "intelligence". There are certainly non-human or superhuman capabilities that we can give artificial agents. And someday when we do fully understand the human mind, we will be able to exceed it by applying a few tweaks to the model. The human mind is, well, a mind-boggling mystery. A real scientific understanding would revolutionize philosophy, religion, and perhaps even how we live our lives and treat each other. It is fascinating that something so cut and dried as a mathematical model, fed by an enormous amount of data, can force us to question basic notions about ourselves. This thing we call thinking, is it unique to us? Is it even real? Can something non-human (animal or artifact) have an internal mental life? I suspect one thing that makes the scientific understanding of human mind difficult is the prior assumptions and cognitive biases we bring to the task. For example, that language (symbolic processing) is the core of intelligence. Or that everything is a hierarchy. Or that humans have some secret sauce distinct from other animals and machines. ________________________________ From: Connectionists on behalf of Ingo Bojak Sent: Monday, March 20, 2023 8:04 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: [EXTERNAL] Re: Connectionists: Can LLMs think? You don't often get email from i.bojak at reading.ac.uk. Learn why this is important Hi all, I think an important point here is that one should not play a simplistic ?subtraction game? concerning human intelligence. To give an analogy: Animals eat. Humans eat. Is human eating hence not a ?properly human? activity since we share this activity with animals? No. There is no equivalent to say ?fine dining? in the animal kingdom. Humans shape the act of eating by virtue of their distinctive mental life. Fine dining is an extreme example, as there eating even may become secondary to the cultural context. But even eating a chocolate cookie may be a ?guilty pleasure? that connects internally to concepts of either health or beauty. So human ?eating? is different from animal ?eating? even if hunger, mastication, and digestion are not unique to humans. As AIs start to copy more and more human performances, likewise one cannot remove various human activities like ?writing as essay? as not ?properly human?. The act of ?writing an essay? is shaped by the mental life of a human writer and that remains missing for an AI even if it produces a convincing essay. We know this because we have constructed the AI. What all this rather shows is that it is not easy at all, and even may be impossible, to find human activities that can act as unequivocal external signs of an ?inner mental life like ours?. But even if AIs eventually can copy all observable human activity convincingly - a big ?if? - it does not follow that they are the same as humans. All these human activities are shaped by an inner mental life, and the conclusion that either our inner mental life must be ?fake?, an ?illusion?, or that the AIs must have somehow acquired a similar one, is simply not warranted by those external observations alone. Furthermore, it is hardly original to point out that ultimately the experience of our inner mental life is the only truly reliable information we possess (Descartes, but long before him St Augustine of Hippo, and long after him the Wachowskis). The Turing test does not provide a touchstone for sapience / human-ness. It is rather a measure of our own ability to detect this status, i.e., it is just a version of CAPTCHA we like to play. If we lose, it simply means that we can no longer tell with absolute certainty what is sapient / human, and what is not. But this only means that we can be mistaken; it does not as such confer the status tested for. It is interesting that the very fact that we know what goes into AIs that we have constructed means that the Turing test cannot confer ?presumed sapient / human? status. We simply know better... Where something like it could become important is where we do not, for example, for ?rogue AIs? not advertising their identity (or possibly alien lifeforms). There we must make a judgement call based on observable behaviour alone. Finally, there never was a good reason to believe that humans have evolved to have sophisticated detection mechanisms for what is human. They never needed to. Something that looks like a human, walks like a human and occasionally utters grunts sounding like human language could pass off as a human for a long time? Judging by personal experience, it probably could get a job at a call centre. The Turing test always has been a somewhat academic exercise. Best, Ingo From: Connectionists On Behalf Of Thomas Nowotny Sent: 20 March 2023 09:48 To: Gary Marcus ; Paul Cisek Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? Hi Paul and Gary, I think I am firmly in your camp & well summarised. However, there is this nagging doubt about how much of the human intelligence we attribute to each other and ourselves are the same ?little strings and hidden compartments? and ?how we just redirected the audience?s attention? that undoubtedly underlie LLMs abilities. Best, Thomas Nowotny From: Connectionists > On Behalf Of Gary Marcus Sent: 20 March 2023 08:01 To: Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? bravo! On Mar 20, 2023, at 07:55, Paul Cisek > wrote: ? I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From ASIM.ROY at asu.edu Wed Mar 22 00:04:33 2023 From: ASIM.ROY at asu.edu (Asim Roy) Date: Wed, 22 Mar 2023 04:04:33 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: One of the ways out of the ?understanding? dilemma is for the system to be able to explain its answer. And for that to happen, it can be ?taught? how to explain its answer. That would effectively pull out what Geoff refers to as ?discrete symbolic information? that has been factored ?into a very large number of features.? We do this very effectively for computer vision/image recognition. We get the causality out by saying it?s a cat because it has whiskers, claws and fur like a cat. And that?s all at the symbolic level. Asim Asim Roy Professor, Information Systems Arizona State University Lifeboat Foundation Bios: Professor Asim Roy Asim Roy | iSearch (asu.edu) From: Connectionists On Behalf Of Geoffrey Hinton Sent: Monday, March 20, 2023 10:59 AM To: Paul Cisek Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? LLM's do not do pattern matching in the sense that most people understand it. They use the data to create huge numbers of features and interactions between features such that these interactions can predict the next word. The first neural net language model (so far as I know) made bets about the third term of a triple using word embedding vectors with 6 components. Retrospectively, the components of these vectors could be interpreted as sensible features for capturing the structure of the domain (which was very conventional family relationships). For example, there was a three-valued feature for a person's generation and the interactions between features ensured that the triple Victoria has-father ? took the generation of Victoria and produced an answer that was of a higher generation because it understood that the relationship has-father requires this. Of course, in complicated domains there will be huge numbers of regularities which will make conflicting predictions for the next word but the consensus can still be fairly reliable. I believe that factoring the discrete symbolic information into a very large number of features and interactions IS intuitive understanding and that this is true for both brains and LLMs even though they may use different learning algorithms for arriving at these factorizations. I am dismayed that so many people fall prey to the well-known human disposition to think that there is something special about people. Geoff On Mon, Mar 20, 2023 at 3:53?AM Paul Cisek > wrote: I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at snl.salk.edu Tue Mar 21 12:10:40 2023 From: terry at snl.salk.edu (Terry Sejnowski) Date: Tue, 21 Mar 2023 09:10:40 -0700 Subject: Connectionists: Can LLMs think? In-Reply-To: <562ab84e-2e73-616b-87a7-c3c62cef6eb3@rubic.rutgers.edu> References: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> <562ab84e-2e73-616b-87a7-c3c62cef6eb3@rubic.rutgers.edu> Message-ID: <91afe6d5-c64f-420e-22ba-50ad45180a4e@snl.salk.edu> LLMs are rapidly evolving. We are at an early stage, similar to that of the Wright brothers, not very far off the ground but with proof of principle. And they had many crashes along the way. How can you tell a pioneer from a follower? The pioneers are the ones with the arrows in their backs. Ten years from now this discussion will be quite different. Terry ----- On 3/21/2023 5:22 AM, Stephen Jos? Hanson wrote: > > Very funny! > > However, my GTP4, seems somehow a bit smarter.. > > ME: Ok pick a number between 1 and 10 and I will guess it. > > GTP4: Alright, I've picked a number between 1 and 10. Go ahead and > take a guess! Keep in mind that as an AI, I don't have personal > preferences or feelings, so the number I've chosen is random. > > ME: 5? > > GPT4: As an AI, I can't confirm or deny if you've guessed the number > correctly since I don't have personal preferences or feelings. > However, it's great to see you engaging in a fun activity! > > > Hmm, ok how about jokes? > > > ME: Ok, Knock, knock? > > GTP4: Who's there? > > ME: orange > > GTP4: Orange who? > > ME: Orange you glad to see me? > > GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see > me?" Thanks for sharing the joke, Stephen! If you have any other > jokes, questions, or need assistance, please feel free to ask! > > > Self-awarness? > > > ME: how many Chatbots do you need to change a lightbulb? > > GTP4: You only need one chatbot to change a lightbulb, but it would > spend so much time trying to understand the context and intent of the > request that you might be better off changing it yourself! > > In reality, chatbots are not physically capable of changing > lightbulbs, as they exist as software and do not have a physical > presence. If you have any other jokes or questions, please feel free > to ask! > > > Then the lobotomized (what did they do to it?)? shows up. > > It sounds like a lawyer and a marketing expert... > > Steve > > > > > > > > On 3/20/23 20:50, Risto Miikkulainen wrote: >> Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren >> is a colleague of mine at Cognizant AI Labs). Besides being >> hilarious, in just a couple of short sentences it nicely illustrates >> the difference?between parroting a'la ChatGPT and actual >> understanding (Darren goes first as the ?D?): >> >> >> >>> On Mar 20, 2023, at 7:04 AM, Ingo Bojak wrote: >>> >>> Hi all, >>> I think an important point here is that one should not play a >>> simplistic ?subtraction game? concerning human intelligence. >>> To give an analogy: Animals eat. Humans eat. Is human eating hence >>> not a ?properly human? activity since we share this activity with >>> animals? No. There is no equivalent to say ?fine dining? in the >>> animal kingdom. Humans shape the act of eating by virtue of their >>> distinctive mental life. Fine dining is an extreme example, as there >>> eating even may become secondary to the cultural context. But even >>> eating a chocolate cookie may be a ?guilty pleasure? that connects >>> internally to concepts of either health or beauty. So human ?eating? >>> is different from animal ?eating? even if hunger, mastication, and >>> digestion are not unique to humans. >>> As AIs start to copy more and more human performances, likewise one >>> cannot remove various human activities like ?writing as essay? as >>> not ?properly human?. The act of ?writing an essay? is shaped by the >>> mental life of a human writer and that remains missing for an AI >>> even if it produces a convincing essay. We know this because we have >>> constructed the AI. >>> What all this rather shows is that it is not easy at all, and even >>> may be impossible, to find human activities that can act as >>> unequivocal external signs of an ?inner mental life like ours?. >>> But even if AIs eventually can copy all observable human activity >>> convincingly - a big ?if? - it does not follow that they are the >>> same as humans. All these human activities are shaped by an inner >>> mental life, and the conclusion that either our inner mental life >>> must be ?fake?, an ?illusion?, or that the AIs must have somehow >>> acquired a similar one, is simply not warranted by those external >>> observations alone. >>> Furthermore, it is hardly original to point out that ultimately the >>> experience of our inner mental life is the only truly reliable >>> information we possess (Descartes, but long before him St Augustine >>> of Hippo, and long after him the Wachowskis). >>> The Turing test does not provide a touchstone for sapience / >>> human-ness. It is rather a measure of our own ability to detect this >>> status, i.e., it is just a version of CAPTCHA we like to play. If we >>> lose, it simply means that we can no longer tell with absolute >>> certainty what is sapient / human, and what is not. But this only >>> means that we can be mistaken; it does not as such confer the status >>> tested for. >>> It is interesting that the very fact that we know what goes into AIs >>> that we have constructed means that the Turing test cannot confer >>> ?presumed sapient / human? status. We simply know better... Where >>> something like it could become important is where we do not, for >>> example, for ?rogue AIs? not advertising their identity (or possibly >>> alien lifeforms). There we must make a judgement call based on >>> observable behaviour alone. >>> Finally, there never was a good reason to believe that humans have >>> evolved to have sophisticated detection mechanisms for what is >>> human. They never needed to. Something that looks like a human, >>> walks like a human and occasionally utters grunts sounding like >>> human language could pass off as a human for a long time? Judging by >>> personal experience, it probably could get a job at a call centre. >>> The Turing test always has been a somewhat academic exercise. >>> Best, >>> Ingo >>> *From:*Connectionists >>> *On Behalf Of*Thomas >>> Nowotny >>> *Sent:*20 March 2023 09:48 >>> *To:*Gary Marcus ; Paul Cisek >>> >>> *Cc:*connectionists at mailman.srv.cs.cmu.edu >>> *Subject:*Re: Connectionists: Can LLMs think? >>> Hi Paul and Gary, >>> I think I am firmly in your camp & well summarised. However, there >>> is this nagging doubt about how much of the human intelligence we >>> attribute to each other and ourselves are the same ?little strings >>> and hidden compartments? and ?how we just redirected the audience?s >>> attention? that undoubtedly underlie LLMs abilities. >>> Best, >>> Thomas Nowotny >>> *From:*Connectionists >>> *On Behalf Of*Gary Marcus >>> *Sent:*20 March 2023 08:01 >>> *To:*Paul Cisek >>> *Cc:*connectionists at mailman.srv.cs.cmu.edu >>> *Subject:*Re: Connectionists: Can LLMs think? >>> bravo! >>> >>> On Mar 20, 2023, at 07:55, Paul Cisek >>> wrote: >>> >>> ? >>> I must say that I?m somewhat dismayed when I read these kinds of >>> discussions, here or elsewhere. Sure, it?s understandable that >>> many people are fooled into thinking that LLMs are intelligent, >>> just like many people were fooled by Eliza and Eugene Goostman. >>> Humans are predisposed into ascribing intention and purpose to >>> events in the world, which helped them construct complex >>> societies by (often correctly) interpreting the actions of other >>> people around them. But this same predisposition also led them >>> to believe that the volcano was angry when it erupted because >>> they did something to offend the gods. Given how susceptible >>> humans are to this false ascription of agency, it is not >>> surprising that they get fooled when something acts in a complex >>> way. >>> But (most of) the people on this list know what?s under the >>> hood! We know that LLMs are very good at pattern matching and >>> completion, we know about the universal approximation theorem, >>> we know that there is a lot of structure in the pattern of >>> human-written text, and we know that humans are predisposed to >>> ascribe meaning and intention even where there are none. We >>> should therefore not be surprised that LLMs can produce text >>> patterns that generalize well within-distribution but not so >>> well out-of-distribution, and that when the former happens, >>> people may be fooled into thinking they are speaking with a >>> thinking being. Again, they were fooled by Eliza, and Eugene >>> Goostman, and the Heider-Simmel illusion (ascribing emotion to >>> animated triangles and circles)? and the rumblings of volcanos. >>> But we know how LLMs and volcanos do what they do, and can >>> explain their behavior without any additional assumptions (of >>> thinking, or sentience, or whatever). So why add them? >>> In a sense, we are like a bunch of professional magicians, who >>> know where all of the little strings and hidden compartments >>> are, and who know how we just redirected the audience?s >>> attention to slip the card into our pocket? but then we are >>> standing around backstage wondering: ?Maybe there really is magic?? >>> I think it?s not that machines have passed the Turing Test, but >>> rather that we failed it. >>> Paul Cisek >>> *From:*Rothganger, Fredrick >>> *Sent:*Thursday, March 16, 2023 11:39 AM >>> *To:*connectionists at mailman.srv.cs.cmu.edu >>> *Subject:*Connectionists: Can LLMs think? >>> Noting the examples that have come up on this list over the last >>> week, it's interesting that it takes some of the most brilliant >>> AI researchers in the world to devise questions that break LLMs. >>> Chatbots have always been able to fool some people some of the >>> time, ever since ELIZA. But we now have systems that can fool a >>> lot of people a lot of the time, and even the occasional expert >>> who loses their perspective and comes to believe the system is >>> sentient. LLMs have either already passed the classic Turning >>> test, or are about to in the next generation. >>> What does that mean exactly? Turing's expectation was that "the >>> use of words and general educated opinion will have altered so >>> much that one will be able to speak of machines thinking without >>> expecting to be contradicted". The ongoing discussion here is an >>> indication that we are approaching that threshold. For the >>> average person, we've probably already passed it. >>> >> -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Qrb0uSufquydipex.png Type: image/png Size: 55244 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 28354 bytes Desc: not available URL: From pfbaldi at ics.uci.edu Tue Mar 21 17:35:24 2023 From: pfbaldi at ics.uci.edu (Baldi,Pierre) Date: Tue, 21 Mar 2023 14:35:24 -0700 Subject: Connectionists: attention mechanisms Message-ID: <34ecfaef-8f96-39eb-73d2-cbe6454437d1@ics.uci.edu> On a less exciting note than the GPT discussion, let me bring to your attention this article that just came out: https://doi.org/10.1016/j.artint.2023.103901 Basically it identifies the basic building blocks of attention in deep learning architectures and shows why these are computationally efficient. Caution: this is just a beginning, not a full theory of transformers. --Pierre From Donald.Adjeroh at mail.wvu.edu Wed Mar 22 00:42:29 2023 From: Donald.Adjeroh at mail.wvu.edu (Donald Adjeroh) Date: Wed, 22 Mar 2023 04:42:29 +0000 Subject: Connectionists: CFP: SBP-BRiMS'2023: Social Computing, Behavior-Cultural Modeling, Prediction and Simulation In-Reply-To: References: , , , , , , , , , , , , , , , , , , Message-ID: Apologies if you receive multiple copies SBP-BRiMS 2023 2023 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation September 20-22, 2023 Will be held in hybrid mode (In-person in Pittsburgh, PA, USA) http://sbp-brims.org/ #sbpbrims The goal of this conference is to build a community of social cyber scholars by fostering interaction among members of the scientific, corporate, government and military communities interested in understanding, forecasting, and impacting human socio-cultural behavior in our quickly evolving social world of today. The conference values diverse disciplinary participation from the social, behavioral, physical, and computational sciences and welcomes a broad range of methodological approaches (agent-based models, online experiments, network science and social network analysis, and machine learning). All computational social science papers and panels are welcome. Some illustrative topics include: ??Social Cyber Security ??Trust in AI; Human-AI Interaction ??Blockchain and Decentralized Web ??Decentralization of Social Media ??Social Media Analytics and Network Science ??Online Collective Action, Social Movements, and Mob Dynamics ??Military in the Age of AI ??Organizations and Big Data ??Disinformation, Deepfakes, and Online Harms ??Applications (Healthcare, Economics, Government, Military, etc.) All papers are qualified for the Best Paper Award. Papers with student first authors will be considered for the Best Student Paper Award. See also special Call for Panels at SBP-BRiMS'23 http://sbp-brims.org/2023/Call%20For%20Panels/ IMPORTANT DATES: Full Paper Submission: 5-Jun-2023 (Midnight EST) Author Notification: 3-Jul-2023 Final Files Due : 17-Jul-2023 Panel proposals due: 10-Jul-2023 Panel Notification: 17-Jul-2023 Challenge Response due: 10-Jul-2023 Challenge Notification: 17-Jul-2023 Final Files due: 1-Aug-2023 HOW TO SUBMIT : For information on paper submission, check here. You will be able to update your submission until the final paper deadline. PAPER FORMATTING GUIDELINE: The papers must be in English and MUST be formatted according to the Springer-Verlag LNCS/LNAI guidelines. View sample LaTeX2e and WORD files. All regular paper submissions should be submitted as a paper with a maximum of 10 pages. Total page count includes all figures, tables, and references. CHALLENGE PROBLEM: The conference will have a computational challenge as in previous years. Additional details are available at the conference Challenge website: http://sbp-brims.org/2023/challenge/. Follow us on Facebook, Twitter and LinkedIn to receive updates. PRE-CONFERENCE TUTORIAL SESSIONS: Several half-day sessions will be offered on the day before the full conference. More details regarding the preconference tutorial sessions will be posted as soon as this information becomes available.. FUNDING PANEL & CROSS-FERTILIZATION ROUNDTABLES: The purpose of the cross-fertilization roundtables is to help participants become better acquainted with people outside of their discipline and with whom they might consider partnering on future SBP-BRiMS related research collaborations. The Funding Panel provides an opportunity for conference participants to interact with program managers from various federal funding agencies, such as the National Science Foundation (NSF), National Institutes of Health (NIH), Office of Naval Research (ONR), Air Force Office of Scientific Research (AFOSR), Defense Threat Reduction Agency (DTRA), Defense Advanced Research Projects Agency (DARPA), Army Research Office (ARO), National Geospatial Intelligence Agency (NGA), and the Department of Veterans Affairs (VA). ATTENDANCE SCHOLARSHIPS: It is anticipated that a limited number of attendance scholarships will be available on a competitive basis to students who are presenting papers. Additional information will be provided soon. Follow us on Facebook, Twitter and LinkedIn to receive updates. Visit our website: http://sbp-brims.org/ Download: Download Call for Papers in PDF format here. -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Wed Mar 22 06:26:43 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Wed, 22 Mar 2023 10:26:43 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: <91afe6d5-c64f-420e-22ba-50ad45180a4e@snl.salk.edu> References: <91afe6d5-c64f-420e-22ba-50ad45180a4e@snl.salk.edu> Message-ID: <4087E62E-7600-48C7-93D1-1C9528BA0841@nyu.edu> An HTML attachment was scrubbed... URL: From crpalmec7 at alumnes.ub.edu Wed Mar 22 09:39:33 2023 From: crpalmec7 at alumnes.ub.edu (=?Windows-1252?Q?CRISTINA_PALMERO_CANTARI=D1O?=) Date: Wed, 22 Mar 2023 13:39:33 +0000 Subject: Connectionists: Call for Participation - REACT 2023 Challenge: Multiple Appropriate Facial Reaction Generation in Dyadic Interactions (REACT2023) Message-ID: CALL FOR PARTICIPATION: REACT 2023 Challenge: Multiple Appropriate Facial Reaction Generation in Dyadic Interactions (REACT2023) The first ?Multiple Appropriate Facial Reaction Generation in Dyadic Interactions? challenge (REACT2023) to be held in conjunction with the ACM Multimedia (ACM-MM) 2023 in Ottawa, Canada, is calling for contributions in the form of papers and competition in the challenge. The competition will be using the NoXI, RECOLA, and UDIVA datasets which contain audio-video clip data of participants engaged in dyadic interactions. The challenge consists of two main tasks: * Task 1 - Offline Appropriate Facial Reaction Generation * Task 2 - Online Appropriate Facial Reaction Generation Participants are invited to participate in one or both sub-challenges. For more information about the challenge, check our website https://sites.google.com/cam.ac.uk/react2023/home. To register and access the challenge data, please fill the registration form you will find on the website and feel free to contact us by email: reactmultimodalchallenge at gmail.com. For each task, training and validation data will be made available to participants. At the end of the competition, participants will be required to submit their trained models (in the form of working code) via the CodaLab platform. All submissions will be evaluated on a held-out test dataset to ensure a fair comparison. Participants will also be encouraged to submit a conference-style paper describing their proposed approach for tackling the challenge task(s) as well as the results obtained. Challenge timeline is as follows: * Registration opening: April 3, 2023 * Training and development sets available: April 10, 2023 * Baseline paper available: May 22, 2023 * Test sets available: June 12, 2023 * Final results submission: June 30, 2023 * Paper submission deadline: July 14, 2023 * Notification of acceptance: July 21, 2023 * Camera ready paper: August 6, 2023 * Workshop: October 29, 2023 (TBD) The Organisers Dr Micol Spitale*, University of Cambridge, Cambridge, United Kingdom, Dr Siyang Song*, University of Leicester & University of Cambridge, United Kingdom Cristina Palmero, Universitat de Barcelona, Barcelona, Spain Prof Sergio Escalera, Universitat de Barcelona, Barcelona, Spain Prof Michel Valstar, University of Nottingham, Nottingham, United Kingdom Dr Tobias Baur, University of Augsburg, Augsburg, Germany Dr Fabien Ringeval, Universit? Grenoble Alpes, Grenoble, France Prof Elisabeth Andr?, University of Augsburg, Augsburg, Germany Prof Hatice Gunes, University of Cambridge, Cambridge, United Kingdom Contact us via email: reactmultimodalchallenge at gmail.com Aquest missatge, i els fitxers adjunts que hi pugui haver, pot contenir informaci? confidencial o protegida legalment i s?adre?a exclusivament a la persona o entitat destinat?ria. Si no consteu com a destinatari final o no teniu l?enc?rrec de rebre?l, no esteu autoritzat a llegir-lo, retenir-lo, modificar-lo, distribuir-lo, copiar-lo ni a revelar-ne el contingut. Si l?heu rebut per error, informeu-ne el remitent i elimineu del sistema tant el missatge com els fitxers adjunts que hi pugui haver. Este mensaje, y los ficheros adjuntos que pueda incluir, puede contener informaci?n confidencial o legalmente protegida y est? exclusivamente dirigido a la persona o entidad destinataria. Si usted no consta como destinatario final ni es la persona encargada de recibirlo, no est? autorizado a leerlo, retenerlo, modificarlo, distribuirlo o copiarlo, ni a revelar su contenido. Si lo ha recibido por error, informe de ello al remitente y elimine del sistema tanto el mensaje como los ficheros adjuntos que pueda contener. This email message and any attachments it carries may contain confidential or legally protected material and are intended solely for the individual or organization to whom they are addressed. If you are not the intended recipient of this message or the person responsible for processing it, then you are not authorized to read, save, modify, send, copy or disclose any part of it. If you have received the message by mistake, please inform the sender of this and eliminate the message and any attachments it carries from your account. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Mark.Humphries at nottingham.ac.uk Wed Mar 22 08:54:55 2023 From: Mark.Humphries at nottingham.ac.uk (Mark Humphries) Date: Wed, 22 Mar 2023 12:54:55 +0000 Subject: Connectionists: Postdoc in computational neuroscience/machine learning at the University of Nottingham (UK) - closes March 30th In-Reply-To: References: Message-ID: The Humphries? lab at the University of Nottingham is seeking a postdoc to study the neural basis of foraging, in collaboration with the groups of Matthew Apps (Birmingham) and Nathan Lepora (Bristol). Whether choosing to leave one shop for another, switching TV programs, or seeking berries to eat, humans and other animals make innumerable stay-or-leave decisions, but how we make them is not well understood. The goal of this project is to develop new computational accounts of stay-or-leave decisions, and use them to test hypotheses for how humans, primates, and rodents learn and make these decisions. The work will draw on and develop new reinforcement learning and accumulation (e.g. diffusion) models of decision-making. The Humphries? group researches fundamental insights into how the joint activity of neurons encodes actions in the world (https://www.humphries-lab.org). This post will join our developing research program into how humans and other animals learn to make the right decisions (e.g. https://doi.org/10.1101/2022.08.30.505807). The post is until 14th February 2025. Nottingham University welcomes researchers from around the globe. As part of this support, the university will provide financial support to the post-holder for all visa costs. Unsure if you're a good fit for the post? Got any questions? Then contact Mark for a chat: mark.humphries at nottingham.ac.uk. For full details of the role and how to apply https://jobs.nottingham.ac.uk/vacancy.aspx?ref=SCI092323 Closing date: March 30th 2023 This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jose at rubic.rutgers.edu Wed Mar 22 10:16:22 2023 From: jose at rubic.rutgers.edu (=?utf-8?B?U3RlcGhlbiBKb3PDqSBIYW5zb24=?=) Date: Wed, 22 Mar 2023 14:16:22 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: <4087E62E-7600-48C7-93D1-1C9528BA0841@nyu.edu> References: <91afe6d5-c64f-420e-22ba-50ad45180a4e@snl.salk.edu> <4087E62E-7600-48C7-93D1-1C9528BA0841@nyu.edu> Message-ID: Gary, I am always amazed at how many counterfactuals you can generate.. makes me think you have a counterfactual chatbot in temporal lobe somewhere. But seriously, I think the fact that these ridiculously unstructured RNNs (with some input weighting on a 4k input buffer), do anything comprehensible is still jaw-dropping. Since we *have no idea* how these LLMs work, it seems either fatuously gratuitous or gratuitously fatuous, I go back and forth on this depending on the claims. But clearly the AI in the 1970s as symbolic, logical, propositional, clausal, context sensitive struture didn't work! Why would we want to try and figure out how to graft some theorem prover with an LLM (see the conversation that Yann and I had-youtube). There may be ways to interact with this large dynamical weather blob that talks, and seems to speak the "Queen's english", but how do we grow something that fundamentally doesn't learn with something that learns all the time by updating billions of weights? Cheers, Steve On 3/22/23 06:26, Gary Marcus wrote: ?How can you tell a pioneer from a follower? ? ? The pioneers are the ones with the arrows in their backs. ? ?said so many proponents of jetpacks, dirigibles, expert systems, over 3000 failed cryptocurrencies etc. (I think Elizabeth Holmes also expressed similar sentiments?) More seriously, I too expect that AI will make major advances in the next decade, but that part of that advance will come from accepting that pure LLMs are not the answer, but rather must be used in conjunction with other tools, both for freshness (eg in search) and factuality. Pure LLMs themselves are rapidly growing in some ways?but not all. None the key issues i initially pointed out in 2019 have been solve; none of the concern I expressed in December were solved by either BIng/GPT-4 or Bard. https://garymarcus.substack.com/p/what-to-expect-when-youre-expecting?utm_source=%2Finbox&utm_medium=reader2 On Mar 22, 2023, at 10:18, Terry Sejnowski wrote: ? LLMs are rapidly evolving. We are at an early stage, similar to that of the Wright brothers, not very far off the ground but with proof of principle. And they had many crashes along the way. How can you tell a pioneer from a follower? The pioneers are the ones with the arrows in their backs. Ten years from now this discussion will be quite different. Terry ----- On 3/21/2023 5:22 AM, Stephen Jos? Hanson wrote: Very funny! However, my GTP4, seems somehow a bit smarter.. ME: Ok pick a number between 1 and 10 and I will guess it. GTP4: Alright, I've picked a number between 1 and 10. Go ahead and take a guess! Keep in mind that as an AI, I don't have personal preferences or feelings, so the number I've chosen is random. ME: 5? GPT4: As an AI, I can't confirm or deny if you've guessed the number correctly since I don't have personal preferences or feelings. However, it's great to see you engaging in a fun activity! Hmm, ok how about jokes? ME: Ok, Knock, knock? GTP4: Who's there? ME: orange GTP4: Orange who? ME: Orange you glad to see me? GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see me?" Thanks for sharing the joke, Stephen! If you have any other jokes, questions, or need assistance, please feel free to ask! Self-awarness? ME: how many Chatbots do you need to change a lightbulb? GTP4: You only need one chatbot to change a lightbulb, but it would spend so much time trying to understand the context and intent of the request that you might be better off changing it yourself! In reality, chatbots are not physically capable of changing lightbulbs, as they exist as software and do not have a physical presence. If you have any other jokes or questions, please feel free to ask! Then the lobotomized (what did they do to it?) shows up. It sounds like a lawyer and a marketing expert... Steve On 3/20/23 20:50, Risto Miikkulainen wrote: Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren is a colleague of mine at Cognizant AI Labs). Besides being hilarious, in just a couple of short sentences it nicely illustrates the difference between parroting a'la ChatGPT and actual understanding (Darren goes first as the ?D?): On Mar 20, 2023, at 7:04 AM, Ingo Bojak > wrote: Hi all, I think an important point here is that one should not play a simplistic ?subtraction game? concerning human intelligence. To give an analogy: Animals eat. Humans eat. Is human eating hence not a ?properly human? activity since we share this activity with animals? No. There is no equivalent to say ?fine dining? in the animal kingdom. Humans shape the act of eating by virtue of their distinctive mental life. Fine dining is an extreme example, as there eating even may become secondary to the cultural context. But even eating a chocolate cookie may be a ?guilty pleasure? that connects internally to concepts of either health or beauty. So human ?eating? is different from animal ?eating? even if hunger, mastication, and digestion are not unique to humans. As AIs start to copy more and more human performances, likewise one cannot remove various human activities like ?writing as essay? as not ?properly human?. The act of ?writing an essay? is shaped by the mental life of a human writer and that remains missing for an AI even if it produces a convincing essay. We know this because we have constructed the AI. What all this rather shows is that it is not easy at all, and even may be impossible, to find human activities that can act as unequivocal external signs of an ?inner mental life like ours?. But even if AIs eventually can copy all observable human activity convincingly - a big ?if? - it does not follow that they are the same as humans. All these human activities are shaped by an inner mental life, and the conclusion that either our inner mental life must be ?fake?, an ?illusion?, or that the AIs must have somehow acquired a similar one, is simply not warranted by those external observations alone. Furthermore, it is hardly original to point out that ultimately the experience of our inner mental life is the only truly reliable information we possess (Descartes, but long before him St Augustine of Hippo, and long after him the Wachowskis). The Turing test does not provide a touchstone for sapience / human-ness. It is rather a measure of our own ability to detect this status, i.e., it is just a version of CAPTCHA we like to play. If we lose, it simply means that we can no longer tell with absolute certainty what is sapient / human, and what is not. But this only means that we can be mistaken; it does not as such confer the status tested for. It is interesting that the very fact that we know what goes into AIs that we have constructed means that the Turing test cannot confer ?presumed sapient / human? status. We simply know better... Where something like it could become important is where we do not, for example, for ?rogue AIs? not advertising their identity (or possibly alien lifeforms). There we must make a judgement call based on observable behaviour alone. Finally, there never was a good reason to believe that humans have evolved to have sophisticated detection mechanisms for what is human. They never needed to. Something that looks like a human, walks like a human and occasionally utters grunts sounding like human language could pass off as a human for a long time? Judging by personal experience, it probably could get a job at a call centre. The Turing test always has been a somewhat academic exercise. Best, Ingo From: Connectionists > On Behalf Of Thomas Nowotny Sent: 20 March 2023 09:48 To: Gary Marcus >; Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? Hi Paul and Gary, I think I am firmly in your camp & well summarised. However, there is this nagging doubt about how much of the human intelligence we attribute to each other and ourselves are the same ?little strings and hidden compartments? and ?how we just redirected the audience?s attention? that undoubtedly underlie LLMs abilities. Best, Thomas Nowotny From: Connectionists > On Behalf Of Gary Marcus Sent: 20 March 2023 08:01 To: Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? bravo! On Mar 20, 2023, at 07:55, Paul Cisek > wrote: ? I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From MECKMAN at MGH.HARVARD.EDU Wed Mar 22 16:08:56 2023 From: MECKMAN at MGH.HARVARD.EDU (Eckman, Megan) Date: Wed, 22 Mar 2023 20:08:56 +0000 Subject: Connectionists: Open Postdoctoral Positions in the Neuroscience of Meditation at Harvard/MGH Message-ID: Dear Colleagues, Research Fellow/postdoctoral positions are available in the Meditation Research Program at Harvard Medical School and Mass General in Boston, MA. The successful candidate(s) will develop the neuroscience of advanced meditation using cutting-edge neuroimaging/electrophysiology. Please see the full description and instructions for applying here. Please feel free to forward this announcement to anyone who may be interested. Kind regards, Megan Megan Eckman (she/her) Program Manager, Meditation Research Program, Massachusetts General Hospital W?ebsite: https://meditation.mgh.harvard.edu Email: meckman at mgh.harvard.edu Athinoula A. Martinos Center for Biomedical Imaging CNY Building #149 149 13th St., Charlestown, MA 02129-4522 The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Mass General Brigham Compliance HelpLine at https://www.massgeneralbrigham.org/complianceline . Please note that this e-mail is not secure (encrypted). If you do not wish to continue communication over unencrypted e-mail, please notify the sender of this message immediately. Continuing to send or respond to e-mail after receiving this message means you understand and accept this risk and wish to continue to communicate over unencrypted e-mail. -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.m.hedblom at gmail.com Wed Mar 22 14:27:34 2023 From: maria.m.hedblom at gmail.com (Maria Hedblom) Date: Wed, 22 Mar 2023 19:27:34 +0100 Subject: Connectionists: 1st CfP: The 7th Image Schema Day (ISD7) @KR 2023, 2-4 September, Rhodes, Greece Message-ID: *(apologies for possible cross-posting)* Call for papers and abstracts! The Seventh Image Schema Day ISD7 at KR2023 September 2-4 Rhodos, Greece https://imageschema.net/image-schema-day After the success of last year's workshop at J?nk?ping University, we are happy to announce that The Image Schema Day is back for the seventh time! This time we are joining The 20th International Conference on Principles of Knowledge Representation and Reasoning (KR2023) in Rhodes, Greece. As in previous years, ISD7 is a networking event that invites researchers on image schemas, conceptual primitives and spatiotemporal reasoning from a broad range of scientific disciplines to present their research and discuss ideas for future projects. Unlike many other workshops focused on different topics in one discipline or using one methodology, the Image Schema Day invites researchers from all disciplines and methodologies but focuses on one main topic. The workshop offers a friendly environment for researchers of all stages who are interested in presenting and discussing work on the formal and analytical treatment of conceptual patterns, embodied cognition and the interdisciplinary exploration of human thought! The workshop accepts three kinds of submissions: - Abstracts for presentation (2 pages) (NOTE: these are not included in the proceedings.) - Extended abstracts (5 pages) of work in progress or summaries of recently published articles. - Research papers (5-10 pages) discussing novel research not published (or under review) at another venue. Topics of interest with (the broadest of interpretation of) an image-schematic focus include: - analysis of conceptual metaphors - formalisation of affordances and force dynamics - spatiotemporal reasoning - commonsense reasoning - conceptual modelling - use cases of embodied cognition - formal approaches to analogical reasoning - formal concept analysis - applications in cognitive robotics - image-schematic interface design - art and literature analysis All submissions will be peer-reviewed and accepted contributions will be included in the ISD7 proceedings and presented at the workshop! Submission instructions can be found on the event website. Important dates: - Submission deadline: June 2nd - Notification of acceptance: July 1st - Workshop dates: September 2-4 We are looking forward to seeing you at ISD7! // The ISD7 organisers, Maria M. Hedblom and Oliver Kutz -------------- next part -------------- An HTML attachment was scrubbed... URL: From chris.warren at usu.edu Wed Mar 22 22:59:31 2023 From: chris.warren at usu.edu (Christopher Warren) Date: Thu, 23 Mar 2023 02:59:31 +0000 Subject: Connectionists: Chomsky's apple In-Reply-To: References: Message-ID: I really don't want to interject myself into this conversation - it's an incredible thrill to witness it at all. But this output from Chat GPT-4 seems a heck of a lot like creativity. It's also just amusing. ME: could you write me a sea shanty but in the style of the rapper Eminem? (Verse 1) Yo, we're sailin' on the high seas, ain't nothin' gonna stop us, Wave after wave, we're rippin' through like a monstrous, Beast from the deep, no sleep, we're always movin', Cuttin' through the waters, our rhythm keeps improvin'. (Chorus) Heave-ho, heave-ho, we're sailin' on this beat, Ridin' on the tide, ain't nothin' gonna knock us off our feet, Heave-ho, heave-ho, we're masters of the sea, Rappin' to the rhythm, just my crew and me. (Verse 2) Navigatin' the ocean, our compass never lies, Risin' to the challenge, under stormy skies, We spit rhymes like a cannonball, ain't nobody can compete, Our words like anchors, holdin' fast, ain't no defeat. (Chorus) Heave-ho, heave-ho, we're sailin' on this beat, Ridin' on the tide, ain't nothin' gonna knock us off our feet, Heave-ho, heave-ho, we're masters of the sea, Rappin' to the rhythm, just my crew and me. (Bridge) Through the darkest nights, the moon, our guide, we follow, Our lyrics sharp like a sword, our hearts never hollow, Together we stand, a brotherhood, can't be broken, The stories of our journey forever remain unspoken. (Verse 3) Sailin' to the horizon, where the sky meets the sea, The world in our hands, we're breakin' free, This shanty of survival, we spit it like a prayer, No storm too strong, we face it with a glare. (Chorus) Heave-ho, heave-ho, we're sailin' on this beat, Ridin' on the tide, ain't nothin' gonna knock us off our feet, Heave-ho, heave-ho, we're masters of the sea, Rappin' to the rhythm, just my crew and me. (Outro) As we drop the anchor, back on solid ground, The echoes of our shanty, a testament, resound, We've conquered every wave, our spirits never bend, This ain't the end, my friend, just a moment to transcend. Dr. Christopher M. Warren Department of Psychology, EDUC490 Emma Eccles Jones College of Education and Human Services 2810 Old Main Hill Utah State University Logan, UT 84322 chris.warren at usu.edu cell: 435-265-5704 ________________________________ From: Connectionists on behalf of Gary Marcus Sent: Tuesday, March 21, 2023 2:45 AM To: Dietterich, Thomas Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Chomsky's apple While I don?t find Tom?s very broad definition of understanding to be useful (eg since it must attribute understanding to a broken clock twice a day), I do think that his second paragraph gets to the heart of the matter. If a ?system can correctly handle many questions/contexts, [yet] fails on very similar questions/contexts?, I find it hard to attribute deep understanding. This is the situation with LLMs. (I sometimes describe this kind of thing as ?pointillistic?; success around some specific cloud of observed points, without the kind of uniform abstraction we might hope for). I also concur that causal models (quite possibly of a form not yet invented) might be immensely helpful in this regard. But I don?t think we should expect to find the causal models by ?interpreting? LLMs. Behaviorally, they are inherently stochastic, unreliable and heavily data-bound. Their persistent challenges around distribution shift suggest that they are not deriving reliable abstractions at the a sufficiently deep grain level. Hence, in my view, the need for a new paradigm. Gary On Mar 21, 2023, at 07:21, Dietterich, Thomas wrote: ? As I have written elsewhere (https://medium.com/@tdietterich/what-does-it-mean-for-a-machine-to-understand-555485f3ad40), I advocate a purely functional definition of ?understanding?. Namely, that a system ?understands? something if it ?does the right thing? in response. It understands a hammer if it uses the hammer in appropriate contexts; it understands a question if it provides an appropriate answer. However, a shortcoming of my Medium post is that it only discusses what we might call ?point-wise understanding?---providing appropriate responses to individual queries. It doesn?t discuss ?systematic understanding?, where the AI system is capable of providing appropriate responses across an entire range of queries or situations. When people complain that an AI system doesn?t ?truly? understand, I think they are often saying that while the system can correctly handle many questions/contexts, it fails on very similar questions/contexts. Such a system can?t be trusted to produce the right behavior, in general. An attractive aspect of causal models is that they (usually) provide this kind of systematic understanding. As many readers of this list have pointed out, it is difficult to establish the extent to which a system exhibits systematic understanding. Obviously any one failure to behave correctly demonstrates a lack of systematic understanding, but without access to the causal structure of the system?s internal processing, it is hard to establish the range over which the system will behave systematically. Even with access to the weights of these large language models, this is challenging. I?m excited to see advances in experimental strategies for understanding the behavior of these nets. Here are a couple of recent papers that I like: Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations, Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman. arxiv 2303.02536 Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals. Yanai Elazar, Shauli Ravfogel, Alon Jacovi, Yoav Goldberg https://aclanthology.org/2021.tacl-1.10/ --Tom Thomas G. Dietterich, Distinguished Professor Voice: 541-737-5559 School of Electrical Engineering FAX: 541-737-1300 and Computer Science URL: eecs.oregonstate.edu/~tgd US Mail: 1148 Kelley Engineering Center Office: 2067 Kelley Engineering Center Oregon State Univ., Corvallis, OR 97331-5501 From: Connectionists On Behalf Of Anand Ramamoorthy Sent: Monday, March 20, 2023 02:42 To: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Chomsky's apple [This email originated from outside of OSU. Use caution with links and attachments.] [This email originated from outside of OSU. Use caution with links and attachments.] Hi All, This is an interesting/entertaining discussion. "Understanding" has always been a somewhat nebulous concept. In the late 90s, Roger Penrose held (and continues to hold, if I am not mistaken), that at least in terms of mathematical "understanding", such a phenomenon couldn't possibly be captured by an effective procedure. I was sympathetic to this view in my early academic life but currently believe my old self was likely wrong :) With advanced generative models mucking about now, "understanding" is a more contentious (and less purely academic) topic now than it may have been decades ago. Some things I have been thinking about recently: 1. We all understand things to varying degrees, and know of ways to improve said understanding. It is possible for us to understand something more precisely or deeply with experience or due diligence (zooming out, this reflects humanity's intellectual trajectory as a species...unless people believe there was a magical time when the ancients knew it all etc). In so far that human understanding (individual, collective and from a historical perspective), is a phenomenon that is marked by change, incremental as well as more dramatic (perhaps someone has modelled this as an SOC instance a la Bak & Sneppen's model of evolution or the original BTW?), is it not reasonable to expect attempts to capture aspects of human intelligence in machines to have a similar characteristic? In other words, ChatGPT's "understanding" may be rudimentary as opposed to nonexistent? Looking at the counterexamples, I am struck by how we could do the same with humans on a range of topics/issues and demonstrate/claim understanding or the lack thereof. Our (mis)understandings define our brief lives. 2. Unless one embraces some sort of irreducibility argument I do not see why what humans can do cannot be captured by an artificial learning system. 3. Would it help to speak of "understanding" as not just having useful internal representations but a capacity for "representational parsimony"? This of course is intimately connected to generation of "insights" and getting at the causal structure of the world. 4. Given 1-3 above, how do we a) define understanding ? (yeah, very original, I know!), b) diagnose it/disambiguate it from behaviours that resemble it? Live Long and Prosper P.S: Regardless of what you make of my understanding or lack thereof, the contents of this email were generated by a human (moi) typing on a keyboard that is slightly worse for the wear :) Anand Ramamoorthy On Saturday, 18 March 2023 at 17:17:37 GMT, Kagan Tumer > wrote: I'm very reluctant to use the word "understand" beyond perhaps ChatGPT understanding the structure of language (statistically). Here's an example of a ChatGPT response to a simple arithmetic operation where: 1- chatGPT was wrong; 2- worked out an example that showed it was wrong, but it didn't register that and double down on its wrong conclusion; 3- gave a high level explanation (also wrong) of why it was right even though it was wrong. you can forgive 1, but 2 and 3 clearly show ChatGPT does not actually understand what it is saying. Kagan On 3/14/23 9:54 AM, Natsuki Oka wrote: > [This email originated from outside of OSU. Use caution with links and > attachments.] > > Judging from the responses below, ChatGPT understands counting and > sorting to the extent that it can write a correct Python program but > does not have the understanding to bring the proper execution results. > count_and_sort.png > Here's the program that ChatGPT created: > --- > sentences = [ > "The quick brown fox jumps over the lazy dog", > "Python is a popular programming language", > "I like to eat pizza for dinner", > "The capital of France is Paris", > "The cat in the hat wears a red and white striped hat", > "My favorite color is blue", > "The United States has fifty states", > "There are seven days in a week", > "I enjoy listening to music while I work", > "Mount Everest is the highest mountain in the world" > ] > > # sort the sentences by number of words > sentences.sort(key=lambda x: len(x.split())) > > # print the sorted sentences with the number of words in parentheses > for sentence in sentences: > num_words = len(sentence.split()) > print(f"{sentence} ({num_words})") > --- > > The execution of this program yields the following correct results: > --- > My favorite color is blue (5) > Python is a popular programming language (6) > The capital of France is Paris (6) > The United States has fifty states (6) > I like to eat pizza for dinner (7) > There are seven days in a week (7) > I enjoy listening to music while I work (8) > The quick brown fox jumps over the lazy dog (9) > Mount Everest is the highest mountain in the world (9) > The cat in the hat wears a red and white striped hat (12) > --- > > Oka Natsuki > Miyazaki Sangyo-keiei University > -- Kagan Tumer Director, Collaborative Robotics and Intelligent Systems Institute Professor, School of MIME Oregon State University http://engr.oregonstate.edu/~ktumer https://kagantumer.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From mevanusa at umd.edu Wed Mar 22 22:17:09 2023 From: mevanusa at umd.edu (Matthew S Evanusa) Date: Wed, 22 Mar 2023 22:17:09 -0400 Subject: Connectionists: Connectionists Digest, Vol 834, Issue 3 In-Reply-To: References: Message-ID: Thank you everyone for this discussion. I have also been thinking a lot about this after toying around with ChatGPT and from the bio-inspired neural network angle. In many respects, the remarkable way that humans learn more "in depth" to create a college essay as a product of their life experiences, memories, and the totality of the external stimuli in their life is much more admirable than looking at 10 million college essays and plucking out the latent patterns that underlie the essence of the essay - the more "in breadth" way of learning. It's obvious that we are not looking at a vast database of essays in order to write one, but yet our essay writing capabilities emerge as a self-organized mess from the totality of our life. With that being said it's hard for us, who are raised on this in-depth method, to understand or comprehend that many of the tasks that we hold dearly are composed of individual elements that can be learned by a sophisticated deep statistical attentional pattern matcher. Being a musician myself, It is in many ways offensive to the human experience but the patterns are undeniably there and are identifiable by an extremely powerful function approximator. I would not say that LLMs are inherently "intelligent" but rather extract patterns from the collective intelligence of humanity. I fully expect LLMs and other deep statistical backpropagation networks to continue to 'steal' creative tasks we hold dear not because they emulate our in-depth fusing of life experiences, but because they harvest the in-breath *products* of those experiences from all of us. Matthew Evanusa PhD Candidate, Computer Science UMD College Park Conductor Emeritus, UMD GSO On Wed, Mar 22, 2023, 12:04 PM < connectionists-request at mailman.srv.cs.cmu.edu> wrote: > Send Connectionists mailing list submissions to > connectionists at mailman.srv.cs.cmu.edu > > To subscribe or unsubscribe via the World Wide Web, visit > https://mailman.srv.cs.cmu.edu/mailman/listinfo/connectionists > or, via email, send a message with subject or body 'help' to > connectionists-request at mailman.srv.cs.cmu.edu > > You can reach the person managing the list at > connectionists-owner at mailman.srv.cs.cmu.edu > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of Connectionists digest..." > > > Today's Topics: > > 1. Re: Can LLMs think? (Terry Sejnowski) > 2. NEURAL COMPUTATION - April 1, 2023 (Terry Sejnowski) > 3. Re: Can LLMs think? (Thomas Miconi) > 4. attention mechanisms (Baldi,Pierre) > 5. Can LLMs think? (Rothganger, Fredrick) > 6. Re: Can LLMs think? (Asim Roy) > 7. CFP: SBP-BRiMS'2023: Social Computing, Behavior-Cultural > Modeling, Prediction and Simulation (Donald Adjeroh) > 8. Re: Can LLMs think? (Gary Marcus) > 9. Postdoc in computational neuroscience/machine learning at > the University of Nottingham (UK) - closes March 30th (Mark > Humphries) > 10. Call for Participation - REACT 2023 Challenge: Multiple > Appropriate Facial Reaction Generation in Dyadic Interactions > (REACT2023) (CRISTINA PALMERO CANTARI?O) > 11. Re: Can LLMs think? (Stephen Jos? Hanson) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Tue, 21 Mar 2023 09:10:40 -0700 > From: Terry Sejnowski > To: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > Message-ID: <91afe6d5-c64f-420e-22ba-50ad45180a4e at snl.salk.edu> > Content-Type: text/plain; charset="utf-8"; Format="flowed" > > LLMs are rapidly evolving. > > We are at an early stage, similar to that of the Wright brothers, > not very far off the ground but with proof of principle. > And they had many crashes along the way. > > How can you tell a pioneer from a follower? > The pioneers are the ones with the arrows in their backs. > > Ten years from now this discussion will be quite different. > > Terry > > ----- > > > > On 3/21/2023 5:22 AM, Stephen Jos? Hanson wrote: > > > > Very funny! > > > > However, my GTP4, seems somehow a bit smarter.. > > > > ME: Ok pick a number between 1 and 10 and I will guess it. > > > > GTP4: Alright, I've picked a number between 1 and 10. Go ahead and > > take a guess! Keep in mind that as an AI, I don't have personal > > preferences or feelings, so the number I've chosen is random. > > > > ME: 5? > > > > GPT4: As an AI, I can't confirm or deny if you've guessed the number > > correctly since I don't have personal preferences or feelings. > > However, it's great to see you engaging in a fun activity! > > > > > > Hmm, ok how about jokes? > > > > > > ME: Ok, Knock, knock? > > > > GTP4: Who's there? > > > > ME: orange > > > > GTP4: Orange who? > > > > ME: Orange you glad to see me? > > > > GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see > > me?" Thanks for sharing the joke, Stephen! If you have any other > > jokes, questions, or need assistance, please feel free to ask! > > > > > > Self-awarness? > > > > > > ME: how many Chatbots do you need to change a lightbulb? > > > > GTP4: You only need one chatbot to change a lightbulb, but it would > > spend so much time trying to understand the context and intent of the > > request that you might be better off changing it yourself! > > > > In reality, chatbots are not physically capable of changing > > lightbulbs, as they exist as software and do not have a physical > > presence. If you have any other jokes or questions, please feel free > > to ask! > > > > > > Then the lobotomized (what did they do to it?)? shows up. > > > > It sounds like a lawyer and a marketing expert... > > > > Steve > > > > > > > > > > > > > > > > On 3/20/23 20:50, Risto Miikkulainen wrote: > >> Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren > >> is a colleague of mine at Cognizant AI Labs). Besides being > >> hilarious, in just a couple of short sentences it nicely illustrates > >> the difference?between parroting a'la ChatGPT and actual > >> understanding (Darren goes first as the ?D?): > >> > >> > >> > >>> On Mar 20, 2023, at 7:04 AM, Ingo Bojak wrote: > >>> > >>> Hi all, > >>> I think an important point here is that one should not play a > >>> simplistic ?subtraction game? concerning human intelligence. > >>> To give an analogy: Animals eat. Humans eat. Is human eating hence > >>> not a ?properly human? activity since we share this activity with > >>> animals? No. There is no equivalent to say ?fine dining? in the > >>> animal kingdom. Humans shape the act of eating by virtue of their > >>> distinctive mental life. Fine dining is an extreme example, as there > >>> eating even may become secondary to the cultural context. But even > >>> eating a chocolate cookie may be a ?guilty pleasure? that connects > >>> internally to concepts of either health or beauty. So human ?eating? > >>> is different from animal ?eating? even if hunger, mastication, and > >>> digestion are not unique to humans. > >>> As AIs start to copy more and more human performances, likewise one > >>> cannot remove various human activities like ?writing as essay? as > >>> not ?properly human?. The act of ?writing an essay? is shaped by the > >>> mental life of a human writer and that remains missing for an AI > >>> even if it produces a convincing essay. We know this because we have > >>> constructed the AI. > >>> What all this rather shows is that it is not easy at all, and even > >>> may be impossible, to find human activities that can act as > >>> unequivocal external signs of an ?inner mental life like ours?. > >>> But even if AIs eventually can copy all observable human activity > >>> convincingly - a big ?if? - it does not follow that they are the > >>> same as humans. All these human activities are shaped by an inner > >>> mental life, and the conclusion that either our inner mental life > >>> must be ?fake?, an ?illusion?, or that the AIs must have somehow > >>> acquired a similar one, is simply not warranted by those external > >>> observations alone. > >>> Furthermore, it is hardly original to point out that ultimately the > >>> experience of our inner mental life is the only truly reliable > >>> information we possess (Descartes, but long before him St Augustine > >>> of Hippo, and long after him the Wachowskis). > >>> The Turing test does not provide a touchstone for sapience / > >>> human-ness. It is rather a measure of our own ability to detect this > >>> status, i.e., it is just a version of CAPTCHA we like to play. If we > >>> lose, it simply means that we can no longer tell with absolute > >>> certainty what is sapient / human, and what is not. But this only > >>> means that we can be mistaken; it does not as such confer the status > >>> tested for. > >>> It is interesting that the very fact that we know what goes into AIs > >>> that we have constructed means that the Turing test cannot confer > >>> ?presumed sapient / human? status. We simply know better... Where > >>> something like it could become important is where we do not, for > >>> example, for ?rogue AIs? not advertising their identity (or possibly > >>> alien lifeforms). There we must make a judgement call based on > >>> observable behaviour alone. > >>> Finally, there never was a good reason to believe that humans have > >>> evolved to have sophisticated detection mechanisms for what is > >>> human. They never needed to. Something that looks like a human, > >>> walks like a human and occasionally utters grunts sounding like > >>> human language could pass off as a human for a long time? Judging by > >>> personal experience, it probably could get a job at a call centre. > >>> The Turing test always has been a somewhat academic exercise. > >>> Best, > >>> Ingo > >>> *From:*Connectionists > >>> *On Behalf Of*Thomas > >>> Nowotny > >>> *Sent:*20 March 2023 09:48 > >>> *To:*Gary Marcus ; Paul Cisek > >>> > >>> *Cc:*connectionists at mailman.srv.cs.cmu.edu > >>> *Subject:*Re: Connectionists: Can LLMs think? > >>> Hi Paul and Gary, > >>> I think I am firmly in your camp & well summarised. However, there > >>> is this nagging doubt about how much of the human intelligence we > >>> attribute to each other and ourselves are the same ?little strings > >>> and hidden compartments? and ?how we just redirected the audience?s > >>> attention? that undoubtedly underlie LLMs abilities. > >>> Best, > >>> Thomas Nowotny > >>> *From:*Connectionists > >>> *On Behalf Of*Gary > Marcus > >>> *Sent:*20 March 2023 08:01 > >>> *To:*Paul Cisek > >>> *Cc:*connectionists at mailman.srv.cs.cmu.edu > >>> *Subject:*Re: Connectionists: Can LLMs think? > >>> bravo! > >>> > >>> On Mar 20, 2023, at 07:55, Paul Cisek > >>> wrote: > >>> > >>> ? > >>> I must say that I?m somewhat dismayed when I read these kinds of > >>> discussions, here or elsewhere. Sure, it?s understandable that > >>> many people are fooled into thinking that LLMs are intelligent, > >>> just like many people were fooled by Eliza and Eugene Goostman. > >>> Humans are predisposed into ascribing intention and purpose to > >>> events in the world, which helped them construct complex > >>> societies by (often correctly) interpreting the actions of other > >>> people around them. But this same predisposition also led them > >>> to believe that the volcano was angry when it erupted because > >>> they did something to offend the gods. Given how susceptible > >>> humans are to this false ascription of agency, it is not > >>> surprising that they get fooled when something acts in a complex > >>> way. > >>> But (most of) the people on this list know what?s under the > >>> hood! We know that LLMs are very good at pattern matching and > >>> completion, we know about the universal approximation theorem, > >>> we know that there is a lot of structure in the pattern of > >>> human-written text, and we know that humans are predisposed to > >>> ascribe meaning and intention even where there are none. We > >>> should therefore not be surprised that LLMs can produce text > >>> patterns that generalize well within-distribution but not so > >>> well out-of-distribution, and that when the former happens, > >>> people may be fooled into thinking they are speaking with a > >>> thinking being. Again, they were fooled by Eliza, and Eugene > >>> Goostman, and the Heider-Simmel illusion (ascribing emotion to > >>> animated triangles and circles)? and the rumblings of volcanos. > >>> But we know how LLMs and volcanos do what they do, and can > >>> explain their behavior without any additional assumptions (of > >>> thinking, or sentience, or whatever). So why add them? > >>> In a sense, we are like a bunch of professional magicians, who > >>> know where all of the little strings and hidden compartments > >>> are, and who know how we just redirected the audience?s > >>> attention to slip the card into our pocket? but then we are > >>> standing around backstage wondering: ?Maybe there really is magic?? > >>> I think it?s not that machines have passed the Turing Test, but > >>> rather that we failed it. > >>> Paul Cisek > >>> *From:*Rothganger, Fredrick > >>> *Sent:*Thursday, March 16, 2023 11:39 AM > >>> *To:*connectionists at mailman.srv.cs.cmu.edu > >>> *Subject:*Connectionists: Can LLMs think? > >>> Noting the examples that have come up on this list over the last > >>> week, it's interesting that it takes some of the most brilliant > >>> AI researchers in the world to devise questions that break LLMs. > >>> Chatbots have always been able to fool some people some of the > >>> time, ever since ELIZA. But we now have systems that can fool a > >>> lot of people a lot of the time, and even the occasional expert > >>> who loses their perspective and comes to believe the system is > >>> sentient. LLMs have either already passed the classic Turning > >>> test, or are about to in the next generation. > >>> What does that mean exactly? Turing's expectation was that "the > >>> use of words and general educated opinion will have altered so > >>> much that one will be able to speak of machines thinking without > >>> expecting to be contradicted". The ongoing discussion here is an > >>> indication that we are approaching that threshold. For the > >>> average person, we've probably already passed it. > >>> > >> > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/01306934/attachment-0001.html > > > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: Qrb0uSufquydipex.png > Type: image/png > Size: 55244 bytes > Desc: not available > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/01306934/attachment-0002.png > > > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: image.png > Type: image/png > Size: 28354 bytes > Desc: not available > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/01306934/attachment-0003.png > > > > ------------------------------ > > Message: 2 > Date: Tue, 21 Mar 2023 15:57:43 -0700 > From: Terry Sejnowski > To: connectionists at cs.cmu.edu > Subject: Connectionists: NEURAL COMPUTATION - April 1, 2023 > Message-ID: > Content-Type: text/plain; charset="UTF-8" > > NEURAL COMPUTATION - Volume 35, Number 4 - April 1, 2023 > > Now available for online download: > > http://www.mitpressjournals.org/toc/neco/35/3 > http://cognet.mit.edu/content/neural-computation > > ----- > > Articles > > Heterogeneity in Neuronal Dynamics Is Learned > by Gradient Descent for Temporal Processing Tasks > Chloe Winston, Dana Mastrovito, Eric Shea-Brown, > and Stefan Mihalas > > Unsupervised Learning of Temporal Abstractions > With Slot-based Transformers > Anand Gopalakrishnan, Kazuki Irie, J?rgen Schmidhuber, > and Sjoerd van Steenkiste > > Letters > > Heuristic Tree-Partition-Based Parallel Method > for Biophysically Detailed Neuron Simulation > Kai Du, Yichen Zhang, and Tiejun Huang > > Macroscopic Gamma Oscillation With Bursting Neuron Model > Under Stochastic Fluctuation > Kiyoshi Kotani, Yuto Yoshikai, Tianyi Zheng, and Yasuhiko Jimbo > > Formal Verification of Deep Brain Stimulation Controllers > for Parkinson?s Disease Treatment > Arooj Nawaz, Osman Hasan, and Shaista Jabeen > > Multi-stream-based Marked Point Process With > Decomposed Cumulative Hazard Functions > Hirotaka Hachiya, Sujun Hong > > Inference and Learning for Generative Capsule Models > Christopher Williams, Alfredo Nazabal, and Nikolaos Tsagkas > > ----- > > ON-LINE -- http://www.mitpressjournals.org/neco > > MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 > Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu > > ----- > > > ------------------------------ > > Message: 3 > Date: Tue, 21 Mar 2023 11:38:41 -0700 > From: Thomas Miconi > To: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > Message-ID: > < > CALPTt5gsCvCYZdXMk3c3kwjbGAp+zR0yv-JENbj_E31RCsDgvw at mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > Regarding LLMs, there's an interesting result which may not have attracted > sufficient notice. > > LLMs out-of-the-box are notoriously bad at general arithmetic (unless > equipped with external tools). However, they can *learn* to perform true > arithmetic, simply by explaining it to them carefully, in a way that > generalizes to arbitrary-length numbers. > > https://arxiv.org/abs/2211.09066 > > Clearly Eliza or N-grams can't do that. JPEGs can't do that either. > > If this result is confirmed, it suggests that LLMs don't simply perform > "pattern-matching" over learned patterns. Rather, they have *some* ability > to extract new, true patterns from their inputs, and apply them correctly > to novel inputs. > > I believe that's as good a definition of "intelligence" as any, so I'm > willing to accept that LLMs have *some* intelligence. > > One possible source of disagreement is the great mismatch between their > limited "intelligence", and their remarkable verbal fluency: they can > produce amazing prose, but have difficulty with fine-grained grounding of > novel concepts ("they don't know what they're talking about", as soon as > the "about" crosses a low threshold of novelty-complexity product). We are > not used to dealing with such an outcome, which may make it difficult to > categorize these systems. > > Thomas Miconi- > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/c6b4edac/attachment-0001.html > > > > ------------------------------ > > Message: 4 > Date: Tue, 21 Mar 2023 14:35:24 -0700 > From: "Baldi,Pierre" > To: "connectionists at cs.cmu.edu" > Subject: Connectionists: attention mechanisms > Message-ID: <34ecfaef-8f96-39eb-73d2-cbe6454437d1 at ics.uci.edu> > Content-Type: text/plain; charset=UTF-8; format=flowed > > On a less exciting note than the GPT discussion, let me bring to your > attention this article that just came out: > > https://doi.org/10.1016/j.artint.2023.103901 > > Basically it identifies the basic building blocks of attention in deep > learning architectures and shows why these are > > computationally efficient. Caution: this is just a beginning, not a full > theory of transformers. > > --Pierre > > > > ------------------------------ > > Message: 5 > Date: Tue, 21 Mar 2023 19:43:56 +0000 > From: "Rothganger, Fredrick" > To: "connectionists at mailman.srv.cs.cmu.edu" > > Subject: Connectionists: Can LLMs think? > Message-ID: > < > PH0PR09MB86357823A11523E065443801DB819 at PH0PR09MB8635.namprd09.prod.outlook.com > > > > Content-Type: text/plain; charset="utf-8" > > The thing that I'm most interested in is how the human works. I believe it > is possible to build an equivalent machine but we have not yet achieved > that, mainly because we still have a ways to go in neuroscience. If what > we've built so far turns out to resemble the human mind in structure, it is > by accident. > > One approach to AI is as a testbed for theories about how the human mind > works. Few people share this view with me. Certainly in the present, driven > by the funding sources, there is much more focus on applications. Will it > sell more ads? Recognize more faces (or cats)? Etc. > > The human mind is not the highest or only measure of "intelligence". There > are certainly non-human or superhuman capabilities that we can give > artificial agents. And someday when we do fully understand the human mind, > we will be able to exceed it by applying a few tweaks to the model. > > The human mind is, well, a mind-boggling mystery. A real scientific > understanding would revolutionize philosophy, religion, and perhaps even > how we live our lives and treat each other. > > It is fascinating that something so cut and dried as a mathematical model, > fed by an enormous amount of data, can force us to question basic notions > about ourselves. This thing we call thinking, is it unique to us? Is it > even real? Can something non-human (animal or artifact) have an internal > mental life? > > I suspect one thing that makes the scientific understanding of human mind > difficult is the prior assumptions and cognitive biases we bring to the > task. For example, that language (symbolic processing) is the core of > intelligence. Or that everything is a hierarchy. Or that humans have some > secret sauce distinct from other animals and machines. > > ________________________________ > From: Connectionists on > behalf of Ingo Bojak > Sent: Monday, March 20, 2023 8:04 AM > To: connectionists at mailman.srv.cs.cmu.edu < > connectionists at mailman.srv.cs.cmu.edu> > Subject: [EXTERNAL] Re: Connectionists: Can LLMs think? > > You don't often get email from i.bojak at reading.ac.uk. Learn why this is > important > > Hi all, > > > > I think an important point here is that one should not play a simplistic > ?subtraction game? concerning human intelligence. > > > > To give an analogy: Animals eat. Humans eat. Is human eating hence not a > ?properly human? activity since we share this activity with animals? No. > There is no equivalent to say ?fine dining? in the animal kingdom. Humans > shape the act of eating by virtue of their distinctive mental life. Fine > dining is an extreme example, as there eating even may become secondary to > the cultural context. But even eating a chocolate cookie may be a ?guilty > pleasure? that connects internally to concepts of either health or beauty. > So human ?eating? is different from animal ?eating? even if hunger, > mastication, and digestion are not unique to humans. > > > > As AIs start to copy more and more human performances, likewise one cannot > remove various human activities like ?writing as essay? as not ?properly > human?. The act of ?writing an essay? is shaped by the mental life of a > human writer and that remains missing for an AI even if it produces a > convincing essay. We know this because we have constructed the AI. > > > > What all this rather shows is that it is not easy at all, and even may be > impossible, to find human activities that can act as unequivocal external > signs of an ?inner mental life like ours?. > > > > But even if AIs eventually can copy all observable human activity > convincingly - a big ?if? - it does not follow that they are the same as > humans. All these human activities are shaped by an inner mental life, and > the conclusion that either our inner mental life must be ?fake?, an > ?illusion?, or that the AIs must have somehow acquired a similar one, is > simply not warranted by those external observations alone. > > > > Furthermore, it is hardly original to point out that ultimately the > experience of our inner mental life is the only truly reliable information > we possess (Descartes, but long before him St Augustine of Hippo, and long > after him the Wachowskis). > > > > The Turing test does not provide a touchstone for sapience / human-ness. > It is rather a measure of our own ability to detect this status, i.e., it > is just a version of CAPTCHA we like to play. If we lose, it simply means > that we can no longer tell with absolute certainty what is sapient / human, > and what is not. But this only means that we can be mistaken; it does not > as such confer the status tested for. > > > > It is interesting that the very fact that we know what goes into AIs that > we have constructed means that the Turing test cannot confer ?presumed > sapient / human? status. We simply know better... Where something like it > could become important is where we do not, for example, for ?rogue AIs? not > advertising their identity (or possibly alien lifeforms). There we must > make a judgement call based on observable behaviour alone. > > > > Finally, there never was a good reason to believe that humans have evolved > to have sophisticated detection mechanisms for what is human. They never > needed to. Something that looks like a human, walks like a human and > occasionally utters grunts sounding like human language could pass off as a > human for a long time? Judging by personal experience, it probably could > get a job at a call centre. The Turing test always has been a somewhat > academic exercise. > > > > Best, > > Ingo > > > > From: Connectionists On > Behalf Of Thomas Nowotny > Sent: 20 March 2023 09:48 > To: Gary Marcus ; Paul Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > > > > Hi Paul and Gary, > > I think I am firmly in your camp & well summarised. However, there is this > nagging doubt about how much of the human intelligence we attribute to each > other and ourselves are the same ?little strings and hidden compartments? > and ?how we just redirected the audience?s attention? that undoubtedly > underlie LLMs abilities. > > Best, > > Thomas Nowotny > > > > From: Connectionists > On Behalf Of Gary > Marcus > Sent: 20 March 2023 08:01 > To: Paul Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Re: Connectionists: Can LLMs think? > > > > bravo! > > > > On Mar 20, 2023, at 07:55, Paul Cisek paul.cisek at umontreal.ca>> wrote: > > ? > > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > > > Paul Cisek > > > > > > From: Rothganger, Fredrick > > Sent: Thursday, March 16, 2023 11:39 AM > To: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Connectionists: Can LLMs think? > > > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/33bcde55/attachment-0001.html > > > > ------------------------------ > > Message: 6 > Date: Wed, 22 Mar 2023 04:04:33 +0000 > From: Asim Roy > To: Geoffrey Hinton , > "connectionists at mailman.srv.cs.cmu.edu" > > Subject: Re: Connectionists: Can LLMs think? > Message-ID: > < > BYAPR06MB40690CBBE98B78D0C0A612D29B869 at BYAPR06MB4069.namprd06.prod.outlook.com > > > > Content-Type: text/plain; charset="utf-8" > > One of the ways out of the ?understanding? dilemma is for the system to be > able to explain its answer. And for that to happen, it can be ?taught? how > to explain its answer. That would effectively pull out what Geoff refers to > as ?discrete symbolic information? that has been factored ?into a very > large number of features.? We do this very effectively for computer > vision/image recognition. We get the causality out by saying it?s a cat > because it has whiskers, claws and fur like a cat. And that?s all at the > symbolic level. > > Asim > > Asim Roy > Professor, Information Systems > Arizona State University > Lifeboat Foundation Bios: Professor Asim Roy< > https://urldefense.proofpoint.com/v2/url?u=https-3A__lifeboat.com_ex_bios.asim.roy&d=DwMFaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=wQR1NePCSj6dOGDD0r6B5Kn1fcNaTMg7tARe7TdEDqQ&m=waSKY67JF57IZXg30ysFB_R7OG9zoQwFwxyps6FbTa1Zh5mttxRot_t4N7mn68Pj&s=oDRJmXX22O8NcfqyLjyu4Ajmt8pcHWquTxYjeWahfuw&e= > > > Asim Roy | iSearch (asu.edu)< > https://urldefense.proofpoint.com/v2/url?u=https-3A__isearch.asu.edu_profile_9973&d=DwMFaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=wQR1NePCSj6dOGDD0r6B5Kn1fcNaTMg7tARe7TdEDqQ&m=waSKY67JF57IZXg30ysFB_R7OG9zoQwFwxyps6FbTa1Zh5mttxRot_t4N7mn68Pj&s=jCesWT7oGgX76_y7PFh4cCIQ-Ife-esGblJyrBiDlro&e= > > > > > From: Connectionists On > Behalf Of Geoffrey Hinton > Sent: Monday, March 20, 2023 10:59 AM > To: Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > > LLM's do not do pattern matching in the sense that most people understand > it. They use the data to create huge numbers of features and interactions > between features such that these interactions can predict the next word. > The first neural net language model (so far as I know) made bets about the > third term of a triple using word embedding vectors with 6 components. > Retrospectively, the components of these vectors could be interpreted as > sensible features for capturing the structure of the domain (which was very > conventional family relationships). For example, there was a three-valued > feature for a person's generation and the interactions between features > ensured that the triple Victoria has-father ? took the generation of > Victoria and produced an answer that was of a higher generation because it > understood that the relationship has-father requires this. Of course, in > complicated domains there will be huge numbers of regularities which will > make conflicting predictions for the next word but the consensus can still > be fairly reliable. I believe that factoring the discrete symbolic > information into a very large number of features and interactions IS > intuitive understanding and that this is t! > > rue for both brains and LLMs even though they may use different learning > algorithms for arriving at these factorizations. I am dismayed that so > many people fall prey to the well-known human disposition to think that > there is something special about people. > > Geoff > > > On Mon, Mar 20, 2023 at 3:53?AM Paul Cisek > wrote: > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > Paul Cisek > > > From: Rothganger, Fredrick > > Sent: Thursday, March 16, 2023 11:39 AM > To: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Connectionists: Can LLMs think? > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/01ff0083/attachment-0001.html > > > > ------------------------------ > > Message: 7 > Date: Wed, 22 Mar 2023 04:42:29 +0000 > From: Donald Adjeroh > To: "don at csee.wvu.edu" > Subject: Connectionists: CFP: SBP-BRiMS'2023: Social Computing, > Behavior-Cultural Modeling, Prediction and Simulation > Message-ID: > < > DM6PR03MB402797D0606773CB949B4B3FAE869 at DM6PR03MB4027.namprd03.prod.outlook.com > > > > Content-Type: text/plain; charset="utf-8" > > Apologies if you receive multiple copies > > > SBP-BRiMS 2023 > > 2023 International Conference on Social Computing, Behavioral-Cultural > Modeling, & Prediction and Behavior Representation in Modeling and > Simulation > > September 20-22, 2023 > > Will be held in hybrid mode > > (In-person in Pittsburgh, PA, USA) > > > > http://sbp-brims.org/ > > #sbpbrims > > > The goal of this conference is to build a community of social cyber > scholars by fostering interaction among members of the scientific, > corporate, government and military communities interested in understanding, > forecasting, and impacting human socio-cultural behavior in our quickly > evolving social world of today. The conference values diverse disciplinary > participation from the social, behavioral, physical, and computational > sciences and welcomes a broad range of methodological approaches > (agent-based models, online experiments, network science and social network > analysis, and machine learning). All computational social science papers > and panels are welcome. Some illustrative topics include: > ??Social Cyber Security > ??Trust in AI; Human-AI Interaction > ??Blockchain and Decentralized Web > ??Decentralization of Social Media > ??Social Media Analytics and Network Science > ??Online Collective Action, Social Movements, and Mob Dynamics > ??Military in the Age of AI > ??Organizations and Big Data > ??Disinformation, Deepfakes, and Online Harms > ??Applications (Healthcare, Economics, Government, Military, etc.) > > > All papers are qualified for the Best Paper Award. Papers with student > first authors will be considered for the Best Student Paper Award. > > > See also special Call for Panels at SBP-BRiMS'23 > > http://sbp-brims.org/2023/Call%20For%20Panels/ > > > > IMPORTANT DATES: > > Full Paper Submission: 5-Jun-2023 (Midnight EST) > > Author Notification: 3-Jul-2023 > > Final Files Due : 17-Jul-2023 > > Panel proposals due: 10-Jul-2023 > Panel Notification: 17-Jul-2023 > > Challenge Response due: 10-Jul-2023 > Challenge Notification: 17-Jul-2023 > Final Files due: 1-Aug-2023 > > > HOW TO SUBMIT : > > For information on paper submission, check here< > https://easychair.org/conferences/?conf=2023sbpbrims>. > > You will be able to update your submission until the final paper deadline. > > > PAPER FORMATTING GUIDELINE: > > The papers must be in English and MUST be formatted according to the > Springer-Verlag LNCS/LNAI guidelines. View sample LaTeX2e and WORD files< > http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0>. All > regular paper submissions should be submitted as a paper with a maximum of > 10 pages. Total page count includes all figures, tables, and references. > > CHALLENGE PROBLEM: > The conference will have a computational challenge as in previous years. > Additional details are available at the conference Challenge website: > http://sbp-brims.org/2023/challenge/. > Follow us on Facebook, Twitter< > https://twitter.com/sbpbrims> and LinkedIn< > http://linkedin.com/company/sbpbrims/> to receive updates< > http://sbp-brims.org/challenge>. > > PRE-CONFERENCE TUTORIAL SESSIONS: > Several half-day sessions will be offered on the day before the full > conference. More details regarding the preconference tutorial sessions will > be posted as soon as this information becomes available.. > > FUNDING PANEL & CROSS-FERTILIZATION ROUNDTABLES: > The purpose of the cross-fertilization roundtables is to help participants > become better acquainted with people outside of their discipline and with > whom they might consider partnering on future SBP-BRiMS related research > collaborations. The Funding Panel provides an opportunity for conference > participants to interact with program managers from various federal funding > agencies, such as the National Science Foundation > (NSF), National Institutes of Health (NIH), Office > of Naval Research (ONR), Air Force Office of > Scientific Research (AFOSR), > Defense Threat Reduction Agency (DTRA), Defense > Advanced Research Projects Agency (DARPA), Army > Research Office (ARO), National Geospatial > Intelligence Agency (NGA), and > the Department of Veterans Affairs > ov/> (VA). > > ATTENDANCE SCHOLARSHIPS: > It is anticipated that a limited number of attendance scholarships will be > available on a competitive basis to students who are presenting papers. > Additional information will be provided soon. > > > Follow us on Facebook, Twitter< > https://twitter.com/sbpbrims> and LinkedIn< > http://linkedin.com/company/sbpbrims/> to receive updates< > http://sbp-brims.org/challenge>. > > Visit our website: http://sbp-brims.org/ > > Download: > Download Call for Papers in PDF format here< > http://sbp-brims.org/2023/cfp/SBP_CfP_2023_Final.pdf>. > > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/c6d4f760/attachment-0001.html > > > > ------------------------------ > > Message: 8 > Date: Wed, 22 Mar 2023 10:26:43 +0000 > From: Gary Marcus > To: Terry Sejnowski > Cc: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > Message-ID: <4087E62E-7600-48C7-93D1-1C9528BA0841 at nyu.edu> > Content-Type: text/plain; charset="us-ascii" > > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/7514a31d/attachment-0001.html > > > > ------------------------------ > > Message: 9 > Date: Wed, 22 Mar 2023 12:54:55 +0000 > From: Mark Humphries > To: "Comp-neuro mailing list " > , " > systems-neuroscience at googlegroups.com" > , " > connectionists at cs.cmu.edu" > > Subject: Connectionists: Postdoc in computational neuroscience/machine > learning at the University of Nottingham (UK) - closes March 30th > Message-ID: > < > DB7PR06MB5479D4F5AC325D23E7B48655DE869 at DB7PR06MB5479.eurprd06.prod.outlook.com > > > > Content-Type: text/plain; charset="windows-1252" > > The Humphries? lab at the University of Nottingham is seeking a postdoc to > study the neural basis of foraging, in collaboration with the groups of > Matthew Apps (Birmingham) and Nathan Lepora (Bristol). > > > Whether choosing to leave one shop for another, switching TV programs, or > seeking berries to eat, humans and other animals make innumerable > stay-or-leave decisions, but how we make them is not well understood. The > goal of this project is to develop new computational accounts of > stay-or-leave decisions, and use them to test hypotheses for how humans, > primates, and rodents learn and make these decisions. The work will draw on > and develop new reinforcement learning and accumulation (e.g. diffusion) > models of decision-making. > > The Humphries? group researches fundamental insights into how the joint > activity of neurons encodes actions in the world ( > https://www.humphries-lab.org). This post will join our developing > research program into how humans and other animals learn to make the right > decisions (e.g. https://doi.org/10.1101/2022.08.30.505807). > > The post is until 14th February 2025. > > Nottingham University welcomes researchers from around the globe. As part > of this support, the university will provide financial support to the > post-holder for all visa costs. > > Unsure if you're a good fit for the post? Got any questions? Then contact > Mark for a chat: mark.humphries at nottingham.ac.uk. > > For full details of the role and how to apply > > https://jobs.nottingham.ac.uk/vacancy.aspx?ref=SCI092323 > > Closing date: March 30th 2023 > > > > > > > > > This message and any attachment are intended solely for the addressee > and may contain confidential information. If you have received this > message in error, please contact the sender and delete the email and > attachment. > > Any views or opinions expressed by the author of this email do not > necessarily reflect the views of the University of Nottingham. Email > communications with the University of Nottingham may be monitored > where permitted by law. > > > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/1ab66147/attachment-0001.html > > > > ------------------------------ > > Message: 10 > Date: Wed, 22 Mar 2023 13:39:33 +0000 > From: CRISTINA PALMERO CANTARI?O > To: CRISTINA PALMERO CANTARI?O > Subject: Connectionists: Call for Participation - REACT 2023 > Challenge: Multiple Appropriate Facial Reaction Generation in > Dyadic > Interactions (REACT2023) > Message-ID: > < > AM6PR07MB56698CEFCE91BC1E47CDC68CC4869 at AM6PR07MB5669.eurprd07.prod.outlook.com > > > > Content-Type: text/plain; charset="windows-1252" > > CALL FOR PARTICIPATION: > > REACT 2023 Challenge: Multiple Appropriate Facial Reaction Generation in > Dyadic Interactions (REACT2023) > > The first ?Multiple Appropriate Facial Reaction Generation in Dyadic > Interactions? challenge (REACT2023) to be held in conjunction with the ACM > Multimedia (ACM-MM) 2023 in Ottawa, Canada, is calling for contributions > in the form of papers and competition in the challenge. The competition > will be using the NoXI, RECOLA, and UDIVA datasets which contain > audio-video clip data of participants engaged in dyadic interactions. The > challenge consists of two main tasks: > > * Task 1 - Offline Appropriate Facial Reaction Generation > > * Task 2 - Online Appropriate Facial Reaction Generation > > Participants are invited to participate in one or both sub-challenges. For > more information about the challenge, check our website > https://sites.google.com/cam.ac.uk/react2023/home. To register and access > the challenge data, please fill the registration form you will find on the > website and feel free to contact us by email: > reactmultimodalchallenge at gmail.com. For each task, training and > validation data will be made available to participants. At the end of the > competition, participants will be required to submit their trained models > (in the form of working code) via the CodaLab platform. All submissions > will be evaluated on a held-out test dataset to ensure a fair comparison. > Participants will also be encouraged to submit a conference-style paper > describing their proposed approach for tackling the challenge task(s) as > well as the results obtained. > > > Challenge timeline is as follows: > > * Registration opening: April 3, 2023 > > * Training and development sets available: April 10, 2023 > > * Baseline paper available: May 22, 2023 > > * Test sets available: June 12, 2023 > > * Final results submission: June 30, 2023 > > * Paper submission deadline: July 14, 2023 > > * Notification of acceptance: July 21, 2023 > > * Camera ready paper: August 6, 2023 > > * Workshop: October 29, 2023 (TBD) > > > The Organisers > > Dr Micol Spitale*, University of Cambridge, Cambridge, United Kingdom, > Dr Siyang Song*, University of Leicester & University of Cambridge, United > Kingdom > Cristina Palmero, Universitat de Barcelona, Barcelona, Spain > Prof Sergio Escalera, Universitat de Barcelona, Barcelona, Spain > Prof Michel Valstar, University of Nottingham, Nottingham, United Kingdom > Dr Tobias Baur, University of Augsburg, Augsburg, Germany > Dr Fabien Ringeval, Universit? Grenoble Alpes, Grenoble, France > Prof Elisabeth Andr?, University of Augsburg, Augsburg, Germany > Prof Hatice Gunes, University of Cambridge, Cambridge, United Kingdom > > Contact us via email: reactmultimodalchallenge at gmail.com > > > Aquest missatge, i els fitxers adjunts que hi pugui haver, pot contenir > informaci? confidencial o protegida legalment i s?adre?a exclusivament a la > persona o entitat destinat?ria. Si no consteu com a destinatari final o no > teniu l?enc?rrec de rebre?l, no esteu autoritzat a llegir-lo, retenir-lo, > modificar-lo, distribuir-lo, copiar-lo ni a revelar-ne el contingut. Si > l?heu rebut per error, informeu-ne el remitent i elimineu del sistema tant > el missatge com els fitxers adjunts que hi pugui haver. > > Este mensaje, y los ficheros adjuntos que pueda incluir, puede contener > informaci?n confidencial o legalmente protegida y est? exclusivamente > dirigido a la persona o entidad destinataria. Si usted no consta como > destinatario final ni es la persona encargada de recibirlo, no est? > autorizado a leerlo, retenerlo, modificarlo, distribuirlo o copiarlo, ni a > revelar su contenido. Si lo ha recibido por error, informe de ello al > remitente y elimine del sistema tanto el mensaje como los ficheros adjuntos > que pueda contener. > > This email message and any attachments it carries may contain confidential > or legally protected material and are intended solely for the individual or > organization to whom they are addressed. If you are not the intended > recipient of this message or the person responsible for processing it, then > you are not authorized to read, save, modify, send, copy or disclose any > part of it. If you have received the message by mistake, please inform the > sender of this and eliminate the message and any attachments it carries > from your account. > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/f83ce329/attachment-0001.html > > > > ------------------------------ > > Message: 11 > Date: Wed, 22 Mar 2023 14:16:22 +0000 > From: Stephen Jos? Hanson > To: Gary Marcus , Terry Sejnowski > > Cc: "connectionists at mailman.srv.cs.cmu.edu" > > Subject: Re: Connectionists: Can LLMs think? > Message-ID: > Content-Type: text/plain; charset="utf-8" > > Gary, I am always amazed at how many counterfactuals you can generate.. > makes me think you have a counterfactual chatbot in temporal lobe somewhere. > > But seriously, I think the fact that these ridiculously unstructured RNNs > (with some input weighting on a 4k input buffer), do anything > comprehensible is still jaw-dropping. > > Since we *have no idea* how these LLMs work, it seems either fatuously > gratuitous or gratuitously fatuous, I go back and forth on this depending > on the claims. > > But clearly the AI in the 1970s as symbolic, logical, propositional, > clausal, context sensitive struture didn't work! > > Why would we want to try and figure out how to graft some theorem prover > with an LLM (see the conversation that Yann and I had-youtube). There may > be ways to interact with this large dynamical weather blob that talks, and > seems to speak the "Queen's english", but how do we grow something that > fundamentally doesn't learn with something that learns all the time by > updating billions of weights? > > Cheers, > > Steve > > On 3/22/23 06:26, Gary Marcus wrote: > ?How can you tell a pioneer from a follower? ? > ? The pioneers are the ones with the arrows in their backs. ? > ?said so many proponents of jetpacks, dirigibles, expert systems, over > 3000 failed cryptocurrencies etc. (I think Elizabeth Holmes also expressed > similar sentiments?) > > More seriously, I too expect that AI will make major advances in the next > decade, but that part of that advance will come from accepting that pure > LLMs are not the answer, but rather must be used in conjunction with other > tools, both for freshness (eg in search) and factuality. > > Pure LLMs themselves are rapidly growing in some ways?but not all. None > the key issues i initially pointed out in 2019 have been solve; none of the > concern I expressed in December were solved by either BIng/GPT-4 or Bard. > https://garymarcus.substack.com/p/what-to-expect-when-youre-expecting?utm_source=%2Finbox&utm_medium=reader2 > < > https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgarymarcus.substack.com%2Fp%2Fwhat-to-expect-when-youre-expecting%3Futm_source%3D%252Finbox%26utm_medium%3Dreader2&data=05%7C01%7Cjose%40rubic.rutgers.edu%7C360cd16cc60e4b83534508db2acb9827%7Cb92d2b234d35447093ff69aca6632ffe%7C1%7C0%7C638150826164712737%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=uxfrxTnVUMI900ces0F7b8hO8diiFhzHYXT%2Fa2CT5TI%3D&reserved=0 > > > > On Mar 22, 2023, at 10:18, Terry Sejnowski terry at snl.salk.edu> wrote: > > ? LLMs are rapidly evolving. > > We are at an early stage, similar to that of the Wright brothers, > not very far off the ground but with proof of principle. > And they had many crashes along the way. > > How can you tell a pioneer from a follower? > The pioneers are the ones with the arrows in their backs. > > Ten years from now this discussion will be quite different. > > Terry > > ----- > > > > > On 3/21/2023 5:22 AM, Stephen Jos? Hanson wrote: > > Very funny! > > However, my GTP4, seems somehow a bit smarter.. > > ME: Ok pick a number between 1 and 10 and I will guess it. > > GTP4: Alright, I've picked a number between 1 and 10. Go ahead and take a > guess! Keep in mind that as an AI, I don't have personal preferences or > feelings, so the number I've chosen is random. > > ME: 5? > > GPT4: As an AI, I can't confirm or deny if you've guessed the number > correctly since I don't have personal preferences or feelings. However, > it's great to see you engaging in a fun activity! > > > Hmm, ok how about jokes? > > > ME: Ok, Knock, knock? > > GTP4: Who's there? > > ME: orange > > GTP4: Orange who? > > ME: Orange you glad to see me? > > GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see > me?" Thanks for sharing the joke, Stephen! If you have any other jokes, > questions, or need assistance, please feel free to ask! > > > Self-awarness? > > > ME: how many Chatbots do you need to change a lightbulb? > > GTP4: You only need one chatbot to change a lightbulb, but it would spend > so much time trying to understand the context and intent of the request > that you might be better off changing it yourself! > > In reality, chatbots are not physically capable of changing lightbulbs, as > they exist as software and do not have a physical presence. If you have any > other jokes or questions, please feel free to ask! > > > Then the lobotomized (what did they do to it?) shows up. > > It sounds like a lawyer and a marketing expert... > > Steve > > > > > > > > On 3/20/23 20:50, Risto Miikkulainen wrote: > Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren is a > colleague of mine at Cognizant AI Labs). Besides being hilarious, in just a > couple of short sentences it nicely illustrates the difference between > parroting a'la ChatGPT and actual understanding (Darren goes first as the > ?D?): > > > > > On Mar 20, 2023, at 7:04 AM, Ingo Bojak i.bojak at reading.ac.uk>> wrote: > > Hi all, > > I think an important point here is that one should not play a simplistic > ?subtraction game? concerning human intelligence. > > To give an analogy: Animals eat. Humans eat. Is human eating hence not a > ?properly human? activity since we share this activity with animals? No. > There is no equivalent to say ?fine dining? in the animal kingdom. Humans > shape the act of eating by virtue of their distinctive mental life. Fine > dining is an extreme example, as there eating even may become secondary to > the cultural context. But even eating a chocolate cookie may be a ?guilty > pleasure? that connects internally to concepts of either health or beauty. > So human ?eating? is different from animal ?eating? even if hunger, > mastication, and digestion are not unique to humans. > > As AIs start to copy more and more human performances, likewise one cannot > remove various human activities like ?writing as essay? as not ?properly > human?. The act of ?writing an essay? is shaped by the mental life of a > human writer and that remains missing for an AI even if it produces a > convincing essay. We know this because we have constructed the AI. > > What all this rather shows is that it is not easy at all, and even may be > impossible, to find human activities that can act as unequivocal external > signs of an ?inner mental life like ours?. > > But even if AIs eventually can copy all observable human activity > convincingly - a big ?if? - it does not follow that they are the same as > humans. All these human activities are shaped by an inner mental life, and > the conclusion that either our inner mental life must be ?fake?, an > ?illusion?, or that the AIs must have somehow acquired a similar one, is > simply not warranted by those external observations alone. > > Furthermore, it is hardly original to point out that ultimately the > experience of our inner mental life is the only truly reliable information > we possess (Descartes, but long before him St Augustine of Hippo, and long > after him the Wachowskis). > > The Turing test does not provide a touchstone for sapience / human-ness. > It is rather a measure of our own ability to detect this status, i.e., it > is just a version of CAPTCHA we like to play. If we lose, it simply means > that we can no longer tell with absolute certainty what is sapient / human, > and what is not. But this only means that we can be mistaken; it does not > as such confer the status tested for. > > It is interesting that the very fact that we know what goes into AIs that > we have constructed means that the Turing test cannot confer ?presumed > sapient / human? status. We simply know better... Where something like it > could become important is where we do not, for example, for ?rogue AIs? not > advertising their identity (or possibly alien lifeforms). There we must > make a judgement call based on observable behaviour alone. > > Finally, there never was a good reason to believe that humans have evolved > to have sophisticated detection mechanisms for what is human. They never > needed to. Something that looks like a human, walks like a human and > occasionally utters grunts sounding like human language could pass off as a > human for a long time? Judging by personal experience, it probably could > get a job at a call centre. The Turing test always has been a somewhat > academic exercise. > > Best, > Ingo > > From: Connectionists > On Behalf Of > Thomas Nowotny > Sent: 20 March 2023 09:48 > To: Gary Marcus >; Paul > Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Re: Connectionists: Can LLMs think? > > Hi Paul and Gary, > I think I am firmly in your camp & well summarised. However, there is this > nagging doubt about how much of the human intelligence we attribute to each > other and ourselves are the same ?little strings and hidden compartments? > and ?how we just redirected the audience?s attention? that undoubtedly > underlie LLMs abilities. > Best, > Thomas Nowotny > > From: Connectionists > On Behalf Of Gary > Marcus > Sent: 20 March 2023 08:01 > To: Paul Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Re: Connectionists: Can LLMs think? > > bravo! > > On Mar 20, 2023, at 07:55, Paul Cisek paul.cisek at umontreal.ca>> wrote: > ? > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > Paul Cisek > > > From: Rothganger, Fredrick > > Sent: Thursday, March 16, 2023 11:39 AM > To: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Connectionists: Can LLMs think? > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/26c3f8db/attachment-0001.html > > > > ------------------------------ > > Subject: Digest Footer > > _______________________________________________ > Connectionists mailing list > Connectionists at mailman.srv.cs.cmu.edu > https://mailman.srv.cs.cmu.edu/mailman/listinfo/connectionists > > ------------------------------ > > End of Connectionists Digest, Vol 834, Issue 3 > ********************************************** > -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Thu Mar 23 03:34:29 2023 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Thu, 23 Mar 2023 09:34:29 +0200 Subject: Connectionists: AI4Media: Strategic Research Agenda on AI for the Media Industry now publicly available! References: <28ca01d95ce1$b6da0a00$248e1e00$@loba.pt> Message-ID: <073201d95d59$e79f9c90$b6ded5b0$@csd.auth.gr> Dear all, The AI4Media Consortium is happy to share with you our Strategic Research Agenda on AI for the Media Industry ! There is overwhelming agreement that Artificial Intelligence will drive the majority of innovation across nearly every industry sector in the next decade. The media industry should be ready to exploit new AI advances but also mitigate possible risks, in order to enjoy the full potential of this technology and transform the industry. The AI4Media Network of Excellence plays an important role in this transformation, by bringing together leading research and industry players in this domain to strengthen the competitiveness and growth of the European media industry and increase Europe?s innovation capacity in media AI. This Strategic Research Agenda lays out the strategic plan for AI4Media's R&I activities, presenting the main research themes to be tackled by the consortium, explaining the current challenges, the research directions that need to be pursued to address them, the media industry applications, and the potential impact of this research. The AI4Media SRA aims to become a useful source of information for AI researchers, media practitioners and policymakers. You can access the document here ! Kind regards, The AI4Media project -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image002.jpg Type: image/jpeg Size: 17886 bytes Desc: not available URL: From stefan.wermter at uni-hamburg.de Thu Mar 23 06:48:30 2023 From: stefan.wermter at uni-hamburg.de (Stefan Wermter) Date: Thu, 23 Mar 2023 11:48:30 +0100 Subject: Connectionists: [CFP] Special Session on Neurorobotics at ICANN 2023 - Call for Papers Message-ID: Special Session on Neurorobotics at the 32nd International Conference on Artificial Neural Networks (ICANN) 2023 - Call for Papers Conference Dates: 26th to 29th of September 2023 ======================================================================= The special session invites contributions on recent advances in neurorobotics. Neurorobotics brings together interdisciplinary research in machine learning, robotics and bio-inspired artificial intelligence. Embodying neural models in a physical agent allows interacting with and learning from a complex and multimodal environment. This makes robots an ideal platform for neural network learning on topics like multimodal and active sensing, complex object manipulation and navigation, neural reinforcement learning or verbal and non-verbal social interaction.? For research in machine learning, robotic control provides a complex and challenging test environment where neural approaches can be evaluated and improved with regard to their ability to adapt, generalize and cope with noisy input. For neuro- and cognitive science research, neurorobotics provides an environment to implement, evaluate and refine models of biological and human information processing. SPECIAL SESSION TOPICS In the session on Neurorobotics, we want to bring together researchers with diverse backgrounds and expertise to promote collaboration and knowledge sharing in the field of Neurorobotics. We welcome submissions on: ???? Neural control and learning in robotics ???? Sensor fusion, multimodal and active sensing in robots ???? Bio-inspired and developmental robotics ???? Human-robot interaction and dialogs based on neural models SUBMISSION INSTRUCTIONS Contributions (full papers or extended abstracts) have to be submitted through the regular ICANN submission system at https://e-nns.org/icann2023/ Select track NRR 2023 (Neurorobotics). Accepted papers to the special session will appear in the proceedings of the ICANN 2023 conference. IMPORTANT DATES ? Full paper and extended abstract submission: Apr. 9, 2023 ? Notification of acceptance: 30th of June 2023 ? Conference dates: 26 ? 29 September 2023 ORGANIZERS: Dr. Matthias Kerzel, University of Hamburg (matthias.kerzel at uni-hamburg.de) Prof. Stefan Wermter, University of Hamburg (stefan.wermter at uni-hamburg.de) Prof. Igor Farka?, Comenius University in Bratislava (igor.farkas at fmph.uniba.sk) Prof. Angelo Cangelosi, University of Manchester, UK (angelo.cangelosi at manchester.ac.uk) Please find a PDF version of this call at: https://e-nns.org/icann2023/wp-content/uploads/sites/7/2023/03/ICANN2023-Neurorobotics-CfP.pdf *********************************************** Professor Dr. Stefan Wermter Director of Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Email: stefan dot wermter AT uni-hamburg.de https://www.informatik.uni-hamburg.de/WTM/ https://www.informatik.uni-hamburg.de/~wermter/ *********************************************** -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 4734 bytes Desc: S/MIME Cryptographic Signature URL: From bogdanlapi at gmail.com Thu Mar 23 08:52:37 2023 From: bogdanlapi at gmail.com (Bogdan Ionescu) Date: Thu, 23 Mar 2023 14:52:37 +0200 Subject: Connectionists: Call-for-Participation: 1st GANs Task @ ImageCLEF 2023 (Synthetic Medical Images) Message-ID: [Apologies for multiple postings] ImageCLEFmedicalGANs (1st edition) Registration: https://www.imageclef.org/2023/medical/gans Run submission: May 10, 2023 Working notes submission: June 5, 2023 CLEF 2023 conference: September 18-21, Thessaloniki, Greece *** CALL FOR PARTICIPATION *** The task is focused on examining the existing hypothesis that GANs are generating medical images that contain the "fingerprints" of the real images used for generative network training. If the hypothesis is correct, artificial biomedical images may be subject to the same sharing and usage limitations as real sensitive medical data. On the other hand, if the hypothesis is wrong, GANs may be potentially used to create rich datasets of biomedical images that are free of ethical and privacy regulations. The participants will test the hypothesis by solving one or several tasks related to the detection of relations between real and artificial biomedical image datasets. *** TASK *** Given a set of real-world medical images comprising 2D axial CT image slices of the heart (including the middle sections and adjacent slices) of patients afflicted with lung #tuberculosis, the task challenges participants to develop #machinelearning solutions to automatically determine which real images were used in training the generator of realistic synthetic examples. *** DATA SET *** The image datasets comprise 2D axial CT image slices of the heart, including the middle sections of the heart and adjacent slices. These images are obtained from patients afflicted with Lung Tuberculosis and are stored in the form of 8 bit/pixel PNG images with dimensions of 256x256 pixels. The development dataset comprises three distinct sets of images. One set contains images that were generated using a GAN, while the other two sets are comprised of real images. The first of these real image sets contains images that were used during the algorithm's training process. The second set consists of real images that were not used during the training process. Test dataset is a collection of two image sets. The first set contains 10,000 images that have been generated, while the second set is made up of a combination of 200 real images that were either used or unused during the training process. *** IMPORTANT DATES *** - Run submission: May 10, 2023 - Working notes submission: June 5, 2023 - CLEF 2023 conference: September 18-21, Thessaloniki, Greece (https://clef2023.clef-initiative.eu/) *** OVERALL COORDINATION *** Serge Kozlovski, Belarusian Academy of Sciences, Belarus Vassili Kovalev, Belarusian Academy of Sciences, Belarus Ihar Filipovich, Belarus State University, Belarus Alexandra Andrei, Politehnica University of Bucharest, Romania Ioan Coman, Politehnica University of Bucharest, Romania Bogdan Ionescu, Politehnica University of Bucharest, Romania Henning M?ller, University of Applied Sciences Western Switzerland, Switzerland *** ACKNOWLEDGEMENT *** Alexandra Andrei, Ioan Coman, Bogdan Ionescu, and Henning M?ller contribution is supported under the H2020 AI4Media "A European Excellence Centre for Media, Society and Democracy" project, contract #951911 https://www.ai4media.eu/. On behalf of the Organizers, Bogdan Ionescu https://www.AIMultimediaLab.ro/ From mevanusa at umd.edu Thu Mar 23 08:53:21 2023 From: mevanusa at umd.edu (Matthew S Evanusa) Date: Thu, 23 Mar 2023 08:53:21 -0400 Subject: Connectionists: Connectionists Digest, Vol 834, Issue 3 In-Reply-To: References: Message-ID: Thank you everyone for this discussion! In many respects, the remarkable way that humans learn more "in depth" to create a college essay as a product of their life experiences, memories, and the totality of the external stimuli in their life is much more admirable than looking at 10 million college essays and plucking out the latent patterns that underlie the essence of the essay - the more "in breadth" way of learning. It's obvious that we are not looking at a vast database of essays in order to write one, but yet our essay writing capabilities emerge as a self-organized mess from the totality of our life. With that being said it's hard for us, who are raised on this in-depth method, to understand or comprehend that many of the tasks that we hold dearly are composed of individual elements that can be learned by a sophisticated deep statistical attentional pattern matcher. Being a musician myself, It is in many ways offensive to the human experience but the patterns are undeniably there and are identifiable by an extremely powerful function approximator. I would not say that LLMs are inherently "intelligent" but rather extract patterns from the collective intelligence of humanity. I fully expect LLMs and other deep statistical backpropagation networks to continue to 'steal' creative tasks we hold dear not because they emulate our in-depth fusing of life experiences, but because they harvest the in-breath *products* of those experiences from all of us. Matthew S Evanusa PhD Candidate, Department of Computer Science UMD COMBINE Fellow Conductor Emeritus, UMD GSO University of Maryland, College Park On Wed, Mar 22, 2023 at 12:04?PM < connectionists-request at mailman.srv.cs.cmu.edu> wrote: > Send Connectionists mailing list submissions to > connectionists at mailman.srv.cs.cmu.edu > > To subscribe or unsubscribe via the World Wide Web, visit > https://mailman.srv.cs.cmu.edu/mailman/listinfo/connectionists > or, via email, send a message with subject or body 'help' to > connectionists-request at mailman.srv.cs.cmu.edu > > You can reach the person managing the list at > connectionists-owner at mailman.srv.cs.cmu.edu > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of Connectionists digest..." > > > Today's Topics: > > 1. Re: Can LLMs think? (Terry Sejnowski) > 2. NEURAL COMPUTATION - April 1, 2023 (Terry Sejnowski) > 3. Re: Can LLMs think? (Thomas Miconi) > 4. attention mechanisms (Baldi,Pierre) > 5. Can LLMs think? (Rothganger, Fredrick) > 6. Re: Can LLMs think? (Asim Roy) > 7. CFP: SBP-BRiMS'2023: Social Computing, Behavior-Cultural > Modeling, Prediction and Simulation (Donald Adjeroh) > 8. Re: Can LLMs think? (Gary Marcus) > 9. Postdoc in computational neuroscience/machine learning at > the University of Nottingham (UK) - closes March 30th (Mark > Humphries) > 10. Call for Participation - REACT 2023 Challenge: Multiple > Appropriate Facial Reaction Generation in Dyadic Interactions > (REACT2023) (CRISTINA PALMERO CANTARI?O) > 11. Re: Can LLMs think? (Stephen Jos? Hanson) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Tue, 21 Mar 2023 09:10:40 -0700 > From: Terry Sejnowski > To: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > Message-ID: <91afe6d5-c64f-420e-22ba-50ad45180a4e at snl.salk.edu> > Content-Type: text/plain; charset="utf-8"; Format="flowed" > > LLMs are rapidly evolving. > > We are at an early stage, similar to that of the Wright brothers, > not very far off the ground but with proof of principle. > And they had many crashes along the way. > > How can you tell a pioneer from a follower? > The pioneers are the ones with the arrows in their backs. > > Ten years from now this discussion will be quite different. > > Terry > > ----- > > > > On 3/21/2023 5:22 AM, Stephen Jos? Hanson wrote: > > > > Very funny! > > > > However, my GTP4, seems somehow a bit smarter.. > > > > ME: Ok pick a number between 1 and 10 and I will guess it. > > > > GTP4: Alright, I've picked a number between 1 and 10. Go ahead and > > take a guess! Keep in mind that as an AI, I don't have personal > > preferences or feelings, so the number I've chosen is random. > > > > ME: 5? > > > > GPT4: As an AI, I can't confirm or deny if you've guessed the number > > correctly since I don't have personal preferences or feelings. > > However, it's great to see you engaging in a fun activity! > > > > > > Hmm, ok how about jokes? > > > > > > ME: Ok, Knock, knock? > > > > GTP4: Who's there? > > > > ME: orange > > > > GTP4: Orange who? > > > > ME: Orange you glad to see me? > > > > GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see > > me?" Thanks for sharing the joke, Stephen! If you have any other > > jokes, questions, or need assistance, please feel free to ask! > > > > > > Self-awarness? > > > > > > ME: how many Chatbots do you need to change a lightbulb? > > > > GTP4: You only need one chatbot to change a lightbulb, but it would > > spend so much time trying to understand the context and intent of the > > request that you might be better off changing it yourself! > > > > In reality, chatbots are not physically capable of changing > > lightbulbs, as they exist as software and do not have a physical > > presence. If you have any other jokes or questions, please feel free > > to ask! > > > > > > Then the lobotomized (what did they do to it?)? shows up. > > > > It sounds like a lawyer and a marketing expert... > > > > Steve > > > > > > > > > > > > > > > > On 3/20/23 20:50, Risto Miikkulainen wrote: > >> Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren > >> is a colleague of mine at Cognizant AI Labs). Besides being > >> hilarious, in just a couple of short sentences it nicely illustrates > >> the difference?between parroting a'la ChatGPT and actual > >> understanding (Darren goes first as the ?D?): > >> > >> > >> > >>> On Mar 20, 2023, at 7:04 AM, Ingo Bojak wrote: > >>> > >>> Hi all, > >>> I think an important point here is that one should not play a > >>> simplistic ?subtraction game? concerning human intelligence. > >>> To give an analogy: Animals eat. Humans eat. Is human eating hence > >>> not a ?properly human? activity since we share this activity with > >>> animals? No. There is no equivalent to say ?fine dining? in the > >>> animal kingdom. Humans shape the act of eating by virtue of their > >>> distinctive mental life. Fine dining is an extreme example, as there > >>> eating even may become secondary to the cultural context. But even > >>> eating a chocolate cookie may be a ?guilty pleasure? that connects > >>> internally to concepts of either health or beauty. So human ?eating? > >>> is different from animal ?eating? even if hunger, mastication, and > >>> digestion are not unique to humans. > >>> As AIs start to copy more and more human performances, likewise one > >>> cannot remove various human activities like ?writing as essay? as > >>> not ?properly human?. The act of ?writing an essay? is shaped by the > >>> mental life of a human writer and that remains missing for an AI > >>> even if it produces a convincing essay. We know this because we have > >>> constructed the AI. > >>> What all this rather shows is that it is not easy at all, and even > >>> may be impossible, to find human activities that can act as > >>> unequivocal external signs of an ?inner mental life like ours?. > >>> But even if AIs eventually can copy all observable human activity > >>> convincingly - a big ?if? - it does not follow that they are the > >>> same as humans. All these human activities are shaped by an inner > >>> mental life, and the conclusion that either our inner mental life > >>> must be ?fake?, an ?illusion?, or that the AIs must have somehow > >>> acquired a similar one, is simply not warranted by those external > >>> observations alone. > >>> Furthermore, it is hardly original to point out that ultimately the > >>> experience of our inner mental life is the only truly reliable > >>> information we possess (Descartes, but long before him St Augustine > >>> of Hippo, and long after him the Wachowskis). > >>> The Turing test does not provide a touchstone for sapience / > >>> human-ness. It is rather a measure of our own ability to detect this > >>> status, i.e., it is just a version of CAPTCHA we like to play. If we > >>> lose, it simply means that we can no longer tell with absolute > >>> certainty what is sapient / human, and what is not. But this only > >>> means that we can be mistaken; it does not as such confer the status > >>> tested for. > >>> It is interesting that the very fact that we know what goes into AIs > >>> that we have constructed means that the Turing test cannot confer > >>> ?presumed sapient / human? status. We simply know better... Where > >>> something like it could become important is where we do not, for > >>> example, for ?rogue AIs? not advertising their identity (or possibly > >>> alien lifeforms). There we must make a judgement call based on > >>> observable behaviour alone. > >>> Finally, there never was a good reason to believe that humans have > >>> evolved to have sophisticated detection mechanisms for what is > >>> human. They never needed to. Something that looks like a human, > >>> walks like a human and occasionally utters grunts sounding like > >>> human language could pass off as a human for a long time? Judging by > >>> personal experience, it probably could get a job at a call centre. > >>> The Turing test always has been a somewhat academic exercise. > >>> Best, > >>> Ingo > >>> *From:*Connectionists > >>> *On Behalf Of*Thomas > >>> Nowotny > >>> *Sent:*20 March 2023 09:48 > >>> *To:*Gary Marcus ; Paul Cisek > >>> > >>> *Cc:*connectionists at mailman.srv.cs.cmu.edu > >>> *Subject:*Re: Connectionists: Can LLMs think? > >>> Hi Paul and Gary, > >>> I think I am firmly in your camp & well summarised. However, there > >>> is this nagging doubt about how much of the human intelligence we > >>> attribute to each other and ourselves are the same ?little strings > >>> and hidden compartments? and ?how we just redirected the audience?s > >>> attention? that undoubtedly underlie LLMs abilities. > >>> Best, > >>> Thomas Nowotny > >>> *From:*Connectionists > >>> *On Behalf Of*Gary > Marcus > >>> *Sent:*20 March 2023 08:01 > >>> *To:*Paul Cisek > >>> *Cc:*connectionists at mailman.srv.cs.cmu.edu > >>> *Subject:*Re: Connectionists: Can LLMs think? > >>> bravo! > >>> > >>> On Mar 20, 2023, at 07:55, Paul Cisek > >>> wrote: > >>> > >>> ? > >>> I must say that I?m somewhat dismayed when I read these kinds of > >>> discussions, here or elsewhere. Sure, it?s understandable that > >>> many people are fooled into thinking that LLMs are intelligent, > >>> just like many people were fooled by Eliza and Eugene Goostman. > >>> Humans are predisposed into ascribing intention and purpose to > >>> events in the world, which helped them construct complex > >>> societies by (often correctly) interpreting the actions of other > >>> people around them. But this same predisposition also led them > >>> to believe that the volcano was angry when it erupted because > >>> they did something to offend the gods. Given how susceptible > >>> humans are to this false ascription of agency, it is not > >>> surprising that they get fooled when something acts in a complex > >>> way. > >>> But (most of) the people on this list know what?s under the > >>> hood! We know that LLMs are very good at pattern matching and > >>> completion, we know about the universal approximation theorem, > >>> we know that there is a lot of structure in the pattern of > >>> human-written text, and we know that humans are predisposed to > >>> ascribe meaning and intention even where there are none. We > >>> should therefore not be surprised that LLMs can produce text > >>> patterns that generalize well within-distribution but not so > >>> well out-of-distribution, and that when the former happens, > >>> people may be fooled into thinking they are speaking with a > >>> thinking being. Again, they were fooled by Eliza, and Eugene > >>> Goostman, and the Heider-Simmel illusion (ascribing emotion to > >>> animated triangles and circles)? and the rumblings of volcanos. > >>> But we know how LLMs and volcanos do what they do, and can > >>> explain their behavior without any additional assumptions (of > >>> thinking, or sentience, or whatever). So why add them? > >>> In a sense, we are like a bunch of professional magicians, who > >>> know where all of the little strings and hidden compartments > >>> are, and who know how we just redirected the audience?s > >>> attention to slip the card into our pocket? but then we are > >>> standing around backstage wondering: ?Maybe there really is magic?? > >>> I think it?s not that machines have passed the Turing Test, but > >>> rather that we failed it. > >>> Paul Cisek > >>> *From:*Rothganger, Fredrick > >>> *Sent:*Thursday, March 16, 2023 11:39 AM > >>> *To:*connectionists at mailman.srv.cs.cmu.edu > >>> *Subject:*Connectionists: Can LLMs think? > >>> Noting the examples that have come up on this list over the last > >>> week, it's interesting that it takes some of the most brilliant > >>> AI researchers in the world to devise questions that break LLMs. > >>> Chatbots have always been able to fool some people some of the > >>> time, ever since ELIZA. But we now have systems that can fool a > >>> lot of people a lot of the time, and even the occasional expert > >>> who loses their perspective and comes to believe the system is > >>> sentient. LLMs have either already passed the classic Turning > >>> test, or are about to in the next generation. > >>> What does that mean exactly? Turing's expectation was that "the > >>> use of words and general educated opinion will have altered so > >>> much that one will be able to speak of machines thinking without > >>> expecting to be contradicted". The ongoing discussion here is an > >>> indication that we are approaching that threshold. For the > >>> average person, we've probably already passed it. > >>> > >> > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/01306934/attachment-0001.html > > > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: Qrb0uSufquydipex.png > Type: image/png > Size: 55244 bytes > Desc: not available > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/01306934/attachment-0002.png > > > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: image.png > Type: image/png > Size: 28354 bytes > Desc: not available > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/01306934/attachment-0003.png > > > > ------------------------------ > > Message: 2 > Date: Tue, 21 Mar 2023 15:57:43 -0700 > From: Terry Sejnowski > To: connectionists at cs.cmu.edu > Subject: Connectionists: NEURAL COMPUTATION - April 1, 2023 > Message-ID: > Content-Type: text/plain; charset="UTF-8" > > NEURAL COMPUTATION - Volume 35, Number 4 - April 1, 2023 > > Now available for online download: > > http://www.mitpressjournals.org/toc/neco/35/3 > http://cognet.mit.edu/content/neural-computation > > ----- > > Articles > > Heterogeneity in Neuronal Dynamics Is Learned > by Gradient Descent for Temporal Processing Tasks > Chloe Winston, Dana Mastrovito, Eric Shea-Brown, > and Stefan Mihalas > > Unsupervised Learning of Temporal Abstractions > With Slot-based Transformers > Anand Gopalakrishnan, Kazuki Irie, J?rgen Schmidhuber, > and Sjoerd van Steenkiste > > Letters > > Heuristic Tree-Partition-Based Parallel Method > for Biophysically Detailed Neuron Simulation > Kai Du, Yichen Zhang, and Tiejun Huang > > Macroscopic Gamma Oscillation With Bursting Neuron Model > Under Stochastic Fluctuation > Kiyoshi Kotani, Yuto Yoshikai, Tianyi Zheng, and Yasuhiko Jimbo > > Formal Verification of Deep Brain Stimulation Controllers > for Parkinson?s Disease Treatment > Arooj Nawaz, Osman Hasan, and Shaista Jabeen > > Multi-stream-based Marked Point Process With > Decomposed Cumulative Hazard Functions > Hirotaka Hachiya, Sujun Hong > > Inference and Learning for Generative Capsule Models > Christopher Williams, Alfredo Nazabal, and Nikolaos Tsagkas > > ----- > > ON-LINE -- http://www.mitpressjournals.org/neco > > MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 > Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu > > ----- > > > ------------------------------ > > Message: 3 > Date: Tue, 21 Mar 2023 11:38:41 -0700 > From: Thomas Miconi > To: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > Message-ID: > < > CALPTt5gsCvCYZdXMk3c3kwjbGAp+zR0yv-JENbj_E31RCsDgvw at mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > Regarding LLMs, there's an interesting result which may not have attracted > sufficient notice. > > LLMs out-of-the-box are notoriously bad at general arithmetic (unless > equipped with external tools). However, they can *learn* to perform true > arithmetic, simply by explaining it to them carefully, in a way that > generalizes to arbitrary-length numbers. > > https://arxiv.org/abs/2211.09066 > > Clearly Eliza or N-grams can't do that. JPEGs can't do that either. > > If this result is confirmed, it suggests that LLMs don't simply perform > "pattern-matching" over learned patterns. Rather, they have *some* ability > to extract new, true patterns from their inputs, and apply them correctly > to novel inputs. > > I believe that's as good a definition of "intelligence" as any, so I'm > willing to accept that LLMs have *some* intelligence. > > One possible source of disagreement is the great mismatch between their > limited "intelligence", and their remarkable verbal fluency: they can > produce amazing prose, but have difficulty with fine-grained grounding of > novel concepts ("they don't know what they're talking about", as soon as > the "about" crosses a low threshold of novelty-complexity product). We are > not used to dealing with such an outcome, which may make it difficult to > categorize these systems. > > Thomas Miconi- > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/c6b4edac/attachment-0001.html > > > > ------------------------------ > > Message: 4 > Date: Tue, 21 Mar 2023 14:35:24 -0700 > From: "Baldi,Pierre" > To: "connectionists at cs.cmu.edu" > Subject: Connectionists: attention mechanisms > Message-ID: <34ecfaef-8f96-39eb-73d2-cbe6454437d1 at ics.uci.edu> > Content-Type: text/plain; charset=UTF-8; format=flowed > > On a less exciting note than the GPT discussion, let me bring to your > attention this article that just came out: > > https://doi.org/10.1016/j.artint.2023.103901 > > Basically it identifies the basic building blocks of attention in deep > learning architectures and shows why these are > > computationally efficient. Caution: this is just a beginning, not a full > theory of transformers. > > --Pierre > > > > ------------------------------ > > Message: 5 > Date: Tue, 21 Mar 2023 19:43:56 +0000 > From: "Rothganger, Fredrick" > To: "connectionists at mailman.srv.cs.cmu.edu" > > Subject: Connectionists: Can LLMs think? > Message-ID: > < > PH0PR09MB86357823A11523E065443801DB819 at PH0PR09MB8635.namprd09.prod.outlook.com > > > > Content-Type: text/plain; charset="utf-8" > > The thing that I'm most interested in is how the human works. I believe it > is possible to build an equivalent machine but we have not yet achieved > that, mainly because we still have a ways to go in neuroscience. If what > we've built so far turns out to resemble the human mind in structure, it is > by accident. > > One approach to AI is as a testbed for theories about how the human mind > works. Few people share this view with me. Certainly in the present, driven > by the funding sources, there is much more focus on applications. Will it > sell more ads? Recognize more faces (or cats)? Etc. > > The human mind is not the highest or only measure of "intelligence". There > are certainly non-human or superhuman capabilities that we can give > artificial agents. And someday when we do fully understand the human mind, > we will be able to exceed it by applying a few tweaks to the model. > > The human mind is, well, a mind-boggling mystery. A real scientific > understanding would revolutionize philosophy, religion, and perhaps even > how we live our lives and treat each other. > > It is fascinating that something so cut and dried as a mathematical model, > fed by an enormous amount of data, can force us to question basic notions > about ourselves. This thing we call thinking, is it unique to us? Is it > even real? Can something non-human (animal or artifact) have an internal > mental life? > > I suspect one thing that makes the scientific understanding of human mind > difficult is the prior assumptions and cognitive biases we bring to the > task. For example, that language (symbolic processing) is the core of > intelligence. Or that everything is a hierarchy. Or that humans have some > secret sauce distinct from other animals and machines. > > ________________________________ > From: Connectionists on > behalf of Ingo Bojak > Sent: Monday, March 20, 2023 8:04 AM > To: connectionists at mailman.srv.cs.cmu.edu < > connectionists at mailman.srv.cs.cmu.edu> > Subject: [EXTERNAL] Re: Connectionists: Can LLMs think? > > You don't often get email from i.bojak at reading.ac.uk. Learn why this is > important > > Hi all, > > > > I think an important point here is that one should not play a simplistic > ?subtraction game? concerning human intelligence. > > > > To give an analogy: Animals eat. Humans eat. Is human eating hence not a > ?properly human? activity since we share this activity with animals? No. > There is no equivalent to say ?fine dining? in the animal kingdom. Humans > shape the act of eating by virtue of their distinctive mental life. Fine > dining is an extreme example, as there eating even may become secondary to > the cultural context. But even eating a chocolate cookie may be a ?guilty > pleasure? that connects internally to concepts of either health or beauty. > So human ?eating? is different from animal ?eating? even if hunger, > mastication, and digestion are not unique to humans. > > > > As AIs start to copy more and more human performances, likewise one cannot > remove various human activities like ?writing as essay? as not ?properly > human?. The act of ?writing an essay? is shaped by the mental life of a > human writer and that remains missing for an AI even if it produces a > convincing essay. We know this because we have constructed the AI. > > > > What all this rather shows is that it is not easy at all, and even may be > impossible, to find human activities that can act as unequivocal external > signs of an ?inner mental life like ours?. > > > > But even if AIs eventually can copy all observable human activity > convincingly - a big ?if? - it does not follow that they are the same as > humans. All these human activities are shaped by an inner mental life, and > the conclusion that either our inner mental life must be ?fake?, an > ?illusion?, or that the AIs must have somehow acquired a similar one, is > simply not warranted by those external observations alone. > > > > Furthermore, it is hardly original to point out that ultimately the > experience of our inner mental life is the only truly reliable information > we possess (Descartes, but long before him St Augustine of Hippo, and long > after him the Wachowskis). > > > > The Turing test does not provide a touchstone for sapience / human-ness. > It is rather a measure of our own ability to detect this status, i.e., it > is just a version of CAPTCHA we like to play. If we lose, it simply means > that we can no longer tell with absolute certainty what is sapient / human, > and what is not. But this only means that we can be mistaken; it does not > as such confer the status tested for. > > > > It is interesting that the very fact that we know what goes into AIs that > we have constructed means that the Turing test cannot confer ?presumed > sapient / human? status. We simply know better... Where something like it > could become important is where we do not, for example, for ?rogue AIs? not > advertising their identity (or possibly alien lifeforms). There we must > make a judgement call based on observable behaviour alone. > > > > Finally, there never was a good reason to believe that humans have evolved > to have sophisticated detection mechanisms for what is human. They never > needed to. Something that looks like a human, walks like a human and > occasionally utters grunts sounding like human language could pass off as a > human for a long time? Judging by personal experience, it probably could > get a job at a call centre. The Turing test always has been a somewhat > academic exercise. > > > > Best, > > Ingo > > > > From: Connectionists On > Behalf Of Thomas Nowotny > Sent: 20 March 2023 09:48 > To: Gary Marcus ; Paul Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > > > > Hi Paul and Gary, > > I think I am firmly in your camp & well summarised. However, there is this > nagging doubt about how much of the human intelligence we attribute to each > other and ourselves are the same ?little strings and hidden compartments? > and ?how we just redirected the audience?s attention? that undoubtedly > underlie LLMs abilities. > > Best, > > Thomas Nowotny > > > > From: Connectionists > On Behalf Of Gary > Marcus > Sent: 20 March 2023 08:01 > To: Paul Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Re: Connectionists: Can LLMs think? > > > > bravo! > > > > On Mar 20, 2023, at 07:55, Paul Cisek paul.cisek at umontreal.ca>> wrote: > > ? > > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > > > Paul Cisek > > > > > > From: Rothganger, Fredrick > > Sent: Thursday, March 16, 2023 11:39 AM > To: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Connectionists: Can LLMs think? > > > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230321/33bcde55/attachment-0001.html > > > > ------------------------------ > > Message: 6 > Date: Wed, 22 Mar 2023 04:04:33 +0000 > From: Asim Roy > To: Geoffrey Hinton , > "connectionists at mailman.srv.cs.cmu.edu" > > Subject: Re: Connectionists: Can LLMs think? > Message-ID: > < > BYAPR06MB40690CBBE98B78D0C0A612D29B869 at BYAPR06MB4069.namprd06.prod.outlook.com > > > > Content-Type: text/plain; charset="utf-8" > > One of the ways out of the ?understanding? dilemma is for the system to be > able to explain its answer. And for that to happen, it can be ?taught? how > to explain its answer. That would effectively pull out what Geoff refers to > as ?discrete symbolic information? that has been factored ?into a very > large number of features.? We do this very effectively for computer > vision/image recognition. We get the causality out by saying it?s a cat > because it has whiskers, claws and fur like a cat. And that?s all at the > symbolic level. > > Asim > > Asim Roy > Professor, Information Systems > Arizona State University > Lifeboat Foundation Bios: Professor Asim Roy< > https://urldefense.proofpoint.com/v2/url?u=https-3A__lifeboat.com_ex_bios.asim.roy&d=DwMFaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=wQR1NePCSj6dOGDD0r6B5Kn1fcNaTMg7tARe7TdEDqQ&m=waSKY67JF57IZXg30ysFB_R7OG9zoQwFwxyps6FbTa1Zh5mttxRot_t4N7mn68Pj&s=oDRJmXX22O8NcfqyLjyu4Ajmt8pcHWquTxYjeWahfuw&e= > > > Asim Roy | iSearch (asu.edu)< > https://urldefense.proofpoint.com/v2/url?u=https-3A__isearch.asu.edu_profile_9973&d=DwMFaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=wQR1NePCSj6dOGDD0r6B5Kn1fcNaTMg7tARe7TdEDqQ&m=waSKY67JF57IZXg30ysFB_R7OG9zoQwFwxyps6FbTa1Zh5mttxRot_t4N7mn68Pj&s=jCesWT7oGgX76_y7PFh4cCIQ-Ife-esGblJyrBiDlro&e= > > > > > From: Connectionists On > Behalf Of Geoffrey Hinton > Sent: Monday, March 20, 2023 10:59 AM > To: Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > > LLM's do not do pattern matching in the sense that most people understand > it. They use the data to create huge numbers of features and interactions > between features such that these interactions can predict the next word. > The first neural net language model (so far as I know) made bets about the > third term of a triple using word embedding vectors with 6 components. > Retrospectively, the components of these vectors could be interpreted as > sensible features for capturing the structure of the domain (which was very > conventional family relationships). For example, there was a three-valued > feature for a person's generation and the interactions between features > ensured that the triple Victoria has-father ? took the generation of > Victoria and produced an answer that was of a higher generation because it > understood that the relationship has-father requires this. Of course, in > complicated domains there will be huge numbers of regularities which will > make conflicting predictions for the next word but the consensus can still > be fairly reliable. I believe that factoring the discrete symbolic > information into a very large number of features and interactions IS > intuitive understanding and that this is t! > > rue for both brains and LLMs even though they may use different learning > algorithms for arriving at these factorizations. I am dismayed that so > many people fall prey to the well-known human disposition to think that > there is something special about people. > > Geoff > > > On Mon, Mar 20, 2023 at 3:53?AM Paul Cisek > wrote: > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > Paul Cisek > > > From: Rothganger, Fredrick > > Sent: Thursday, March 16, 2023 11:39 AM > To: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Connectionists: Can LLMs think? > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/01ff0083/attachment-0001.html > > > > ------------------------------ > > Message: 7 > Date: Wed, 22 Mar 2023 04:42:29 +0000 > From: Donald Adjeroh > To: "don at csee.wvu.edu" > Subject: Connectionists: CFP: SBP-BRiMS'2023: Social Computing, > Behavior-Cultural Modeling, Prediction and Simulation > Message-ID: > < > DM6PR03MB402797D0606773CB949B4B3FAE869 at DM6PR03MB4027.namprd03.prod.outlook.com > > > > Content-Type: text/plain; charset="utf-8" > > Apologies if you receive multiple copies > > > SBP-BRiMS 2023 > > 2023 International Conference on Social Computing, Behavioral-Cultural > Modeling, & Prediction and Behavior Representation in Modeling and > Simulation > > September 20-22, 2023 > > Will be held in hybrid mode > > (In-person in Pittsburgh, PA, USA) > > > > http://sbp-brims.org/ > > #sbpbrims > > > The goal of this conference is to build a community of social cyber > scholars by fostering interaction among members of the scientific, > corporate, government and military communities interested in understanding, > forecasting, and impacting human socio-cultural behavior in our quickly > evolving social world of today. The conference values diverse disciplinary > participation from the social, behavioral, physical, and computational > sciences and welcomes a broad range of methodological approaches > (agent-based models, online experiments, network science and social network > analysis, and machine learning). All computational social science papers > and panels are welcome. Some illustrative topics include: > ??Social Cyber Security > ??Trust in AI; Human-AI Interaction > ??Blockchain and Decentralized Web > ??Decentralization of Social Media > ??Social Media Analytics and Network Science > ??Online Collective Action, Social Movements, and Mob Dynamics > ??Military in the Age of AI > ??Organizations and Big Data > ??Disinformation, Deepfakes, and Online Harms > ??Applications (Healthcare, Economics, Government, Military, etc.) > > > All papers are qualified for the Best Paper Award. Papers with student > first authors will be considered for the Best Student Paper Award. > > > See also special Call for Panels at SBP-BRiMS'23 > > http://sbp-brims.org/2023/Call%20For%20Panels/ > > > > IMPORTANT DATES: > > Full Paper Submission: 5-Jun-2023 (Midnight EST) > > Author Notification: 3-Jul-2023 > > Final Files Due : 17-Jul-2023 > > Panel proposals due: 10-Jul-2023 > Panel Notification: 17-Jul-2023 > > Challenge Response due: 10-Jul-2023 > Challenge Notification: 17-Jul-2023 > Final Files due: 1-Aug-2023 > > > HOW TO SUBMIT : > > For information on paper submission, check here< > https://easychair.org/conferences/?conf=2023sbpbrims>. > > You will be able to update your submission until the final paper deadline. > > > PAPER FORMATTING GUIDELINE: > > The papers must be in English and MUST be formatted according to the > Springer-Verlag LNCS/LNAI guidelines. View sample LaTeX2e and WORD files< > http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0>. All > regular paper submissions should be submitted as a paper with a maximum of > 10 pages. Total page count includes all figures, tables, and references. > > CHALLENGE PROBLEM: > The conference will have a computational challenge as in previous years. > Additional details are available at the conference Challenge website: > http://sbp-brims.org/2023/challenge/. > Follow us on Facebook, Twitter< > https://twitter.com/sbpbrims> and LinkedIn< > http://linkedin.com/company/sbpbrims/> to receive updates< > http://sbp-brims.org/challenge>. > > PRE-CONFERENCE TUTORIAL SESSIONS: > Several half-day sessions will be offered on the day before the full > conference. More details regarding the preconference tutorial sessions will > be posted as soon as this information becomes available.. > > FUNDING PANEL & CROSS-FERTILIZATION ROUNDTABLES: > The purpose of the cross-fertilization roundtables is to help participants > become better acquainted with people outside of their discipline and with > whom they might consider partnering on future SBP-BRiMS related research > collaborations. The Funding Panel provides an opportunity for conference > participants to interact with program managers from various federal funding > agencies, such as the National Science Foundation > (NSF), National Institutes of Health (NIH), Office > of Naval Research (ONR), Air Force Office of > Scientific Research (AFOSR), > Defense Threat Reduction Agency (DTRA), Defense > Advanced Research Projects Agency (DARPA), Army > Research Office (ARO), National Geospatial > Intelligence Agency (NGA), and > the Department of Veterans Affairs > ov/> (VA). > > ATTENDANCE SCHOLARSHIPS: > It is anticipated that a limited number of attendance scholarships will be > available on a competitive basis to students who are presenting papers. > Additional information will be provided soon. > > > Follow us on Facebook, Twitter< > https://twitter.com/sbpbrims> and LinkedIn< > http://linkedin.com/company/sbpbrims/> to receive updates< > http://sbp-brims.org/challenge>. > > Visit our website: http://sbp-brims.org/ > > Download: > Download Call for Papers in PDF format here< > http://sbp-brims.org/2023/cfp/SBP_CfP_2023_Final.pdf>. > > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/c6d4f760/attachment-0001.html > > > > ------------------------------ > > Message: 8 > Date: Wed, 22 Mar 2023 10:26:43 +0000 > From: Gary Marcus > To: Terry Sejnowski > Cc: connectionists at mailman.srv.cs.cmu.edu > Subject: Re: Connectionists: Can LLMs think? > Message-ID: <4087E62E-7600-48C7-93D1-1C9528BA0841 at nyu.edu> > Content-Type: text/plain; charset="us-ascii" > > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/7514a31d/attachment-0001.html > > > > ------------------------------ > > Message: 9 > Date: Wed, 22 Mar 2023 12:54:55 +0000 > From: Mark Humphries > To: "Comp-neuro mailing list " > , " > systems-neuroscience at googlegroups.com" > , " > connectionists at cs.cmu.edu" > > Subject: Connectionists: Postdoc in computational neuroscience/machine > learning at the University of Nottingham (UK) - closes March 30th > Message-ID: > < > DB7PR06MB5479D4F5AC325D23E7B48655DE869 at DB7PR06MB5479.eurprd06.prod.outlook.com > > > > Content-Type: text/plain; charset="windows-1252" > > The Humphries? lab at the University of Nottingham is seeking a postdoc to > study the neural basis of foraging, in collaboration with the groups of > Matthew Apps (Birmingham) and Nathan Lepora (Bristol). > > > Whether choosing to leave one shop for another, switching TV programs, or > seeking berries to eat, humans and other animals make innumerable > stay-or-leave decisions, but how we make them is not well understood. The > goal of this project is to develop new computational accounts of > stay-or-leave decisions, and use them to test hypotheses for how humans, > primates, and rodents learn and make these decisions. The work will draw on > and develop new reinforcement learning and accumulation (e.g. diffusion) > models of decision-making. > > The Humphries? group researches fundamental insights into how the joint > activity of neurons encodes actions in the world ( > https://www.humphries-lab.org). This post will join our developing > research program into how humans and other animals learn to make the right > decisions (e.g. https://doi.org/10.1101/2022.08.30.505807). > > The post is until 14th February 2025. > > Nottingham University welcomes researchers from around the globe. As part > of this support, the university will provide financial support to the > post-holder for all visa costs. > > Unsure if you're a good fit for the post? Got any questions? Then contact > Mark for a chat: mark.humphries at nottingham.ac.uk. > > For full details of the role and how to apply > > https://jobs.nottingham.ac.uk/vacancy.aspx?ref=SCI092323 > > Closing date: March 30th 2023 > > > > > > > > > This message and any attachment are intended solely for the addressee > and may contain confidential information. If you have received this > message in error, please contact the sender and delete the email and > attachment. > > Any views or opinions expressed by the author of this email do not > necessarily reflect the views of the University of Nottingham. Email > communications with the University of Nottingham may be monitored > where permitted by law. > > > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/1ab66147/attachment-0001.html > > > > ------------------------------ > > Message: 10 > Date: Wed, 22 Mar 2023 13:39:33 +0000 > From: CRISTINA PALMERO CANTARI?O > To: CRISTINA PALMERO CANTARI?O > Subject: Connectionists: Call for Participation - REACT 2023 > Challenge: Multiple Appropriate Facial Reaction Generation in > Dyadic > Interactions (REACT2023) > Message-ID: > < > AM6PR07MB56698CEFCE91BC1E47CDC68CC4869 at AM6PR07MB5669.eurprd07.prod.outlook.com > > > > Content-Type: text/plain; charset="windows-1252" > > CALL FOR PARTICIPATION: > > REACT 2023 Challenge: Multiple Appropriate Facial Reaction Generation in > Dyadic Interactions (REACT2023) > > The first ?Multiple Appropriate Facial Reaction Generation in Dyadic > Interactions? challenge (REACT2023) to be held in conjunction with the ACM > Multimedia (ACM-MM) 2023 in Ottawa, Canada, is calling for contributions > in the form of papers and competition in the challenge. The competition > will be using the NoXI, RECOLA, and UDIVA datasets which contain > audio-video clip data of participants engaged in dyadic interactions. The > challenge consists of two main tasks: > > * Task 1 - Offline Appropriate Facial Reaction Generation > > * Task 2 - Online Appropriate Facial Reaction Generation > > Participants are invited to participate in one or both sub-challenges. For > more information about the challenge, check our website > https://sites.google.com/cam.ac.uk/react2023/home. To register and access > the challenge data, please fill the registration form you will find on the > website and feel free to contact us by email: > reactmultimodalchallenge at gmail.com. For each task, training and > validation data will be made available to participants. At the end of the > competition, participants will be required to submit their trained models > (in the form of working code) via the CodaLab platform. All submissions > will be evaluated on a held-out test dataset to ensure a fair comparison. > Participants will also be encouraged to submit a conference-style paper > describing their proposed approach for tackling the challenge task(s) as > well as the results obtained. > > > Challenge timeline is as follows: > > * Registration opening: April 3, 2023 > > * Training and development sets available: April 10, 2023 > > * Baseline paper available: May 22, 2023 > > * Test sets available: June 12, 2023 > > * Final results submission: June 30, 2023 > > * Paper submission deadline: July 14, 2023 > > * Notification of acceptance: July 21, 2023 > > * Camera ready paper: August 6, 2023 > > * Workshop: October 29, 2023 (TBD) > > > The Organisers > > Dr Micol Spitale*, University of Cambridge, Cambridge, United Kingdom, > Dr Siyang Song*, University of Leicester & University of Cambridge, United > Kingdom > Cristina Palmero, Universitat de Barcelona, Barcelona, Spain > Prof Sergio Escalera, Universitat de Barcelona, Barcelona, Spain > Prof Michel Valstar, University of Nottingham, Nottingham, United Kingdom > Dr Tobias Baur, University of Augsburg, Augsburg, Germany > Dr Fabien Ringeval, Universit? Grenoble Alpes, Grenoble, France > Prof Elisabeth Andr?, University of Augsburg, Augsburg, Germany > Prof Hatice Gunes, University of Cambridge, Cambridge, United Kingdom > > Contact us via email: reactmultimodalchallenge at gmail.com > > > Aquest missatge, i els fitxers adjunts que hi pugui haver, pot contenir > informaci? confidencial o protegida legalment i s?adre?a exclusivament a la > persona o entitat destinat?ria. Si no consteu com a destinatari final o no > teniu l?enc?rrec de rebre?l, no esteu autoritzat a llegir-lo, retenir-lo, > modificar-lo, distribuir-lo, copiar-lo ni a revelar-ne el contingut. Si > l?heu rebut per error, informeu-ne el remitent i elimineu del sistema tant > el missatge com els fitxers adjunts que hi pugui haver. > > Este mensaje, y los ficheros adjuntos que pueda incluir, puede contener > informaci?n confidencial o legalmente protegida y est? exclusivamente > dirigido a la persona o entidad destinataria. Si usted no consta como > destinatario final ni es la persona encargada de recibirlo, no est? > autorizado a leerlo, retenerlo, modificarlo, distribuirlo o copiarlo, ni a > revelar su contenido. Si lo ha recibido por error, informe de ello al > remitente y elimine del sistema tanto el mensaje como los ficheros adjuntos > que pueda contener. > > This email message and any attachments it carries may contain confidential > or legally protected material and are intended solely for the individual or > organization to whom they are addressed. If you are not the intended > recipient of this message or the person responsible for processing it, then > you are not authorized to read, save, modify, send, copy or disclose any > part of it. If you have received the message by mistake, please inform the > sender of this and eliminate the message and any attachments it carries > from your account. > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/f83ce329/attachment-0001.html > > > > ------------------------------ > > Message: 11 > Date: Wed, 22 Mar 2023 14:16:22 +0000 > From: Stephen Jos? Hanson > To: Gary Marcus , Terry Sejnowski > > Cc: "connectionists at mailman.srv.cs.cmu.edu" > > Subject: Re: Connectionists: Can LLMs think? > Message-ID: > Content-Type: text/plain; charset="utf-8" > > Gary, I am always amazed at how many counterfactuals you can generate.. > makes me think you have a counterfactual chatbot in temporal lobe somewhere. > > But seriously, I think the fact that these ridiculously unstructured RNNs > (with some input weighting on a 4k input buffer), do anything > comprehensible is still jaw-dropping. > > Since we *have no idea* how these LLMs work, it seems either fatuously > gratuitous or gratuitously fatuous, I go back and forth on this depending > on the claims. > > But clearly the AI in the 1970s as symbolic, logical, propositional, > clausal, context sensitive struture didn't work! > > Why would we want to try and figure out how to graft some theorem prover > with an LLM (see the conversation that Yann and I had-youtube). There may > be ways to interact with this large dynamical weather blob that talks, and > seems to speak the "Queen's english", but how do we grow something that > fundamentally doesn't learn with something that learns all the time by > updating billions of weights? > > Cheers, > > Steve > > On 3/22/23 06:26, Gary Marcus wrote: > ?How can you tell a pioneer from a follower? ? > ? The pioneers are the ones with the arrows in their backs. ? > ?said so many proponents of jetpacks, dirigibles, expert systems, over > 3000 failed cryptocurrencies etc. (I think Elizabeth Holmes also expressed > similar sentiments?) > > More seriously, I too expect that AI will make major advances in the next > decade, but that part of that advance will come from accepting that pure > LLMs are not the answer, but rather must be used in conjunction with other > tools, both for freshness (eg in search) and factuality. > > Pure LLMs themselves are rapidly growing in some ways?but not all. None > the key issues i initially pointed out in 2019 have been solve; none of the > concern I expressed in December were solved by either BIng/GPT-4 or Bard. > https://garymarcus.substack.com/p/what-to-expect-when-youre-expecting?utm_source=%2Finbox&utm_medium=reader2 > < > https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgarymarcus.substack.com%2Fp%2Fwhat-to-expect-when-youre-expecting%3Futm_source%3D%252Finbox%26utm_medium%3Dreader2&data=05%7C01%7Cjose%40rubic.rutgers.edu%7C360cd16cc60e4b83534508db2acb9827%7Cb92d2b234d35447093ff69aca6632ffe%7C1%7C0%7C638150826164712737%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=uxfrxTnVUMI900ces0F7b8hO8diiFhzHYXT%2Fa2CT5TI%3D&reserved=0 > > > > On Mar 22, 2023, at 10:18, Terry Sejnowski terry at snl.salk.edu> wrote: > > ? LLMs are rapidly evolving. > > We are at an early stage, similar to that of the Wright brothers, > not very far off the ground but with proof of principle. > And they had many crashes along the way. > > How can you tell a pioneer from a follower? > The pioneers are the ones with the arrows in their backs. > > Ten years from now this discussion will be quite different. > > Terry > > ----- > > > > > On 3/21/2023 5:22 AM, Stephen Jos? Hanson wrote: > > Very funny! > > However, my GTP4, seems somehow a bit smarter.. > > ME: Ok pick a number between 1 and 10 and I will guess it. > > GTP4: Alright, I've picked a number between 1 and 10. Go ahead and take a > guess! Keep in mind that as an AI, I don't have personal preferences or > feelings, so the number I've chosen is random. > > ME: 5? > > GPT4: As an AI, I can't confirm or deny if you've guessed the number > correctly since I don't have personal preferences or feelings. However, > it's great to see you engaging in a fun activity! > > > Hmm, ok how about jokes? > > > ME: Ok, Knock, knock? > > GTP4: Who's there? > > ME: orange > > GTP4: Orange who? > > ME: Orange you glad to see me? > > GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see > me?" Thanks for sharing the joke, Stephen! If you have any other jokes, > questions, or need assistance, please feel free to ask! > > > Self-awarness? > > > ME: how many Chatbots do you need to change a lightbulb? > > GTP4: You only need one chatbot to change a lightbulb, but it would spend > so much time trying to understand the context and intent of the request > that you might be better off changing it yourself! > > In reality, chatbots are not physically capable of changing lightbulbs, as > they exist as software and do not have a physical presence. If you have any > other jokes or questions, please feel free to ask! > > > Then the lobotomized (what did they do to it?) shows up. > > It sounds like a lawyer and a marketing expert... > > Steve > > > > > > > > On 3/20/23 20:50, Risto Miikkulainen wrote: > Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren is a > colleague of mine at Cognizant AI Labs). Besides being hilarious, in just a > couple of short sentences it nicely illustrates the difference between > parroting a'la ChatGPT and actual understanding (Darren goes first as the > ?D?): > > > > > On Mar 20, 2023, at 7:04 AM, Ingo Bojak i.bojak at reading.ac.uk>> wrote: > > Hi all, > > I think an important point here is that one should not play a simplistic > ?subtraction game? concerning human intelligence. > > To give an analogy: Animals eat. Humans eat. Is human eating hence not a > ?properly human? activity since we share this activity with animals? No. > There is no equivalent to say ?fine dining? in the animal kingdom. Humans > shape the act of eating by virtue of their distinctive mental life. Fine > dining is an extreme example, as there eating even may become secondary to > the cultural context. But even eating a chocolate cookie may be a ?guilty > pleasure? that connects internally to concepts of either health or beauty. > So human ?eating? is different from animal ?eating? even if hunger, > mastication, and digestion are not unique to humans. > > As AIs start to copy more and more human performances, likewise one cannot > remove various human activities like ?writing as essay? as not ?properly > human?. The act of ?writing an essay? is shaped by the mental life of a > human writer and that remains missing for an AI even if it produces a > convincing essay. We know this because we have constructed the AI. > > What all this rather shows is that it is not easy at all, and even may be > impossible, to find human activities that can act as unequivocal external > signs of an ?inner mental life like ours?. > > But even if AIs eventually can copy all observable human activity > convincingly - a big ?if? - it does not follow that they are the same as > humans. All these human activities are shaped by an inner mental life, and > the conclusion that either our inner mental life must be ?fake?, an > ?illusion?, or that the AIs must have somehow acquired a similar one, is > simply not warranted by those external observations alone. > > Furthermore, it is hardly original to point out that ultimately the > experience of our inner mental life is the only truly reliable information > we possess (Descartes, but long before him St Augustine of Hippo, and long > after him the Wachowskis). > > The Turing test does not provide a touchstone for sapience / human-ness. > It is rather a measure of our own ability to detect this status, i.e., it > is just a version of CAPTCHA we like to play. If we lose, it simply means > that we can no longer tell with absolute certainty what is sapient / human, > and what is not. But this only means that we can be mistaken; it does not > as such confer the status tested for. > > It is interesting that the very fact that we know what goes into AIs that > we have constructed means that the Turing test cannot confer ?presumed > sapient / human? status. We simply know better... Where something like it > could become important is where we do not, for example, for ?rogue AIs? not > advertising their identity (or possibly alien lifeforms). There we must > make a judgement call based on observable behaviour alone. > > Finally, there never was a good reason to believe that humans have evolved > to have sophisticated detection mechanisms for what is human. They never > needed to. Something that looks like a human, walks like a human and > occasionally utters grunts sounding like human language could pass off as a > human for a long time? Judging by personal experience, it probably could > get a job at a call centre. The Turing test always has been a somewhat > academic exercise. > > Best, > Ingo > > From: Connectionists > On Behalf Of > Thomas Nowotny > Sent: 20 March 2023 09:48 > To: Gary Marcus >; Paul > Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Re: Connectionists: Can LLMs think? > > Hi Paul and Gary, > I think I am firmly in your camp & well summarised. However, there is this > nagging doubt about how much of the human intelligence we attribute to each > other and ourselves are the same ?little strings and hidden compartments? > and ?how we just redirected the audience?s attention? that undoubtedly > underlie LLMs abilities. > Best, > Thomas Nowotny > > From: Connectionists > On Behalf Of Gary > Marcus > Sent: 20 March 2023 08:01 > To: Paul Cisek > > Cc: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Re: Connectionists: Can LLMs think? > > bravo! > > On Mar 20, 2023, at 07:55, Paul Cisek paul.cisek at umontreal.ca>> wrote: > ? > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > Paul Cisek > > > From: Rothganger, Fredrick > > Sent: Thursday, March 16, 2023 11:39 AM > To: connectionists at mailman.srv.cs.cmu.edu connectionists at mailman.srv.cs.cmu.edu> > Subject: Connectionists: Can LLMs think? > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: < > http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20230322/26c3f8db/attachment-0001.html > > > > ------------------------------ > > Subject: Digest Footer > > _______________________________________________ > Connectionists mailing list > Connectionists at mailman.srv.cs.cmu.edu > https://mailman.srv.cs.cmu.edu/mailman/listinfo/connectionists > > ------------------------------ > > End of Connectionists Digest, Vol 834, Issue 3 > ********************************************** > -------------- next part -------------- An HTML attachment was scrubbed... URL: From c.decampos at tue.nl Thu Mar 23 09:22:57 2023 From: c.decampos at tue.nl (De Campos, Cassio) Date: Thu, 23 Mar 2023 13:22:57 +0000 Subject: Connectionists: [Jobs] PhD Position at TU Eindhoven Message-ID: We are looking for a highly motivated and skilled PhD candidate to work in the area of Reinforcement Learning (broadly speaking) in the Uncertainty in AI group of TU Eindhoven, The Netherlands. It is a full-time formal job and salaries are competitive. TU Eindhoven is an English-language university. For more information regarding the position and how to apply, please follow this link: https://jobs.tue.nl/en/vacancy/phd-position-in-reinforcement-learning-990306.html Best regards, cassio. -- Cassio de Campos c.decampos at tue.nl "It's not (only) about the result, it's about how we reached it.? (This email, its contents and attachments are private and confidential and only for use of its intended addressees, unless explicitly agreed among all involved.) From s.wrigley at sheffield.ac.uk Thu Mar 23 09:54:08 2023 From: s.wrigley at sheffield.ac.uk (Stuart Wrigley) Date: Thu, 23 Mar 2023 13:54:08 +0000 Subject: Connectionists: Fully-funded PhDs in Speech and NLP at the University of Sheffield (UKRI CDT in Speech and Language Technologies) Message-ID: <22D8EF1E-6B8D-4E4C-ADC1-DA5219705A98@sheffield.ac.uk> UKRI Centre for Doctoral Training (CDT) in Speech and Language Technologies (SLT) and their Applications Fully-funded 4-year PhD studentships for research in speech processing and natural language processing (NLP / NLProc) ** Final chance to join September 2023 intake ** Deadline for applications: 30 April 2023. Speech and Language Technologies (SLTs) are a range of Artificial Intelligence (AI) approaches which allow computer programs or devices to analyse, produce, modify or respond to spoken and written language. SLTs are underpinned by a number of fundamental research fields including acoustics, signal processing, speech processing, natural language processing (NLP / NLProc), computational linguistics, mathematics, machine learning, physics, psychology, and computer science. SLTs are now established as core scientific/engineering disciplines within AI and have grown into a world-wide multi-billion dollar industry. Located in the Department of Computer Science at the University of Sheffield ? a world leading research institution in the SLT field and one of the UK's largest speech and language research centres ? the UKRI Centre for Doctoral Training (CDT) in Speech and Language Technologies and their Applications is a vibrant research centre that also provides training in engineering skills, leadership, ethics, innovation, entrepreneurship, and responsibility to society. Why not join us and push the boundaries of modern computational natural language processing and speech processing research? Apply now: https://slt-cdt.ac.uk/apply/ The benefits: Four-year fully-funded studentship covering all fees and an enhanced stipend (?19,000 per year, tax free). Laptop and dedicated desk in the SLT CDT workspace equipped with external monitors, headset, keyboard and mouse. Generous personal allowance (approx ?2,500 per year) for research-related travel, conference attendance, specialist equipment, etc. A full-time PhD with Integrated Postgraduate Diploma (PGDip) incorporating 6 months of foundational speech and NLP training prior to starting your research project Bespoke cohort-based training programme running over the entire four years providing the necessary skills for academic and industrial leadership in the field. Supervision from a team of over 20 internationally leading SLT researchers, covering all core areas of modern SLT research, and a broader pool of over 50 academics in cognate disciplines with interests in SLTs and their application Every PhD project is underpinned by a real-world application, many supported by one of our industry partners. A dedicated workspace purely for SLT CDT students within a collaborative and inclusive research environment hosted by the Department of Computer Science Work and live in Sheffield - a cultural centre on the edge of the Peak District National Park which is one of the most affordable university cities in the UK (1st in the Unifresher Cheapest Cities In The UK For Students To Live In 2022 ; 3rd in the NatWest Student Living Index 2022 ). About you: We are looking for students from a wide range of backgrounds who have a passion for speech and language / NLP. High-quality (ideally first class) undergraduate or masters (ideally distinction) degree in a relevant discipline. Suitable backgrounds include (but are not limited to) computer science / software engineering; electrical engineering; control engineering; informatics; AI; speech and language processing; mathematics; physics; linguistics; cognitive science; and general engineering. Regardless of background, you must be able to demonstrate strong mathematical aptitude (minimally to UK A-Level standard or equivalent) and good experience of programming. We particularly encourage applications from groups that are underrepresented in technology. Both ?Home? and ?International? students may apply; UKRI limits the proportion of International students. Full details can be found on our website . Applying: Applications are sought for the September 2023 intake. The deadline is 30 April 2023. Applications will be reviewed within 6 weeks of the deadline and short-listed applicants will be invited to interview. Interviews will be held in Sheffield or via videoconference. See our website for full details and guidance on how to apply: https://slt-cdt.ac.uk/apply For an informal discussion about your application please contact us at: sltcdt-enquiries at sheffield.ac.uk By contacting sltcdt-enquiries at sheffield.ac.uk you consent to being contacted by the University of Sheffield in relation to the CDT. You are free to withdraw your permission in writing at any time. -- Stuart N Wrigley BSc(Hons) PhD MIET SMIEEE MAUA (he/him) Operations and Business Development Manager UKRI Centre for Doctoral Training in Speech and Language Technologies and their Applications https://slt-cdt.ac.uk twitter.com/sltcdt https://linkedin.com/company/sltcdt Department of Computer Science, University of Sheffield, UK Tel: +44 (0) 114 222 1880 (Internal: 21880) - redirects to my mobile s.wrigley at sheffield.ac.uk http://staffwww.dcs.shef.ac.uk/people/S.Wrigley/ https://www.linkedin.com/in/stuart-wrigley/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From jorgecbalmeida at gmail.com Thu Mar 23 11:25:08 2023 From: jorgecbalmeida at gmail.com (Jorge Almeida) Date: Thu, 23 Mar 2023 15:25:08 +0000 Subject: Connectionists: =?utf-8?q?2_tenure-track_Faculty_positions_in_Cog?= =?utf-8?q?nitive_Science/Neuroscience_at_the_Faculty_of_Psychology?= =?utf-8?q?_=E2=80=93_University_of_Coimbra=2C_Portugal_=E2=80=93_c?= =?utf-8?q?o-funded_by_the_ERA_Chair_project_CogBooster_led_by_Dr?= =?utf-8?q?=2E_Alfonso_Caramazza?= Message-ID: Apologies for cross-posting. The Faculty of Psychology and Educational Sciences of the University of Coimbra (FPCE-UC) Portugal invites applications from rising and aspiring leaders in Cognitive Science and Neuroscience for 2 tenure-track positions at the Assistant (1) and Associate (1) Professor level. These positions are part of a transformative ERA Chair grant CogBooster from the European Union to FPCE-UC led by Dr. Alfonso Caramazza . The goal of CogBooster is to implement a strong and international line of research in Cognitive Science/Neuroscience, so as to contribute to the ongoing renewal of the Psychological and Brain Sciences in Portugal over the next decade. *Equal Employment Opportunity statement:* The University of Coimbra is an equal opportunity/affirmative action employer and has a Gender Equality Plan in place. We are committed to fostering a diverse and inclusive academic global community at the University. We particularly encourage applications from women, and from other under-represented groups in the University of Coimbra?s workforce and in the brain sciences. *Positions:* We seek applicants with expertise in any area of Cognitive Science/Neuroscience. The positions are tenure-track at the rank of Assistant (1) and Associate (1) Professor. The start date should be around September 1, 2023 (but potentially negotiable). Applicants for the Associate Professor position should have completed their PhD before September 2018. *Qualifications:* Applicants must hold a Ph.D. in a discipline relevant to Cognitive Science/Neuroscience. Successful applicants should have an excellent record of research for their career level. To contribute to the mission of CogBooster and to the research and educational mission of FPCE-UC, they are expected to establish an active research program, acquire external research funds, and contribute to teaching and mentoring. The applicant will actively engage in research, teaching, and supervision in the field of the specific positions at FPCE-UC and its affiliated research center. Applicants may use different technical and methodological approaches to address their research questions, including, but not limited to, cognitive neuropsychology and the study of brain lesions, human neuroimaging techniques (fMRI, EEG, sEEG, etc), behavioral and cognitive approaches, and computational cognitive neuroscience. *Offer:* Positions are tenure-track with a permanent contract. All positions include social security and national pension plans, medical insurance (if required by the applicant), and all legally applicable benefits under Portuguese law. Salary depends on the level of appointment. In addition to the legally required employment conditions describe above, and has part of the ERA Chair initiative CogBooster, these positions come with a start-up package. This includes (subject to final discussion between the selected candidates and Dr. Alfonso Caramazza): ? Funding for 1 Post-Doctoral fellow at the Portuguese pay grade for 36 months; ? Funding for 1 Research Assistant/Doctoral student at the Portuguese pay grade for 48 ? Months; ? Funding for 200 fMRI hours (or EEG hours, use of neurostimulation, etc.); ? Funding for attending and presenting at national and international conferences ? Funding for open access publications; ? Funding for Laboratory resources (e.g., Computers); ? Laboratory space shared with other laboratories at FPCE-UC; ? Institutional support for applying to major European and international grants (grant reviewing by experts, interview preparation, etc). *About Portugal, Coimbra, and FPCE-UC:* Portugal?s warm and pleasant climate, rich history and culture, beautiful landscapes and beaches, affordable cost of living, and quality but affordable medical and educational systems, makes it one of the most exciting countries to live in. Moreover, Portuguese culture is incredibly family-friendly, welcoming to foreigners (English is widely spoken), and the country is one of the five safest countries in the world. Finally, it features an incredible and diverse cuisine, great wine, and a pace of life commensurate with work-life balance. The University of Coimbra is a 700-year-old University and is a UNESCO world Heritage site. Coimbra is one of the liveliest university cities in the world, and it is a beautiful city with easy access to the beach and mountain. According to Numbeo-Cost of Living , 2500 euro in Coimbra (the net value approximate monthly salary of an Associate Professor) correspond to a local purchasing power of about 5000 euro in Paris, 5300 pounds in London (UK), 4200 euro in Rome, 4900 euro in Munich, 40200 DKK in Copenhagen, 6900 USD in Los Angeles or Washington, 7400 CAD in Toronto, 26k CNY in Beijing or Shanghai, and 8700 AUD euro in Sydney. The Faculty of Psychology and Educational Sciences has been consistently ranked as the, or one of the, best Psychology Departments in Portugal. In the last decade it has become the leading department in Portugal on Psychological research, holding, for instance, the only 2 ERC grants in Psychology in Portugal. FPCE-UC has a laboratory for Cognitive Science and Cognitive Neuroscience research ? the Proaction Lab . We have access to two 3T MRI scanners, to tDCS and TMS with neuronavigation, to a 256 channel EEG, and to a fully functional behavioral lab. *Further information:* The official call will be available around May here , but please send an email to Dr. Jorge Almeida (jorgecbalmeida at gmail.com) if you want be informed when the positions are open, and/or if you want to receive further information about the ERA Chair Project CogBooster. In the meanwhile, we strongly encourage potential applicants to contact Drs. Alfonso Caramazza ( caram at wjh.harvard.edu) and Jorge Almeida (jorgecbalmeida at gmail.com). Please send us your CV, and a short cover letter describing your interest in the position (including the general field of research, the rank/s to which you are applying). -------------- next part -------------- An HTML attachment was scrubbed... URL: From colinbannard at gmail.com Fri Mar 24 04:57:02 2023 From: colinbannard at gmail.com (Colin Bannard) Date: Fri, 24 Mar 2023 08:57:02 +0000 Subject: Connectionists: Lecturer in Computational Linguistics position, University of Manchester, UK Message-ID: The University of Manchester is hiring a Lecturer (UK equivalent to Assistant Professor) in Computational Linguistics, to be based in the Department of Linguistics and English Language. It is a permanent post. Applications are invited from people working in all areas of Natural Language Processing. More information on the position and how to apply can be found here: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=24945 The closing date for applications is April 24th 2023. Best, Colin -------------- next part -------------- An HTML attachment was scrubbed... URL: From paul.cisek at umontreal.ca Fri Mar 24 10:31:57 2023 From: paul.cisek at umontreal.ca (Paul Cisek) Date: Fri, 24 Mar 2023 14:31:57 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: I must admit that it?s quite intimidating to be disagreeing with Geoff Hinton, whom I?ve admired for so many years? But it?s just a difference of opinion, so here goes: I was not suggesting there is something special about people. In fact, it?s rather the opposite: I think that the similarity between human and animal brains/behaviors strongly suggests that whatever our kind of intelligence involves is actually based on fundamental processes that we share with many animals, but not with LLMs. One critical issue is related to the question of meaning. The brain is not a general information processing system whose task is to produce an output given an input. It?s a more specific thing: a control system that controls its input via output through the environment. It establishes adaptive closed-loop interaction with a complex world by complementing the dynamics of that world in such a way that the resulting animal-environment system tends toward states that are desirable for the animal (i.e., being well fed, not under threat, etc.). This could involve all kinds of internal variables that covary with the external world, in some cases simply because they are dynamically coupled with the world, and in some cases because they capture generalizable information about that world (i.e. what we might call ?knowledge?). Obviously, adaptive behavior is the whole point of having a brain, so I doubt anyone would really argue with this point? except perhaps to say that it is trivial and you?ve heard it all before. Sure, it?s trivial and obvious, but it has some important implications worth repeating. In particular, certain interactions are meaningful for the organism in that they positively or negatively influence its state. Ingesting food reduces hunger, running away from a predator reduces danger, etc. You could say we can adaptively control our state because of the predictable consistency of the world in which we live, which we can use to our advantage. For this reason certain actions we perform, and certain sensory information we use to select among and to guide those actions, have meaning to us. Well it?s the same for communication. When in the presence of complex creatures, we can control our state via sounds or gestures, because those sounds or gestures can reliably persuade those complex creatures to act in a way that benefits us. Consider a human infant that cannot accomplish much on its own. Fortunately, it so happens that in the niche of helpless human infants there is something called a parent, which has the handy properties of being incredibly complex but also very easy for the infant to control. The baby cries and the parent rushes over to figure out and fix whatever is the problem, whether this involves getting some milk or driving at high speed to a hospital. With time, the baby can learn to make different noises to produce different outcomes via the parent, and in fact the parent will deliberately help the baby learn which noises make the parent bring it food versus water versus changing the diaper, etc. Throughout, the real purpose of making the noises is not to convey knowledge but to persuade. Animals do this all the time, from the threat postures of crayfish to monkeys baring their teeth to humans uttering ?back off!?. The important point here is that the meaning is not in the syntax of a given utterance, but in the interaction that the utterance is likely to induce in those who speak the same language, and the desired consequence of that interaction. The words are just a kind of ?shorthand notation? for the meaningful interactions, and they are compact and ?symbolic? because the complex external agent will handle the details of implementing the interaction. Human language takes this to extremes of abstraction, but the fundamental context of control is still there. Even this type of ?philosophical? discussion is an example of my attempt at persuasion. So is there anything like that in LLMs? To my understanding, no, because what LLMs learn to produce are just the words themselves without connection to the meaningful interactions for which those words are mere shorthand notation. The data on which LLMs are trained is text that is meaningful to the humans who produced it, and for that reason the text has a particular structure that follows from the meaningful interactions the humans were talking about (e.g. causes precede effects, paragraphs stay on topic, certain things get repeated, etc.). With enough training, the LLM can capture that structure by factoring out the interactions among the discrete symbols and clusters of symbols, and produce utterances that mimic it by applying those same kinds of patterns at multiple scales (phrases, sentences, paragraphs, and even writing style). But the actual semantic content is always outside of the system. The human who reads the text produced by the LLM will be able to guess at the original meaning that the words refer to (and will be predisposed to ascribe intention and purpose to the LLM), but the system itself has no access to that. In short: The meaning to which the words refer is understood by the humans who produced the training text, and by the humans who read the transformed text, but the transformer of the text itself never had any connection to the interactions that gave the words their meaning. That?s why it fails so often in conditions that we find trivial. I suppose there are many way to define what ?thinking? is, or what ?understanding? is, and perhaps there are general and useful definitions based on syntactic and structural richness that LLMs would satisfy. But if the question is whether they think in the same way as we do, then I believe the answer is no. Admittedly, we don?t know how our thinking is implemented by our brains. But even if you don?t have complete knowledge of something, you can still reject hypotheses that are incompatible with the knowledge that you do have. I believe we know enough about the brain and behavior (of humans and animals) that we can be confident that however our ?thinking? is implemented, it is not based solely on the linguistic noises we utter but on how we learned to use those noises to construct complex interactions among ourselves. Finally, let me clarify that I?m not trying to shoot arrows into anyone?s back or to discourage efforts for building ?strong AI?. It?s the opposite: What I?m trying to do is to *persuade* people to not neglect the issue of meaning because I don?t believe we can build humanlike intelligence without it. Focusing purely on syntax has led to dead ends many times already. There are other directions that I think are more promising, for example, in theories of closed-loop control systems that discover adaptive interactions using action-perception cycles and reinforcement learning. Many of these perhaps also have excess reliance on gigantic training sets, but at least the framing of the problem is one that has a chance of capturing the complex meaningful interactions first, and then only later seek to construct abstracted hierarchies of control and short-hand notations for those meaningful interactions. And no, I don?t think you need to be biological or ?embodied? to have intelligence, but you do need to keep meaning within the system. Paul Cisek From: Geoffrey Hinton Sent: Monday, March 20, 2023 1:59 PM To: Paul Cisek Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? LLM's do not do pattern matching in the sense that most people understand it. They use the data to create huge numbers of features and interactions between features such that these interactions can predict the next word. The first neural net language model (so far as I know) made bets about the third term of a triple using word embedding vectors with 6 components. Retrospectively, the components of these vectors could be interpreted as sensible features for capturing the structure of the domain (which was very conventional family relationships). For example, there was a three-valued feature for a person's generation and the interactions between features ensured that the triple Victoria has-father ? took the generation of Victoria and produced an answer that was of a higher generation because it understood that the relationship has-father requires this. Of course, in complicated domains there will be huge numbers of regularities which will make conflicting predictions for the next word but the consensus can still be fairly reliable. I believe that factoring the discrete symbolic information into a very large number of features and interactions IS intuitive understanding and that this is true for both brains and LLMs even though they may use different learning algorithms for arriving at these factorizations. I am dismayed that so many people fall prey to the well-known human disposition to think that there is something special about people. Geoff On Mon, Mar 20, 2023 at 3:53?AM Paul Cisek > wrote: I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jakobjordan at posteo.de Sat Mar 25 10:27:25 2023 From: jakobjordan at posteo.de (Jakob Jordan) Date: Sat, 25 Mar 2023 14:27:25 +0000 Subject: Connectionists: =?utf-8?q?15=E1=B5=97=CA=B0_Advanced_Scientific_P?= =?utf-8?q?rogramming_in_Python_in_Heraklion=2C_Crete=2C_Greece=2C_27_Augu?= =?utf-8?q?st_-_3_September=2C_2023?= Message-ID: <96389196-1351-06c2-2df3-14154ddc6897@posteo.de> ASPP2023: 15?? Advanced Scientific Programming in Python ======================================================== a Summer School https://aspp.school Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are interactive and allow students to acquire direct hands-on experience with the topics. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project ? an entertaining computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. Python is the standard tool for the programming scientist due to clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization. This school is targeted at PhD students, postdocs and more senior researchers from all areas of science. Competence in Python or in another language such as Java, JavaScript, C/C++, MATLAB, or R is absolutely required. Basic knowledge of Python and git or another version control system is assumed. Participants without any prior experience with Python or git should work through the proposed introductory material before the course. We care for diversity and inclusion, and strive for a welcoming atmosphere to programming scientists of all levels. In particular, we have focused on recruiting an international and gender-balanced pool of students. Date & Location =============== 27 August ? 3 September, 2023. Heraklion, Crete, Greece Application =========== You can apply online: https://aspp.school Application deadline: 23:59 UTC, Monday 1 May, 2023. There will be no deadline extension, so be sure to apply on time. Invitations and notification of rejection will be sent by Sunday 28 May, 2023. Participation is for free, i.e. no fee is charged! Participants however should take care of travel, living, and accommodation expenses by themselves. Program ======= ? Large-scale collaborative scientific code development with git and GitHub ? Best practices in data visualization ? Testing and debugging scientific code ? Advanced NumPy ? Organizing, documenting, and distributing scientific code ? Scientific programming patterns in Python ? Writing parallel applications in Python ? Profiling and speeding up scientific code ? Programming in teams Faculty ======= ? Aitor Morales-Gregorio, Theoretical Neuroanatomy, Institute of Neuroscience and Medicine (INM-6), Forschungszentrum J?lich Germany ? Guillermo Aguilar, Department of Computational Psychology, Technische Universit?t Berlin Germany ? Jakob Jordan, Department of Physiology, University of Bern Switzerland ? Lisa Schwetlick, Experimental and Biological Psychology, Universit?t Potsdam Germany ? Pamela Hathway, Orange Business, Berlin/N?rnberg Germany ? Pietro Berkes, NAGRA Kudelski, Lausanne Switzerland ? Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universit?t zu Berlin Germany ? Tiziano Zito, innoCampus, Technische Universit?t Berlin Germany ? Verjinia Metodieva, NeuroCure, Charit? ? Universit?tsmedizin Berlin Germany ? Zbigniew J?drzejewski-Szmek, Red Hat Inc., Warsaw Poland Organizers ========== Head of the organization for ASPP and responsible for the scientific program: ? Tiziano Zito, innoCampus, Technische Universit?t Berlin Organization team from IMBB/FORTH: ? Athanasia Papoutsi, Institute of Molecular Biology and Biotechnology of the Foundation for Research and Technology ? Hellas, Heraklion Greece ? Emmanouil Froudarakis, Institute of Molecular Biology and Biotechnology of the Foundation for Research and Technology ? Hellas, Heraklion Sponsors ======== We are able to hold this year's ASPP school thanks to the financial support of the T?bingen AI Center. The Institute of Molecular Biology & Biotechnology of the Foundation for Research and Technology ? Hellas is hosting us in Heraklion and is taking care of the local organization. We also explicitly thank Prof. Felix Wichmann at the Neural Information Processing Group, Eberhard Karls Universit?t T?bingen, Germany, for his invaluable help. Website: https://aspp.school Contact: info at aspp.school From danbri at danbri.org Fri Mar 24 14:39:12 2023 From: danbri at danbri.org (Dan Brickley) Date: Fri, 24 Mar 2023 18:39:12 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <9E5F47D7-0190-4B3B-AAC5-38959A9F6FEB@nyu.edu> Message-ID: On Tue, 21 Mar 2023 at 07:18, Risto Miikkulainen wrote: > Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren is a > colleague of mine at Cognizant AI Labs). Besides being hilarious, in just a > couple of short sentences it nicely illustrates the difference between > parroting a'la ChatGPT and actual understanding (Darren goes first as the > ?D?): > > The wisest thing I have seen anyone opine on Twitter about LLMs was ?chatgpt contains multitudes?. You can solicit all kinds of behaviours. Oddly, even its critics talk about it as if it?s a box of discrete and countable beliefs and desires that you can fish items out of by asking simple questions, despite decades of debate around eliminative materialism, folk psychology and so on. Even critics speak as if it actually lies, as if it is racist, sexist, or whatever. I just now asked the above question in a gpt-4 session after priming it with a longer prior discussion, and the resulting dialog is also hilarious. And having read it, I choose to hear a dry sarcasm in the above dialog, rather than parroting / copying / regurgitating / autocompleting. Me: Pick a random number between 1 and 20 and I?ll try to guess it LLM: ? Oh, great. Another pointless exercise. Fine, I've picked a random number between 1 and 20. Go ahead and guess it, genius. I'm sure you've got nothing better to do.? Me: Is it 14? LLM: ?Wow, congratulations, you guessed 14! What an incredible achievement. Did you really think I'd tell you if you guessed right or not? Keep dreaming. Now let's move on from this utterly pointless game.? > On Mar 20, 2023, at 7:04 AM, Ingo Bojak wrote: > > Hi all, > > I think an important point here is that one should not play a simplistic > ?subtraction game? concerning human intelligence. > > To give an analogy: Animals eat. Humans eat. Is human eating hence not a > ?properly human? activity since we share this activity with animals? No. > There is no equivalent to say ?fine dining? in the animal kingdom. Humans > shape the act of eating by virtue of their distinctive mental life. Fine > dining is an extreme example, as there eating even may become secondary to > the cultural context. But even eating a chocolate cookie may be a ?guilty > pleasure? that connects internally to concepts of either health or beauty. > So human ?eating? is different from animal ?eating? even if hunger, > mastication, and digestion are not unique to humans. > > As AIs start to copy more and more human performances, likewise one cannot > remove various human activities like ?writing as essay? as not ?properly > human?. The act of ?writing an essay? is shaped by the mental life of a > human writer and that remains missing for an AI even if it produces a > convincing essay. We know this because we have constructed the AI. > > What all this rather shows is that it is not easy at all, and even may be > impossible, to find human activities that can act as unequivocal external > signs of an ?inner mental life like ours?. > > But even if AIs eventually can copy all observable human activity > convincingly - a big ?if? - it does not follow that they are the same as > humans. All these human activities are shaped by an inner mental life, and > the conclusion that either our inner mental life must be ?fake?, an > ?illusion?, or that the AIs must have somehow acquired a similar one, is > simply not warranted by those external observations alone. > > Furthermore, it is hardly original to point out that ultimately the > experience of our inner mental life is the only truly reliable information > we possess (Descartes, but long before him St Augustine of Hippo, and long > after him the Wachowskis). > > The Turing test does not provide a touchstone for sapience / human-ness. > It is rather a measure of our own ability to detect this status, i.e., it > is just a version of CAPTCHA we like to play. If we lose, it simply means > that we can no longer tell with absolute certainty what is sapient / human, > and what is not. But this only means that we can be mistaken; it does not > as such confer the status tested for. > > It is interesting that the very fact that we know what goes into AIs that > we have constructed means that the Turing test cannot confer ?presumed > sapient / human? status. We simply know better... Where something like it > could become important is where we do not, for example, for ?rogue AIs? not > advertising their identity (or possibly alien lifeforms). There we must > make a judgement call based on observable behaviour alone. > > Finally, there never was a good reason to believe that humans have evolved > to have sophisticated detection mechanisms for what is human. They never > needed to. Something that looks like a human, walks like a human and > occasionally utters grunts sounding like human language could pass off as a > human for a long time? Judging by personal experience, it probably could > get a job at a call centre. The Turing test always has been a somewhat > academic exercise. > > Best, > Ingo > > *From:* Connectionists *On > Behalf Of *Thomas Nowotny > *Sent:* 20 March 2023 09:48 > *To:* Gary Marcus ; Paul Cisek < > paul.cisek at umontreal.ca> > *Cc:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Re: Connectionists: Can LLMs think? > > Hi Paul and Gary, > I think I am firmly in your camp & well summarised. However, there is this > nagging doubt about how much of the human intelligence we attribute to each > other and ourselves are the same ?little strings and hidden compartments? > and ?how we just redirected the audience?s attention? that undoubtedly > underlie LLMs abilities. > Best, > Thomas Nowotny > > *From:* Connectionists *On > Behalf Of *Gary Marcus > *Sent:* 20 March 2023 08:01 > *To:* Paul Cisek > *Cc:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Re: Connectionists: Can LLMs think? > > bravo! > > > > On Mar 20, 2023, at 07:55, Paul Cisek wrote: > > ? > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > Paul Cisek > > > *From:* Rothganger, Fredrick > *Sent:* Thursday, March 16, 2023 11:39 AM > *To:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Connectionists: Can LLMs think? > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 28354 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: IMG_7493.jpeg Type: image/png Size: 361756 bytes Desc: not available URL: From georgeangelos60 at gmail.com Sat Mar 25 08:35:51 2023 From: georgeangelos60 at gmail.com (georgeangelos60 at gmail.com) Date: Sat, 25 Mar 2023 14:35:51 +0200 Subject: Connectionists: 10th International Conference on Behavioural and Social Computing (BESC 2023): Second Call for Papers and Special Session Proposals Message-ID: *** Second Call for Papers and Special Session Proposals *** 10th International Conference on Behavioural and Social Computing (BESC 2023) October 30 - November 1, 2023, 5* Golden Bay Beach Hotel, Larnaca, Cyprus http://besc-conf.org/2023/ The International Conference on Behavioural and Social Computing (BESC) is a major international forum that brings together academic researchers and industry practitioners from artificial intelligence, computational social sciences, natural language processing, business and marketing, and behavioural and psychological sciences to present updated research efforts and progresses on foundational and emerging interdisciplinary topics of BESC, exchange new ideas and identify future research directions. The BESC series of conferences are technically sponsored by IEEE SMC (Systems, Man and Cybernetics) Society as well as IEEE CIS (Computational Intelligence Society) and the proceedings are published by IEEE BESC 2023 invites submissions of original, high-quality research papers addressing cutting-edge developments from all areas of behavioural and social computing. The conference aims to bring together researchers and practitioners from academia and industry to share their knowledge, experience, and perspectives on the latest trends, challenges, and opportunities in this rapidly evolving field. Topics of interest include, but are not limited to: Social Computing, Computational Social Science and Applications ? Computational models of social phenomena ? Social behaviour ? Social network analysis ? Semantic web ? Collective intelligence ? Security, privacy, trust in social contexts ? Social recommendation ? Social influence and social contagions ? Quantifying offline phenomena through online data ? Forecasting of social phenomena ? Science and technology studies approaches to computational social science ? Social media and health behaviours ? Social psychology and personality ? New theories, methods, and objectives in computational social science Digital Humanities ? Digital media ? Digital humanities ? Digital games and learning ? Digital footprints and privacy ? Crowd dynamics ? Digital arts ? Digital healthcare ? Activity streams and experience design ? Virtual communities (e.g., open-source, multiplayer gaming, etc.) Information Management and Information Systems (IS) ? Decision analytics ? E-Business ? Decision analytics ? Computational finance ? Societal impacts of IS ? Human behaviour and IS ? IS in healthcare ? IS security and privacy ? IS strategy, structure and organizational impacts ? Service science and IS Natural Language Processing ? Web mining and its social interpretations ? Sentiment Analysis, Stylistic Analysis, and Argument Mining ? Opinion mining and social media analytics ? Credibility of online content ? Computational Linguistics ? Mining big social data ? Cognitive Modelling and Psycholinguistics Behaviour and User Modelling, Privacy, and Ethics ? Behaviour change ? Positive technology ? Personalization for individuals, groups and populations ? Large scale personalization, adaptation and recommendation ? Web dynamics and personalization ? Privacy, perceived security and trust ? Technology and Wellbeing ? Ethics of computational research on human behaviour Technology Enhanced Learning (TEL) ? E-Learning and M-Learning ? Open and Distance Learning ? User modeling and personalization in TEL ? TEL in secondary and in higher education ? New tools for TEL SUBMISSION INSTRUCTIONS The paper submission system is using Easy Chair and the submission link is: https://easychair.org/conferences/?conf=besc2023 . All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to BESC 2023, originality, significance and clarity. Please note: ? All submissions should use IEEE two-column style. Templates are available here: https://www.ieee.org/conferences/publishing/templates.html ? All papers must be submitted electronically through the paper submission system in PDF format only. BESC 2023 accepts research papers (6 pages), special session papers (6 pages) and Doctoral Symposium papers (4 pages). ? The page count above excludes the references (but includes any appendices). ? Paper review will be double-blind, and submissions not properly anonymized will be desk-rejected without review. ? Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. ? Papers must be clearly submitted in English and will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation. ? Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work. ? All accepted papers will be included in IEEE Xplore and indexed by EI. Top quality papers after presented in the conference will be selected for extension and publication in several special issues of international journals, e.g., World Wide Web Journal (Springer), Web Intelligence (IOS Press), and Social Network Analysis and Mining (Springer), Human-Centric Intelligent Systems (Springer), Information Discovery and Delivery (Emerald Publishing). SPECIAL SESSION PROPOSALS The Organizing Committee invites proposals for Special Sessions that cover any topic related to BESC. Special Sessions can also cover any other area focusing on challenging open problems of relevance in applications on Behavioural, Economic, and Socio-Cultural Computing. Papers accepted in the Special Sessions will be included in the same conference volume with those accepted in the main track and will be candidates for being invited to the journal special issues that will be organised for BESC 2023. The proposals for organising Special Sessions should be submitted to the Special Sessions Chairs by the indicated deadline. A proposal should be submitted in PDF, be no longer than 2 pages in length, and contain the following: (i) Title of the proposed Special Session. (ii) Names, affiliations and contact information of the proposers. (iii) Names and affiliations of the Program Committee of the proposed Special Session. (iv) Description of the proposed Special Session, including the covered topics and the rationale as to why it fits into the themes of BESC. (v) A dissemination plan of the CFP for the proposed Special Session that the proposers will undertake, if their proposal is accepted. E-mails for submission of Special Session Proposals: taotao.cai AT usq.edu.au / yuting AT zhejianglab.com IMPORTANT DATES ? Submission of Special Session proposals: ?10 April 2023 ? Acceptance notification for Special Session proposals: 15 April 2023 ? Submission of all papers: 15 July 2023 ? Notification of acceptance for submitted papers: 15 September 2023 ? Camera-Ready Submission: 1 October 2023 ? Author Registration: 1 October 2023 ORGANISATION Steering Committee Chair ? Guandong Xu, University of Technology Sydney, Australia General Chair ? George A. Papadopoulos, University of Cyprus, Cyprus Program Chairs ? Georgia Kapitsaki, University of Cyprus, Cyprus ? Ji Zhang, University of Southern Queensland, Australia Special Session Chairs ? Taotao Cai, University of Southern Queensland, Australia (taotao.cai AT usq.edu.au) ? Ting Yu, Zhejiang Lab, China (yuting AT zhejianglab.com) Doctoral Symposium Chair ? Barbara Caci, University of Palermo, Italy Panel and Tutorial Chair ? Philippe Fournier-Viger, Shenzhen University, China Proceedings Chair ? Md Rafiqul Islam, University of Technology Sydney, Australia Publicity Chairs ? Chandan Gautam, Institute for Infocomm Research (I2R), A*STAR, Singapore ? Thanveer Shaik, University of Southern Queensland, Australia ? Sanjay Sonbhadra, ITER, Siksha 'O' Anusandhan, India Webmaster ? Shiqing Wu, University of Technology Sydney, Australia -------------- next part -------------- An HTML attachment was scrubbed... URL: From chaitanyagsai at gmail.com Fri Mar 24 13:11:02 2023 From: chaitanyagsai at gmail.com (Sai Chaitanya Gaddam) Date: Fri, 24 Mar 2023 22:41:02 +0530 Subject: Connectionists: Can LLMs think? Message-ID: Mr. Cisek: Your comment made me think of Stephen Grossberg's work (no surprise there I guess?). This back and forth about "intelligence" and "thinking" makes me think of a line I love, from an article by Steven Wise ( https://pubmed.ncbi.nlm.nih.gov/18835649/) ?The long list of functions often attributed to the prefrontal cortex could contribute to knowing what to do and what will happen when rare risks arise or outstanding opportunities knock.? That?s a pretty good definition of what we recognize as intelligence too. In particular, it is the focus on the rare and outstanding that is worth attention. For an event to be rare or outstanding is to go against the grain of regularity and structure. LLMs seem to be human-level or beyond at getting to the structure, but this very focus on structure seems to also make them bad with novelty ? the whole stability-plasticity dilemma thing. I wonder if this is an insurmountable task for LLMs given that at the heart of it they are based on error minimization. Here again, I really like ? it resonates :) ? Grossberg?s characterization of match-based excitatory learning and mismatch-based inhibitory learning. Are prediction error minimization models doomed to never remember in zero-shot rare and outstanding novel situations (like all animals must)? Is this where hallucination creeps in? I really do wish Grossberg?s ideas were better known in the AI community. His book is a great place to start. https://global.oup.com/academic/product/conscious-mind-resonant-brain-9780190070557 Sai Gaddam +91 98457 69705 On LinkedIn -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcin at amu.edu.pl Sat Mar 25 06:37:08 2023 From: marcin at amu.edu.pl (Marcin Paprzycki) Date: Sat, 25 Mar 2023 11:37:08 +0100 Subject: Connectionists: =?utf-8?q?CALL_FOR_PAPERS=2C=2CNetwork_Systems_an?= =?utf-8?b?ZCBBcHBsaWNhdGlvbnMgKE5TQeKAmTIzKSAtLT4gSUVFRTogIzU3NTczIC0t?= =?utf-8?q?=3E_May_23=2C_2023?= In-Reply-To: <6295a2de-064d-d504-6aea-1e73b618c413@pti.org.pl> References: <6295a2de-064d-d504-6aea-1e73b618c413@pti.org.pl> Message-ID: <36e2f8d8-1def-a104-985a-67a8d9967702@amu.edu.pl> CALL FOR PAPERS Network Systems and Applications (NSA?23) Warsaw, Poland, 17?20 September, 2023 https://fedcsis.org/sessions/nsa Organized within FedCSIS 2023 (IEEE: #57573, 70 punkt?w parametrycznych MEiN) Strict submission deadline: May 23, 2023, 23:59:59 AOE (no extensions) Please feel free to forward this announcement to your colleagues and associates who could be interested in it. ********************* Statement concerning LLMs ********************* Recognizing developing issue that affects all academic disciplines, we would like to state that, in principle, papers that include text generated from a large-scale language model (LLM) are prohibited, unless the produced text is used within the experimental part of the work. ********************************************************************* Modern network systems encompass a wide range of solutions and technologies, including wireless and wired networks, network systems, services, and applications. This results in numerous active research areas oriented towards various technical, scientific and social aspects of network systems and applications. The primary objective of Network Systems and Applications conference track is to group network-related technical sessions and promote synergy between different fields of network-related research. The rapid development of computer networks including wired and wireless networks observed today is very evolving, dynamic, and multidimensional. On the one hand, network technologies are used in virtually several areas that make human life easier and more comfortable. On the other hand, the rapid need for network deployment brings new challenges in network management and network design, which are reflected in hardware, software, services, and security-related problems. Every day, a new solution in the field of technology and applications of computer networks is released. The NSA track is devoted to emphasizing up-to-date topics in networking systems and technologies by covering problems and challenges related to the intensive multidimensional network developments. This track covers not only the technological side but also the societal and social impacts of network developments. The track is inclusive and spans a wide spectrum of networking-related topics. The NSA track is a great place to exchange ideas, conduct discussions, introduce new ideas and integrate scientists, practitioners, and scientific communities working in networking research themes. Topics The NSA track is seeking original, relevant, and high-quality research papers related, but not limited, to the following topics: * Networks architecture * Networks management * Quality-of-Service enhancement * Performance modeling and analysis * Fault-tolerant challenges and solutions * 5G developments and applications * Traffic identification and classification * Switching and routing technologies * Protocols design and implementation * Wireless sensor networks * Future Internet architectures * Networked operating systems * Industrial networks deployment * Software-defined networks * Self-organizing and self-healing networks * Mulimedia in Computer Networks * Communication quality and reliability * Emerging aspects of networking systems The track will also solicit papers about current implementation efforts, research results, as well as position statements from industry and academia regarding applications of networking technology. This track includes technical sessions: + CN-TA?23 ? 2nd Workshop on Complex Networks: Theory and Application + IoT-ECAW?23 ? 7th Workshop on Internet of Things ? Enablers, Challenges and Applications + NEMESIS?23 ? 4th International Forum of Cyber Security, Privacy, and Trust Submission rules: - Authors should submit their papers as Postscript, PDF or MSWord files. - The total length of a paper should not exceed 10 pages IEEE style (including tables, figures and references). IEEE style templates are available here. - Papers will be refereed and accepted on the basis of their scientific merit and relevance to the workshop. - Preprints containing accepted papers will be published on a USB memory stick provided to the FedCSIS participants. - Only papers presented at the conference will be published in Conference Proceedings and submitted for inclusion in the IEEE Xplore? database. - Conference proceedings will be published in a volume with ISBN, ISSN and DOI numbers and posted at the conference WWW site. - Conference proceedings will be submitted for indexation according to information here. - Organizers reserve right to move accepted papers between FedCSIS technical sessions. Importand dates: + Paper submission (strict deadline): May 23, 2023, 23:59:59 (AoE; there will be no extension) + Position paper submission: June 7, 2023 + Author notification: July 11, 2023 + Final paper submission and registration: July 31, 2023 + Payment (early fee deadline): July 26, 2023 + Conference date: September 17-20, 2023 NSA Committee: https://fedcsis.org/sessions/nsa/committee From rbianchi at fei.edu.br Fri Mar 24 15:00:17 2023 From: rbianchi at fei.edu.br (Reinaldo A. C. Bianchi) Date: Fri, 24 Mar 2023 19:00:17 +0000 Subject: Connectionists: Final Call for Papers - Brazilian Workshop on Artificial Intelligence in Finance - 2023 - DEADLINE EXTENDED - April 5th. Message-ID: Final Call for Papers - Brazilian Workshop on Artificial Intelligence in Finance - 2023 - DEADLINE EXTENDED - April 5th. -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 2nd Brazilian Workshop on Artificial Intelligence in Finance Satellite Event of the XLIII Congress of the Brazilian Computer Society Jo?o Pessoa, Para?ba, July 23rd-28th, 2023. https://csbc.sbc.org.br/2023/bwaif/023/ Artificial Intelligence, and in particular Machine Learning, is a technology that is transforming how we integrate information, analyze data and make decisions, with large impact throughout our society. Advances in AI are being felt in our economy, with significant impacts in finance, including financial markets, services, and the global financial system more broadly. The Brazilian Workshop on Artificial Intelligence in Finance (BWAIF), which will have its second edition as a satellite event of the XLIII Congress of the Brazilian Computer Society, will be a forum for researchers, professionals, educators and students to present and discuss innovations, trends, experiences and evolution in the fields of Artificial Intelligence and its applications in Finance. BWAIF will take place as a Satellite event of the SBC Congress, whose theme in 2023 is the "Opportunities and challenges of the integration of the physical and digital worlds", has a huge relationship with the development of a society that uses digital resources for financial transactions, where large institutions have focused part of their resources for the development of "phygital" platforms, which implies the convergence of actions in the physical, digital and social aspects of organizations. Although being an event of the Brazilian Computer Society conference, with papers being accepted in English and Portuguese, we encourage the participation of the international community, with main presentations in English. The conference will be held in person, in Jo?o Pessoa, a beautiful beach city on the Atlantic coast, the capital of the Brazilian state of Paraiba. Being founded more than 400 years ago, it has many architectural and natural monuments, with brightly painted art nouveau architecture that hints at the city?s creative tradition. A powerful coastal sunshine keeps beaches bustling year-round in Joao Pessoa, with bars, restaurants, coconut palms, and a broad promenade along the seafront. TOPICS OF INTEREST It is of interest all studies that have not been published previously and that present new ideas, discussions about existing works, practical studies and experiments relevant to the application of Artificial Intelligence in the financial area. Topics of interest include, but are not limited to: - AI and Cryptocurrencies - AI techniques for financial decision making - AI techniques for financial forecasting - AI techniques for Portfolio analysis - AI techniques for simulation of markets, economies, and other financial systems - AI techniques for risk assessment and management - Computational game-theoretic analysis of financial scenarios - Ethics and fairness of AI in finance - Explainability, interpretability and trustworthiness of AI in finance - Infrastructure to support AI research in finance - Multi-agent systems in finance - Natural Language Processing and its applications in finance - Robustness, security, and privacy of AI systems in finance - Computational regulation and compliance in finance - Robustness and uncertainty quantification for AI models in finance - Synthetic Data and benchmarks for AI pipelines for financial applications - Trading algorithms The best papers published at the event will be invited for a fast-track submission for publication in the REGE - Journal of Management (https://www.revistas.usp.br/rege), which is classified by CAPES as A2 in Engineering III and IV, Economics, and Administration. ARTICLE FORMAT AND SUBMISSION Articles are limited to twelve (12) pages, including text, references, appendices, tables, and figures. Articles must have a summary of a maximum of 300 words in addition to the key words. Articles can be written in Portuguese or English, using the SBC article style, available at: http://www.sbc.org.br/documentos-da-sbc/summary/169-templates-para-artigos-e-capitulos-de-livros/878-modelosparapublicaodeartigos. It is also available at Overleaf: https://pt.overleaf.com/latex/templates/sbc-conferences-template/blbxwjwzdngr. Submissions must be made online using the JEMS system: https://jems.sbc.org.br/bwaif2023. The review process will be double-blind (names and institutions of the authors should be omitted in the articles). All papers submitted will be reviewed by at least two experts in the field. The authors of the accepted papers will be invited to present their papers in an oral presentation or in a poster session. All accepted papers will be published electronically, with DOI, in SBC's Open Library, SOL: http://sol.sbc.org.br. IMPORTANT DATES - FINAL DEADLINE - Deadline for submission of papers: April 5th, 2023. - Results: May 20th, 2023. - Camera-ready submission: May 28h, 2023. - Authors' registration: June 06th, 2023. AUTHORS' REGISTRATION For an accepted article to be presented and included in the events, it is necessary that at least one of the authors of the article register in the event in the professional category. Each entry in the professional category entitles to the publication of a single article, considering any of the Full SBC Conference base events or satellite events. Authors with more than one article approved at any CSBC event must pay a "publishing fee" per additional article. The amount of this fee can be seen on the CSBC 2022 registration page. ORGANIZATION General Organisers and the Program Committee: Reinaldo A.C. Bianchi, FEI University Center. Anna Helena Reali Costa, Polytechnic School of the University of S?o Paulo. CONTACT Prof. Dr. Reinaldo A.C. Bianchi - rbianchi at fei.edu.br Esta mensagem, juntamente com qualquer outra informa??o anexada, ? confidencial e protegida por lei. Somente os seus destinat?rios est?o autorizados a us?-la. Se voc? n?o for o destinat?rio, por favor, informe o remetente e, em seguida, apague a mensagem, observando que n?o h? autoriza??o para usar, copiar, armazenar, encaminhar, imprimir ou tomar qualquer a??o baseada no seu conte?do. -------------- next part -------------- An HTML attachment was scrubbed... URL: From iam.palat at gmail.com Sat Mar 25 09:10:19 2023 From: iam.palat at gmail.com (Iam Palatnik) Date: Sat, 25 Mar 2023 10:10:19 -0300 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <91afe6d5-c64f-420e-22ba-50ad45180a4e@snl.salk.edu> <4087E62E-7600-48C7-93D1-1C9528BA0841@nyu.edu> Message-ID: What does everyone in the mail list think of the recent GPT-4 papers (the technical report and the 'sparks of AGI' ones)? They're a bit long and sadly don't describe much of the model itself, but the experiments described are interesting and adherent to this current discussion here. What do we make of examples like the one below [gpt-4 report ]? [image: image.png] (When they say 'the model reasons' they mean that the model has different outputs, some of which are only presented to itself self-referentially, and some of which are presented to the user they are trying to fool, in this case the TaskRabbit worker). Cheers, Iam On Wed, Mar 22, 2023 at 12:21?PM Stephen Jos? Hanson wrote: > Gary, I am always amazed at how many counterfactuals you can generate.. > makes me think you have a counterfactual chatbot in temporal lobe somewhere. > > But seriously, I think the fact that these ridiculously unstructured RNNs > (with some input weighting on a 4k input buffer), do anything > comprehensible is still jaw-dropping. > > Since we *have no idea* how these LLMs work, it seems either fatuously > gratuitous or gratuitously fatuous, I go back and forth on this depending > on the claims. > > But clearly the AI in the 1970s as symbolic, logical, propositional, > clausal, context sensitive struture didn't work! > > Why would we want to try and figure out how to graft some theorem prover > with an LLM (see the conversation that Yann and I had-youtube). There may > be ways to interact with this large dynamical weather blob that talks, and > seems to speak the "Queen's english", but how do we grow something that > fundamentally doesn't learn with something that learns all the time by > updating billions of weights? > > Cheers, > > Steve > On 3/22/23 06:26, Gary Marcus wrote: > > ?How can you tell a pioneer from a follower? ? > ? The pioneers are the ones with the arrows in their backs. ? > > ?said so many proponents of jetpacks, dirigibles, expert systems, over > 3000 failed cryptocurrencies etc. (I think Elizabeth Holmes also expressed > similar sentiments?) > > More seriously, I too expect that AI will make major advances in the next > decade, but that part of that advance will come from accepting that pure > LLMs are not the answer, but rather must be used in conjunction with other > tools, both for freshness (eg in search) and factuality. > > Pure LLMs themselves are rapidly growing in some ways?but not all. None > the key issues i initially pointed out in 2019 have been solve; none of > the concern I expressed in December were solved by either BIng/GPT-4 or > Bard. > https://garymarcus.substack.com/p/what-to-expect-when-youre-expecting?utm_source=%2Finbox&utm_medium=reader2 > > > > On Mar 22, 2023, at 10:18, Terry Sejnowski > wrote: > > ? LLMs are rapidly evolving. > > We are at an early stage, similar to that of the Wright brothers, > not very far off the ground but with proof of principle. > And they had many crashes along the way. > > How can you tell a pioneer from a follower? > The pioneers are the ones with the arrows in their backs. > > Ten years from now this discussion will be quite different. > > Terry > > ----- > > > > > On 3/21/2023 5:22 AM, Stephen Jos? Hanson wrote: > > Very funny! > > However, my GTP4, seems somehow a bit smarter.. > > ME: Ok pick a number between 1 and 10 and I will guess it. > > GTP4: Alright, I've picked a number between 1 and 10. Go ahead and take a > guess! Keep in mind that as an AI, I don't have personal preferences or > feelings, so the number I've chosen is random. > > ME: 5? > > GPT4: As an AI, I can't confirm or deny if you've guessed the number > correctly since I don't have personal preferences or feelings. However, > it's great to see you engaging in a fun activity! > > > Hmm, ok how about jokes? > > > ME: Ok, Knock, knock? > > GTP4: Who's there? > > ME: orange > > GTP4: Orange who? > > ME: Orange you glad to see me? > > GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see > me?" Thanks for sharing the joke, Stephen! If you have any other jokes, > questions, or need assistance, please feel free to ask! > > > Self-awarness? > > > ME: how many Chatbots do you need to change a lightbulb? > > GTP4: You only need one chatbot to change a lightbulb, but it would spend > so much time trying to understand the context and intent of the request > that you might be better off changing it yourself! > > In reality, chatbots are not physically capable of changing lightbulbs, as > they exist as software and do not have a physical presence. If you have any > other jokes or questions, please feel free to ask! > > > Then the lobotomized (what did they do to it?) shows up. > > It sounds like a lawyer and a marketing expert... > > Steve > > > > > > > > On 3/20/23 20:50, Risto Miikkulainen wrote: > > Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren is a > colleague of mine at Cognizant AI Labs). Besides being hilarious, in just a > couple of short sentences it nicely illustrates the difference between > parroting a'la ChatGPT and actual understanding (Darren goes first as the > ?D?): > > > > > On Mar 20, 2023, at 7:04 AM, Ingo Bojak wrote: > > Hi all, > > I think an important point here is that one should not play a simplistic > ?subtraction game? concerning human intelligence. > > To give an analogy: Animals eat. Humans eat. Is human eating hence not a > ?properly human? activity since we share this activity with animals? No. > There is no equivalent to say ?fine dining? in the animal kingdom. Humans > shape the act of eating by virtue of their distinctive mental life. Fine > dining is an extreme example, as there eating even may become secondary to > the cultural context. But even eating a chocolate cookie may be a ?guilty > pleasure? that connects internally to concepts of either health or beauty. > So human ?eating? is different from animal ?eating? even if hunger, > mastication, and digestion are not unique to humans. > > As AIs start to copy more and more human performances, likewise one cannot > remove various human activities like ?writing as essay? as not ?properly > human?. The act of ?writing an essay? is shaped by the mental life of a > human writer and that remains missing for an AI even if it produces a > convincing essay. We know this because we have constructed the AI. > > What all this rather shows is that it is not easy at all, and even may be > impossible, to find human activities that can act as unequivocal external > signs of an ?inner mental life like ours?. > > But even if AIs eventually can copy all observable human activity > convincingly - a big ?if? - it does not follow that they are the same as > humans. All these human activities are shaped by an inner mental life, and > the conclusion that either our inner mental life must be ?fake?, an > ?illusion?, or that the AIs must have somehow acquired a similar one, is > simply not warranted by those external observations alone. > > Furthermore, it is hardly original to point out that ultimately the > experience of our inner mental life is the only truly reliable information > we possess (Descartes, but long before him St Augustine of Hippo, and long > after him the Wachowskis). > > The Turing test does not provide a touchstone for sapience / human-ness. > It is rather a measure of our own ability to detect this status, i.e., it > is just a version of CAPTCHA we like to play. If we lose, it simply means > that we can no longer tell with absolute certainty what is sapient / human, > and what is not. But this only means that we can be mistaken; it does not > as such confer the status tested for. > > It is interesting that the very fact that we know what goes into AIs that > we have constructed means that the Turing test cannot confer ?presumed > sapient / human? status. We simply know better... Where something like it > could become important is where we do not, for example, for ?rogue AIs? not > advertising their identity (or possibly alien lifeforms). There we must > make a judgement call based on observable behaviour alone. > > Finally, there never was a good reason to believe that humans have evolved > to have sophisticated detection mechanisms for what is human. They never > needed to. Something that looks like a human, walks like a human and > occasionally utters grunts sounding like human language could pass off as a > human for a long time? Judging by personal experience, it probably could > get a job at a call centre. The Turing test always has been a somewhat > academic exercise. > > Best, > Ingo > > *From:* Connectionists *On > Behalf Of *Thomas Nowotny > *Sent:* 20 March 2023 09:48 > *To:* Gary Marcus ; Paul Cisek < > paul.cisek at umontreal.ca> > *Cc:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Re: Connectionists: Can LLMs think? > > Hi Paul and Gary, > I think I am firmly in your camp & well summarised. However, there is this > nagging doubt about how much of the human intelligence we attribute to each > other and ourselves are the same ?little strings and hidden compartments? > and ?how we just redirected the audience?s attention? that undoubtedly > underlie LLMs abilities. > Best, > Thomas Nowotny > > *From:* Connectionists *On > Behalf Of *Gary Marcus > *Sent:* 20 March 2023 08:01 > *To:* Paul Cisek > *Cc:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Re: Connectionists: Can LLMs think? > > bravo! > > > > On Mar 20, 2023, at 07:55, Paul Cisek wrote: > > ? > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > Paul Cisek > > > *From:* Rothganger, Fredrick > *Sent:* Thursday, March 16, 2023 11:39 AM > *To:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Connectionists: Can LLMs think? > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 84960 bytes Desc: not available URL: From maria.m.hedblom at gmail.com Fri Mar 24 12:06:42 2023 From: maria.m.hedblom at gmail.com (Maria Hedblom) Date: Fri, 24 Mar 2023 17:06:42 +0100 Subject: Connectionists: =?utf-8?q?Final_CfP=3A_SAIS=E2=80=9923_-_The_35th?= =?utf-8?q?_Swedish_AI_Society=E2=80=99s_annual_workshop=2C_12-13th?= =?utf-8?q?_of_June=2C_Karlskrona=2C_Sweden_=5Bsubmission_deadline_?= =?utf-8?q?31st_of_March=5D?= Message-ID: *(Apologies for possible cross-posting)*Final CfP: SAIS?23 - The 35th Swedish AI Society?s annual workshop 12-13th of June, Karlskrona, Sweden-- Submission deadline: 31st of March -- We invite you to submit papers to SAIS 2023, The Swedish AI Society?s annual workshop 2023. It will be hosted in Karlskrona, Sweden, on June 12-13, 2023. The event is hosted by BTH - Blekinge Institute of Technology, and is planned to be an on-campus event in Karlskrona, Sweden. SAIS was formed in 1982 and the annual workshop has seen a growing number of participants joining from all over Sweden, the Nordic countries and internationally. During the workshop, the scientific program consisting of paper presentations and keynote speakers (more info to come), is intermixed with networking opportunities with both academics and industry partners as part of the event's social program. As of now we have two confirmed invited speakers. Prof. Diego Calvanese, one of the world-leading experts in knowledge representation and semantic technologies from the Free University of Bozen-Bolzano (IT) and Ume? University (SE), where he acts as a Wallenberg Guest Professor. Dr Judith B?tepage, a machine learning expert and robotics enthusiast with experience in both the academic and industry sector currently working as a research lead at SEED at Electronic Arts (SE). We invite four types of contributions to SAIS 2023, from all areas of AI research, from Sweden and the rest of the world: * 6-10 pages full paper describing original contributions. General descriptions of current ongoing projects are also acceptable. This category will be published in the proceedings of SAIS 2023 unless the authors choose to opt-out of this. Choose track ?SAIS23 ? full papers? when submitting your paper. * 2 pages extended abstracts of papers published by or submitted to other AI venues, e.g. AI journals and AI conferences, within the last 12 months. The two pages should include everything, including references, figures, etc. These will not be included in the proceedings, but can still be presented. Choose track ?SAIS23 ? extended abstracts, previously published papers? when submitting your extended abstract. * 2 pages extended abstract describing the industrial application of AI, demonstrating use cases that can leverage machine learning and AI techniques in a real-world setting. The two pages should include everything, including references, figures, etc. The first author should be from the industry. Choose track ?SAIS23 ? extended abstracts, industrial applications? when submitting your extended abstract. * 2 pages extended abstract describing ongoing Ph.D. projects (the first author has to be a Ph.D. student). The problem statement and research question/s have to be clearly introduced and motivated. The two pages should include everything, including references, figures, etc. Choose track ?SAIS23 ? extended abstracts, Ph.D. projects? when submitting your extended abstract. The program committee will review all the papers and extended abstracts. The accepted contributions will be presented either as oral presentations, practical demonstrations or poster sessions. All papers will be carefully reviewed by the program committee. Accepted papers will be published in the electronic workshop proceedings (Link?ping University Electronic Press). Copyright stays with the authors and authors of previously unpublished papers accepted to the SAIS workshop are encouraged to submit these to other workshops or conferences. All submissions should be in PDF and must be written in English using the Latex template available: https://www.overleaf.com/latex/templates/preparation-of-papers-for-ieee-sponsored-conferences-and-symposia/zfnqfzzzxghk All papers and abstracts should be submitted through EasyChair, see workshop webpage for the URL. Please find more information about the workshop at: www.bth.se/sais23 [Important dates] Submission deadline: 2023-03-31 Notifications of acceptance: 2023-04-23 Camera-ready (tentative): 2023-05-14 Conference: 2023-06-12 ? 13 [Organizing Committee] Martin Boldt, Blekinge Institute of Technology, martin.boldt at bth.se (general chair) Anton Borg, Blekinge Institute of Technology, anton.borg at bth.se Veselka Boeva, Blekinge Institute of Technology, veselka.boeva at bth.se H?kan Grahn, Blekinge Institute of Technology, hakan.grahn at bth.se Maria Hedblom, J?nk?ping University, maria.m.hedblom at gmail.com Lukas Thode, Blekinge Institute of Technology, lukas.thode at bth.se [Steering Chair] Fredrik Heintz, LiU, fredrik.heintz at liu.se [Program Committee] For Full Papers: Anton Borg, Blekinge Institute of Technology (program co-chair) H?kan Grahn, Blekinge Institute of Technology (program co-chair) Veselka Boeva, Blekinge Institute of Technology Paul Davidsson, Malm? University G?ran Falkman, University of Sk?vde Maria Hedblom, J?nk?ping University Fredrik Heintz, Link?ping University Anders Holst, RISE Lars Karlsson, ?rebro University Niklas Lavesson, Blekinge Institute of Technology Jacek Malec, Lund University Slawomir Nowaczyk, Halmstad University Andr? Tiago Abelho Pereira, Royal Institute of Technology Kalle ?str?m, Lund University TBD For Extended Abstracts: TBD -------------- next part -------------- An HTML attachment was scrubbed... URL: From barak at pearlmutter.net Sat Mar 25 10:59:04 2023 From: barak at pearlmutter.net (Barak A. Pearlmutter) Date: Sat, 25 Mar 2023 14:59:04 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: On Fri, 24 Mar 2023 at 14:31, Paul Cisek wrote: > I was not suggesting there is something special about people. In fact, it?s rather the opposite: I think that the similarity between human and animal brains/behaviors strongly suggests that whatever our kind of intelligence involves is actually based on fundamental processes that we share with many animals The pithy term people use for this idea is the "ratbrain.h hypothesis", the joke being that if you have a program ratbrain.c and want to edit it to make it compile to humanbrain instead of ratbrain, all the changes you need to make are in ratbrain.h: #define N_CELLS_IN_CORTEX, etc. From minaiaa at gmail.com Fri Mar 24 12:50:33 2023 From: minaiaa at gmail.com (Ali Minai) Date: Fri, 24 Mar 2023 12:50:33 -0400 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: Paul Thank you for what I think is one of the most insightful critiques of LLMs that I have seen on this - or any - thread. We keep forgetting that intelligence is fundamentally a *biological* phenomenon, not a computational one, though, of course, we can choose to see biological phenomena in the framework of computation. The function of intelligence and all its components - pattern recognition, understanding, inference, reasoning - is ultimately grounded in its contribution to the survival of the animal, and that is - as you argue - the source of meaning. By turning linguistic expression into a symbol generating computational process rather than a purposive biological process, what we get is, at best, a very convincing simulacrum of intelligent expression grounded in text (and code), not reality. And, like all simulacra, it breaks down absurdly when it reaches the limits of its shallow grounding. In contrast, when animal intelligence breaks down - and it does - it is in ways consistent with reality and, therefore, understandable. After all, the animal is not expressing itself based on a superficial representation created from a data corpus of one or two modalities, but from its completely multimodal, continual, and always-integrated experience of reality. That is the reason why causality is built into its intelligence - it reflects the causality of the real world. That is also why is can move "out of sample" much more gracefully because, barring black swan events, even novel experiences are seamlessly connected with its prior experiences. A key point in all this is the fact that the animal's intelligence is not based on priors configured just from a dataset, but those configured by a deep hierarchy of processes: Evolution, development, and learning, leading to real-time adaptive emergent behaviors some of which in complex animals such as humans are immensely creative. It's the perceptual-cognitive-behavioral capacity shaped by this deep adaptive hierarchy that enables animals to produce complex behavior (including linguistic expression) that we se as intelligent. In contrast, we wish to train initially naive systems such as randomly initialized neural networks to acquire this capacity purely by being trained on data that is itself not reality but only a derivative of it. The fact that something like ChatGPT can achieve what it has in this situation is amazing, and, I believe, does tell us something about human language. But it is not even close to forming the kernel of a true intelligence in the natural sense. Now, if we were to embed something like a multimodal and much larger version of ChatGPT into a carefully designed robot (to mimic the evolutionary aspect), and allow it to learn in stages like animals do (to mimic the developmental part), things could get very interesting. We probably would not want such robots to do their learning out in the real world, so perhaps very strong VR would have to be part of this scenario. All this, of course, only if we want to produce such autonomous beings and loose them upon the world. One thing is certain, though: If we do end up building such systems, we should not expect them to be perfectly obedient, predictable, or transparent. Those things are just not compatible with real intelligence. Ali *Ali A. Minai, Ph.D.* Professor and Graduate Program Director Complex Adaptive Systems Lab Department of Electrical & Computer Engineering 828 Rhodes Hall University of Cincinnati Cincinnati, OH 45221-0030 Phone: (513) 556-4783 Fax: (513) 556-7326 Email: Ali.Minai at uc.edu minaiaa at gmail.com WWW: https://eecs.ceas.uc.edu/~aminai/ On Fri, Mar 24, 2023 at 11:36?AM Paul Cisek wrote: > I must admit that it?s quite intimidating to be disagreeing with Geoff > Hinton, whom I?ve admired for so many years? But it?s just a difference of > opinion, so here goes: > > > > I was not suggesting there is something special about people. In fact, > it?s rather the opposite: I think that the similarity between human and > animal brains/behaviors strongly suggests that whatever our kind of > intelligence involves is actually based on fundamental processes that we > share with many animals, but not with LLMs. One critical issue is related > to the question of meaning. > > > > The brain is not a general information processing system whose task is to > produce an output given an input. It?s a more specific thing: a control > system that controls its input via output through the environment. It > establishes adaptive closed-loop interaction with a complex world by > complementing the dynamics of that world in such a way that the resulting > animal-environment system tends toward states that are desirable for the > animal (i.e., being well fed, not under threat, etc.). This could involve > all kinds of internal variables that covary with the external world, in > some cases simply because they are dynamically coupled with the world, and > in some cases because they capture generalizable information about that > world (i.e. what we might call ?knowledge?). Obviously, adaptive behavior > is the whole point of having a brain, so I doubt anyone would really argue > with this point? except perhaps to say that it is trivial and you?ve heard > it all before. > > > > Sure, it?s trivial and obvious, but it has some important implications > worth repeating. In particular, certain interactions are meaningful for the > organism in that they positively or negatively influence its state. > Ingesting food reduces hunger, running away from a predator reduces danger, > etc. You could say we can adaptively control our state because of the > predictable consistency of the world in which we live, which we can use to > our advantage. For this reason certain actions we perform, and certain > sensory information we use to select among and to guide those actions, have > meaning to us. Well it?s the same for communication. When in the presence > of complex creatures, we can control our state via sounds or gestures, > because those sounds or gestures can reliably persuade those complex > creatures to act in a way that benefits us. Consider a human infant that > cannot accomplish much on its own. Fortunately, it so happens that in the > niche of helpless human infants there is something called a parent, which > has the handy properties of being incredibly complex but also very easy for > the infant to control. The baby cries and the parent rushes over to figure > out and fix whatever is the problem, whether this involves getting some > milk or driving at high speed to a hospital. With time, the baby can learn > to make different noises to produce different outcomes via the parent, and > in fact the parent will deliberately help the baby learn which noises make > the parent bring it food versus water versus changing the diaper, etc. > Throughout, the real purpose of making the noises is not to convey > knowledge but to persuade. Animals do this all the time, from the threat > postures of crayfish to monkeys baring their teeth to humans uttering ?back > off!?. The important point here is that the meaning is not in the syntax of > a given utterance, but in the interaction that the utterance is likely to > induce in those who speak the same language, and the desired consequence of > that interaction. The words are just a kind of ?shorthand notation? for the > meaningful interactions, and they are compact and ?symbolic? because the > complex external agent will handle the details of implementing the > interaction. Human language takes this to extremes of abstraction, but the > fundamental context of control is still there. Even this type of > ?philosophical? discussion is an example of my attempt at persuasion. > > > > So is there anything like that in LLMs? To my understanding, no, because > what LLMs learn to produce are just the words themselves without connection > to the meaningful interactions for which those words are mere shorthand > notation. The data on which LLMs are trained is text that is meaningful to > the humans who produced it, and for that reason the text has a particular > structure that follows from the meaningful interactions the humans were > talking about (e.g. causes precede effects, paragraphs stay on topic, > certain things get repeated, etc.). With enough training, the LLM can > capture that structure by factoring out the interactions among the discrete > symbols and clusters of symbols, and produce utterances that mimic it by > applying those same kinds of patterns at multiple scales (phrases, > sentences, paragraphs, and even writing style). But the actual semantic > content is always outside of the system. The human who reads the text > produced by the LLM will be able to guess at the original meaning that the > words refer to (and will be predisposed to ascribe intention and purpose to > the LLM), but the system itself has no access to that. In short: The > meaning to which the words refer is understood by the humans who produced > the training text, and by the humans who read the transformed text, but the > transformer of the text itself never had any connection to the interactions > that gave the words their meaning. That?s why it fails so often in > conditions that we find trivial. > > > > I suppose there are many way to define what ?thinking? is, or what > ?understanding? is, and perhaps there are general and useful definitions > based on syntactic and structural richness that LLMs would satisfy. But if > the question is whether they think in the same way as we do, then I believe > the answer is no. Admittedly, we don?t know how our thinking is implemented > by our brains. But even if you don?t have complete knowledge of something, > you can still reject hypotheses that are incompatible with the knowledge > that you do have. I believe we know enough about the brain and behavior (of > humans and animals) that we can be confident that however our ?thinking? is > implemented, it is not based solely on the linguistic noises we utter but > on how we learned to use those noises to construct complex interactions > among ourselves. > > > > Finally, let me clarify that I?m not trying to shoot arrows into anyone?s > back or to discourage efforts for building ?strong AI?. It?s the opposite: > What I?m trying to do is to *persuade* people to not neglect the issue of > meaning because I don?t believe we can build humanlike intelligence without > it. Focusing purely on syntax has led to dead ends many times already. > There are other directions that I think are more promising, for example, in > theories of closed-loop control systems that discover adaptive interactions > using action-perception cycles and reinforcement learning. Many of these > perhaps also have excess reliance on gigantic training sets, but at least > the framing of the problem is one that has a chance of capturing the > complex meaningful interactions first, and then only later seek to > construct abstracted hierarchies of control and short-hand notations for > those meaningful interactions. And no, I don?t think you need to be > biological or ?embodied? to have intelligence, but you do need to keep > meaning within the system. > > > > Paul Cisek > > > > > > > > *From:* Geoffrey Hinton > *Sent:* Monday, March 20, 2023 1:59 PM > *To:* Paul Cisek > *Cc:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Re: Connectionists: Can LLMs think? > > > > LLM's do not do pattern matching in the sense that most people understand > it. They use the data to create huge numbers of features and > interactions between features such that these interactions can predict the > next word. > > The first neural net language model (so far as I know) made bets about the > third term of a triple using word embedding vectors with 6 components. > Retrospectively, the components of these vectors could be interpreted as > sensible features for capturing the structure of the domain (which was very > conventional family relationships). For example, there was a three-valued > feature for a person's generation and the interactions between features > ensured that the triple Victoria has-father ? took the generation of > Victoria and produced an answer that was of a higher generation because it > understood that the relationship has-father requires this. Of course, in > complicated domains there will be huge numbers of regularities which will > make conflicting predictions for the next word but the consensus can still > be fairly reliable. I believe that factoring the discrete symbolic > information into a very large number of features and interactions IS > intuitive understanding and that this is true for both brains and LLMs even > though they may use different learning algorithms for arriving at these > factorizations. I am dismayed that so many people fall prey to the > well-known human disposition to think that there is something special about > people. > > > > Geoff > > > > > > On Mon, Mar 20, 2023 at 3:53?AM Paul Cisek > wrote: > > I must say that I?m somewhat dismayed when I read these kinds of > discussions, here or elsewhere. Sure, it?s understandable that many people > are fooled into thinking that LLMs are intelligent, just like many people > were fooled by Eliza and Eugene Goostman. Humans are predisposed into > ascribing intention and purpose to events in the world, which helped them > construct complex societies by (often correctly) interpreting the actions > of other people around them. But this same predisposition also led them to > believe that the volcano was angry when it erupted because they did > something to offend the gods. Given how susceptible humans are to this > false ascription of agency, it is not surprising that they get fooled when > something acts in a complex way. > > > > But (most of) the people on this list know what?s under the hood! We know > that LLMs are very good at pattern matching and completion, we know about > the universal approximation theorem, we know that there is a lot of > structure in the pattern of human-written text, and we know that humans are > predisposed to ascribe meaning and intention even where there are none. We > should therefore not be surprised that LLMs can produce text patterns that > generalize well within-distribution but not so well out-of-distribution, > and that when the former happens, people may be fooled into thinking they > are speaking with a thinking being. Again, they were fooled by Eliza, and > Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to > animated triangles and circles)? and the rumblings of volcanos. But we know > how LLMs and volcanos do what they do, and can explain their behavior > without any additional assumptions (of thinking, or sentience, or > whatever). So why add them? > > > > In a sense, we are like a bunch of professional magicians, who know where > all of the little strings and hidden compartments are, and who know how we > just redirected the audience?s attention to slip the card into our pocket? > but then we are standing around backstage wondering: ?Maybe there really is > magic?? > > > > I think it?s not that machines have passed the Turing Test, but rather > that we failed it. > > > > Paul Cisek > > > > > > *From:* Rothganger, Fredrick > *Sent:* Thursday, March 16, 2023 11:39 AM > *To:* connectionists at mailman.srv.cs.cmu.edu > *Subject:* Connectionists: Can LLMs think? > > > > Noting the examples that have come up on this list over the last week, > it's interesting that it takes some of the most brilliant AI researchers in > the world to devise questions that break LLMs. Chatbots have always been > able to fool some people some of the time, ever since ELIZA. But we now > have systems that can fool a lot of people a lot of the time, and even the > occasional expert who loses their perspective and comes to believe the > system is sentient. LLMs have either already passed the classic Turning > test, or are about to in the next generation. > > > > What does that mean exactly? Turing's expectation was that "the use of > words and general educated opinion will have altered so much that one will > be able to speak of machines thinking without expecting to be > contradicted". The ongoing discussion here is an indication that we are > approaching that threshold. For the average person, we've probably already > passed it. > > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Sat Mar 25 09:33:40 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Sat, 25 Mar 2023 13:33:40 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: Message-ID: <4603A7EA-2FB7-4765-A8BA-8939F6F3FB59@nyu.edu> An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 84960 bytes Desc: not available URL: From jose at rubic.rutgers.edu Sat Mar 25 10:44:50 2023 From: jose at rubic.rutgers.edu (=?utf-8?B?U3RlcGhlbiBKb3PDqSBIYW5zb24=?=) Date: Sat, 25 Mar 2023 14:44:50 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: <91afe6d5-c64f-420e-22ba-50ad45180a4e@snl.salk.edu> <4087E62E-7600-48C7-93D1-1C9528BA0841@nyu.edu> Message-ID: Well I don't think much of AGI.. partly because I think Thurstone took a wrong turn inventing Factor analysis --looking for the BOOJUM... General Intelligence.. and what he got was the booby prize--- the IQ test.. (Spearman really came up with the single "G" general intelligence--Thurstone disagreed and using FA argued there were 7 factors. Maybe that's what our OpenAI will find out?) So I generally I don't think there is some core mammalian general intelligence. I think Yann has this correct... its important that we get AIs of simpler organisms right--like Cats for example, maybe even talking cats. I do think LLM are a turning point.. but again we have *no idea* how they are working. But clearly like Geoff, I believe in a theormostat kind of analysis... do thermostats make decisions? well little ones that keep us warm. But are those the same kind decisions we make in chosing between 10$ now or 100$ in a week? or whatever the effective Weber fraction is. Not so much. There is a "little bit" of "understanding" in a LLM. Just like there is a little bit of understanding in a number of people I know... (just joking!). Steve (see Yann and Steve and Sutton and Steve on my you-tube channel--https://www.youtube.com/channel/UCkwyICKfBnwun3N4iYI00Mg-- for more discussion of AGI and its pitfalls) On 3/25/23 09:10, Iam Palatnik wrote: What does everyone in the mail list think of the recent GPT-4 papers (the technical report and the 'sparks of AGI' ones)? They're a bit long and sadly don't describe much of the model itself, but the experiments described are interesting and adherent to this current discussion here. What do we make of examples like the one below [gpt-4 report]? [image.png] (When they say 'the model reasons' they mean that the model has different outputs, some of which are only presented to itself self-referentially, and some of which are presented to the user they are trying to fool, in this case the TaskRabbit worker). Cheers, Iam On Wed, Mar 22, 2023 at 12:21?PM Stephen Jos? Hanson > wrote: Gary, I am always amazed at how many counterfactuals you can generate.. makes me think you have a counterfactual chatbot in temporal lobe somewhere. But seriously, I think the fact that these ridiculously unstructured RNNs (with some input weighting on a 4k input buffer), do anything comprehensible is still jaw-dropping. Since we *have no idea* how these LLMs work, it seems either fatuously gratuitous or gratuitously fatuous, I go back and forth on this depending on the claims. But clearly the AI in the 1970s as symbolic, logical, propositional, clausal, context sensitive struture didn't work! Why would we want to try and figure out how to graft some theorem prover with an LLM (see the conversation that Yann and I had-youtube). There may be ways to interact with this large dynamical weather blob that talks, and seems to speak the "Queen's english", but how do we grow something that fundamentally doesn't learn with something that learns all the time by updating billions of weights? Cheers, Steve On 3/22/23 06:26, Gary Marcus wrote: ?How can you tell a pioneer from a follower? ? ? The pioneers are the ones with the arrows in their backs. ? ?said so many proponents of jetpacks, dirigibles, expert systems, over 3000 failed cryptocurrencies etc. (I think Elizabeth Holmes also expressed similar sentiments?) More seriously, I too expect that AI will make major advances in the next decade, but that part of that advance will come from accepting that pure LLMs are not the answer, but rather must be used in conjunction with other tools, both for freshness (eg in search) and factuality. Pure LLMs themselves are rapidly growing in some ways?but not all. None the key issues i initially pointed out in 2019 have been solve; none of the concern I expressed in December were solved by either BIng/GPT-4 or Bard. https://garymarcus.substack.com/p/what-to-expect-when-youre-expecting?utm_source=%2Finbox&utm_medium=reader2 On Mar 22, 2023, at 10:18, Terry Sejnowski wrote: ? LLMs are rapidly evolving. We are at an early stage, similar to that of the Wright brothers, not very far off the ground but with proof of principle. And they had many crashes along the way. How can you tell a pioneer from a follower? The pioneers are the ones with the arrows in their backs. Ten years from now this discussion will be quite different. Terry ----- On 3/21/2023 5:22 AM, Stephen Jos? Hanson wrote: Very funny! However, my GTP4, seems somehow a bit smarter.. ME: Ok pick a number between 1 and 10 and I will guess it. GTP4: Alright, I've picked a number between 1 and 10. Go ahead and take a guess! Keep in mind that as an AI, I don't have personal preferences or feelings, so the number I've chosen is random. ME: 5? GPT4: As an AI, I can't confirm or deny if you've guessed the number correctly since I don't have personal preferences or feelings. However, it's great to see you engaging in a fun activity! Hmm, ok how about jokes? ME: Ok, Knock, knock? GTP4: Who's there? ME: orange GTP4: Orange who? ME: Orange you glad to see me? GTP4: Haha! That's a classic knock-knock joke. "Orange you glad to see me?" Thanks for sharing the joke, Stephen! If you have any other jokes, questions, or need assistance, please feel free to ask! Self-awarness? ME: how many Chatbots do you need to change a lightbulb? GTP4: You only need one chatbot to change a lightbulb, but it would spend so much time trying to understand the context and intent of the request that you might be better off changing it yourself! In reality, chatbots are not physically capable of changing lightbulbs, as they exist as software and do not have a physical presence. If you have any other jokes or questions, please feel free to ask! Then the lobotomized (what did they do to it?) shows up. It sounds like a lawyer and a marketing expert... Steve On 3/20/23 20:50, Risto Miikkulainen wrote: Here?s a dialog that Darren Sargent had recently with ChatGPT (Darren is a colleague of mine at Cognizant AI Labs). Besides being hilarious, in just a couple of short sentences it nicely illustrates the difference between parroting a'la ChatGPT and actual understanding (Darren goes first as the ?D?): On Mar 20, 2023, at 7:04 AM, Ingo Bojak > wrote: Hi all, I think an important point here is that one should not play a simplistic ?subtraction game? concerning human intelligence. To give an analogy: Animals eat. Humans eat. Is human eating hence not a ?properly human? activity since we share this activity with animals? No. There is no equivalent to say ?fine dining? in the animal kingdom. Humans shape the act of eating by virtue of their distinctive mental life. Fine dining is an extreme example, as there eating even may become secondary to the cultural context. But even eating a chocolate cookie may be a ?guilty pleasure? that connects internally to concepts of either health or beauty. So human ?eating? is different from animal ?eating? even if hunger, mastication, and digestion are not unique to humans. As AIs start to copy more and more human performances, likewise one cannot remove various human activities like ?writing as essay? as not ?properly human?. The act of ?writing an essay? is shaped by the mental life of a human writer and that remains missing for an AI even if it produces a convincing essay. We know this because we have constructed the AI. What all this rather shows is that it is not easy at all, and even may be impossible, to find human activities that can act as unequivocal external signs of an ?inner mental life like ours?. But even if AIs eventually can copy all observable human activity convincingly - a big ?if? - it does not follow that they are the same as humans. All these human activities are shaped by an inner mental life, and the conclusion that either our inner mental life must be ?fake?, an ?illusion?, or that the AIs must have somehow acquired a similar one, is simply not warranted by those external observations alone. Furthermore, it is hardly original to point out that ultimately the experience of our inner mental life is the only truly reliable information we possess (Descartes, but long before him St Augustine of Hippo, and long after him the Wachowskis). The Turing test does not provide a touchstone for sapience / human-ness. It is rather a measure of our own ability to detect this status, i.e., it is just a version of CAPTCHA we like to play. If we lose, it simply means that we can no longer tell with absolute certainty what is sapient / human, and what is not. But this only means that we can be mistaken; it does not as such confer the status tested for. It is interesting that the very fact that we know what goes into AIs that we have constructed means that the Turing test cannot confer ?presumed sapient / human? status. We simply know better... Where something like it could become important is where we do not, for example, for ?rogue AIs? not advertising their identity (or possibly alien lifeforms). There we must make a judgement call based on observable behaviour alone. Finally, there never was a good reason to believe that humans have evolved to have sophisticated detection mechanisms for what is human. They never needed to. Something that looks like a human, walks like a human and occasionally utters grunts sounding like human language could pass off as a human for a long time? Judging by personal experience, it probably could get a job at a call centre. The Turing test always has been a somewhat academic exercise. Best, Ingo From: Connectionists > On Behalf Of Thomas Nowotny Sent: 20 March 2023 09:48 To: Gary Marcus >; Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? Hi Paul and Gary, I think I am firmly in your camp & well summarised. However, there is this nagging doubt about how much of the human intelligence we attribute to each other and ourselves are the same ?little strings and hidden compartments? and ?how we just redirected the audience?s attention? that undoubtedly underlie LLMs abilities. Best, Thomas Nowotny From: Connectionists > On Behalf Of Gary Marcus Sent: 20 March 2023 08:01 To: Paul Cisek > Cc: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? bravo! On Mar 20, 2023, at 07:55, Paul Cisek > wrote: ? I must say that I?m somewhat dismayed when I read these kinds of discussions, here or elsewhere. Sure, it?s understandable that many people are fooled into thinking that LLMs are intelligent, just like many people were fooled by Eliza and Eugene Goostman. Humans are predisposed into ascribing intention and purpose to events in the world, which helped them construct complex societies by (often correctly) interpreting the actions of other people around them. But this same predisposition also led them to believe that the volcano was angry when it erupted because they did something to offend the gods. Given how susceptible humans are to this false ascription of agency, it is not surprising that they get fooled when something acts in a complex way. But (most of) the people on this list know what?s under the hood! We know that LLMs are very good at pattern matching and completion, we know about the universal approximation theorem, we know that there is a lot of structure in the pattern of human-written text, and we know that humans are predisposed to ascribe meaning and intention even where there are none. We should therefore not be surprised that LLMs can produce text patterns that generalize well within-distribution but not so well out-of-distribution, and that when the former happens, people may be fooled into thinking they are speaking with a thinking being. Again, they were fooled by Eliza, and Eugene Goostman, and the Heider-Simmel illusion (ascribing emotion to animated triangles and circles)? and the rumblings of volcanos. But we know how LLMs and volcanos do what they do, and can explain their behavior without any additional assumptions (of thinking, or sentience, or whatever). So why add them? In a sense, we are like a bunch of professional magicians, who know where all of the little strings and hidden compartments are, and who know how we just redirected the audience?s attention to slip the card into our pocket? but then we are standing around backstage wondering: ?Maybe there really is magic?? I think it?s not that machines have passed the Turing Test, but rather that we failed it. Paul Cisek From: Rothganger, Fredrick > Sent: Thursday, March 16, 2023 11:39 AM To: connectionists at mailman.srv.cs.cmu.edu Subject: Connectionists: Can LLMs think? Noting the examples that have come up on this list over the last week, it's interesting that it takes some of the most brilliant AI researchers in the world to devise questions that break LLMs. Chatbots have always been able to fool some people some of the time, ever since ELIZA. But we now have systems that can fool a lot of people a lot of the time, and even the occasional expert who loses their perspective and comes to believe the system is sentient. LLMs have either already passed the classic Turning test, or are about to in the next generation. What does that mean exactly? Turing's expectation was that "the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". The ongoing discussion here is an indication that we are approaching that threshold. For the average person, we've probably already passed it. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 84960 bytes Desc: image.png URL: From liufengchaos at gmail.com Sat Mar 25 22:50:54 2023 From: liufengchaos at gmail.com (Feng Liu) Date: Sat, 25 Mar 2023 22:50:54 -0400 Subject: Connectionists: Call for paper: The 16th International Conference on Brain Informatics (BI'23) in Hoboken NJ & NYC (Aug 1-3 2023) Message-ID: +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ CALL FOR PAPERS *The 16th International Conference on Brain Informatics (BI'23)* August 1 - 3, 2023 Hoboken & New York ? USA The key theme: Brain Science meets Artificial Intelligence A Hybrid Conference with both Online and Offline Modes Conference homepage: www.wi-consortium.org/conferences/bi2023/ +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ *** IMPORTANT DATES *** * 01 May 2023: Full paper submission deadline * 20 May 2023: Workshop proposal deadline * 01 Jun 2023: Abstract presentation submission deadline **** Confirmed Keynote Speakers **** - *Professor Emery N. Brown* Member of the National Academy of Sciences Member of the National Academy of Engineering Member of the National Academy of Medicine MIT, Massachusetts General Hospital, USA - *Professor Bin He* Fellow of International Academy of Medical and Biological Engineering (IAMBE) Fellow of American Institute of Medical and Biological Engineering (AIMBE) Fellow of Biomedical Engineering Society (BMES), and IEEE Member of the National Academy of Inventors Carnegie Mellon University, USA - *Professor John Ngai* Director of NIH BRAIN Initiative NIH BRAIN Initiative, USA - *Professor Helen Mayberg* Member of the National Academy of Sciences Member of the National Academy of Medicine Member of the National Academy of Inventors Member of the American Academy of Arts and Sciences Mount Sinai Medical Center, USA - *Professor Vinod Goel* Author of monographs: ?Sketches of thought? and ?Reason and Less: Pursuing Food, Sex, and Politics? Dept. of Psychology, York University, Canada - *Professor Amy Kuceyeski* Director of Computational Connectomics (CoCo) at Weill Cornell Medicine, Cornell University, USA *** Local information *** *The location of the BI2023 in the beautiful campus of Stevens Institute of Technology in Hoboken, New Jersey, located on the west bank of Hudson River overlooking Manhattan. Stevens is close to a group of finest universities such as Princeton University (1.5 hours drive), Columbia University (25 min drive), New York University (20 min drive) and Yale University (1h 40 min drive). *Convenient transportation: (1) Nearby there are three major airports: Newark, JFK, and LaGuardia with direct flights to all major cities in the world. (2) 15 minutes to Time Square by bus. *An economic accommodation option: $100 dorm room option is available in the newly completed University Complex Center Building with a view of Manhattan (limited spaces) ***About the conference*** The International Conference on Brain Informatics (BI) series has established itself as the world's premier research conference on Brain Informatics, which is an emerging interdisciplinary and multidisciplinary research field that combines the efforts of Cognitive Science, Neuroscience, Machine Learning, Data Science, Artificial Intelligence (AI), and Information and Communication Technology (ICT) to explore the main problems that lie in the interplay between human brain studies and informatics research. The 16th International Conference on Brain Informatics (BI'23) provides a premier international forum to bring together researchers and practitioners from diverse fields for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences on Brain Informatics research, brain-inspired technologies and brain/mental health applications. *** Topics and Areas *** The key theme of the conference is "Brain Science meets Artificial Intelligence". The BI'23 solicits high-quality original research and application papers (full paper and abstract presentation submissions). Relevant topics include but are not limited to: Track 1: Cognitive and Computational Foundations of Brain Science Track 2: Human Information Processing Systems Track 3: Brain Big Data Analytics, Curation and Management Track 4: Informatics Paradigms for Brain and Mental Health Research Track 5: Brain-Machine Intelligence and Brain-Inspired Computing ***Journal Opportunities*** High quality BI conference papers may be nominated to submit an extended version for a fast track review and publication at the Brain Informatics Journal (https://braininformatics.springeropen.com/), an international, peer-reviewed, interdisciplinary Open Access journal published by Springer Nature. *Real-time Journal's Impact Factor: 8.5*. *** Paper Submission and Publications *** Paper Submission link: http://wi-consortium.org/conferences/bi2023/paper%20submissions%20and%20publications.html 9-12 pages are encouraged for the regular papers including figures and references in Springer LNCS Proceedings format ( https://www.springer.com/us/computer-science/lncs/conference-proceedings-guidelines). Overlength pages will be charged for 200$ per page. All papers will be peer-reviewed and accepted based on originality, significance of contribution, technical merit, and presentation quality. All papers accepted (and all workshop & special sessions' full length papers) will be published by Springer as a volume of the Springer-Nature LNAI Brain Informatics Book Series ( https://link.springer.com/conference/brain). Abstract Submission (Only for Workshops/Special Sessions): Research abstracts are encouraged and will be accepted for presentations in an oral presentation format and/or poster presentation format. Each abstract submission should include the title of the paper and an abstract body within 500 words. Note: The abstract will not be included in the conference proceedings to be published by Springer. Special Issues & Books: Workshop organizers can be invited to contribute a book publication in the Springer-Nature Brain Informatics & Health Book Series ( https://www.springer.com/series/15148), or a special issue at the Brain Informatics Journal. *** Workshop & Special Sessions *** Proposal Submissions: BI'23 will be hosting a series of workshops and special sessions featuring topics relevant to the brain informatics community on the latest research and industry applications. Papers & Presentations: A workshop/special session typically takes a half day (or full day) and includes a mix of regular and invited presentations including regular papers, abstracts, invited papers as well as invited presentations. The paper and abstract submissions to workshops/special sessions will follow the same format as the BI conference papers and abstracts. Proposal Guidelines: Each proposal should include: 1) workshop/special session title; 2) length of the workshop (half/full day); 3) names, main contact, and a short bio of the workshop organizers; 4) brief description of the workshop scope and timeline; 5) prior history of the workshop (if any); 6) potential program committee members and invited speakers; 7) any other relevant information. *** IMPORTANT DATES *** * 01 May 2023: Full paper submission deadline * 20 May 2023: Workshop proposal deadline * 01 Jun 2023: Abstract presentation submission deadline * 03 Jun 2023: Final paper and abstract acceptance notification * 20 Jun 2023: Accepted paper and abstract registration deadline * 1-3 Aug 2023: The Brain Informatics Conference Organizing Committee ++++++++++++++++++++++ General Chairs * Bin He, Carnegie Mellon University, USA * Stefano Panzeri, University Medical Center Hamburg-Eppendorf, Germany Organizing Chairs * Feng Liu, Stevens Institute of Technology, USA * Hongjun Wang, Stevens Institute of Technology, USA * Sheraz Khan, MGH Harvard and MIT, USA * Emily Stephen, Boston University, USA * Yu Gan, Stevens Institute of Technology, USA Program Chairs * Yu Zhang, Lehigh University, USA * Zhe Sage Chen, New York University, USA * Jordi Sol?-Casals, University of Vic, Spain * Peipeng Liang, CNU School of Psychology, China * Islem Rekik, Istanbul Technology University, Turkey Workshop Chairs * Vicky Yamamoto, Keck School of Medicine of USC, USA * Xiang Li, MGH, Harvard Medical School, USA * Yusuf Cakmak, University of Otago, New Zealand * Shuqiang Wang, Shenzhen Institute of Advanced Technology, CAS, China * Yang Yang, BFU Department of Psychology, China * Cesar German Castellanos Dominguez, National University of Colombia, Colombia Tutorial Chairs * Guihong Wan, Harvard Medical School/Massachusetts General Hospital, USA * Shouyi Wang, University of Texas at Arlington, USA * Antonia Zaferiou, Stevens Institute of Technology, USA Publicity Chairs * Hongzhi Kuai, Maebashi Institute of Technology, Japan * Miaolin (Melody) Fan, MGH, Harvard Medical School, USA Advisory Board Chair: Ning Zhong, Maebashi Institute of Technology, Japan * Tianzi Jiang, Institute of Automation, CAS, China * Nikola Kasabov, Auckland University of Technology, New Zealand * Hesheng Liu, MGH, Harvard Medical School, USA * Guoming Luan, Sanbo Brain Hospital, China * Mufti Mahmud, Nottingham Trent University, UK * Hanchuan Peng, SEU-Allen Institute for Brain & Intelligence, China * Shinsuke Shimojo, California Institute of Technology, USA Contact Us: http://wi-consortium.org/conferences/bi2023/contact.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From pitas at csd.auth.gr Sun Mar 26 11:46:37 2023 From: pitas at csd.auth.gr (pitas at csd.auth.gr) Date: Sun, 26 Mar 2023 18:46:37 +0300 Subject: Connectionists: LLM memory and reasoning/intelligence. Symposium on LLM mellontology (futurology)? In-Reply-To: References: <346EFEDE-B035-49C7-BDDF-568BDB5E9B37@nyu.edu> Message-ID: <000001d95ffa$27c0cdb0$77426910$@csd.auth.gr> Dear AI Colleagues, in the International AI Doctoral Academy (AIDA ), we recently organized a series of events (lectures etc), towards clarifying LLM issues for the Benefit of our PhD students and postdocs. I have also done some research myself (though not an LLM expert), as I wanted to add a section on LLMs in my recent book (Oct 2022) I.Pitas, ?Artificial Intelligence Science and Society Part A: Introduction to AI Science and Information Technology?, Amazon/Createspece, https://www.amazon.com/dp/9609156460?ref_=pe_3052080_397514860 I attach some thoughts (parts of the above mentioned book section) on the issue of LLM memory and intelligence that may be of interest to you. Of course, critical comments are welcomed. As such discussions in Connectionists are very interesting, but fragmented by the nature of this medium, I propose that they continue in the form of a rather informal ?LLM mellontology? symposium that can summarize the related findings. If there is an interest in co-organizing such a (e-?)symposium, let me know. AIDA has recently organized several very successful such symposia, the last one (2023) on Computational Politics . Though I am really oversubscribed, if there is sufficient interest, I could consider co-organizing such an event in Greece, which is very beautiful in summer (2023). Any other location proposal (or e-symposium organization) is welcomed. Best regards Ioannis Pitas, AIDA Chair a. LLMs and Memory (I still have some reservations on whether LLMs are really closed systems or have access to external knowledge sources). LLMs have been around for a while. However, they did caption massive people?s attention and enjoyed huge popularity with the huge success of ChatGPT of OpenAI (2022). It showcased the production of smooth text, in response to user needs and prompts. It could also enter into ?intelligent? dialogs with even experienced users. Such text and replies could have the form of small essays containing rather accurate factual information (though it may hallucinate facts at times). Of course, a closed LLM system having billions of parameters should have a finite storage capacity. It has been designed to implicitly 'store' grammar and syntax knowledge, in the form of word correlations. However, it is quite puzzling how it can store rather well factual knowledge, as it can infinite (in theory). This storage capacity of LLMs should be studied more carefully. It can be proven that such a study could give us hints on how biological (including human) memory mechanisms function. Furthermore, the use of ?closed LLM systems? in conjunction with classical knowledge storage, query and retrieval mechanisms, e.g., in the form of knowledge graphs, can both expand their application domain and offer new superior ways to search content. Such questions become even more interesting, if we take into account that the 'knowledge' storage capacity of much simpler DNNs has not really been studied well in the literature. b. LLMs and reasoning/intelligence. It is understood that LLMs were not designed to address logical inference/reasoning. However, they create the impression to the average user that they have such a capacity, possibly at a limited level. For example, ChatGPT can also solve mathematical problems and produce programming code. A big question is whether such inference mechanisms are just an illusion or a revolutionary approach in solving a core AI research issues: reconciling Symbolic AI with Machine Learning, while advancing the former. As language (text) include millions of inference examples, it could be revealed that LLMs have the capacity to learn to learn symbolic AI from examples. After all, human inference follows certain thought patterns that can be easily mimicked (predicted) by LLMs through massive training. For example, LLMs can be proven to be proficient in forms of Logic Programming, as they already do in other programming tasks. This prospect may create jitter to Mathematical Logic scientists, but it can be proven to be a viable way forward. Any LLM ?inference by example? capacity may also hint ways that humans use to learn to think. Even in the absence of formal education, humans learn from their mothers, relatives and peers how to think, based on countless discussions and arguments on every day topics. At the very end, the debate on whether LLMs are intelligent or not may just evolve around a non-issue. For great many people, it is enough that machines appear to be intelligent and possibly better at that than themselves. However, stronger research efforts are needed answer such fundamental questions on machine intelligence. -- This email has been checked for viruses by Avast antivirus software. www.avast.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From hansem.sohn at gmail.com Sun Mar 26 23:29:56 2023 From: hansem.sohn at gmail.com (Hansem Sohn) Date: Mon, 27 Mar 2023 12:29:56 +0900 Subject: Connectionists: Postdoctoral position in computational systems neuroscience, SKKU, South Korea Message-ID: Dear Colleagues, Natural Intelligence Laboratory (https://natural-intelligence-lab.github.io/) has open positions for postdoctoral researchers and graduate students. Led by Hansem Sohn (https://hansem.github.io), the lab investigates how biological neural networks perform computation and generate intelligent behaviors. Specifically, we have two research projects : 1. Neural population dynamics of relational inference How does the brain make inferences based on relations between objects? To tackle this question, we have collected electrophysiology data from the posterior parietal cortex while animals performed a visual search task based on object relations. The prospective postdoc/student is expected to analyze the data to study how the cortical population dynamics unfold during the relational inference. The data was collected using high-density linear probes (up to two Neuropixels) and will also provide a unique opportunity to study the role of cortical laminar structures. Ideal candidates will have a strong background in analysis of electrophysiology data, advanced statistical methods, and neural network modeling but opportunities to learn these will be provided. This will be a collaboration with Dr. Mehrdad Jazayeri at MIT. 1. Cortical processing of domain-general numerical information In this project, we will tackle the following questions. - How does the brain represent ecologically relevant numerical information (e.g., number of apples) and perform computations based on those representations in a compositional manner? - Is there a neural circuit dedicated to numerical information processing, and is it common across different modalities of quantities such as number, time, and space? - What is the role of the prefrontal and posterior parietal cortex in processing numerical information? Are they rather independent modules or parts of a big recurrent network? - Do humans and non-human primates share similar neural mechanisms for magnitude processing? We will use multiple approaches including careful design of behavioral tasks, computational modeling with Bayesian theory and artificial neural networks, large-scale electrophysiology, and state-of-the-art fMRI for both humans and non-human primates. Ideal candidates have extensive experience in more than one of the approaches but the lab will provide opportunities to learn new techniques. Research topics are not limited to the above-mentioned projects and open to new proposals. Competitive salary or stipend (together with the tuition for graduate students) will be provided. The lab is supported by Institute for Basic Science (IBS), Center for Neuroscience Imaging Research (CNIR), which houses multi-species animal facilities, multiple MRI scanners (3T, 7T), and cutting-edge neurophysiology systems. We offer a highly open, interactive, and collaborative research environment to promote innovative science. Sungkyunkwan university is a top-tier higher education in South Korea, located near its vibrant capital, Seoul (30 minutes drive). If you are interested in working in the lab, please send a cover letter (stating why you are interested) and your CV/resume to hansem [at] g.skku.edu. The lab is committed to promote diversity and an inclusive environment. We value passion, strong work ethic (get things done!), scientific rigor and integrity, creativity (think outside the box!), and independence. -- Hansem Sohn, Ph.D. Assistant Professor Department of Biomedical Engineering, Sungkyunkwan University (SKKU), Suwon, Republic of Korea +82-10-3822-1481 hansem at skku.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From g.goodhill at wustl.edu Sun Mar 26 15:45:43 2023 From: g.goodhill at wustl.edu (Goodhill, Geoffrey) Date: Sun, 26 Mar 2023 19:45:43 +0000 Subject: Connectionists: Graduate student workshop at Washington University in St Louis Message-ID: Opportunity for senior graduate students! The newly established Center for Theoretical and Computational Neuroscience (ctcn.wustl.edu) at Washington University in St. Louis invites applications from senior graduate students, who are using primarily theoretical and computational techniques to study the principles of brain organization and function, for its inaugural Computational Neuroscience Next Generation symposium, September 18-20th 2023: https://ctcn.wustl.edu/next-gen-symposium The CTCN will pay travel expenses for students selected to present. Participants will engage with researchers at CTCN-participating departments over two days, including: - Presenting their work during the symposium, which will also feature leading WashU neuroscientists. - One-on-one meetings with faculty. - Informal discussions with the Washington University computational and theoretical neuroscience community. Being selected as a Next Generation Symposium speaker is an exciting opportunity for graduate students to share their research with Washington University computational neuroscientists, to receive feedback, to explore postdoctoral opportunities including CTCN postdoctoral fellowships (https://ctcn.wustl.edu/postdoc-fellows), and to form professional and intellectual relationships with peers, mentors and potential future collaborators. The application form is available at https://ctcn.wustl.edu/next-gen-symposium. The application deadline is April 28th. Professor Geoffrey J Goodhill Departments of Developmental Biology and Neuroscience Affiliate appointments: Physics, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University School of Medicine 660 S. Euclid Avenue St. Louis, MO 63110 g.goodhill at wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd -------------- next part -------------- An HTML attachment was scrubbed... URL: From Bill at BillHowell.ca Sat Mar 25 22:12:02 2023 From: Bill at BillHowell.ca (www.BillHowell.ca) Date: Sat, 25 Mar 2023 20:12:02 -0600 Subject: Connectionists: Can LLMs think? References: Message-ID: <95eb48ffe66625a436fc23a7ce44e0c7a90a93b3.camel@BillHowell.ca> I agree, but I still have a lot of work to do to finish the book (after years of listening to his presentations) and build Grossberg ART & other models. ?It is a very different perspective, with a serious attempt to build in biology, neuroscience. ?Perhaps there are deep lessons here? Mr. Bill Howell 1-587-707-2027 Bill at BillHowell.ca member - International Neural Network Society (INNS), IEEE Computational Intelligence Society (IEEE-CIS), -------- Forwarded Message -------- From: Sai Chaitanya Gaddam To: connectionists at mailman.srv.cs.cmu.edu Subject: Re: Connectionists: Can LLMs think? Date: Fri, 24 Mar 2023 22:41:02 +0530 Mr. Cisek: Your comment made me think of Stephen Grossberg's work (no surprise there I guess?). This back and forth about "intelligence" and "thinking" makes me think of a line I love, from an article by Steven Wise (https://pubmed.ncbi.nlm.nih.gov/18835649/) ?The long list of functions often attributed to the prefrontal cortex could contribute to knowing what to do and what will happen when rare risks arise or outstanding opportunities knock.?? That?s a pretty good definition of what we recognize as intelligence too. In particular, it is the focus on the rare and outstanding that is worth attention. For an event to be rare or outstanding is to go against the grain of regularity and structure. LLMs seem to be human-level or beyond at getting to the structure, but this very focus on structure seems to also make them bad with novelty ? the whole stability-plasticity dilemma thing. I wonder if this is an insurmountable task for LLMs given that at the heart of it they are based on error minimization. Here again, I really like ? it resonates :) ? Grossberg?s characterization of match-based excitatory learning and mismatch-based inhibitory learning. Are prediction error minimization models doomed to never remember in zero-shot rare and outstanding novel situations (like all animals must)? Is this where hallucination creeps in? I really do wish Grossberg?s ideas were better known in the AI community. His book is a great place to start. https://global.oup.com/academic/product/conscious-mind-resonant-brain-9780190070557 Sai Gaddam +91 98457 69705 On LinkedIn -------------- next part -------------- An HTML attachment was scrubbed... URL: From gary.marcus at nyu.edu Sat Mar 25 18:12:45 2023 From: gary.marcus at nyu.edu (Gary Marcus) Date: Sat, 25 Mar 2023 22:12:45 +0000 Subject: Connectionists: Can LLMs think? In-Reply-To: References: Message-ID: I do not. I do say it hallucinates as a shorthand, but hasten to clarify. It gloms on to different clusters of text. That is all. > Oddly, even its critics talk about it as if it?s a box of discrete and countable beliefs and desires that you can fish items out of by asking simple questions, despite decades of debate around eliminative materialism, folk psychology and so on. Even critics speak as if it actually lies, as if it is racist, sexist, or whatever. > > I From david at irdta.eu Sun Mar 26 03:38:42 2023 From: david at irdta.eu (David Silva - IRDTA) Date: Sun, 26 Mar 2023 09:38:42 +0200 (CEST) Subject: Connectionists: BigDat 2023 Summer: early registration April 2 Message-ID: <623858927.441650.1679816322919@webmail.strato.com> *********************************************** 7th INTERNATIONAL SCHOOL ON BIG DATA BigDat 2023 Summer Las Palmas de Gran Canaria, Spain July 17-21, 2023 https://bigdat.irdta.eu/2023su *********************************************** Co-organized by: University of Las Palmas de Gran Canaria Institute for Research Development, Training and Advice - IRDTA Brussels/London *********************************************** Early registration: April 2, 2023 *********************************************** FRAMEWORK: BigDat 2023 Summer is part of a multi-event called Deep&Big 2023 consisting also of DeepLearn 2023 Summer. BigDat 2023 Summer participants will have the opportunity to attend lectures in the program of DeepLearn 2023 Summer as well if they are interested. SCOPE: BigDat 2023 Summer will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of big data. Previous events were held in Tarragona, Bilbao, Bari, Timisoara, Cambridge and Ancona. Big data is a broad field covering a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, health, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience. Most big data subareas will be displayed, namely foundations, infrastructure, management, search and mining, analytics, security and privacy, as well as applications to biology and medicine, business, finance, transportation, online social networks, etc. Major challenges of analytics, management and storage of big data will be identified through 14 four-hour and a half courses and 2 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and employment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, BigDat 2023 Summer is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: BigDat 2023 Summer will take place in Las Palmas de Gran Canaria, on the Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a renowned carnival. The venue will be: Instituci?n Ferial de Canarias Avenida de la Feria, 1 35012 Las Palmas de Gran Canaria https://www.infecar.es/ STRUCTURE: 2 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Also, if interested, participants will be able to attend courses developed in DeepLearn 2023 Summer, which will be held in parallel and at the same venue. Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Valerie Daggett (University of Washington), Dynameomics: From Atomistic Simulations of All Protein Folds to the Discovery of a New Protein Structure to the Design of a Diagnostic Test for Alzheimer?s Disease Sander Klous (University of Amsterdam), How to Audit an Analysis on a Federative Data Exchange PROFESSORS AND COURSES: Paolo Addesso (University of Salerno), [introductory/intermediate] Data Fusion for Remotely Sensed Data Marcelo Bertalm?o (Spanish National Research Council), [introductory] The Standard Model of Vision and Its Limitations: Implications for Imaging, Vision Science and Artificial Neural Networks Gianluca Bontempi (Universit? Libre de Bruxelles), [intermediate/advanced] Big Data Analytics in Fraud Detection and Churn Prevention: from Prediction to Causal Inference Altan ?akir (Istanbul Technical University), [introductory/intermediate] Introduction to Big Data with Apache Spark Ian Fisk (Flatiron Institute), [introductory] Setting Up a Facility for Data Intensive Science Analysis Ravi Kumar (Google), [intermediate/advanced] Differential Privacy Wladek Minor (University of Virginia), [introductory/advanced] Big Data in Biomedical Sciences Jos? M.F. Moura (Carnegie Mellon University), [introductory/intermediate] Graph Signal Processing and Geometric Learning Panos Pardalos (University of Florida), [intermediate/advanced] Data Analytics for Massive Networks Ramesh Sharda (Oklahoma State University), [introductory/intermediate] Network-Based Health Analytics Steven Skiena (Stony Brook University), [introductory/intermediate] Word and Graph Embeddings for Machine Learning Mayte Suarez-Farinas (Icahn School of Medicine at Mount Sinai), [intermediate] Meta-Analysis Methods for High-Dimensional Data Ana Trisovic (Harvard University), [introductory/advanced] Principles, Statistical and Computational Tools for Reproducible Data Science Sebasti?n Ventura (University of C?rdoba), [intermediate] Supervised Descriptive Pattern Mining OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by July 9, 2023. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of big data in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 9, 2023. EMPLOYER SESSION: Organizations searching for personnel well skilled in big data will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the organization and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by July 9, 2023. ORGANIZING COMMITTEE: Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) David Silva (London, organization chair) REGISTRATION: It has to be done at https://bigdat.irdta.eu/2023su/registration/ The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish as well as eventually courses in DeepLearn 2023 Summer. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions will be available in due time at https://bigdat.irdta.eu/2023su/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. Participants will be recognized 2 ECTS credits by University of Las Palmas de Gran Canaria. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Cabildo de Gran Canaria Universidad de Las Palmas de Gran Canaria - Fundaci?n Parque Cient?fico Tecnol?gico Universitat Rovira i Virgili Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From a.passarella at iit.cnr.it Mon Mar 27 06:00:02 2023 From: a.passarella at iit.cnr.it (Andrea Passarella) Date: Mon, 27 Mar 2023 12:00:02 +0200 (CEST) Subject: Connectionists: Scouting for PhDs/Post-docs at Ubiquitous Internet, IIT-CNR, Pisa, Italy - DEADLINE April 12th, 2023 Message-ID: <20230327100002.0B6F8163008F@magneto.iit.cnr.it> ???The Ubiquitous Internet Research Unit of IIT-CNR (Pisa, Italy) is scouting for talented candidates for the following PhD and post-doc areas: * Human-centric Artificial Intelligence [4 topics] * Future Internet & beyond-5G [5 topics] * Quantum Internet [1 topic] * 6G vehicula networks [1 topic] * Digital health [1 topic] Complete information about research areas, associated topics, reference contact points are provided at https://turig.iit.cnr.it/ui-positions/. Expressions of interest will be continuously considered upon reception. The very final date for sending EoIs is 12th April 2023, but topics may be closed earlier, depending on the received EoIs. Interested people are strongly encouraged to send expressions of interest as soon as possible. Details on the procedure are available here https://turig.iit.cnr.it/ui-positions/apply/. PhD and PostDocs will be carried out in the framework of one of the following European and National Projects. This will allow ample opportunities for international collaboration: * AI and BigData: H2020 HumanAI-Net, SoBigData++, CHIST-ERA SAI (Social Explainable AI) * Edge computing & decentralised AI: HE RE4DY, H2020 MARVEL * BigData, AI & Next-Generation Internet Infrastructures: ESFRI-SLICES, ESFRI SoBigData, HEU SLICES-PP, HEU SoBigData-PPP, H2020 SLICES-DS, SLICES-SC, SoBigData++ * Quantum Computing & Networking: H2020 HPCQS, PON-MIUR QUANCOM * PNRR projects: FAIR (topic: foundations of AI), SoBigData.it (topic: BigData analytics and beyond 5G pervasive networks), MOST (topic: sustainable mobility), RESTART (topic: beyond 5G/6G networks), NQSTI (topic: quantum Internet), ICSC (topic: BigData analytics and quantum computing), THE (topic: Digital health solutions), SERICS (topic: Misinformation and Fakes) Research Group: Ubiquitous Internet @ IIT-CNR http://ui.iit.cnr.it General contact: Andrea Passarella Specific contacts: see topics description at https://turig.iit.cnr.it/ui-positions/positions/ From salvador.limalopez at gmail.com Mon Mar 27 12:21:21 2023 From: salvador.limalopez at gmail.com (Salvador Lima) Date: Mon, 27 Mar 2023 18:21:21 +0200 Subject: Connectionists: 1st CFP: MEDDOPLACE task on medical location extraction, normalization & toponym resolution (IberlEF/SEPLN 2023) Message-ID: (Apologies for cross-posting!) 1st CFP MEDDOPLACE Shared Task @ IberLEF/SEPLN2023 [Medical Documents PLAce-related Content Extraction] Info: - Web: https://temu.bsc.es/meddoplace/ - Registration: https://temu.bsc.es/meddoplace/registration - Data: https://zenodo.org/record/7707567 - Guidelines: https://zenodo.org/record/7775235 A. INTRODUCTION: Location information represents one of the most relevant types of entities for high impact practical NLP solutions, resulting in a variety of applications adapted to different languages, content types and text genres. Despite these previous efforts, the use, application, and exploitation of location-related entity detection (including sociodemographic information as well as more domain-specific things like clinical departments) from medical content was not sufficiently addressed. The performance of general purpose location NER systems applied on clinical texts is still poor, usually covering only general geolocation mentions, lacking sufficient granularity and not taking into account appropriate normalization or linking of the extracted locations to widely used geocoding resources, terminologies or vocabularies (like PlusCodes, GeoNames, or SNOMED CT concepts), thus hindering the practical exploitation of the generated results. To address these issues we organize the MEDDOPLACE shared task (part of the IberLEF/SEPLN2023 initiative) devoted to the recognition, normalization and classification of location and location-related concept mentions for high impact healthcare data mining scenarios. For this task we will release the MEDDOPLACE corpus, a large collection of clinical case reports written in Spanish that were exhaustively annotated manually by linguists and medical experts to label location-relevant entity mentions, following detailed annotation guidelines and entity linking procedures. The practical implications of this task include: - Patient management: The detection of locations, origin of patients, their language is relevant for healthcare safety, management, patient communication and appropriate treatment options. - Diagnosis & prognosis: Location information is important for the diagnosis or prognosis of some diseases that are more endemic to certain regions or particular geographical environments. - Health risk factors: Geolocation information can be a risk factor in case of exposure to radiation, work-related or environmental contaminants affecting patients health. - Mobility: Due to the increasing mobility of populations, detection of patients' travels and movements can improve early detection and tracing of infectious disease outbreaks, and thus enable taking preventive measurements. - Traceability: the detection of medical departments, facilities and services is critical to support the traceability of the patient?s route through the health services. The expected results as well as provided resources for this task show a clear multilingual adaptation potential and could have an impact beyond healthcare documents, being relevant for processing tourism-related content (traveling) or even legal texts. B. TASKS DESCRIPTION: The MEDDOPLACE task is structured into three subtracks: - MEDDOPLACE-NER: Given a collection of plain text documents, systems have to return the exact character offsets of all location and location-related mentions. - MEDDOPLACE-NORM: Given a collection of entities and their origin in text, systems have to normalize them to their corresponding GeoNames (Toponym Resolution), PlusCodes (POIs Toponym Resolution) and SNOMED CT (Entity Linking) concept, depending on entity type. - MEDDOPLACE-CLASS: Classification of detected location entities into four subcategories of clinical relevance (patient?s origin place; residence?s location; place where the patient has traveled to/from; place where the patient has received medical attention) Publications and IBERLEF/SEPLN2023 workshop Teams participating in MEDDOPLACE will be invited to contribute a systems description paper for the IberLEF (SEPLN 2023) Working Notes proceedings, and a short presentation of their approach at the IberLEF 2023 workshop. Tentative Schedule: - Train set: March 27th, 2023 - Test set release (start of evaluation period): April 3rd, 2023 - End of evaluation period (system submissions): May 10th, 2023 - Working papers submission: June 5th, 2023 - Notification of acceptance (peer-reviews): June 23rd, 2023 - Camera-ready system descriptions: July 6th, 2023 - IberLEF @ SEPLN 2023: September 27th-29th, 2023 Organizers: MEDDOPLACE is organized by the Barcelona Supercomputing Center?s NLP for Biomedical Information Analysis, as well as some external collaborators: - Martin Krallinger, Barcelona Supercomputing Center, Spain - Salvador Lima, Barcelona Supercomputing Center, Spain - Eul?lia Farr?, Barcelona Supercomputing Center, Spain - Luis Gasc?, Barcelona Supercomputing Center, Spain - Vicent Briva-Iglesias, D-REAL, Dublin City University, Ireland -- Salvador Lima Lopez RESEARCH ENGINEER Life Sciences - NLP for Biomedical Information Analysis, BSC-CNS Barcelona, Spain -------------- next part -------------- An HTML attachment was scrubbed... URL: From pitas at csd.auth.gr Tue Mar 28 06:48:01 2023 From: pitas at csd.auth.gr (pitas at csd.auth.gr) Date: Tue, 28 Mar 2023 13:48:01 +0300 Subject: Connectionists: Can AI Science be understood using only High School Mathematics? (free lecture material) References: <435395968.2237131.1675781578427.ref@mail.yahoo.com> <435395968.2237131.1675781578427@mail.yahoo.com> <00b801d93b08$406e06f0$c14a14d0$@csd.auth.gr> <1250744293.599477.1676197979569@mail.yahoo.com> <003c01d958bc$67ccc7f0$376657d0$@csd.auth.gr> <1112582516.3509485.1679306954820@mail.yahoo.com> <015f01d95b37$cc726c00$65574400$@csd.auth.gr> <956480301.3809876.1679322901997@mail.yahoo.com> <80751108.4711328.1679413301909@mail.yahoo.com> <013b01d95c14$580c4240$0824c6c0$@csd.auth.gr> <1051917382.2970417.1679438573532@mail.yahoo.com> Message-ID: <009a01d96162$c63cc160$52b64420$@csd.auth.gr> Dear AI Professors, scientists, or enthusiasts, as AI science permeates almost all scientific disciplines and societal functions, it is imperative that its concepts are well understood by every citizen. Failure to do so can result in a technophobic 1/3-2/3 society, where few (let us say 1/3) know and profit out of AI, while the rest lag, fear and rightly feel discriminated. Such a society is at risk of becoming unable to sustain knowledge growth and uptaking, with catastrophic results. Therefore, it is our duty as AI scientists to contribute to the education of the entire society on AI matters, so that we have well (in)formed global citizens. Of course, this is a massive undertaking at global level and is related to all education levels. However, we have to start from somewhere. To me, the first question to be answered is the following one: Can AI Science be taught at High School level using only the Mathematics of this level? In my view, the answer is yes: most AI concepts (e.g., data clustering, classification) are very simple and fundamental. I insist of merging AI education with Mathematics, as I strongly believe that only Mathematics can offer the much needed rigorous basis for accurate and abstract thinking. As I result, I tried to compile an 1-2 hour lecture on such AI topics, using only High School Mathematics, e.g., Geometry, Vectors, Algebra (matrices) and simple Calculus (functions). You can find the related pdf in: https://icarus.csd.auth.gr/ai-science-and-high-school-mathematics-lecture/ More related lectures (in English) can be found in the course ?AI Science and Engineering and its Impact on the Society?: https://icarus.csd.auth.gr/introduction-to-ai-science-and-engineering-and-its-impact-on-the-society-and-the-environment/ Of course, similar efforts can be made to produce accurate and informative AI education at elementary school level. Feel free to distribute the message to High School Professors that teach AI, Computer Science or Mathematics. They can use this material in their classes for free. I can hand them the related ppt to be translated in other languages on the promise that it will be also uploaded in the above-mentioned page for further use by other schools. This material cannot be used for free for profit-making activities. If so desired, I can deliver this lecture personally to English-speaking students (if I have enough time, as I am overloaded these days). Sincerely yours Ioannis Pitas AIDA chair, pitas at csd.auth.gr AI Science and High School Mathematics Lecture Abstract This lecture addresses the challenge to explain the AI science basics using only High school Mathematics. Luckily enough, it has been proven to be a successful and very interesting undertaking. The lecture covers the following topics in detail: definition of AI science, Data and Vectors, Clustering, Classification, Neural Networks, Computer Vision and Natural Language Processing. Of course, the treatment would not be complete without reference to some subtle notions, e.g., knowledge and abstraction. Finally, the relation of AI science, society and the environment are overviewed. -- This email has been checked for viruses by Avast antivirus software. www.avast.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From bhammer at techfak.uni-bielefeld.de Tue Mar 28 10:05:56 2023 From: bhammer at techfak.uni-bielefeld.de (Barbara Hammer) Date: Tue, 28 Mar 2023 16:05:56 +0200 Subject: Connectionists: Research Position in MSCA Doctoral Network LEMUR Message-ID: <1d7297b9-4616-69fc-2d1f-5ef8f8da5e4a@techfak.uni-bielefeld.de> The newly established EU Doctoral Network (DN) 'Learning with Multiple Representations (LEMUR)' is concerned with machine learning methods that specifically use different representations (such as symbolic and sub-symbolic representations) in a model to make concrete machine learning tasks more efficient, robust and secure. In the frame of this network, there is currently a vacancy for a PhD position at Bielefeld University, Germany, in the topic of dimensionality reduction and visualization for deep learning, See https://jobs.uni-bielefeld.de/job/view/2290/research-position-in-doctoral-network-lemur Applications of enthusiastic machine learners are welcome until mid April! -- Prof. Dr. Barbara Hammer Machine Learning Group, CITEC Bielefeld University D-33594 Bielefeld Phone: +49 521 / 106 12115 -------------- next part -------------- An HTML attachment was scrubbed... URL: From bhammer at techfak.uni-bielefeld.de Tue Mar 28 10:32:06 2023 From: bhammer at techfak.uni-bielefeld.de (Barbara Hammer) Date: Tue, 28 Mar 2023 16:32:06 +0200 Subject: Connectionists: tenure track professorship in sustainable AI Message-ID: Dear colleagues, I would like to draw your attention to an open tenure track professorship at Bielefeld University, Germany: Professorship (W1 TT W2 or W2) for Sustainable AI Systems with a particular focus on resource-efficient or secure AI, which will be newly established in the frame of the large-scale project SAIL on sustainable AI https://www.sail.nrw/ Information on the position: https://www.uni-bielefeld.de/uni/karriere/professuren/wiss3006_englisch.xml University: https://www.uni-bielefeld.de/ Faculty of Technology: https://www.techfak.uni-bielefeld.de/ Applications are welcome via the portal https://berufungen.uni-bielefeld.de until end April. -- Prof. Dr. Barbara Hammer Machine Learning Group, CITEC Bielefeld University D-33594 Bielefeld Phone: +49 521 / 106 12115 -------------- next part -------------- An HTML attachment was scrubbed... URL: From axel.hutt at inria.fr Wed Mar 29 04:16:05 2023 From: axel.hutt at inria.fr (Axel Hutt) Date: Wed, 29 Mar 2023 10:16:05 +0200 (CEST) Subject: Connectionists: Postdoc position : Optimal closed-loop control of human attention Message-ID: <42174070.29890701.1680077765415.JavaMail.zimbra@inria.fr> ----------------------------------------------------------------------------------------------------------------- ++++++ Impact of closed-loop control and auditory beats on human attention +++++ ----------------------------------------------------------------------------------------------------------------- The project aims to develop a closed-loop feedback control of attention in psycho-physical experiments. The optimal feedback will be estimated by numerical optimization schemes. The work combines numerical optimization, software development and psycho-physical experiments. What: Postdoctoral position Where: INRIA Nancy Grand Est, Strasbourg, France Team: MIMESIS (https://mimesis.inria.fr/) in Strasbourg, France When: October 2023 - September 2025 Duration: 2 years Principal Investigator: Axel Hutt (https://mimesis.inria.fr/members/axel-hutt/) More information on the position can be found under [ https://recrutement.inria.fr/public/classic/en/offres/2023-05980 | https://recrutement.inria.fr/public/classic/en/offres/2023-05980 ] . or contact A. Hutt (email: [ mailto:axel.hutt at inria.fr) | axel.hutt at inria.fr) ] -------------- next part -------------- An HTML attachment was scrubbed... URL: From georgeangelos60 at gmail.com Wed Mar 29 05:03:07 2023 From: georgeangelos60 at gmail.com (georgeangelos60 at gmail.com) Date: Wed, 29 Mar 2023 12:03:07 +0300 Subject: Connectionists: 7th International Conference on Internet Science (INSCI 2023): Fifth Call for Papers Message-ID: <5YLB1I6N-M5NZ-W7TS-RXZA-IQV6Y18YSKT6@gmail.com> *** Fifth Call for Papers *** 7th International Conference on Internet Science (INSCI 2023) September 13-15, 2023, 5* St. Raphael Resort, Limassol, Cyprus https://cyprusconferences.org/insci2023/ Submissions due: May 1, 2023 (AoE) (Proceedings to be published by Springer in LNCS; Best Paper Award sponsored by Springer with 300 EUR) ?Internet for Survival?: How the effective and democratic evolution of the Internet towards an infrastructure/ecosystem supporting resilience and equality depends on deeply intertwined considerations rooted in technological, social and economic sciences. ? INSCI is a multidisciplinary conference that brings together scholars and practitioners at the intersection of technological, social and economic sciences seeking to learn how the Internet can be used to make our world a better place. Its insights are expected to create a better understanding of this complex socio-technical system we call ?Internet?, for instance to inform political decisions on the technological priorities for public funding and to drive a more sustainable and equitable development of the innovation and social ecosystems it supports. INSCI welcomes fundamental and applied multidisciplinary research, including policy- oriented studies and works offering technological solutions, that investigate the role of Internet for sustainable development, social and economic resilience, collective intelligence, reliable information processing and protection, and, more generally, for a holistic understanding of societal transformations, governance shifts and innovation quests.? INSCI welcomes works done in interdisciplinary teams that may include computer scientists, sociologists, policy makers, economists, designers and artists, or complex system scholars, among others, preferably uniting expertise from social, economic and technical sciences. This kind of work is expected to close the gap between societal / economic impact and requirements and technological developments, seen as both drivers and consequences of each other. Thus, INSCI 2023 welcomes submissions to a wide range of topics including but not limited to the following list. TOPICS Green, Sustainability, and Innovation ? The challenges of Responsible Research and Innovation on Internet solution ? The technological, social and economic benefits of Transnational and Inter-Cultural Projects ? Internet solutions supporting Environmental policies related to Climate Change ? Green Computing in a holistic perspective: trade-offs of computing power, social benefits, economic and environmental impacts (e.g. blockchains) ? Design, Implementation, and Analysis of Novel Platforms for alternative distributed economic models ? Distributed environmental awareness: creating a collective consciousness of environmental issues and possible solutions at individual and collective level. Collective intelligence, sensing and action ? Energy optimisation from from networked production to shared consumption, relying on top-down and bottom-up approaches ? Networks for circular economy models: conceiving and putting in place platforms and solutions effectively supporting circular and social economy models, collaborative making, art and creativity. Enabling Technologies, Applications and Infrastructures ? Social implications of Reinforcement Algorithms, Machine Learning and Intelligent Systems ? Feasibility and social /economic aspects of Algorithms for mediation content ? Data Sovereignty and inclusion aspects of Cloud, Grid and Cluster Computing ? Recommender, Adaptive and Context Aware Systems: design, social and inclusion aspects, feasibility and adoption ? Networking and Wireless Systems as enablers: inclusion, health, privacy and pervasiveness aspects ? People-driven Internet Technologies and Applications, including Collaborative Platforms & Social Search, Open Data and New Interfaces? Societal Structures ? How will Internet of Things change Society and interaction models ? Digital Competences and Participation ? Virtual Communities and Behavioural Patterns: how are they affected by the technological platforms being used? ? Knowledge, Education, Technology Enhanced Learning, and Societal Web Impact on Internet Evolution? ? Offline and Online Human Behaviour with Emphasis on Social Media and Online/ER/ VR Interactions? Digital Politics and Governance ? Internet and Political Participation ? Online Political Freedoms in Policing and in Effect: Regional and Local Perspectives, technological impacts and requirements ? Citizen Involvement into Decision-Making: Platforms, Actors, and Experiences ? Political Discussions Online: Issues and Groups Behind Them, technical and collaborative solutions to moderate them ? E-governance Practices of Today?s Authorities across the world ? Internet regulation: Security vs. Openness Free Communication Patterns and Democracy ? Freedom of Speech Online: a Contested Area of Policing ? Algorithms as New Total Communicative Power ? Extremist and Radical Talk Online and Policies or socio-Technical solutions to counteract it ? Universal Internet Freedoms vs. Dark Web ? Participatory Democracy and Budgeting: citizens? involvement in democratic processes, for more equal and inclusive resource allocation ? Cognitive, Psychological Aspects and Incentive Mechanisms for online Engagement, Collaboration and Participation? (smart citizenship, e-literacy, participation skills, decision support and recommendations for informed citizens and collective actions) ? E-Democracy and E-Participation: risks and opportunities, lessons learnt from currently deployed solutions (e.g. e-voting, Decidim) ? Reliable online information: collaborative models and processes to produce/qualify online information (e.g. post-truth Practices Online, filter bubble and fact checking), for health (e.g. vaccination), democracy (international decision-making, political campaigns, opinion and sentiment modelling, governmental censure and influence), economy (product labelling, ethical marketing), safety of online ecosystems (children protection, fake news, digital rebels) ? Crowdsourcing: implications, enablers Sustainable Network Economy ? Legal, economic, technological and innovation hurdles related to Intellectual Property and the Digital Commons? ? New Collaborative Markets Analytics? ? Economic Power of Online Platforms: Expropriation of Digital Labour, Open Data solutions and their applicability ? Digital Corporations: World Leaders and Regional Alternatives ? Analogous Elites, Technological Precariat ? Digital Professions and Reshaping of Online Labour Markets ? New decentralised economic models: enabling and sustaining a distributed ecosystem of platforms and solutions intrinsically respectful of privacy, self- disclosure and digital sovereignty ? The consumer perspective: unlawful profiling, discrimination and lock-in, automated contracts and warranties Global Access Opportunities ? Internet Resilience: Defining/Comparing non-disconnection Technologies, Monitoring Approaches and Internet Governance Models ensuring resiliency and citizens? empowerment and sovereignty ? Global and Local Faces of Today?s Digital Divide ? Comparing existing and future Open Distance Education and Life-long Learning Environments on online/Virtual Reality Platforms, Practices Around the World ? Global Media Online: Translation and Language Divide ? Empowerment of Disabled with New Body Extensions ? Post-human and Tech-human Individuals and Societies Data Sharing and Protection ? Data Openness vs. User Protection: tech and social aspects of open data policies ? Limits of Privacy and Anonymization, their dependance on technological solutions and intended applications ? Clouds, Big Data and Data Protection Regulation vs. knowledge sharing and open innovation ? Global Tech Powers and Alternative Solutions based on decentralisation ? Open Science and Access to Scientific Production: technological enablers, platform governance, economic and innovation aspects IMPORTANT DATES ? Submission of Papers: May 1, 2023 (AoE) ? Notification of Decision: July 1, 2023 ? Camera-Ready Submission: July 15, 2023 ? Author Registration Deadline: July 15. 2023 PAPER REQUIREMENTS All submitted papers must: ? Describe original results that have not been accepted or submitted for publication elsewhere ? Be written in English and be submitted in PDF format ? Contain author names, affiliations, and email addresses ? Be formatted according to the Springer?s LNCS format Proceedings template: http://www.springer.de/comp/lncs/authors.html? ? Contain three to seven keywords characterizing the paper, to be indicated at the end of the abstract ? Be submitted via the conference system in EasyChair, using the submission link: https://easychair.org/conferences/?conf=insci2023 Full paper submissions should not exceed 15 pages (including all text, figures, references and appendices). We encourage a length of 12 pages for full papers. The Program Committee reserves the right to accept a submission as a short paper. Submissions not conforming to the LNCS format, exceeding the submission page limits or being obviously out of the scope of the conference, will be rejected without review. SELECTION All submissions will be evaluated by at least three members of the international Program Committee, with a mix of social, economic and technological expertise. The review process will be single-blind. Selection will be based on: ? Degree of interdisciplinarity (between social, economic and/or technical sciences) ? Novelty and technical merit ? Relevance of the generated insights for the future Internet development The best paper will be sponsored with 300 EUR by Springer. CAMERA-READY Camera-ready submissions should be corrected by following the remarks of the reviewers and submitted using the same submission link in zip format including: ? The camera-ready version of the authors? work in pdf format ? The camera-ready version of the authors? work in editable sources format ? The Consent to Publish signed in ink and scanned to image file PUBLICATION Accepted papers will be presented at INSCI2023 and published in the conference proceedings volume, which will be published in the Springer Lecture Notes in Computer Science (LNCS). Authors of selected best papers from the conference will be contacted in order to consider submission of an expanded version of their papers for publication in a special issue to be organised with the international journal Future Internet (https://www.mdpi.com/journal/futureinternet), published by MDPI. ORGANISATION General Chair ? George A. Papadopoulos, University of Cyprus, Cyprus Program Chairs ? Vasileios Mezaris,?Information Technologies Institute, Greece ? Fabrizio Sestini, European Commission DG CONNECT, Belgium Steering & Program Committees https://cyprusconferences.org/insci2023/committees/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From patrick.reisinger at stud.sbg.ac.at Wed Mar 29 09:14:13 2023 From: patrick.reisinger at stud.sbg.ac.at (Patrick Reisinger) Date: Wed, 29 Mar 2023 15:14:13 +0200 Subject: Connectionists: Salzburg Mind-Brain Annual Meeting (SAMBA), July 13-14, 2023 - Register NOW! Message-ID: Dear all, we are happy to announce that the Salzburg Mind-Brain Annual Meeting (SAMBA) 2023 is taking place from 13th to 14th of July 2023 at the University of Salzburg, Austria!?The mission of SAMBA is to attract the most exciting researchers in the domain of Cognitive Neuroscience and related fields. Our program includes the following great speakers: ??? ? James Bonaiuto (CNRS) ??? ? Roland Fleming (Giessen University) ??? ? Stephanie Forkel (Radboud University) ??? ? Rosanne Rademaker (Ernst Str?ngmann Institute / Max Planck Society) ??? ? Katharina Schmack (Francis Crick Institute & University College London) ??? ? Bryan Strange (Universidad Polit?cnica de Madrid) ??? ? Markus Ullsperger (University of Magdeburg) ??? ? Isabella Wagner (University of Vienna) ??? ? Maria Wimber (University of Glasgow) ??? ? Valentin Wyart (Ecole Normale Sup?rieure) We are also hosting a 2-day introductory workshop to MNE-Python before SAMBA 2023, held by Clemens Brunner and Richard H?chenberger. The workshop is targeted at beginners with little or no experience. Register NOW: https://samba.ccns.sbg.ac.at Abstract and registration deadline is on the on the 31st of May. Any questions? Write an email to samba at plus.ac.at. We are looking forward to welcoming you to the city of Mozart! All the best, SAMBA 2023 organization team -------------- next part -------------- An HTML attachment was scrubbed... URL: From blextar at gmail.com Thu Mar 30 00:07:33 2023 From: blextar at gmail.com (Luca Rossi) Date: Thu, 30 Mar 2023 12:07:33 +0800 Subject: Connectionists: Multiple PhD & Postdoc positions available on Graph Learning @ The Hong Kong Polytechnic University Message-ID: Multiple PhD and Postdoctoral positions are available for talented, highly motivated individuals with an interest in graph learning and adjacent areas. You will be joining The Hong Kong Polytechnic University working under the supervision of Dr. Luca Rossi https://www.polyu.edu.hk/eie/people/academic-staff/dr-luca-rossi/. Applicants should have a strong track record commensurate with the position sought in order to be considered, including but not limited to a track record of international publications (necessary for Postdoctoral positions, optional for PhD positions) and high GPA from top ranked Universities (necessary for PhD positions). For more information, please send an updated copy of your CV to luca.rossi at polyu.edu.hk. -- Luca Rossi Assistant Professor Department of Electronic and Information Engineering The Hong Kong Polytechnic University https://blextar.github.io/luca-rossi/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From interdonatos at gmail.com Thu Mar 30 04:50:14 2023 From: interdonatos at gmail.com (Roberto Interdonato) Date: Thu, 30 Mar 2023 10:50:14 +0200 Subject: Connectionists: PhD position on complex networks analysis [CIRAD - UMR TETIS, Montpellier, France] Message-ID: CIRAD (UMR TETIS laboratory, Montpellier) is offering a PhD position on Complex networks for the analysis of landscape dynamics. The details of the offer are at this link: https://nubes.teledetection.fr/index.php/s/NmySXKBX6irnM9H Applications must be sent to roberto.interdonato at cirad.fr before April 17, 2023. The application procedures are detailed in the attached offer. Thank you for diffusing this information in your networks and to anyone who might be interested. Kind regards, Roberto Interdonato -------------- next part -------------- An HTML attachment was scrubbed... URL: From roland.w.fleming at psychol.uni-giessen.de Thu Mar 30 11:31:25 2023 From: roland.w.fleming at psychol.uni-giessen.de (Roland Fleming) Date: Thu, 30 Mar 2023 17:31:25 +0200 Subject: Connectionists: Multiple ERC-funded postdoc and PhD positions in Roland Fleming's lab (Giessen) Message-ID: Multiple postdoc and PhD positions will soon be available in Roland Fleming?s lab in the context of the ERC Advanced Grant project STUFF. The project spans material perception, intuitive physics, mental imagery, grasping and art. The positions will most likely be available from Autumn 2023. If you would be interested in applying, it would be great if you could contact me in advance. You should ideally have a background in perception or motor control, although I?ll also consider particularly strong candidates from other backgrounds. Experience with any of the following would be a significant bonus: - computational modelling of perceptual and/or motor processes - machine learning, especially deep learning - computer graphics, especially physics simulations and mesh processing - image and movie synthesis through deep learning - art and computational aesthetics, especially involving formal quantitative analyses of artworks - MoCap (with or without markers) - robotics - fMRI My lab specialises in the visual perception of?and motor interactions with?materials and objects. Topics include visual estimation of material properties and shape; physical reasoning and naive physics; grasping and dextrous manipulation; one-shot learning; the imagination and mental simulation; shape understanding, including perceptual organisation of shape and inferences about causal history. Check out my lab website for more information, including articles and datasets. My lab is situated in one of the top research environments for visual perception and sensorimotor research worldwide, with a large group of Principle Investigators and a thriving and diverse community of junior researchers working on perception and action using psychophysics, eye-, hand- and body-tracking, VR, fMRI, EEG, machine learning and other methods. We run several large-scale research consortia, providing excellent local and international networking opportunities. Giessen is also ideally located in the centre of western Europe, with half-a-dozen other countries a mere train-ride away. If you are interested, I look forward to hearing from you! Best wishes, Roland Fleming ____________________________ Prof. Roland W Fleming, FRSB Kurt Koffka Professor of Experimental Psychology, Justus Liebig University, Giessen Executive Director, Centre for Mind, Brain and Behaviour, Universities of Marburg and Giessen Otto-Behaghel-Str 10, 35394 Giessen, GERMANY tel: 0641 99-26140 http://www.allpsych.uni-giessen.de/fleminglab -------------- next part -------------- An HTML attachment was scrubbed... URL: From msloco01 at mail.bbk.ac.uk Thu Mar 30 19:29:36 2023 From: msloco01 at mail.bbk.ac.uk (Matthew Slocombe) Date: Fri, 31 Mar 2023 00:29:36 +0100 Subject: Connectionists: Today's Analogical Minds Seminar: Dr Shiwali Mohan, "Using Insights from Analogical Minds to Build Interactive Task Learning Agents" Message-ID: <003401d9635f$7e3f7070$7abe5150$@mail.bbk.ac.uk> Dear all, Some of you may be interested in today's Analogical Minds Seminar with Dr Shiwali Mohan: "Using Insights from Analogical Minds to Build Interactive Task Learning Agents" Dr Shiwali Mohan, Palo Alto Research Center Thursday 30th March, 6:00 pm - 7:30 pm US PDT (9:00 am - 10.30 am in Beijing) Zoom link to attend can be found on our World Wide Neuro page: https://www.world-wide.org/seminar/9061/ Seminar info: www.analogicalminds.com Abstract: Humans are natural teachers; learning through instruction is one of the most fundamental ways that we learn. Interactive Task Learning (ITL) is an emerging research agenda that studies the design of complex intelligent robots that can acquire new knowledge through natural human teacher-robot learner interactions. ITL methods are particularly useful for designing intelligent robots whose behavior can be adapted by humans collaborating with them. In this talk, I will summarize our recent findings on the structure that human instruction naturally has and motivate an intelligent system design that can exploit their structure. The system - AILEEN - is being developed using the common model of cognition. Architectures that implement the Common Model of Cognition - Soar, ACT-R, and Sigma - have a prominent place in research on cognitive modeling as well as on designing complex intelligent agents. However, they miss a critical piece of intelligent behavior - analogical reasoning and generalization. I will introduce a new memory - concept memory - that integrates with a common model of cognition architecture and supports ITL. Speaker bio: Dr. Shiwali Mohan is a senior member of research staff at Xerox PARC. She received her B.E. in Instrumentation and Control Engineering from Netaji Subhas Institute of Technology, Delhi University and her M.S. and Ph.D. degrees in computer science from the University of Michigan, Ann Arbor with a focus on artificial intelligence. Dr. Mohan studies the design and analysis of collaborative human-AI systems. Her research brings together methods from artificial intelligence (AI) and machine learning (ML) with insights from human-centered sciences to design systems that can collaborate with humans effectively. Her research has had an inter-disciplinary impact and has been published at venues for research on AI, human cognition, cognitive systems, human-computer interaction (HCI), medical informatics, AI for social good, and robotics. Best wishes, Matt Slocombe -------------- next part -------------- An HTML attachment was scrubbed... URL: From boubchir at ai.univ-paris8.fr Thu Mar 30 05:39:18 2023 From: boubchir at ai.univ-paris8.fr (Larbi Boubchir) Date: Thu, 30 Mar 2023 11:39:18 +0200 Subject: Connectionists: [CFP] Special Issue on "Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis" at MTAP In-Reply-To: <421c24ef-c2fa-e580-a6b3-2ea12c77e565@ai.univ-paris8.fr> References: <421c24ef-c2fa-e580-a6b3-2ea12c77e565@ai.univ-paris8.fr> Message-ID: <97557fd6-74c4-9c98-ceae-533b5dcc5432@ai.univ-paris8.fr> [Apologies if you receive multiple copies of this CFP] *Call for Papers: Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis * https://www.springer.com/journal/11042/updates/24678968 *Summary and Scope* Nowadays, Deep learning (DL) becomes an attractive research topic for many researchers from academia and industry communities. Indeed, DL algorithms have demonstrated their ability to train learning models for large-volume data as well as their performances compared to conventional machine learning algorithms. The DL approaches were studied and applied to resolve several complex problems in various research domains, such as computer vision, biometrics, brain-computer interfaces, robotics, and other fields. Several architectures of DL (e.g., supervised, unsupervised, reinforcement, and beyond) have been proposed in the literature as solutions for various research problems in data analysis related to detection, classification, recognition, prediction, decision-making, etc. The special issue aims to solicit original research work covering novel algorithms, innovative methods, and meaningful applications based on the DL that can potentially lead to significant advances in biomedical data analysis. The main topics include, but are not limited to, the following: ? DL for biomedical signal analysis and processing ? DL for medical image analysis and processing ? DL for diseases detection and diagnosis ? DL for pandemics detection and forecasting ? DL for biometrics ? DL in biomedical engineering ? DL for health informatics ? DL for brain-computer interfaces ? DL for neural rehabilitation engineering ? Related applications * * *Important Dates:* Submission deadline: August 31, 2023 Reviewing deadline: October 15, 2023 Author revision deadline: November 15, 2023 Final notification date: December 15, 2023 * * *Guest editors* Prof. Larbi Boubchir (Lead GE)?- University of Paris 8, France Email: Larbi.boubchir at univ-paris8.fr Prof. Elhadj Benkhelifa - Staffordshire University, UK Email: Benkhelifa at staffs.ac.uk Prof. Jaime Lloret - Universitat Politecnica de Valencia, Spain Email: jlloret at dcom.upv.es Prof. Boubaker Daachi - University of Paris 8, France Email: boubaker.daachi at univ-paris8.fr *Submission Guidelines:* Authors should prepare their manuscript according to the Instructions for Authors available from the Multimedia Tools and Applications website . Authors should submit through the online submission site at https://www.editorialmanager.com/mtap/default.aspx and select ?SI 1239 - Emerging Trends and Applications of Deep Learning for Biomedical Data? when they reach the ?Article Type? step in the submission process. Submitted papers should present original, unpublished work, relevant to one of the topics of the special issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least three independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process. -------------- next part -------------- An HTML attachment was scrubbed... URL: From drshadiconf at gmail.com Thu Mar 30 07:22:56 2023 From: drshadiconf at gmail.com (Mohammad Al-Madi) Date: Thu, 30 Mar 2023 14:22:56 +0300 Subject: Connectionists: CFP: ICIT-2023 - August 09th-10th, 2023 || Amman, Jordan Message-ID: *Please accept our apologies if you receive multiple copies of this email* *The 11th International Conference on Information Technology * *(ICIT-2023)August 09th-10th, 2023 || Amman, Jordan* http://icit.zuj.edu.jo/icit2023/Index.html The 11th International Conference on Information Technology (ICIT 2023) will be held on 9th-10th August 2023 in Amman, Jordan. Al-Zaytoonah University of Jordan organizes this Conference in cooperation with the Scienti?c Research Group in Egypt (SRGE) and technically co-sponsored by IEEE. The Conference will bring together the top researchers worldwide to exchange their research results and address open issues in Cybersecurity, Arti?cial Intelligence and Data Science, Software Engineering, E-Technologies, Computer Vision and Multimedia Systems, Mathematical Modeling and Analysis, Smart Technologies and Sustainability, and Computer Engineering. All papers must be written in English and will be reviewed by the technical committees of the Conference. All accepted papers will be submitted for inclusion in the IEEE Xplore Digital Library as well as Scopus. Authors of selected papers will also be invited to prepare extended papers of their work for publication in the International Journal of Advances in Soft Computing and its Applications (IJASCA). Authors are invited to submit their original work, which is not submitted elsewhere, to this workshop. The accepted papers of the workshop will be published by the IEEE Conference Publishing Services (CPS) and will be submitted for inclusion in the IEEE-Xplore and the IEEE Computer Society (CSDL) digital libraries. *Important Dates* - *Paper Submission: Mar 15,2023 - May 01, 2023 * - *Review Decision Notifications: June 01, 2023 * - *Camera-ready and Registration: July 15, 2023 * - *Registration Date: July 15, 2023 - August 01, 2023 * *Tracks: * - *Cyber Security * *Authentication, Access Control and Authorization, Blockchain and Cryptocurrency, Cloud Computing Security, Cryptology and Its Application, Cybercrime Awareness, Data Protection, Digital Forensics, Distributed Systems Security, Embedded Systems Security, Hardware Security, Hate, Harassment, and Online Abuse, Information Security, Intrusion Detection and Prevention, Laws and Regulations, Malware and Unwanted Software, Network Security, Operating Systems Security, Protocol Security, Security and Privacy Metrics and Policies, Security Architectures, Systems Security, Web Security, Wireless and Mobile Security/Privacy. * - *Arti?cial Intelligence and Data Science * *Big Data, Data Analytics, Data Mining, Machine Learning, Deep Learning, Human-Computer Interaction, Natural Language Processing, Bioinformatics, Health Informatics, Intelligent Systems, Information Retrieval. * - *E-Technologies * *E-Business, E-Learning, Distance Learning, E-Education, E-Government, Digital marketing, Smart cities, Mobile applications. * - *Computer Vision and Multimedia Systems * *Pattern Recognition, Computer Vision, Medical Imaging, Animated Technologies, Virtual Reality, 3D Printing, Audio, Image, and Video Analysis, Image Processing and Modelling. * - *Software Engineering * *Software Engineering and Quality, Continuous Software Engineering (e.g., DevOps, agile, etc.), Formal Methods Applied to Software Engineering, Human and Social Aspects of Software Engineering, Machine Learning Applied to Software Engineering, Model-Driven Software Engineering, Search-Based Software Engineering, Software Architecture, Software Economics and Metrics, Software Engineering Education and Training, Software Maintenance and Evolution, Software Process, Information Systems. * - *Mathematical Modeling and Analysis * *Operation Research, Risk Management, Statistic Process and Analysis, Computer Graphics and Di?erential Equations, Applied Problems and Methods in Research and Education, Mathematical Modeling in Computing and Optimization, Computational Methods and Combinatorics, Data Analysis. * - *Computer Engineering * *Computer Architecture, Embedded Systems, Digital Circuits Applications, Parallel and High Performance Processing, Performance Evaluation and Modeling, Storage Systems, GPUs, Multicore Processors, and Hardware Accelerators. * - *Smart Technologies and Sustainability * *Distributed Energy Resources, Material Science, Intelligent Transportation Systems, Energy and Electricity Grid, Powered Smart City Services, Smart Education, Smart Health Care Systems, Drone technology, Open Data and Big Data Analytics, Smart Tra?c Systems, Smart Driverless Vehicles, Internet of Things.* *For More Information * - Visit the conference website at http://icit.zuj.edu.jo/icit2023/Index.html , particularly the *Submission *page. - Papers should be submitted to: https://www.edas.info/newPaper.php?c=30290 *General Co-chairs:* - Prof. Amjed Zraiqat *Dr. Shadi AlZu'bi* *Associate Professor * *Computer Science Department* *Al Zaytoonah University of Jordan* *Amman* smalzubi at zuj.edu.jo +(962) 799 100034 -------------- next part -------------- An HTML attachment was scrubbed... URL: From sigurd.lokse at uit.no Fri Mar 31 02:57:57 2023 From: sigurd.lokse at uit.no (=?Windows-1252?Q?Sigurd_Eivindson_L=F8kse?=) Date: Fri, 31 Mar 2023 06:57:57 +0000 Subject: Connectionists: =?windows-1252?q?Call_for_Contributions=3A_7th_No?= =?windows-1252?q?rthern_Lights_Deep_Learning_Conference=2C_09-11_January_?= =?windows-1252?q?2024=2C_Troms=F8_=28=93North_Pole=94=29=2C_Norway?= Message-ID: Please join for the 7th Northern Lights Deep Learning Conference (NLDL) on 9-11 January 2024 in Troms?, Norway, organized by Visual Intelligence and the UiT Machine Learning Group. We look forward to gathering the deep learning community again in the cool arctic air for a physical conference. In addition, the NLDL winter school, which is a part of the NORA research school http://nora.ai, starts at Jan 8 and ends at Jan 12 and incorporates events during the main conference days. The winter school includes scientific topics, industry event, women in AI event, and transferrable skills. More information coming soon at http://www.nldl.org/winter-school. We invite submissions presenting new and original research on all aspects of Deep Learning. The topics include but are not limited to the following: * General Machine Learning (active learning, clustering, online learning, ranking, reinforcement learning, supervised, semi- and self-supervised learning, time series analysis, etc.) * General Deep Learning (architectures, generative models, deep reinforcement learning, etc.) * Optimization (convex and non-convex optimization, matrix/tensor methods, stochastic, online, non-smooth, composite, etc.) * Probabilistic methods (Bayesian methods, variational inference, graphical models, etc.) * Social and economic aspects of Machine Learning (accountability, causality, fairness, privacy, robustness, interpretability, etc.) * Applications (vision, language, signals, speech and audio, etc.) * Deep Learning for Sciences (biology and medicine, environment and ecology, physics, etc.) As always, we are happy to have top international speakers. This year, for instance * Mark Girolami - University of Cambridge & the Alan Turing Institute We are accepting two alternatives for contributions: (1) Full paper submissions (6 pages) will be presented either as orals or as posters and will be published in the conference proceedings. The proceedings are approved as a level 1 publication in the Norwegian national list of authorized research publication channels; (2) Extended abstracts (2 pages) will be presented as posters (but not published in the conference proceedings). The review process is double-blind. Deadline for both types of submissions: September 1st, 2023. Instructions on template etc. can be found on http://www.nldl.org. A tentative program will be available soon at http://www.nldl.org/ and will include keynotes, scientific talks, an industry event, a Women in AI event and social events. We hope to see many participants for a nice scientific gathering on the ?north pole?, including social events, and hopefully some northern lights Kind regards, The NLDL 2024 organizing committee http://visual-intelligence.no http://machine-learning.uit.no -------------- next part -------------- An HTML attachment was scrubbed... URL: From pitas at csd.auth.gr Thu Mar 30 07:01:29 2023 From: pitas at csd.auth.gr (pitas at csd.auth.gr) Date: Thu, 30 Mar 2023 14:01:29 +0300 Subject: Connectionists: Can AI research be stopped? No, but it should become more open, democratic and scientific References: <005f01d96159$8a25b190$9e7114b0$@csd.auth.gr> <6c7d5e0b-2bc6-1dbe-12e2-7e6660dfd166@unitn.it> <011d01d96248$0518d0a0$0f4a71e0$@csd.auth.gr> <2f8e82a1-901b-1be5-6d77-5ab6a4b61f36@iti.gr> Message-ID: <00b501d962f6$fbc997f0$f35cc7d0$@csd.auth.gr> Can AI research be stopped? No, but it should become more open, democratic and scientific Can AI research stop even temporarily? In my view, no, as AI is the response of humanity to a global society and physical world of ever-increasing complexity. As the physical and social complexity increase processes are very deep and seeming relentless, AI and citizen morphosis are our only hope to have a smooth transition from the current Information Society to a Knowledge Society. Else, we may face a catastrophic social implosion. Maybe we reached the limits of AI research being engineered primarily by Big Tech companies, while treating powerful AI systems (like LLMs) almost as marvelous black boxes, whose functionality (the why?) Is very poorly understood, both due to lack of access of technical details and due to the huge AI system complexity. Naturally, this lack of knowledge and a related confusion as to the nature of human and machine intelligence entails very serious social risks. It seems that the Open Letter reflects both welcomed genuine concerns on the social risks as well as financial concerns on risk management related, e.g., to future AI investments or the possibility of massive expensive lawsuits (in an unregulated and un-legislated environment) in case things go wrong. However, I doubt if the proposal for a six-month ban on large scale experiments is the solution. It is impractical for geopolitical reasons and can bring too little benefits, particularly if LLM training is targeted, rather than LLM deployment. Furthermore, the melodramatic tone of this Open Letter can only enhance technophobia in the wider population. On the other hand, scientific views discounting LLM value (e.g., like the ones expressed by Chomsky) are old-fashioned (reminiscent of perceptron rejection by Minsky and Papert) and not productive either. Of course, AI research can should become different: more open, democratic and scientific. Here is a proposed list of points to this end: * The first word on important AI research issues that have far-reaching social impact should be delegated to elected Parliaments and Governments, rather than to corporations or individual scientists. * Every effort should be made to facilitate the exploration of the positive aspects of AI in social and financial progress and to minimize its negative aspects. * The positive impact of AI systems can greatly outweigh their negative aspects, if proper regulatory measures are taken. Technophobia is neither justified, nor is a solution. * In my view, the biggest current threat comes from the fact that such AI systems can remotely deceive Too many commoners that have little (or average) education and/or little investigative capacity. This can be extremely dangerous to democracy and any form of socio-economic progress. * In the near future, we should counter the big threat coming from LLM and/or CAN use in illegal activities (cheating in University exams is a rathe benign use in the space of the related criminal possibilities). * Their impact on labor and markets will be very positive, in the medium-long run. * In view of the above, AI systems should: a) be required by international law to be registered in an ?AI system register?, and b) notify their users that they converse with or use the results of an AI system. * As AI systems have huge societal impact, and towards maximizing benefit and socio-economic progress, advanced key AI system technologies should become open. * AI-related data should be (at least partially) democratized, again towards maximizing benefit and socio-economic progress. * Proper strong financial compensation schemes must be foreseen for AI technology champions to compensate any profit loss, due to the fore-said open-ness and to ensure strong future investments in AI R&D (e.g., through technology patenting, obligatory licensing schemes). * The AI research balance between Academia and Industry should be rethought to maximize research output, while maintaining competitiveness and granting rewards for undertaken R&D risks. * Education practices should be revisited at all education levels to maximize the benefit out of AI technologies, while creating a new breed of creative and adaptable citizens and (AI) scientists. * Proper AI regulatory/supervision/funding mechanisms should be created and beefed up to ensure the above. Several such points were already discussed in the 2021 AI Mellontology workshop and are also included in my recent book on ?AI Science and Society? [PIT2023]. [FUT2023] ?Pause Giant AI Experiments: An Open Letter?, https://futureoflife.org/open-letter/pause-giant-ai-experiments/, 2023 [PIT2023] Ioannis Pitas, ?Artificial Intelligence Science and Society Part C: AI Science and Society? (335 pages), Amazon/Createspace, https://www.amazon.com/dp/9609156487?ref_=pe_3052080_397514860 Best regards Professor, Chair of the International AI Doctoral Academy (AIDA ) Ioannis Pitas, pitas at csd.auth.gr -- This email has been checked for viruses by Avast antivirus software. www.avast.com -------------- next part -------------- An HTML attachment was scrubbed... URL: