Connectionists: Distributed Artificial Brains (DAB), at the IEEE Symposium on Computational Intelligence for Human-like Intelligence (IEEE CIHLI)

[Wlodek Duch]

*Distributed Artificial Brains (DAB), at the IEEE Symposium on 
Computational Intelligence for Human-like Intelligence (IEEE CIHLI)*

This year a lot of exciting new development in artificial intelligence 
have been introduced, leading to systems that have superhuman abilities 
in many domains. Large language models (LLMs) based on Generative 
Pretrained Transformers achieved a surprisingly high level of 
competence. Many enhancements have been proposed, giving these models 
multimodal capabilities, visual question answering, emergent abilities, 
such as the theory of mind, and the creation of inner images. The 
addition of algorithms that enable reflection, iterative prompting for 
self-improvement, chains and trees of thought, autoGPT mode, 
explanation-based learning, and many other exciting developments make 
the functioning of these models increasingly similar to the high-level 
brain processes.

The ability to use specialized plugins gives the LLMs great power of 
using tools to realize planned actions, making these systems a kind of 
Distributed Artificial Brains (DAB). It seems that the conscious-like 
behavior of such models is inevitable. IEEE Symposium on Computational 
Intelligence for Human-like Intelligence will be a great place to 
discuss the latest development in all facets of human-like intelligence, 
both in theory and practice. We are especially interested in submissions 
discussing further developments of LLMs and relation to the brain 
processes, and identification of qualities that may lead to a higher 
level of intelligence.

*Other topics*

The CIHLI organizers invite submissions of original previously 
unpublished innovative research in any topic related to practical and 
theoretical aspects of human-like intelligent behavior including, but 
not limited to:**

·Models and architectures, including cognitively-plausible architectures 
and systems for human-like intelligence and humanized computing in 
theory and practical applications

·Problem solving based on nature, heuristic, intuition, creativity, 
insight, curiosity and imagination

·Theory and application of deep learning, reinforcement learning, 
autonomous learning, transfer learning and active learning

·Theory and application of evolutionary, heuristics and bio inspired 
algorithms, neural networks, fuzzy logic, rule based systems and their 
hybrid constructions

·Theoretical and practical aspects of future generation computing models 
and paradigms

·Ambient intelligence and human-like intelligence in image processing, 
pattern recognition, expert systems, engineering problems, data mining 
and optimization for industry, finance, transport, logistics, economy, 
manufacturing, security, games, IoT, VR, healthcare, science, and other 
domains.


IEEE Symposium on Computational Intelligence for Human-like Intelligence 
(IEEE CIHLI) - SSCI 2023 
<https://attend.ieee.org/ssci-2023/ieee-symposium-on-computational-intelligence-for-human-like-intelligence-ieee-cihli/> 

Wlodzislaw Duch (NCU), Jacek Mandziuk (WUT), Marcin Wożniak (SUT)



<https://www.is.umk.pl/~duch/>


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