Connectionists: short Op-ed to address AI problems

Fri Jun 7 05:18:33 EDT 2024

see also "The Roles of Symbols in Neural-Based AI: They Are Not What You 
Think!" by Daniel L. Silver, Tom M. Mitchell
https://ebooks.iospress.nl/volumearticle/63710

*Abstract*

We propose that symbols are first and foremost external communication 
tools used between intelligent agents that allow knowledge to be 
transferred in a more efficient and effective manner than having to 
experience the world directly. But, they are also used internally within 
an agent through a form of self-communication to help formulate, 
describe and justify subsymbolic patterns of neural activity that truly 
implement thinking. Symbols, and our languages that make use of them, 
not only allow us to explain our thinking to others and ourselves, but 
also provide beneficial constraints (inductive bias) on learning about 
the world. In this paper we present relevant insights from neuroscience 
and cognitive science, about how the human brain represents symbols and 
the concepts they refer to, and how today’s artificial neural networks 
can do the same. We then present a novel neuro-symbolic hypothesis and a 
plausible architecture for intelligent agents that combines subsymbolic 
representations for symbols and concepts for learning and reasoning. Our 
hypothesis and associated architecture imply that symbols will remain 
critical to the future of intelligent systems NOT because they are the 
fundamental building blocks of thought, but because they are 
characterizations of subsymbolic processes that constitute thought.

Am 07.06.24 um 10:06 schrieb Weng, Juyang:
> Dear Asim,
>     You wrote, That single cell firing in a cat’s brain having 
> “meaning” is not due to “Asim” or “a Government.” These cells with 
> “meaning” develop NATURALLY.
>    Your statement "single cell firing having meaning" is not 
> mathematically meaningful.  The brain is a vector of $10^{14}$ 
> dimension.  Each neuron corresponds to a dimension.  Each neuron does 
> not have a one-to-one correspondence with a symbol (like "Asim".  
>  Review the definition of one-to-one correspondence. If you do not 
> mean one-to-one correspondence, your statement is not mathematically 
> meaningful.
>     Best regards,
> -John Weng
> ------------------------------------------------------------------------
> *From:* Asim Roy <ASIM.ROY at asu.edu>
> *Sent:* Thursday, June 6, 2024 11:21 PM
> *To:* Weng, Juyang <weng at msu.edu>; Stephen José Hanson 
> <jose at rubic.rutgers.edu>; Gary Marcus <gary.marcus at nyu.edu>
> *Cc:* connectionists at mailman.srv.cs.cmu.edu 
> <connectionists at mailman.srv.cs.cmu.edu>
> *Subject:* RE: Connectionists: short Op-ed to address AI problems
>
> Dear John,
>
> There is no “Asim” or “Government” in any brain, human or otherwise. 
> That single cell firing in a cat’s brain having “meaning” is not due 
> to “Asim” or “a Government.” These cells with “meaning” develop 
> NATURALLY. And that’s what you are missing in your Development Network 
> theory. You have not been able to capture in your systems that side of 
> development. Perhaps time to go back to the drawing board. Symbols 
> follow directly from “single cells having meaning.”
>
> All the best,
>
> 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:*Weng, Juyang <weng at msu.edu>
> *Sent:* Thursday, June 6, 2024 8:09 PM
> *To:* Asim Roy <ASIM.ROY at asu.edu>; Stephen José Hanson 
> <jose at rubic.rutgers.edu>; Gary Marcus <gary.marcus at nyu.edu>
> *Cc:* connectionists at mailman.srv.cs.cmu.edu
> *Subject:* Re: Connectionists: short Op-ed to address AI problems
>
> Dear Asim,
>
>    You wrote, "Let’s do one issue at a time. Let’s try symbols 
> first."  This approach misleads you to the wrong track.
>
>    Case 1: neuron level symbols (your position).
>
>    Case 2: area level symbols.
>
>    Case 3: task level symbols.
>
>    They are all dead ends because Asim is the government of the 
> "brain" model.
>
>     For all those Asim knows, it is too expensive to create all 
> symbols for the "brain" model.
>
>     For all those Asim does not know, the model does not know either.
>
>     Deadends!  If you continue this "one issue at a time route," you 
> waste too much time in your life.  This is because the first issue is 
> wrong to consider.
>
>     Best regards,
>
> -John Weng
>
> ------------------------------------------------------------------------
>
> *From:*Asim Roy <ASIM.ROY at asu.edu>
> *Sent:* Thursday, June 6, 2024 10:06 PM
> *To:* Weng, Juyang <weng at msu.edu>; Stephen José Hanson 
> <jose at rubic.rutgers.edu>; Gary Marcus <gary.marcus at nyu.edu>
> *Cc:* connectionists at mailman.srv.cs.cmu.edu 
> <connectionists at mailman.srv.cs.cmu.edu>
> *Subject:* RE: Connectionists: short Op-ed to address AI problems
>
> Dear John,
>
> Let’s do one issue at a time. Let’s try symbols first. There is plenty 
> of evidence in neurophysiology that one can associate “meaning” to the 
> activation of certain individual cells. As far as I know, all of the 
> brain-related Nobel prizes were about finding “meaning” in the 
> activations of certain single neurons. Here I quote from Wikipedia 
> (Single-unit recording - Wikipedia 
> <https://urldefense.com/v3/__https:/en.wikipedia.org/wiki/Single-unit_recording__;!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNkNR1ZZ9A$>):
>
>   * 1928: One of the earliest accounts of being able to record from
>     the nervous system was by Edgar Adrian
>     <https://urldefense.com/v3/__https:/en.wikipedia.org/wiki/Edgar_Adrian__;!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNnQtx1LXQ$> in
>     his 1928 publication "The Basis of Sensation". In this, he
>     describes his recordings of electrical discharges in _single nerve
>     fibers_ using a Lippmann electrometer
>     <https://urldefense.com/v3/__https:/en.wikipedia.org/wiki/Lippmann_electrometer__;!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNn6lQGgzA$>.
>     He won the Nobel Prize in 1932 for his work revealing the function
>     of neurons.^[11]
>     <https://urldefense.com/v3/__https:/en.wikipedia.org/wiki/Single-unit_recording*cite_note-11__;Iw!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNk6I8LNhA$>
>
>   * 1957: John Eccles
>     <https://urldefense.com/v3/__https:/en.wikipedia.org/wiki/John_Carew_Eccles__;!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNkFV1ULMA$> used
>     intracellular _single-unit recording_ to study synaptic mechanisms
>     in motoneurons (for which he won the Nobel Prize in 1963).
>   * 1959: Studies by David H. Hubel
>     <https://urldefense.com/v3/__https:/en.wikipedia.org/wiki/David_H._Hubel__;!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNkJaa_aew$> and
>     Torsten Wiesel
>     <https://urldefense.com/v3/__https:/en.wikipedia.org/wiki/Torsten_Wiesel__;!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNndrzwVDg$>.
>     They used _single neuron recordings_ to map the visual cortex in
>     unanesthesized, unrestrained cats using tungsten electrodes. This
>     work won them the Nobel Prize in 1981 for information processing
>     in the visual system.
>
>   * And the work of Mosers and O’Keefe on grid and place cells that
>     won them the Nobel: The 2014 Nobel Prize in Physiology or Medicine
>     - Press release
>     <https://urldefense.com/v3/__https:/www.nobelprize.org/prizes/medicine/2014/press-release/__;!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNm67pI7iQ$>.
>     Here’s a quote about the work on place cells:
>
> “/Most neuroscientists once doubted that brain activity could be 
> linked with behaviour, but in the late 1960s, *O*’Keefe began to 
> record signals from individual neurons in the brains of rats moving 
> freely in a box. He put electrodes in the hippocampus and was 
> surprised to find that _individual cells fired_ when the rats moved to 
> particular spots/.”Nobel prize for decoding brain’s sense of place | 
> Nature 
> <https://urldefense.com/v3/__https:/www.nature.com/articles/514153a*:*:text=Most*20neuroscientists*20once*20doubted*20that*20brain*20activity*20could,fired*20when*20the*20rats*20moved*20to*20particular*20spots.__;I34lJSUlJSUlJSUlJSUlJQ!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNnqimHsFw$>
>
> And then the findings about concept cells (Jennifer Aniston cells), 
> which are single cell recordings. Here’s from Reddy and Thorpe (2014) 
> <https://urldefense.com/v3/__https:/www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2020.00059/full*B6__;Iw!!HXCxUKc!2pFG0g1tPh-88cfwjJImIxJxtBhaOQ1wWf15ZEUkChi5vUb8q_qEXUDZt7bsQ9QjqzSglNlbw-6x9Q$>: 
> “concept cells have “*/_meaning_/* of a given stimulus in a manner 
> that is */invariant/* to different representations of that stimulus.”
>
> We all try to generalize from data, right. If you examine these 
> findings, the most important feature is that they all found “meaning” 
> in single cell activations. So the most fundamental question for you 
> is: Do you accept these findings and the general conclusion that 
> single cell activations can have meaning? Again, beware that, beyond 
> winning Nobel prizes, much work in neuroscience and other fields 
> follows from these findings.
>
> All the best,
>
> 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:*Weng, Juyang <weng at msu.edu>
> *Sent:* Thursday, June 6, 2024 1:09 AM
> *To:* Asim Roy <ASIM.ROY at asu.edu>; Stephen José Hanson 
> <jose at rubic.rutgers.edu>; Gary Marcus <gary.marcus at nyu.edu>; Weng, 
> Juyang <weng at msu.edu>
> *Cc:* connectionists at mailman.srv.cs.cmu.edu
> *Subject:* Re: Connectionists: short Op-ed to address AI problems
>
> Dear Asim,
>
>    You wrote, "We are doing neurosymbolic with image processing – the 
> symbolic stuff on top of a DL model. It also brings in the explanation 
> side."
>
>    Not only DL is misconduct, but symbols are another devil.
>
>    In my IJCNN 2022 paper,
>
> http://www.cse.msu.edu/~weng/research/20M-IJCNN2022rvsd-cite.pdf 
> <https://urldefense.com/v3/__http:/www.cse.msu.edu/*weng/research/20M-IJCNN2022rvsd-cite.pdf__;fg!!IKRxdwAv5BmarQ!YZcFaLmNraAEJLpxRQGKzKZTVt_nn3J9i52_xG7zhEgKn6ZASf_q59sOFVdSPylt7_NueMymM_EI7GNl$>
>
>    I proved "symbol-free" as one of the 20 million-dollar problems for 
> us to understand human brains.
>
>    The definition of symbols requires a government,  but 
> government-free is one of the 20 million-dollar problems for us to 
> understand human brains.
>
>    Let us consider three cases:
>
>   Case 1:  If a human designs symbols within a network (e.g., LSTM) 
> and assigns the symbols to some individual neurons (e.g., 
> task-specific gates) of the network, this human is a government within 
> the network since he is task-aware.
>
>   Case 2: If a human designs symbols within a network and assigns 
> roles to blocks in a functional block diagram, e.g., [Starzyk10], this 
> human is a government within the network.
>
>   Case 3: In the symbolic AI school, a human programmer designs 
> symbolic representations for a task that is assigned to a computer 
> program or network.  This human is a government within the symbolic AI 
> system since he is task-aware.
>
>    All the 3 cases do not solve the government-free problem.
>
>   I have attached an image that further explains the symbol problem in 
> the same paper.
>
>   Let me know if you still do not agree that the brain must be free 
> from symbols after you read the entire paper.
>
>    By the way, I am surprised that as a mathematician, you still do 
> not understand the Post-Selection misconduct in DL that I raised to 
> you earlier.  Please use your own words to explain Post-Selection and 
> why you can handle explanation using Post-Selection misconduct.
>
>    Best regards,
>
> -John Weng
>
> ------------------------------------------------------------------------
>
> *From:* Connectionists <connectionists-bounces at mailman.srv.cs.cmu.edu> 
> on behalf of Asim Roy <ASIM.ROY at asu.edu>
> *Sent:* Wednesday, June 5, 2024 6:49 PM
> *To:* Stephen José Hanson <jose at rubic.rutgers.edu>; Gary Marcus 
> <gary.marcus at nyu.edu>
> *Cc:* connectionists at mailman.srv.cs.cmu.edu 
> <connectionists at mailman.srv.cs.cmu.edu>
> *Subject:* Re: Connectionists: short Op-ed to address AI problems
>
> Dear Stephen,
>
> We are doing neurosymbolic with image processing – the symbolic stuff 
> on top of a DL model. It also brings in the explanation side. The 
> results are astounding. We get better performance than a pure DL 
> model. And exploring applications with defense agencies. They are 
> impressed with the results we have so far. So, neurosymbolic is 
> definitely the way forward.
>
> Best,
>
> Asim Roy
>
> Professor, Information Systems
>
> Arizona State University
>
> _Asim Roy | ASU Search 
> <https://urldefense.com/v3/__https:/search.asu.edu/profile/9973__;!!HXCxUKc!1ZzSj6Uim5wWu5W-JiBNqp_Cig3tUkK5DgMhDEBYnERP1f-pOAReghJiHzEk3hEHKL31roB_8qivsA$>_
>
> _Lifeboat Foundation Bios: Professor Asim Roy 
> <https://urldefense.com/v3/__https:/lifeboat.com/ex/bios.asim.roy__;!!HXCxUKc!1ZzSj6Uim5wWu5W-JiBNqp_Cig3tUkK5DgMhDEBYnERP1f-pOAReghJiHzEk3hEHKL31roAnhJU86A$>_
>
> *From:* Connectionists <connectionists-bounces at mailman.srv.cs.cmu.edu> 
> *On Behalf Of *Stephen José Hanson
> *Sent:* Wednesday, June 5, 2024 6:06 AM
> *To:* Gary Marcus <gary.marcus at nyu.edu>
> *Cc:* connectionists at mailman.srv.cs.cmu.edu
> *Subject:* Re: Connectionists: short Op-ed to address AI problems
>
> Dear Flabbergasted:
>
> Thankyou, I endeavor to provide short but useful commentary that could 
> be considered a "work of art".  Graci!
>
> Now either my memory is failing since 2017(not impossible), or you are 
> smoothing over a time series of claims that are actually like a seesaw.
>
> I think if we just rewind some of the connectionist comments; it would 
> be clear, in fact, for example, you had a long series of comments with 
> Geoff that seemed to indicate you were being misreprented as well.  
> Your complaints have always be around the fact that DL-AI has false 
> alarms (and to be fair other problems)   And sometimes pretty 
> odd-ones.  LLMs human and non-human errors are even more interesting.  
> The fact that they seem to grow circuits in the attention-heads is 
> gobsmacking!   I thought then and think now you are complaining about 
> peas under a very thick mattress (oh-oh,  metaphors now- I may have 
> opened pandora's box.)
>
> But I will go look at the budding NeuroSymbolic paper you mentioned, 
> but I have my doubts that the statistical bias is equivalent with the 
> architectually simplistic LLMs.  Nonetheless, I have not read it.
>
> I will also make a  coarse  timeline of your comments since 2017, but 
> anyone out there that would like to help, greatly appreciated!
>
> Best,
>
> Stephen
>
> On 6/5/24 8:41 AM, Gary Marcus wrote:
>
>     Wow, Stephen, you have outdone yourself. This note is a startling
>     mixture of rude, condescending, inaccurate, and uninformed. A work
>     of art!
>
>     To correct four misunderstandings:
>
>     1. Yes, my essay was written before LLMs were popular (though
>     around the time Transformers were proposed as it happens). It was
>     however /precisely/ “  a moonshot idea, that doesn't involve
>     leaving the blackbox in the hands of corporate types who value
>     profits over knowledge.” Please read what I wrote. It’s one page,
>     linked below, and you obviously couldn’t be bothered,.
>     (Parenthetically, I was one of the first people to warn that
>     OpenAI was likely to be problematic,  and have done so repeatedly
>     at my Substack.)
>
>     2. My argument throughout (back to 2012, in the New Yorker, 2018
>     in my Deep Learning: A Critical Appraisal, etc) has been that deep
>     learning has some role but cannot solve all things, and that it
>     would be not reliable on its own. In 2019 onwards I emphasized
>     many of the social problems that arise from relying on such
>     unreliable architectures. I have never wavered from any of that.
>     (Again, please read my work before so grossly distorting it.)
>     Unreliable systems that are blind to truth and values can cause
>     harm (bias), be exploited (to create disinformation), etc. There
>     is absolutely no contradiction there, as I have explained numerous
>     times in my writings.
>
>     3. It’s truly rude to dismiss an entire field as “flotsam and
>     jetsam”,  and you obviously aren’t following the neurosymbolic
>     literature, e.g., you must have missed DeepMind’s neurosymbolic
>     AlphaGeometry paper, in Nature, with its state of the art results,
>     beating pure neural nets.
>
>     4. Again, nothing has changed about my view; your last remark is
>     gratuitous and based on a misunderstanding.
>
>     Truly flabbergasted,
>
>     Gary
>
>         On Jun 5, 2024, at 05:18, Stephen José Hanson
>         _<jose at rubic.rutgers.edu> <mailto:jose at rubic.rutgers.edu>_ wrote:
>
>         
>
>         Gary, this was before the LLM discovery. Pierre is proposing a
>         moonshot idea, that doesn't involve leaving the blackbox in
>         the hands of corporate types who value profits over
>         knowledge.  OPENAI seems to be flailing and having serious
>         safety and security issues.  It certainly could be recipe for
>         diaster.
>
>         Frankly your views have been all over the place.  DL doesn't
>         work, DL could work but should be merged with the useless
>         flotsam and jetsam from GOFAI over the last 50 years, and now
>         they are too dangerous because they work but they are
>         unreliable, like most humans.
>
>         Its hard to know what views of yours to take seriously as they
>         seem change so rapidly.
>
>         Cheers
>
>         Stephen
>
>         On 6/4/24 9:53 AM, Gary Marcus wrote:
>
>             I would just point out that I first made this suggestion
>             [CERN for AI] in the New York Times in 2017, and several
>             others have since. There is some effort ongoing to try to
>             make it happen, if you search you will see.
>
>             <30gray-facebookJumbo.jpg>
>
>             _Opinion | Artificial Intelligence Is Stuck. Here’s How to
>             Move It Forward. (Gift Article)
>             <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nytimes.com_2017_07_29_opinion_sunday_artificial-2Dintelligence-2Dis-2Dstuck-2Dheres-2Dhow-2Dto-2Dmove-2Dit-2Dforward.html-3Funlocked-5Farticle-5Fcode-3D1.xE0.mcIz.lT-5FK7BZdonGJ-26smid-3Dnytcore-2Dios-2Dshare-26referringSource-3DarticleShare-26u2g-3Di-26sgrp-3Dc-2Dcb&d=DwMGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=wQR1NePCSj6dOGDD0r6B5Kn1fcNaTMg7tARe7TdEDqQ&m=fwBsbQ5xjEJFDg3c0iXuOBcr84mxEGxR0cEG4-hstVM8dJNyq3HVvpCACElUGWT2&s=TGZDkK1TsB_rNyjmal5jG1694upjB2JDhtj3UOe4Cws&e=>_
>
>             _nytimes.com
>             <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nytimes.com_2017_07_29_opinion_sunday_artificial-2Dintelligence-2Dis-2Dstuck-2Dheres-2Dhow-2Dto-2Dmove-2Dit-2Dforward.html-3Funlocked-5Farticle-5Fcode-3D1.xE0.mcIz.lT-5FK7BZdonGJ-26smid-3Dnytcore-2Dios-2Dshare-26referringSource-3DarticleShare-26u2g-3Di-26sgrp-3Dc-2Dcb&d=DwMGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=wQR1NePCSj6dOGDD0r6B5Kn1fcNaTMg7tARe7TdEDqQ&m=fwBsbQ5xjEJFDg3c0iXuOBcr84mxEGxR0cEG4-hstVM8dJNyq3HVvpCACElUGWT2&s=TGZDkK1TsB_rNyjmal5jG1694upjB2JDhtj3UOe4Cws&e=>_
>
>                 On Jun 3, 2024, at 22:58, Baldi,Pierre
>                 _<pfbaldi at ics.uci.edu>
>                 <mailto:pfbaldi at ics.uci.edu>_ wrote:
>
>                 
>                 I would appreciate feedback from this group,especially
>                 dissenting feedback,  on the attached Op-ed. You can
>                 send it to my personal email which you can find on my
>                 university web site if you prefer. The basic idea is
>                 simple:
>
>                 IF for scientific, security, or other societal reasons
>                 we want academics to develop and study the most
>                 advanced forms of AI, I can see only one solution: 
>                 create  a national or international effort around the
>                 largest data/computing center on Earth with a
>                 CERN-like structure comprising permanent staff, and
>                 1000s of affiliated academic laboratories. There are
>                 many obstacles, but none is completely insurmountable
>                 if we wanted to.
>
>                 Thank you.
>
>                 Pierre
>
>
>                 <AI-CERN-Baldi2024FF.pdf>
>
>         -- 
>
>         Stephen José Hanson
>
>         Professor of Psychology
>
>         Director of RUBIC
>
>         Member of Exc Comm RUCCS
>
> -- 
> Stephen José Hanson
> Professor of Psychology
> Director of RUBIC
> Member of Exc Comm RUCCS
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