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Dear Gary,</div>
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    You wrote, "you must have missed DeepMind’s neurosymbolic AlphaGeometry paper, in Nature, with its state of the art results, beating pure neural nets."   Based on this statement, I am afraid that you do not have algorithmic expertise to understand my Post-Selection
 misconduct allegation against Alphabet's all AI projects so far:</div>
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    It is my ethical duty to inform you that I alleged "Deep Learning" including “LLMs” like ChatGPT to be Post-Selection misconduct (cheating and hiding).  Read J. Weng, On "Deep Learning" Misconduct, ISAIC 2022 and also https://ui.adsabs.harvard.edu/abs/2022arXiv221116350W/abstract
   </div>
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    If you train multiple systems each using different parameters, you need to report the average errors of all trained systems on a validation set.  Better, also report the minimum, 25%, 50%, 75%, and maximum of the ranked errors on the validation set.   If
 you only report the error of the luckiest few networks on the validation set, you grossly underestimate its error in a future new test. Namely, the luck on the validation set does not transfer to a similar luck on a new future test.    </div>
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    Please see this Newsletter for the latest developments if there is such a future test:   https://www.cse.msu.edu/amdtc/amdnl/CDSNL-V18-N1.pdf   </div>
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     If you are interested in discussing this important matter, I invite you to write an [AI Crisis] Dialogue.         See https://www.cse.msu.edu/amdtc/amdnl/CDSNL-V18-N2.pdf   </div>
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    Best regards,</div>
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-John Weng</div>
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Brain-Mind Institute</div>
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<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> Connectionists <connectionists-bounces@mailman.srv.cs.cmu.edu> on behalf of Gary Marcus <gary.marcus@nyu.edu><br>
<b>Sent:</b> Wednesday, June 5, 2024 8:41 AM<br>
<b>To:</b> Stephen José Hanson <jose@rubic.rutgers.edu><br>
<b>Cc:</b> connectionists@mailman.srv.cs.cmu.edu <connectionists@mailman.srv.cs.cmu.edu><br>
<b>Subject:</b> Re: Connectionists: short Op-ed to address AI problems</font>
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<div dir="ltr">Wow, Stephen, you have outdone yourself. This note is a startling mixture of rude, condescending, inaccurate, and uninformed. A work of art! </div>
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<div dir="ltr">To correct four misunderstandings:</div>
<div dir="ltr">1. Yes, my essay was written before LLMs were popular (though around the time Transformers were proposed as it happens). It was however
<i>precisely</i> “  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.)</div>
<div dir="ltr">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.</div>
<div dir="ltr">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.</div>
<div dir="ltr">4. Again, nothing has changed about my view; your last remark is gratuitous and based on a misunderstanding.</div>
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<div dir="ltr">Truly flabbergasted,</div>
<div dir="ltr">Gary</div>
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<blockquote type="cite">On Jun 5, 2024, at 05:18, Stephen José Hanson <jose@rubic.rutgers.edu> wrote:<br>
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<p>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.<br>
</p>
<p>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.</p>
<p>Its hard to know what views of yours to take seriously as they seem change so rapidly.  
<br>
</p>
<p>Cheers</p>
<p>Stephen<br>
</p>
<div class="x_moz-cite-prefix">On 6/4/24 9:53 AM, Gary Marcus wrote:<br>
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<div dir="ltr">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.</div>
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<blockquote type="cite">On Jun 3, 2024, at 22:58, Baldi,Pierre <a class="x_moz-txt-link-rfc2396E" href="mailto:pfbaldi@ics.uci.edu">
<pfbaldi@ics.uci.edu></a> wrote:<br>
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<span>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:</span><br>
<span></span><br>
<span>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.</span><br>
<span></span><br>
<span>Thank you.</span><br>
<span></span><br>
<span>Pierre</span><br>
<span></span><br>
<span></span><br>
<span></span><br>
<span></span><br>
<span></span><br>
<div><AI-CERN-Baldi2024FF.pdf></div>
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<pre class="x_moz-signature" cols="72">-- 
Stephen José Hanson
Professor of Psychology
Director of RUBIC
Member of Exc Comm RUCCS</pre>
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