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<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> Somebody wrote, "Deeply disappointing that someone would try to inject actual empirical
evidence into this discussion."</span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> I agree. If we are unclear about the mathematical definition, we waste time here.</span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> When I said "There is no neuron (or a set of neurons) that has a one-to-one correspondence
with a symbol", I meant that</span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">without "one-to-one correspondence" definition, the neuron is NOT a symbol neuron you
have in mind.</span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> From Wikipedia:<br>
A bijection, bijective function, or one-to-one correspondence between two mathematical sets is a function such that each element of the second set (the codomain) is mapped to from exactly one element of the first set (the domain). Equivalently, a bijection
is a relation between two sets such that each element of either set is paired with exactly one element of the other set.</span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> In other words, one-to-one correspondence is "one-to-one" and "onto".</span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> If we are not careful, we slip into something like "grandmother cells" without a
definition. Because there are no symbol neurons, </span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">there must be no grandmother cells in the brain. </span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> Why? All neurons in the brain detect a spatiotemporal feature of the sensory space
and the motor space. </span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> If you have read my book, NAI, you understand what this means and why it must be
the case because the brain must not have a government inside the skull.</span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> Best regards,</span></div>
<div class="elementToProof"><span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">-John</span></div>
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</span></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> Thursday, February 22, 2024 12:44 PM<br>
<b>To:</b> Jeffrey Bowers <J.Bowers@bristol.ac.uk><br>
<b>Cc:</b> connectionists@mailman.srv.cs.cmu.edu <connectionists@mailman.srv.cs.cmu.edu><br>
<b>Subject:</b> Connectionists: neurons, grandmothers, symbols and pi.</font>
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<div dir="ltr">Generally agree with Jeff, but would add this to the general discussion:</div>
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<div dir="ltr">We need to be careful about what the question we are asking is here. Mathematicians for example represent and manipulate <span style="color:rgb(51,51,51); text-align:center; background-color:rgb(255,255,255); font-size:27px">š
</span>, both symbolically
and (with some precision) numerically. We donāt know how the brain instantiates either of those representations. But itās absurd to presume that we since donāt understand how either of those representations are instantiated neurally, that there is no symbolic
or numeric representation thereof.</div>
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<div dir="ltr">Physically, the symbolic representation of pi presumably occupies the labors of multiple neurons, but in some contexts those neurons may work together as a single logical whole, and it is possible that some of the neurons involved reach threshold
only when pi is being processed.</div>
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<div dir="ltr">Gary</div>
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<blockquote type="cite">On Feb 22, 2024, at 07:32, Jeffrey Bowers <J.Bowers@bristol.ac.uk> wrote:<br>
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<p class="x_MsoNormal"><span style="font-size:11.0pt">Good point, I should not have used simple cells as an example of grandmother cells. In fact, I agree that some sort of population coding is likely supporting our perception of orientation. For example,
simple cells are oriented in steps of about 5 degrees, but we can perceive orientations at a much finer granularity, so it must be a combination of cells driving our perception.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">The other reason I should have not used simple cells is that grandmother cells are a theory about how we identify familiar categories of objects (my grandmother, or a dog or a cat). Orientation is a continuous
dimension where distributed coding may be more suitable. The better example I gave is the word representation DOG in the IA model. The fact that the DOG detector is partly activated by the input CAT does not falsify the hypothesis that DOG is locally coded.
Indeed, it has hand-wired to be localist. In the same way, the fact that a Jennifer Aniston neuron might be weakly activated by another face does not rule out the hypothesis that the neuron selectively codes for Jennifer Aniston. I agree it is not strong
evidence for a grandmother cell ā there may be other images that drive the neuron even more, we just donāt know given the limited number of images presented to the patient. But it is interesting that there are various demonstrations that artificial networks
learn grandmother cells under some conditions ā when you can test the model on all the familiar categories it has seen. So, I would not rule out grandmother cells out of hand.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Jeff </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
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<p class="x_MsoNormal" style="margin-bottom:12.0pt"><b><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">From:
</span></b><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">KENTRIDGE, ROBERT W. <robert.kentridge@durham.ac.uk><br>
<b>Date: </b>Wednesday, 21 February 2024 at 20:56<br>
<b>To: </b>Jeffrey Bowers <J.Bowers@bristol.ac.uk>, Gary Marcus <gary.marcus@nyu.edu>, Laurent Mertens <laurent.mertens@kuleuven.be><br>
<b>Cc: </b>connectionists@mailman.srv.cs.cmu.edu <connectionists@mailman.srv.cs.cmu.edu><br>
<b>Subject: </b>Re: Connectionists: Early history of symbolic and neural network approaches to AI</span></p>
</div>
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<p class="x_MsoNormal"><span style="font-size:11.0pt">Again, it is great to be examining the relationship between ārealā neural coding and the ins and outs of representation in ANNs. Iām really pleased to be able to make a few contributions to a list which
Iāve lurked on since the late 1980s!</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">I feel I should add an alternative interpretation of orientation coding in primary visual cortex to that so clearly explained by Jeffrey. It is, indeed, tempting to think of orientation tuned cells as labelled
lines or grandmother cells where we read off activity in individual cells as conveying the presence of a line segment with a specific orientation at a particular location in the visual field. As neuroscientists we can certainly do this. The key question is
whether brain areas outside primary visual cortex, which are consumers of information coded in primary visual cortex, also do this. The alternative view of orientation coding is that orientation is represented by a population code where orientation is represented
as the vector sum of orientation preferences in cells with many different orientation tunings, weighted by their levels of activity, and that it is this population code that is read by areas that are consumers of orientation information. The notion of neural
population coding of orientation was first tested electrophysiologically by Georgopoulos in 1982, examining population coding of the direction of arm movements in primary motor cortex. There is more recent psychophysical evidence that peopleās confidence in
their judgements of the orientation of a visual stimulus can be predicted on the basis of a population coding scheme (Bays, 2016, A signature of neural coding at human perceptual limits. Journal of Vision,
</span><a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__jov.arvojournals.org_article.aspx-3Farticleid-3D2552242&d=DwMGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=wQR1NePCSj6dOGDD0r6B5Kn1fcNaTMg7tARe7TdEDqQ&m=sG1Xdlih_sVqjQeOguhFEwtXavYdLzHaKPGgErxcEHlfYl0C7BnglI8bTPl6UNvA&s=aSyy_rYvvPjfLucV1td7Y5O7JtPHcZdQmylfTXWPL4c&e="><span style="font-size:11.0pt">https://jov.arvojournals.org/article.aspx?articleid=2552242</span></a><span style="font-size:11.0pt">),
where a personās judgment is indicative of the state of a high level consumer of orientation information.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">So again, Iād err on the side of suggesting that although we can conceive of single neurons in primary visual cortex as encoding information (maybe not really symbols in this case anyway), it isnāt our ability
to interpret things like this that matters, rather, it is the way the rest of the brain interprets information delivered by primary visual cortex.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">cheers,</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Bob</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
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<p class="x_MsoNormal"><span style="font-size:11.0pt">Professor of Psychology, University of Durham.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Durham PaleoPsychology Group.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Durham Centre for Vision and Visual Cognition.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Durham Centre for Visual Arts and Culture.</span></p>
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<p class="x_MsoNormal"><span style="font-size:11.0pt">Fellow. </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Canadian Institute for Advanced Research,
</span></p>
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<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Department of Psychology,</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">University of Durham,</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Durham DH1 3LE, UK.</span></p>
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<p class="x_MsoNormal" style="margin-bottom:12.0pt"><b><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">From:
</span></b><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">Jeffrey Bowers <J.Bowers@bristol.ac.uk><br>
<b>Date: </b>Wednesday, 21 February 2024 at 12:31<br>
<b>To: </b>KENTRIDGE, ROBERT W. <robert.kentridge@durham.ac.uk>, Gary Marcus <gary.marcus@nyu.edu>, Laurent Mertens <laurent.mertens@kuleuven.be><br>
<b>Cc: </b>connectionists@mailman.srv.cs.cmu.edu <connectionists@mailman.srv.cs.cmu.edu><br>
<b>Subject: </b>Re: Connectionists: Early history of symbolic and neural network approaches to AI</span></p>
</div>
<div>
<p class="x_MsoNormal"><strong><span style="font-size:12.0pt; font-family:"Calibri",sans-serif; color:black; background:#FFFECF">[EXTERNAL EMAIL]</span></strong></p>
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<p class="x_MsoNormal">It is possible to define a grandmother cell in a way that falsifies them. For instance, defining grandmother cells as single neurons that only *respond* to inputs from one category. Another definition that is more plausible is single
neurons that only *represent* one category. In psychology there are ālocalistā models that have single units that represent one category (e.g., there is a unit in the Interactive Activation Model that codes for the word DOG). And a feature of localist codes
is that they are partly activated by similar inputs. So a DOG detector is partly activated by the input HOG by virtue of sharing two letters. But that partial activation of the DOG unit from HOG is no evidence against a localist or grandmother cell representation
of the word DOG in the IA model. Just as a simple cell of a vertical line is partly activated by a line 5 degrees off vertical ā that does not undermine the hypothesis that the simple cell *represents* vertical lines. I talk about the plausibility of Grandmother
cells and discuss the Aniston cells in a paper I wrote sometime back:</p>
<p class="x_MsoNormal"> </p>
<p class="x_MsoNormal"><span style="font-family:"Arial",sans-serif; color:#222222; background:white">Bowers, J. S. (2009). On the biological plausibility of grandmother cells: implications for neural network theories in psychology and neuroscience.<span class="x_apple-converted-space"> </span></span><i><span style="font-family:"Arial",sans-serif; color:#222222">Psychological
review</span></i><span style="font-family:"Arial",sans-serif; color:#222222; background:white">,<span class="x_apple-converted-space"> </span></span><i><span style="font-family:"Arial",sans-serif; color:#222222">116</span></i><span style="font-family:"Arial",sans-serif; color:#222222; background:white">(1),
220.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
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<p class="x_MsoNormal" style="margin-bottom:12.0pt"><b><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">From:
</span></b><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">Connectionists <connectionists-bounces@mailman.srv.cs.cmu.edu> on behalf of KENTRIDGE, ROBERT W. <robert.kentridge@durham.ac.uk><br>
<b>Date: </b>Wednesday, 21 February 2024 at 11:48<br>
<b>To: </b>Gary Marcus <gary.marcus@nyu.edu>, Laurent Mertens <laurent.mertens@kuleuven.be><br>
<b>Cc: </b>connectionists@mailman.srv.cs.cmu.edu <connectionists@mailman.srv.cs.cmu.edu><br>
<b>Subject: </b>Re: Connectionists: Early history of symbolic and neural network approaches to AI</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:11.0pt">I agree ā empirical evidence is just what we need in this super-interesting discussion.
</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">I should point out a few things about the Quiroga et al 2005 āJennifer Aniston cellā finding (<i>Nature</i>, <b>435</b>. 1102 - 1107 ).
</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Quiroga et al themselves are at pains to point out that whilst the cells they found responded to a wide variety of depictions of specific individuals they were not āGrandmother cellsā as defined by Jerry
Lettvin ā that is, specific cells that respond to a broad range of depictions of an individual and *<b>only</b>* of that individual, meaning that one can infer that this individual is being perceived, thought of, etc. whenever that cell is active.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">The cells Quiroga found do, indeed, respond to remarkably diverse ranges of stimuli depicting individuals, including not just photos in different poses, at different ages, in different costumes (including
Hale Berry as Catwoman for the Hale Berry cell), but also names presented as text (e.g. āHALE BERRYā). Quiroga et al only presented stimuli representing a relatively small range of individuals and so it is unsafe to conclude that the cells they found respond
*<b>only</b>* to the specific individuals they found. Indeed, they report that the Jennifer Aniston cell also responded strongly to an image of a different actress, Lisa Kudrow, who appeared in āFriendsā along with Jennifer Aniston.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">So, the empirical evidence is still on the side of activity in sets of neurons as representing specific symbols (including those standing for specific individuals) rather than individual cells standing for
specific symbols.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">cheers</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Bob</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
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<p class="x_MsoNormal"><span style="font-size:11.0pt">Professor of Psychology, University of Durham.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Durham PaleoPsychology Group.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Durham Centre for Vision and Visual Cognition.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Durham Centre for Visual Arts and Culture.</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
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<p class="x_MsoNormal"><span style="font-size:11.0pt">Fellow. </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Canadian Institute for Advanced Research,
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<p class="x_MsoNormal"><span style="font-size:11.0pt"> </span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Department of Psychology,</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">University of Durham,</span></p>
<p class="x_MsoNormal"><span style="font-size:11.0pt">Durham DH1 3LE, UK.</span></p>
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<p class="x_MsoNormal" style="margin-bottom:12.0pt"><b><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">From:
</span></b><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">Connectionists <connectionists-bounces@mailman.srv.cs.cmu.edu> on behalf of Gary Marcus <gary.marcus@nyu.edu><br>
<b>Date: </b>Wednesday, 21 February 2024 at 05:49<br>
<b>To: </b>Laurent Mertens <laurent.mertens@kuleuven.be><br>
<b>Cc: </b>connectionists@mailman.srv.cs.cmu.edu <connectionists@mailman.srv.cs.cmu.edu><br>
<b>Subject: </b>Re: Connectionists: Early history of symbolic and neural network approaches to AI</span></p>
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<p class="x_MsoNormal"><strong><span style="font-size:12.0pt; font-family:"Calibri",sans-serif; color:black; background:#FFFECF">[EXTERNAL EMAIL]</span></strong></p>
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<p class="x_MsoNormal"><span style="font-size:11.0pt">Deeply disappointing that someone would try to inject actual empirical evidence into this discussion.
</span><span style="font-size:11.0pt; font-family:"Apple Color Emoji"">š</span></p>
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<p class="x_MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:11.0pt">On Feb 20, 2024, at 08:41, Laurent Mertens <laurent.mertens@kuleuven.be> wrote:</span></p>
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<p class="x_MsoNormal"><span style="font-size:11.0pt">ļ»æ </span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">Reacting to your statement:</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">"However, inside the skull of my brain, there are not any neurons that have a one-to-one correspondence to the symbol."</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">What about the Grandmother/Jennifer Aniston/Halle Berry neuron?</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">(See, e.g.,
</span><a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__www.caltech.edu_about_news_single-2Dcell-2Drecognition-2Dhalle-2Dberry-2Dbrain-2Dcell-2D1013&d=DwMFAw&c=slrrB7dE8n7gBJbeO0g-IQ&r=wQR1NePCSj6dOGDD0r6B5Kn1fcNaTMg7tARe7TdEDqQ&m=it3XOFrc2yBru1bmF9dud4UoT60mjmur8mR3zGu365JPKmtWSuFnJTxRJOV4WSpa&s=kh-rqxQw6qcxbM8bhUYTHNaJHN5jtc3SLI5RXC5XgWA&e="><span style="font-size:12.0pt; font-family:"Aptos",sans-serif">https://www.caltech.edu/about/news/single-cell-recognition-halle-berry-brain-cell-1013</span></a><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">)</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">KR,</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">Laurent</span></p>
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<p class="x_MsoNormal"><b><span style="font-size:11.0pt; color:black">From:</span></b><span style="font-size:11.0pt; color:black"> Connectionists <connectionists-bounces@mailman.srv.cs.cmu.edu> on behalf of Weng, Juyang <weng@msu.edu><br>
<b>Sent:</b> Monday, February 19, 2024 11:11 PM<br>
<b>To:</b> Michael Arbib <arbib@usc.edu>; connectionists@mailman.srv.cs.cmu.edu <connectionists@mailman.srv.cs.cmu.edu><br>
<b>Subject:</b> Re: Connectionists: Early history of symbolic and neural network approaches to AI</span><span style="font-size:11.0pt">
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">Dear Michael,</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black"> You wrote, "Your brain did not deal with symbols?"</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black"> I have my Conscious Learning (DN-3) model that tells me:<br>
My brain "deals with symbols" that are sensed from the extra-body world by the brain's sensors and effecters.</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black"> However, inside the skull of my brain, there are not any neurons that have a one-to-one correspondence to the symbol. In this sense, the brain does not
have any symbol in the skull.</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black"> This is my educated hypothesis. The DN-3 brain does not need any symbol inside the skull.</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black"> In this sense, almost all neural network models are flawed about the brain, as long as they have a block diagram where each block corresponds to a function
concept in the extra-body world. I am sorry to say that, which may make many enemies. </span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black"> Best regards,</span></p>
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<p class="x_MsoNormal"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">-John </span></p>
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<p class="x_MsoNormal"><b><span style="font-size:11.0pt; color:black">From:</span></b><span style="font-size:11.0pt; color:black"> Michael Arbib <arbib@usc.edu><br>
<b>Sent:</b> Monday, February 19, 2024 1:28 PM<br>
<b>To:</b> Weng, Juyang <weng@msu.edu>; connectionists@mailman.srv.cs.cmu.edu <connectionists@mailman.srv.cs.cmu.edu><br>
<b>Subject:</b> RE: Connectionists: Early history of symbolic and neural network approaches to AI</span><span style="font-size:11.0pt">
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<p style="margin:0cm">So you believe that, as you wrote out these words, the neural networks in your brain did not deal with symbols?</p>
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<p style="margin:0cm"><b>From:</b> Connectionists <connectionists-bounces@mailman.srv.cs.cmu.edu>
<b>On Behalf Of </b>Weng, Juyang<br>
<b>Sent:</b> Monday, February 19, 2024 8:07 AM<br>
<b>To:</b> connectionists@mailman.srv.cs.cmu.edu<br>
<b>Subject:</b> Connectionists: Early history of symbolic and neural network approaches to AI</p>
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<p style="margin:0cm"><span style="font-size:12.0pt; font-family:"Aptos",sans-serif; color:black">I do not agree with
<span style="background:white">Newell and Simon</span> if they wrote that. Otherwise, images and video are also symbols. They probably were not sophisticated enough in 1976 to realize why neural networks in the brain should not contain or deal with symbols.</span></p>
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