<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body dir="auto"><div dir="ltr">The whole point of the neurosymbolic approach is to develop systems that can accommodate both vectors and symbols, since neither on their own seems adequate.<div dir="ltr"><div dir="ltr"><br></div><div dir="ltr">If there are arguments against trying to do that, we would be interested.</div><div dir="ltr"><br><div dir="ltr"></div><blockquote type="cite">On Feb 4, 2022, at 4:17 AM, Stephen José Hanson <jose@rubic.rutgers.edu> wrote:<br><br></blockquote></div><blockquote type="cite"><div dir="ltr">
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<p><font size="+1">Geoff's position is pretty clear. He said in
the conversation we had and in this thread, "vectors of soft
features",</font></p>
<p><font size="+1">Some of my claim is in several of the
conversations with Mike Jordan and Rich Sutton, but briefly,
there are a number of<br>
very large costly efforts from the 1970s and 1980s, to create,
deploy and curate symbol AI systems that were massive failures.
Not counterfactuals, but factuals that failed. The MCC comes
to mind with Adm Bobby Inmann's national US mandate to counter
the Japanese so called"Fifth-generation AI systems" as a
massive failure of symbolic AI. <br>
</font></p>
<p><font size="+1">--------------------<br>
</font></p>
<p><font size="+1">In 1982, Japan launched its Fifth Generation
Computer Systems project (FGCS), designed to develop intelligent
software that would run on novel computer hardware. As the first
national, large-scale artificial intelligence (AI) research and
development (R&D) project to be free from military influence
and corporate profit motives, the FGCS was open, international,
and oriented around public goods.<br>
</font></p>
<div class="moz-cite-prefix">On 2/3/22 6:34 PM, Francesca Rossi2
wrote:<br>
</div>
<blockquote type="cite" cite="mid:BN8PR15MB273890B80829AA8EB71E13B3D7289@BN8PR15MB2738.namprd15.prod.outlook.com">
<pre class="moz-quote-pre" wrap="">Hi all.
Thanks Gary for adding me to this thread.
I also would be interested in knowing why Steve thinks that NS AI did not work in the past, and why this is an indication that it cannot work now or in the future.
Thanks,
Francesca.
------------------
Francesca Rossi
IBM Fellow and AI Ethics Global Leader
T.J. Watson Research Center, Yorktown Heights, USA
+1-617-3869639
________________________________________
From: Artur Garcez <a class="moz-txt-link-rfc2396E" href="mailto:arturdavilagarcez@gmail.com"><arturdavilagarcez@gmail.com></a>
Sent: Thursday, February 3, 2022 6:00 PM
To: Gary Marcus
Cc: Stephen José Hanson; Geoffrey Hinton; AIhub; <a class="moz-txt-link-abbreviated" href="mailto:connectionists@mailman.srv.cs.cmu.edu">connectionists@mailman.srv.cs.cmu.edu</a>; Luis Lamb; Josh Tenenbaum; Anima Anandkumar; Francesca Rossi2; Swarat Chaudhuri; Gadi Singer
Subject: [EXTERNAL] Re: Connectionists: Stephen Hanson in conversation with Geoff Hinton
It would be great to hear Geoff's account with historical reference to his 1990 edited special volume of the AI journal on connectionist symbol processing. Judging from recent reviewing for NeurIPS, ICLR, ICML but also KR, AAAI, IJCAI (traditionally ZjQcmQRYFpfptBannerStart
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It would be great to hear Geoff's account with historical reference to his 1990 edited special volume of the AI journal on connectionist symbol processing.
Judging from recent reviewing for NeurIPS, ICLR, ICML but also KR, AAAI, IJCAI (traditionally symbolic), there is a clear resurgence of neuro-symbolic approaches.
Best wishes,
Artur
On Thu, Feb 3, 2022 at 5:00 PM Gary Marcus <<a class="moz-txt-link-abbreviated" href="mailto:gary.marcus@nyu.edu">gary.marcus@nyu.edu</a><a class="moz-txt-link-rfc2396E" href="mailto:gary.marcus@nyu.edu"><mailto:gary.marcus@nyu.edu></a>> wrote:
Steve,
I’d love to hear you elaborate on this part,
Many more shoes will drop in the next few years. I for one don't believe one of those shoes will be Hybrid approaches to AI, I've seen that movie before and it didn't end well.
I’d love your take on why you think the impetus towards hybrid models ended badly before, and why you think that the mistakes of the past can’t be corrected. Also it’ would be really instructive to compare with deep learning, which lost steam for quite some time, but reemerged much stronger than ever before. Might not the same happen with hybrid models?
I am cc’ing some folks (possibly not on this list) who have recently been sympathetic to hybrid models, in hopes of a rich discussion. (And, Geoff, still cc’d, I’d genuinely welcome your thoughts if you want to add them, despite our recent friction.)
Cheers,
Gary
On Feb 3, 2022, at 5:10 AM, Stephen José Hanson <<a class="moz-txt-link-abbreviated" href="mailto:jose@rubic.rutgers.edu">jose@rubic.rutgers.edu</a><a class="moz-txt-link-rfc2396E" href="mailto:jose@rubic.rutgers.edu"><mailto:jose@rubic.rutgers.edu></a>> wrote:
I would encourage you to read the whole transcript, as you will see the discussion does intersect with a number of issues you raised in an earlier post on what is learned/represented in DLs.
Its important for those paying attention to this thread, to realize these are still very early times. Many more shoes will drop in the next few years. I for one don't believe one of those shoes will be Hybrid approaches to AI, I've seen that movie before and it didn't end well.
Best and hope you are doing well.
Steve
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