Connectionists: Stephen Hanson in conversation with Geoff Hinton

[Stephen José Hanson]

Well I don't like counterfactual arguments or ones that start with "It 
can't be done with neural networks.."--as this amounts to the old 
Rumelhart saw, of "proof by lack of imagination".

I think my position and others (I can't speak for Geoff and won't) is 
more of a "purist" view that brains have computationally complete 
representational power to do what ever is required of human level mental 
processing.  AI symbol systems are remote descriptions of this level of 
processing.     Looking at 1000s of brain scans, one begins to see a 
pattern of interacting large and smaller scale networks, probably 
related to Resting state and the Default Mode networks in some important 
competitive way.   But what one doesn't find is modular structure (e.g. 
face area.. nope)  or evidence of "symbols" being processed.    Research 
on Numbers is interesting in this regard, as number representation 
should provide some evidence of  discrete symbol processing as would  
letters.   But again the processing states from brain imaging  more 
generally appear to be distributed representations of some sort.

One other direction has to do with prior rules that could be neurally 
coded and therefore provide an immediate bias in learning and thus 
dramatically reduce the number of examples required for  asymptotic 
learning.     Some of this has been done with pre-training-- on let's 
say 1000s of videos that are relatively generic, prior to learning on a 
small set of videos related to a specific topic-- say two individuals 
playing a monopoly game.  In that case, no game-like videos were sampled 
in the pre-training, and the LSTM was trained to detect change point on 
2 minutes of video, achieving a 97% match with human parsers.    In 
these senses I have no problem with this type of hybrid training.

Steve

On 2/4/22 9:07 AM, Gary Marcus wrote:
> 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.
>
> If there are arguments against trying to do that, we would be interested.
>
>> On Feb 4, 2022, at 4:17 AM, Stephen José Hanson 
>> <jose at rubic.rutgers.edu> wrote:
>>
>> 
>>
>> Geoff's position is pretty clear.   He said in the conversation we 
>> had and in this thread, "vectors of soft features",
>>
>> Some of my claim is in several of the conversations with Mike Jordan 
>> and Rich Sutton, but briefly,  there are a number of
>> 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.
>>
>> --------------------
>>
>> 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.
>>
>> On 2/3/22 6:34 PM, Francesca Rossi2 wrote:
>>> 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<arturdavilagarcez at gmail.com>
>>> Sent: Thursday, February 3, 2022 6:00 PM
>>> To: Gary Marcus
>>> Cc: Stephen José Hanson; Geoffrey Hinton; AIhub;connectionists at mailman.srv.cs.cmu.edu; 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
>>> This Message Is From an External Sender
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>>> ZjQcmQRYFpfptBannerEnd
>>>
>>> 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 <gary.marcus at nyu.edu<mailto:gary.marcus at nyu.edu>> 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 <jose at rubic.rutgers.edu<mailto:jose at rubic.rutgers.edu>> 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
>>>
>> -- 
>> <signature.png>
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