The real question for AI is this: can we do reasoning and causality without symbol-manipulation? Deep learning founders like @YLeCun (see our debate) and Hinton (eg https://sites.google.com/site/krr2015/home/schedule …) have said no; I have argued yes.https://twitter.com/GaryMarcus/status/1065280340669816832 …
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Replying to @GaryMarcus @ylecun
Neural networks have sufficient expressive power, so the main difference between symbolic AI and ML is whether we use hand crafted solutions or automatic function approximation. Could you state in which way your idea of symbol manipulation differs from what a neural TM could do?
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No, this isn't true in a practical sense. Having the system work out how to 1) Find composable symbols 2) perform constraint propagation 3) perform backtracking search 4) work out look-ahead optimizations is extra work that the NTM won't be able to do. And can be skipped
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I have mentioned the NTM only as a proof of concept (symbolic operations in NN). I don't think anyone but individual cells use a TM design for practical computations.
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i talk about universal function approximation vs symbol manipulation in chapter two of algebraic mind; too subtle for twitter, perhaps
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Replying to @GaryMarcus @Plinz
If you don't want to buy a book you can also check out http://www.psych.nyu.edu/gary/marcusArticles/Marcus%202013%20treelets%20%5Bproofs%5D.pdf … if you haven't. There are advantages, disadvantages, tradeoffs between explitcitly vs implicitly symbolic, discrete vs continuous and search/sampling vs optimization. Lots of people don't acknowledge
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And the idea that GOFAI ideas didn't lead anywhere is the biggest myth. Every database, verifier, WaveFunctionCollapse,symbolic algebra,type system, SMT is argument against it. In my case I could write yet another image analogy tool or I can write something that helps teach math
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Replying to @sir_deenicus @GaryMarcus
I would not make any such claim. I also don't think that the ML folks deny that we learn how to reason symbolically. The strongest claims I hear are more along the lines that symbolic reasoning happens when the functions we approximate become low dimensional and discrete.
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This simply rewrites history. See for example last sentence of Lecun, Hinton, Bengio in Nature 2015, or Rumelhart and McClelland’s declaration that symbol-manipulation is not essence of human cognition. Or Hinton’s “aeitherial symbols” talk.
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Replying to @GaryMarcus @sir_deenicus
I don't see this as a contradiction. The essence of human cognition may better be described by the mechanisms that enable perception. I think it may be more plausible to extend perception into symbol manipulation than the other way around.
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Replying to @Plinz @sir_deenicus
? You said that the ML folks dont deny that we (learn) how to reason symbolically. They do (or did; Yann seemed to backtrack some today).
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