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fchollet's profile
François Chollet
François Chollet
François Chollet
Verified account
@fchollet

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François CholletVerified account

@fchollet

Deep learning @google. Creator of Keras. Author of 'Deep Learning with Python'. Opinions are my own.

United States
fchollet.com
Joined August 2009

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    1. François Chollet‏Verified account @fchollet 24 Jun 2018

      Statements like "X is can be used to represent any program/function, therefore it is all we are every going to need" are pretty silly.

      5 replies 16 retweets 104 likes
      Show this thread
    2. Shubhendu Trivedi‏ @_onionesque 24 Jun 2018
      Replying to @fchollet

      I don't think any serious CS person would make that straw-man claim. X can be used to represent any function is a pretty interesting fact by itself. It might be trivial for you, it is not for me. (I saw an exchange, I think the other gentleman was making a much broader point)

      1 reply 0 retweets 0 likes
    3. Shubhendu Trivedi‏ @_onionesque 24 Jun 2018
      Replying to @_onionesque @fchollet

      I think it goes without saying that any system of interest in what you are talking about has to be Turing complete. But that by itself does not say anything (and that is obvious). It is really a problem for representation (architectural?)/ perhaps in terms of optimization? etc.

      1 reply 0 retweets 0 likes
    4. Shubhendu Trivedi‏ @_onionesque 24 Jun 2018
      Replying to @_onionesque @fchollet

      I do think that RNNs are like the brainfuck equivalent of NNs to PLs in the Turing tarpit, but I would think that is obvious and that people wouldn't actually believe hat they can be used to solve what that some C++ NN equivalent could solve, but maybe I am wrong...

      1 reply 0 retweets 1 like
    5. François Chollet‏Verified account @fchollet 24 Jun 2018
      Replying to @_onionesque

      I regularly do see this claim verbatim, with Turing-completeness being used as "proof". It's not a straw man, it's a surprisingly common position. Before RNNs were cool, the "universal approximator" argument was being used in the same way to say that NNs were sufficient for AGI.

      2 replies 0 retweets 11 likes
      François Chollet‏Verified account @fchollet 24 Jun 2018
      Replying to @fchollet @_onionesque

      Mostly, it seems like an excuse to avoid having to think about what (R)NNs really do, and where their limitations lie.

      4:58 PM - 24 Jun 2018
      • 11 Likes
      • ChinHuiChen Nexidava Jprwg Lukáš Banič R4_Unit Donald E Frederick, PhD Yaser Sulaiman Tejas Kulkarni Alex V. Mantzaris
      1 reply 0 retweets 11 likes
        1. Shubhendu Trivedi‏ @_onionesque 24 Jun 2018
          Replying to @fchollet

          I think that is fair to think in that case.

          0 replies 0 retweets 0 likes
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