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Meaningness's profile
David Chapman
David Chapman
David Chapman
@Meaningness

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David Chapman

@Meaningness

Better ways of thinking, feeling, and acting—around problems of meaning and meaninglessness; self and society; ethics, purpose, and value.

meaningness.com/about-my-sites
Joined September 2010

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    1. michael_nielsen‏ @michael_nielsen 8 Oct 2019
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      Replying to @Meaningness @IntuitMachine

      Pretty much. There are useful ideas from physics in deep learning research, but I don't think any (currently) really key/dominant ideas are from physics. Maybe I'm not thinking of one?

      3 replies 0 retweets 3 likes
    2. David Chapman‏ @Meaningness 8 Oct 2019
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      Replying to @michael_nielsen @IntuitMachine

      I mean... the whole thing looks like physics to me? You’re shaking a ball on an energy surface.

      2 replies 0 retweets 2 likes
    3. michael_nielsen‏ @michael_nielsen 8 Oct 2019
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      Replying to @Meaningness @IntuitMachine

      Minimizing a cost function using SGD/backprop is like physics in much the same way as eigenvectors are part of quantum mechanics.

      1 reply 0 retweets 8 likes
    4. michael_nielsen‏ @michael_nielsen 8 Oct 2019
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      Replying to @michael_nielsen @Meaningness @IntuitMachine

      It occurs to me that I don't know where the theory of mathematical optimization (& notions like objective function, gradient descent) comes from. Certainly, it was buzzing as a subject independent of physics by the 1950s. But its roots may be in part in physics, earlier.

      5 replies 0 retweets 7 likes
    5. David Chapman‏ @Meaningness 8 Oct 2019
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      Replying to @michael_nielsen @IntuitMachine

      One major strand in the history would be cybernetics/control theory, which was applied physics initially—the radar-controlled antiaircraft gun being the paradigm for the field

      2 replies 0 retweets 6 likes
    6. Carlos E. Perez‏ @IntuitMachine 8 Oct 2019
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      Replying to @Meaningness @michael_nielsen

      This is the long forgotten connection. What happened was that the Dartmouth AI folk didn't invite Wiener because his approach was very different from emerging computer paradigm.

      2 replies 0 retweets 0 likes
    7. David Chapman‏ @Meaningness 8 Oct 2019
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      Replying to @IntuitMachine @michael_nielsen

      Right. And that antipathy led to the Minsky/Papert Perceptrons book, and then the standard histrionics takes over. But the mid-80s backprop people were very big on physics analogies, as I recall it, and that shaped the texture of the field.

      2 replies 0 retweets 1 like
    8. Carlos E. Perez‏ @IntuitMachine 8 Oct 2019
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      Replying to @Meaningness @michael_nielsen

      True. Hopfield was a physicist.

      1 reply 0 retweets 0 likes
    9. David Chapman‏ @Meaningness 8 Oct 2019
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      Replying to @IntuitMachine @michael_nielsen

      And the Boltzman machine was a big deal for about a year then.

      1 reply 0 retweets 0 likes
    10. Carlos E. Perez‏ @IntuitMachine 8 Oct 2019
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      Replying to @Meaningness @michael_nielsen

      Yes, without a doubt these are physics inspired models. They kicked started the deep learning field. But, few use these models anymore.

      1 reply 0 retweets 0 likes
      David Chapman‏ @Meaningness 8 Oct 2019
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      Replying to @IntuitMachine @michael_nielsen

      Yes; I understand and applaud your frustration that potentially relevant physical methods and intuitions are now being ignored.

      2:07 PM - 8 Oct 2019
      1 reply 0 retweets 0 likes
        1. New conversation
        2. Carlos E. Perez‏ @IntuitMachine 8 Oct 2019
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          Replying to @Meaningness @michael_nielsen

          Honestly, I am not sure if it's relevant anymore. We've entered the realm of massive computation and likely biology is more important than physics.

          2 replies 0 retweets 0 likes
        3. David Chapman‏ @Meaningness 8 Oct 2019
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          Replying to @IntuitMachine @michael_nielsen

          As in, neuroscience is a better source of analogies?

          1 reply 0 retweets 0 likes
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