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Plinz's profile
Joscha Bach
Joscha Bach
Joscha Bach
@Plinz

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Joscha Bach

@Plinz

FOLLOWS YOU. Artificial Intelligence, Cognitive Architectures, Computation. The goal is integrity, not conformity.

San Francisco, CA
bach.ai
Joined April 2009

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    1. Edward Grefenstette‏ @egrefen 1 Jun 2018
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      Replying to @egrefen @timkindberg and

      Don't get me wrong: it's great that people are pointing these things out and testing the limits of DL. But it's good to form a balanced view. Things aren't as black and white as "omg neural nets can do everything" vs "omg here's one failure mode let's ditch it all" 😛

      1 reply 0 retweets 15 likes
    2. Gary Marcus‏ @GaryMarcus 1 Jun 2018
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      Replying to @egrefen @timkindberg @filippie509

      Agree w @egrefen here, too, but find that no matter how hard I advocate for hybrid models people always think I am arguing against all of ML... I think ML will play a huge role in AGI, but only w proper biases, including representations of operations over variables.

      2 replies 1 retweet 12 likes
    3. Shlomo Engelson Argamon‏ @ShlomoArgamon 1 Jun 2018
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      Replying to @GaryMarcus @egrefen and

      Properly understood, #MachineLearning is the study of the relationship of biases to what can be learned with each (and how to implement them computationally). It's bias, all the way down.

      1 reply 1 retweet 8 likes
    4. Gary Marcus‏ @GaryMarcus 1 Jun 2018
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      Replying to @ShlomoArgamon @egrefen and

      and yet innateness is a dirty word in ML. amazing.

      1 reply 1 retweet 2 likes
    5. Thomas G. Dietterich‏ @tdietterich 1 Jun 2018
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      Replying to @gchrupala @GaryMarcus and

      Gary, are you really arguing that anything you can't get your ML algorithm to do, you can just build in and declare it to be "innate". It is totally ad hoc science to rely on innateness to solve your machine learning problems.

      5 replies 0 retweets 2 likes
    6. Joscha Bach‏ @Plinz 1 Jun 2018
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      Replying to @tdietterich @gchrupala and

      Gary seems to think that nature's evolutionary search has resulted in parameters that cannot be found by any artificial search. The idea is so obviously flawed that it may be driven by motivated reasoning, i.e. an identification with a particular perspective rather than insight.

      2 replies 0 retweets 1 like
    7. Tim Kindberg‏ @timkindberg 1 Jun 2018
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      Replying to @Plinz @tdietterich and

      Parameters? Evolution has built a *system*. In what space does one 'artificially search' for one of those?

      2 replies 0 retweets 2 likes
    8. Joscha Bach‏ @Plinz 1 Jun 2018
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      Replying to @timkindberg @tdietterich and

      A system is a machine that can be described by a single global transition function (if the function changes you have a different system). Building a system amounts to traversing the implementation space of transition functions. There is no magic boundary between biology and comp

      1 reply 0 retweets 0 likes
    9. Tim Kindberg‏ @timkindberg 1 Jun 2018
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      Replying to @Plinz @tdietterich and

      Actually a system is an arbitrary concurrent, interactive union of what you describe, including nondeterminism. You're going to search in that space?

      2 replies 0 retweets 0 likes
      Joscha Bach‏ @Plinz 1 Jun 2018
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      Replying to @timkindberg @tdietterich and

      To the degree to which a system exists, it must be implemented. Understood like this, a system can be described by its source code, i.e. as a computable function. (Nondeterminism is not a challenge to this.)

      3:13 PM - 1 Jun 2018
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      • Gary Marcus
      0 replies 0 retweets 1 like

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