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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. TTIVanguard‏ @TTIVanguard 12 Jun 2018
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      Deep learning is just another way of doing statistics. -it makes strong assumption -you have large amounts of data -classifying into categories. -test data aren't far from training examples @GaryMarcus #ttiintelligencepic.twitter.com/7xcFRNE3NI

      4 replies 6 retweets 20 likes
    2. Joscha Bach‏ @Plinz 12 Jun 2018
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      Replying to @TTIVanguard @GaryMarcus

      Cognition is also just another way of doing statistics

      1 reply 1 retweet 0 likes
    3. Gary Marcus‏ @GaryMarcus 12 Jun 2018
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      Replying to @Plinz @TTIVanguard

      doing statistics is just one (important) aspect of cognition. at other extreme, would you call formal logic statistics?

      2 replies 0 retweets 1 like
    4. Rebel Science‏ @RebelScience 12 Jun 2018
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      Replying to @GaryMarcus @Plinz @TTIVanguard

      Ha! Statistics has absolutely nothing to do with cognition. As Judea Pearl once correctly said, people are not probability thinkers but cause-effect thinkers. The brain uses a winner-take-all method to handle uncertainty.https://medium.com/@RebelScience/the-brain-is-not-probabilistic-82ac88e0a3bf …

      1 reply 0 retweets 0 likes
    5. Nick‏ @NickRhymesWitMc 12 Jun 2018
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      Replying to @RebelScience @GaryMarcus and

      I disagree here. I think the brain uses probabilistic assumptions. I believe nested sampling would work best as the Monte Carlo Markov Chain Method, which in cognitive psychology is the assumed method of the brain.

      1 reply 0 retweets 0 likes
    6. Rebel Science‏ @RebelScience 12 Jun 2018
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      Replying to @NickRhymesWitMc @GaryMarcus and

      Well, I will not argue my point further other than to say this: none of us see 1%, 15% or 90% cow. It's either cow or no cow.

      2 replies 0 retweets 2 likes
    7. Joscha Bach‏ @Plinz 12 Jun 2018
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      Replying to @RebelScience @NickRhymesWitMc and

      If you imagine or perceive a cow, you will have to represent a superpositional state that approximates probabilities. But when you access that representation for reasoning or prediction, you will get a collapsed version (because a probability cloud shaped cow is very unlikely).

      1 reply 0 retweets 0 likes
    8. Rebel Science‏ @RebelScience 12 Jun 2018
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      Replying to @Plinz @NickRhymesWitMc and

      It's impossible to represent every possible cow in memory seen from different angles because the number is infinite. We only maintain high level bits of what a cow looks like. And yet we can recognize a cow image mixed with > 90% noise. And when we do, we are 100% certain.

      1 reply 0 retweets 0 likes
      Joscha Bach‏ @Plinz 12 Jun 2018
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      Replying to @RebelScience @NickRhymesWitMc and

      We can represent the angle as indeterminate. If you need to reason about the cow, you generate it with a definite angle but put low confidence on it, so the angle is not clamped down and can be regenerated if the constraints change.

      8:54 PM - 12 Jun 2018 from Davis Square, Somerville
      1 reply 0 retweets 0 likes
        1. Joscha Bach‏ @Plinz 12 Jun 2018
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          Replying to @Plinz @RebelScience and

          Other representations use multiple alternative prototypes to cover the feature space. What fools you is that attentional access uses lateral inhibition to collapse it into one.

          0 replies 0 retweets 0 likes
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