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AdamMarblestone's profile
Adam Marblestone
Adam Marblestone
Adam Marblestone
@AdamMarblestone

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Adam Marblestone

@AdamMarblestone

Technologist, Scientist

adammarblestone.org
Joined February 2009

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    1. Adam Marblestone‏ @AdamMarblestone 26 Dec 2019
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      This is a cool way to build highly specific prior knowledge into neural nets: via highly specific loss functions https://arxiv.org/abs/1609.05566  Don’t just maximize likelihood of the data or predict the next frame—build all the constraints you can know into the loss and make NN satisfy.

      1 reply 30 retweets 154 likes
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    2. Adam Marblestone‏ @AdamMarblestone 26 Dec 2019
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      Adam Marblestone Retweeted jovo

      Related to this conjecture: @neuro_datahttps://mobile.twitter.com/neuro_data/status/1204038229273518083 …

      Adam Marblestone added,

      jovo @neuro_data
      Replying to @AdamMarblestone @tyrell_turing and 3 others
      yes, exactly that it seems! i should have known jascha already wrote this down :)
      1 reply 0 retweets 2 likes
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    3. Adam Marblestone‏ @AdamMarblestone 26 Dec 2019
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      This is also what @KordingLab and Greg and I meant with highly specific evolutionarily programmed “bootstrap cost functions” being the things brain would optimize if it does some powerful online optimization during organism lifetime a la DL

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    4. Adam Marblestone‏ @AdamMarblestone 26 Dec 2019
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      I think it is also obvious to @tyrell_turing that this is the level of specificity of loss function evolution could build in for brain to optimize, if it “does DL” — things like this, but specific to brain area and developmental stage, and specific animal’s ethological needs

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    5. Adam Marblestone‏ @AdamMarblestone 26 Dec 2019
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      When one speculates about brain as some kind of DL type system, it does not mean having architecture or loss function similar to current systems: to me, it means a) powerful optimization alg. on during organism lifetime + b) many highly specific evolved loss fxn recipes like this

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    6. michael_nielsen‏ @michael_nielsen 26 Dec 2019
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      Replying to @AdamMarblestone @tyrell_turing

      GANs, of course, are all about learning incredibly specific loss functions.

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      Adam Marblestone‏ @AdamMarblestone 26 Dec 2019
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      Replying to @michael_nielsen @tyrell_turing

      Very much so, and indeed they followed up the above with https://arxiv.org/abs/1805.10561  which uses something like a GAN to learn these types of constraints, like from a simulator that obeys physics we want our NN trained on real movies to respect

      12:32 PM - 26 Dec 2019
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        1. Adam Marblestone‏ @AdamMarblestone 26 Dec 2019
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          Replying to @AdamMarblestone @michael_nielsen @tyrell_turing

          Although for the case of using this as a (crappy) conceptual model of what/how the brain could learn, evolution serves as the outer loop that builds these losses

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