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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. Joscha Bach‏ @Plinz 2 Dec 2017
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      On a positive note, I am optimistic that near term AI technology will mostly obliterate bullshit jobs (transport, retail, packaging), while making the services of experts dramatically better and affordable. There will be a lot more quality jobs, including entirely new professions

      9 replies 2 retweets 19 likes
    2. Justin Scholz‏ @JMoVS 2 Dec 2017
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      Replying to @Plinz

      Do you think we’ll create a self-improving AI that is self-improving in a more than linear pace?

      1 reply 0 retweets 0 likes
    3. Joscha Bach‏ @Plinz 2 Dec 2017
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      Replying to @JMoVS

      I don't know how to put any probability estimates on it, but self improving AI is quite certainly possible, and a sigmoid is the default pattern one would expect, no?

      1 reply 0 retweets 0 likes
    4. Justin Scholz‏ @JMoVS 2 Dec 2017
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      Replying to @Plinz

      Most technology adoption happens in sigmoid fashion as @asymco shows again and again. But what I wonder is if we’re really up to sth or in some dead-end street regarding neural networks…

      1 reply 0 retweets 0 likes
    5. Joscha Bach‏ @Plinz 2 Dec 2017
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      Replying to @JMoVS @asymco

      Convnets and stochastic gradient descent are probably not the right answer. But it might be that meta learning breakthroughs, new ways of adaptive credit assignment, autocompositional reward optimizer networks, or function agnostic Gibbs samplers are just around the corner?

      2 replies 0 retweets 5 likes
    6. David Kedmey‏ @DKedmey 3 Dec 2017
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      Replying to @Plinz @JMoVS @asymco

      What if you let nodes in the neural net grow connections to any other node, rather than just change the weights of pre-existing connections? And also the ability to add nodes and layers? Along with some (flexible) criteria to judge success of the model.

      1 reply 0 retweets 0 likes
    7. Justin Scholz‏ @JMoVS 3 Dec 2017
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      Replying to @DKedmey @Plinz @asymco

      I’m not that deep into the field yet, but has there been some experimentation with multi-dimensional neural networks? All I’ve seen were linear NN that were able to be represented in a 2D-fashion

      1 reply 0 retweets 0 likes
    8. Joscha Bach‏ @Plinz 3 Dec 2017
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      Replying to @JMoVS @DKedmey @asymco

      Almost all approaches deal with high dimensional spaces, by reducing a very high dimensional space of input values to a smaller set of dimensions. https://www.quora.com/How-could-artificial-intelligence-work-to-understand-perspective-i-e-our-3-dimensions/answer/Joscha-Bach-1?__filter__&__nsrc__=2&__snid3__=1757276987 …

      2 replies 0 retweets 0 likes
    9. Justin Scholz‏ @JMoVS 4 Dec 2017
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      Replying to @Plinz @DKedmey @asymco

      maybe I’m misunderstanding your point - what I have in mind is this graph with different layers, but in all the representations I’ve seen, there are only ever 2 layers connected to each other. They seem to never be cross-connected.

      1 reply 0 retweets 0 likes
      Joscha Bach‏ @Plinz 4 Dec 2017
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      Replying to @JMoVS @DKedmey @asymco

      Recurrent networks are currently harder to train, but some types (like LSTMs) are quite popular. But that is unrelated to 3d.

      12:45 AM - 4 Dec 2017
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      • Justin Scholz
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