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suryabhupa

HN member
Joined
Fri, Jun 12, 2015, 8:18 PM UTC
HN karma
53
Public activity
20 items

About suryabhupa

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Recent public activity

  1. comment
    Comment #40812058

    In practice, and at scale, that's exactly what having and tokens allow you to easily and programmatically do.

  2. comment
    Comment #40812044

    The announcements are live on Twitter! See this for example: https://x.com/suryabhupa/status/1806342617191379167

  3. comment
    Comment #40812031

    Surya here from the core Gemma team -- we can think of a distillation loss as learning to model the entire distribution of tokens that are likely to follow the prefix thus far, ins…

  4. comment
    Comment #28687050

    This is really remarkable! How hard do you think it will be to support new models, i.e. does the tooling you’ve built generalize to you being able to serve other large scale models…

  5. comment
    Comment #18618257

    Hi everyone! One of the creators of DFL here. In an attempt to more deeply understand fundamental concepts in machine learning, we designed Depth First Learning. It's a pedagogy fo…

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  8. comment
    Comment #14851488

    Many machine learning and reinforcement learning models are susceptible to adversarial attacks; it's not unique to deep learning. However, because so many systems that are currentl…

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  10. comment
    Comment #14173296

    There are talks of incorporating this into Excel at some point in the future, but it may take a _while_ before it can be fully productionized.

  11. comment
    Comment #14173292

    That would be pretty cool to see what it learns, but I don't think we've tried that :P

  12. comment
    Comment #14173289

    That's one manifestation of this kind of research being used in real life by programmers around the world. :)

  13. comment
    Comment #14173284

    I'm not too familiar with evolutionary computation methods, but I imagine the approaches may be similar in nature.

  14. comment
    Comment #14173273

    Theorem solving is very closely related to program induction (we just change the grammar). Just as with Python, the underlying search space would be incredibly large, and while in …

  15. comment
    Comment #14173260

    It turns out the full grammar of Python (and almost all real programming languages) is quite large; this is very early and new work in neural program synthesis, and so we chose a p…

  16. comment
    Comment #14173258

    Eventually, yes.

  17. comment
    Comment #14168221

    One of the authors here -- would love to answer any questions about the work! :)

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    Comment #12954462

    How do you imagine going about this?

  20. comment
    Comment #11273446

    The idea is that even there's a policy network that is able to decide at some point what the best possible move is, the tree search is done to refine this choice and to "evaluate" …