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tonii141

HN member
Joined
Tue, Sep 17, 2024, 10:25 AM UTC
HN karma
20
Public activity
22 items

About tonii141

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Recent public activity

  1. comment
    Comment #45912269

    I just see a lot of people who’ve put money in the LLM basket and get scared by any reasonable comment about why LLMs aren’t almighty AGIs and may never be. Or maybe they are just …

  2. comment
    Comment #45899469

    I’m not demanding anything, I’m pointing out that performance tends to degrade as context scales, which follows from current LLM architectures as autoregressive models. In that sen…

  3. comment
    Comment #45898433

    a) That "no-tools" win depends on prompt orchestration which can still be categorized as tooling. b) Next-token training doesn’t magically grant inner long-horizon planners.. c) Lo…

  4. comment
    Comment #45898169

    a) Still true: vanilla LLMs can’t do math, they pattern-match unless you bolt on tools. b) Still true: next-token prediction isn’t planning. c) Still true: error accumulation is mi…

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  7. comment
    Comment #45567564

    Not true. AI has been around far longer than modern LLMs and has performed well in non-generative areas, often with orders of magnitude fewer parameters.

  8. comment
    Comment #45566998

    What do you mean by "they add instability"?

  9. comment
    Comment #45566748

    I agree, but maybe there is no need for billions of neurons to be simulated right away. Artificial neural networks were pretty small at the time.

  10. story
    Ask HN: Why doesn't AI use dynamical neurons instead of static activations?

    Why doesn’t AI use dynamical neurons instead of static activations even when it is known that biological neurons are dynamical systems?

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  12. comment
    Comment #45037044

    https://archive.is/lYTN8

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  15. comment
    Comment #44200079

    I have been involved in research focused on ML control for some time, and believe me, I would love to see an AI model capable of controlling arbitrary systems at different operatin…

  16. comment
    Comment #44189466

    Let's not forget that this works solely for this particular racing setup. If you change a single gate, the AI they are using would not be able to adapt. Still fascinating, though.

  17. comment
    Comment #44094936

    If the model uses FP16 precision and has 7 billion active parameters, it would require approximately 14 GB of VRAM. I didn't read the paper.

  18. comment
    Comment #44040217

    AI is used in scene understanding for those applications, but there is no neural network that is steering the wheel.

  19. comment
    Comment #44039066

    "they just totally failed to live up to expectation" Because the expectation was too high. If you are aiming for precision, neural networks might not be the best solution for you. …

  20. comment
    Comment #44038873

    This article addresses the misconception that arises when someone lacks a clear understanding of the underlying mathematics of neural networks and mistakenly believes they are a ma…

  21. comment
    Comment #41566212

    [flagged]

  22. comment
    Comment #41566196

    Random generator of tokens can also solve any problem if you give it enough time and memory.