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idiliv

HN member
Joined
Wed, Oct 25, 2017, 5:30 PM UTC
HN karma
228
Public activity
60 items

About idiliv

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Recent public activity

  1. comment
    Comment #48388204

    Uber is likely on an enterprise plan - these charge tokens at API cost, which can be much more expensive than the $20 flat rate.

  2. comment
    Comment #46680228

    Sometimes model developers coordinate with inference platforms to time releases in sync.

  3. story
  4. comment
    Comment #43188925

    Wait, but we're doing that already, and it works well (Qwen 2.5 VL)? If need be, you can always resort to structured generation to enforce schema conformity?

  5. comment
    Comment #41890412

    Duplicate, posted on October 9: https://news.ycombinator.com/item?id=41784591

  6. comment
    Comment #41650115

    Where do you see the MMLU-Pro evaluation for Llama 3.2 90B? On the link I only see Llama 3.2 90B evaluated against multimodal benchmarks.

  7. comment
    Comment #41626977

    Is the "Ultra Deep" analysis worth it over the standard "Deep" analysis?

  8. comment
    Comment #41523892

    In the demo, O1 implements an incorrect version of the "squirrel finder" game? The instructions state that the squirrel icon should spawn after three seconds, yet it spawns immedia…

  9. story
  10. comment
    Comment #40678642

    How are flexible working hours equivalent to more money?

  11. comment
    Comment #40668538

    You can rent them online for ~ 4-5 $ per hour per GPU. Not cheap, but definitely feasible as a weekend project.

  12. comment
    Comment #39995200

    Just tried this again and I also arrive at 16.92B. Not sure what I did wrong the first time, thanks for double-checking this!

  13. comment
    Comment #39988119

    Oh, and to answer your actual question: Assuming that the model is released with 16 bits per parameter, then it as 281GB / 16 bit = 140.5 parameters.

  14. comment
    Comment #39988103

    In Mixtral 8x7B, the 8 means that the model uses Mixture-of-Experts (MoE) layers with 8 experts. The 7B means that if you were to remove 7 of the 8 experts in each layer, then you …

  15. comment
    Comment #39446232

    Hi Martin! It's Robert from Cambridge (you were my DOS :)). Glad to see your name pop up on HN!

  16. comment
    Comment #39387009

    People here seem mostly impressed by the high resolution of these examples. Based on my experience doing research on Stable Diffusion, scaling up the resolution is the conceptually…

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  18. comment
    Comment #39070274

    Hmm, are you sure that translations of LLMs like ChatGPT are not incorporating cultural context?

  19. comment
    Comment #39017632

    I'm curious how they evaluated model quality. The only information I could find is "Quality: Index based on several quality benchmarks".

  20. comment
    Comment #38761482

    They could join Mistral AI, which has published weights for at least some of its models. Another option is Meta AI, which has published weights for Llama and Llama 2.

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  22. comment
    Comment #38531645

    Parent post is talking about LLMs, i.e. Large LMs. Research on LLMs is indeed in its infancy.

  23. comment
    Comment #38488970

    When I try out the topics you suggest at the huggingface endpoint you link, the answer is either my question translated into Chinese, or no answer when I prompt the model in Chines…

  24. comment
    Comment #38486127

    I've tried out DeepSeek on deepseek.com and it refuses conversations about several topics censored in China (Tiananmen, Xi Jinping as Winnieh-the-Pooh). Has anyone tried if this al…

  25. comment
    Comment #38451613

    "Each atomic step would normally take over 5,000 CPU hours on a supercomputer. Now, we can do the same calculation in 2 milliseconds on a desktop," Is this phrase equivalent to "Ea…