Birbla

Join the discussion

Write your take first — we'll ask for email only when you're ready to publish.

Sign in
  • Hacker News
  • I've been vibecoding an open source hardware AV1 decoder: https://github.com/Jonahss/openav1
    by jonahss
  • Opened the RTL, looked at the floating point math, learned that apparently you don't need correct floating point operations for LLMs, closed the page.
    by random__duck
  • I feel like there is a lot to be gained from an experienced user pointing an LLM in a tasteful direction.
    by vatsachak
  • "Recursive self-improvement will kill us all!"

    Also: Here is our recursive self-improvement hard at work...

    by xg15
  • After using AI to develop risc-v CPU cores, the same technique was used for developing openTPU. An open source AI inference engine. It's able to run most of the modern models like Qwen 3.5, Gemma 4, and many others. The TPU started able to produce only a few tokens per second and trough a recursive self improvement loop got to 80+ tok/sec on the smallers models.
    by fsbonetto
  • I haven't really dug into the results yet, but my guess is that a SOTA model has been able to produce an accelerator that runs a model since around December.

    The obvious next step is to get enough memory throughput to run that SOTA model itself so that it develop its own hardware.

    But perhaps the more interesting question is this: Can an AI be given a big FPGA and design a model architecture that takes advantage of the fabric being reconfigurable.

    by athrowaway3z
  • Well, as long as it doesn't start developing anatomically accurate metal skeletons with red glowing eyes...
    by rcarmo
  • Really dumb question from a software guy. Why aren't the labs burning their frontier models into chips already? Seems like the performance gains and cost per request would be worth it. That said, I understand neither the economics nor the physical challenges to doing this.
    by pcarolan

Explore Birbla archives