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How OpenAI Used Its Own LLMs to Design Its Jalapeño Chip

206 points · 139 comments · maxall4

  1. pama · · focus · HN ↗
    Having worked with people doing bringup of specialized chips, I am awed at how the world has changed.

    > When the first chips came back from the foundry in May, the team pointed its internal AI models at designing software to run benchmarks such as SemiAnalysis’s InferenceX. On DeepSeek’s multi-head latent attention kernel benchmark, performance climbed from 0.31 percent of the theoretical ceiling (set by the chip’s compute and memory bandwidth) to 88.94 percent in roughly 40 hours. Ho says this result is repeatable, so the time between when foundries deliver the first chips and when production ramps up can be reduced. “All our schedule assumptions are going to be based on the fact we have this capability now,” he says.

    1. wmf · · focus · HN ↗
      Back in the day you'd write the code before the chip came back but I guess today it's faster to wait.
      1. LoganDark · · focus · HN ↗
        Back when teams proved their designs and actually understood them...
        1. RussianBot9580 · · focus · HN ↗
          Haha - understood. Good one!

          They'd write a limited test for a feature based on an ask from the software team garbled by a five layer game of telephone. Claim that the module passed validation. A few months later the software folks would have to pull a few all nighters to figure out how to work around the resulting turd during bringup.

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