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Jeff – Jev-compatible 0.8B decision models, trained at home, ~30 ms

575 points · 225 comments · firelex

  1. adrithmetiqa · · focus · HN ↗
    Forgive my lack of understanding but how long before Jev type functionality is just built straight into all frontier models?
    1. tbeseda · · focus · HN ↗
      If I had to guess, it's already built and is just waiting on Product's/Marketing's desk. How do you position this without looking like your roadmap is being determined by newcomers? Probably don't want to adopt the same verbiage+acronyms - but also can't be seen to be just sherlocking features.
      1. seizethecheese · · focus · HN ↗
        I think Apple has demonstrated that shipping second has essentially no negative impact if your product is seen as higher quality.
        1. bigyabai · · focus · HN ↗
          I think Nvidia has demonstrated that shipping first is a multi-trillion dollar opportunity if you don't shy away from a challenge.
          1. throwaway27448 · · focus · HN ↗
            Chip manufacturing intrinsically comes with one hell of a moat. There's not much parallel in software.
            1. slashdev · · focus · HN ↗
              That’s kind of funny because Nvidia’s biggest moat is arguably CUDA, the software ecosystem around their chips
              1. mcmcmc · · focus · HN ↗
                CUDA is a lock-in moat, the infrastructure needed for chip manufacturing is a barrier-to-entry moat. Two different things.
                1. angry_octet · · focus · HN ↗
                  There are many microarchitecture patents used in NVIDIA chips. I'm sure they have a team that rips apart AMD chips looking for infringement. The way CUDA works is tied to many GPU architecture decisions and it would be hard to decouple them efficiently. Obviously a huge effort was made to get PyTorch decoupled from CUDA.
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