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Introducing System One Models and Jev

1989 points · 520 comments · albelfio

  1. jacobgold · · focus · HN ↗
    First, congrats to the team on launching something genuinely interesting and new.

    Seems like a more accurate title would be "Jev: Trading general purpose generation for fast typed inference" or something like that.

    This is interesting, but the speed comparison seems misleading? A generative model that can output code in a Turing-complete language can do anything a computer can do.

    Jev can only generate structured output, right? This is probably super useful for classification/routing/scoring, but it's nothing like the code generating models we're all using today for code and automation.

    Also "can't hallucinate" seems wrong? Sure, it can't emit an invalid type, but it can still emit a completely wrong valid value. You can enforce structured output from an LLM too, with an appropriate harness, etc.

    Assuming there's no funny business, the Doom demo is cool.

    1. hdjrudni · · focus · HN ↗
      > Assuming there's no funny business, the Doom demo is cool.

      The Doom demo seems very funny business. They're not feeding it video, they're feeding it a text description of what's going on in the game. It's not reading pixel data.

      I think LLMs would play a lot better with that input too but Jev does seem to have a huge speed advantage; I don't know if the other models could do that in real-time.

      1. headgasket · · focus · HN ↗
        I'be interested to see how they get doom frame json representation...
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