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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. Ohentis · · focus · HN ↗
      I don't think there would be any utility for that. Anything jev can do, a frontier model can also do. Just not as quickly or as cheaply.
      1. tbeseda · · focus · HN ↗
        I think these products (Jev and the inevitable offerings from Anthropic, OpenAI, etc) want to become more than end-user output machines. They'd benefit from being in the hotpath of other services. Not backgrounded generation but in-band, request-time work.

        1M x $0.50 == 1B x $0.0005

        1. transitorykris · · focus · HN ↗
          To expand a bit for my current use cases. Inline routing of work to heavy task specific models, and prompt/context generation (user is asking something, what and how much should we prompt the expensive LLM with). Latency or time to first token does matter for some applications.
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