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

575 points · 225 comments · firelex

hadlock · 1790654014 · focus · HN ↗
If you're looking for a more impressive doom example, I put together laya-duum which uses open source micropython implementation of doom (duum) and freeware freedoom1.wad. It uses the standard jev api and will play through the first two levels to completion: <a href="https://github.com/Hadlock/laya-duum" rel="nofollow">https://github.com/Hadlock/laya-duum
1. antman · 1790667634 · focus · HN ↗
  - Laya receives semantic snapshots, not the framebuffer.
  What does tjis mean? Another generative model?
  1. ovi256 · 1790676660 · focus · HN ↗
    Laya is the model this uses. Like Jev, it's blind - it can't take an image as an input. So how can it play Doom, or Atari games, or do other visual tasks, as people have shown it to do? They write a bit of app-specific adapter code that transforms the game state into a structured piece of data (here, the "semantic snapshot"). And that is what these models take as input

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