Original Summary

I made typesafeAI's new model Jev play Minecraft after i saw how well it played doom in the demo. Jev completely bypasses traditional LLMs text generation that makes it so much capable at the fraction of cost and time. How it works: I use mineflayer library to setup a bot that join a minecraft world (local or server). It gets a game state in the form of a json with things like : State: health, food, hostiles, position, time, goal This state gets sent to Jev every 600ms. Jev doesn't generate text — it returns typed probabilistic decisions. I ask it 4 questions in parallel per tick: Threat level? (Score: Safe → Critical, 5 levels) 2. What to do? (Choice: fight / flee / eat / continue_goal / look_around) 3. Should I eat? (Noul: yes/no probability) 4. Which way to flee? (Choice: north/south/east/west) All 4 run in one API call. Jev returns probabilities + confidence for each, and the code acts on whichever passes the confidence threshold. Low confidence = safe fallback. The interesting part — it has emotions: The bot tracks fear, satisfaction, curiosity, and urgency as 0-1 floats. Taking damage spikes fear. Completing a goal boosts satisfaction. Sitting idle builds curiosity. Night without shelter raises urgency. These flow into every Jev question, so a scared bot flees more, a curious bot explores more. What Jev is NOT doing: It doesn't see the screen. No screenshots, no vision model. Mineflayer gives structured game data and Jev makes decisions on that. It also doesn't generate any text or do any "reasoning" — it's pure fast probabilistic judgments, which is what makes it work at 600ms per tick . Limitations: The physical actions (mine, place, craft) are still coded sequences. Jev decides WHAT to do but not HOW. If I coded a bad mining sequence, Jev can't fix it. Also it's not amazing — it survives, gathers resources, crafts tools, but it's not speedrunning. Think of it as an AI that plays like someone's first day in Minecraft. https://github.com/akash-kamat/jev-craft feel free to contribute and make it better. Please share your thoughts   submitted by   /u/dwarfLevi [link]   [comments]

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/20 11:30:52