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Jev: A Different Approach to AI Decision-Making

Jev: A Different Approach to AI Decision-Making For the last few years, much of the AI ecosystem has focused on making language models better at generating and understanding language . We built increasingly capable autoregressive models that generate text token by token. We added reasoning capabili…

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  1. 2026-09-24 17:14 · DEV Community — Machine Learning
    Jev: A Different Approach to AI Decision-Making

More stories

  1. notjev – Turn any local LLM into a Jev-style decision engine (one token + logprobs) — r/LocalLLM
  2. A Coding Guide to TypeSafe AI Jev: Typed Decisions, Calibrated Confidence, and Speculative Fan-Out with a System One Model — MarkTechPost
  3. How to train your own Jev for $17 — Together AI Blog
  4. Trained a per-task head on top of convaiinnovations/laya (frozen encoder) and served it behind the Jev API: 38% zero-shot on 77 intents is fixable with your own rows — r/huggingface
  5. stuntd: a local Jev-compatible server on Laya that learns from your own traffic (no API key needed) — r/LocalLLaMA
  6. Jev's calibration was measured. The LLMs won [D] — r/MachineLearning
  7. I built an open-weight alternative to Jev / TypeSafe - introducing OpenJudgement-4B (early preview) — r/LocalLLaMA
  8. An Introduction to Jev — Towards Data Science

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