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Jev vs. LLMs: When AI moves from Generation to Decision-making

I tested TypeSafe AI’s Jev on 3,080 classification tasks to see how its accuracy, latency, calibration, and confidence compare with LLMs — and whether it works as a practical decision layer for AI systems. The post Jev vs. LLMs: When AI moves from Generation to Decision-making appeared first on Tow…

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  1. 2026-09-25 11:00 · Towards Data Science
    Jev vs. LLMs: When AI moves from Generation to Decision-making

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  1. A Coding Guide to TypeSafe AI Jev: Typed Decisions, Calibrated Confidence, and Speculative Fan-Out with a System One Model — MarkTechPost
  2. How to train your own Jev for $17 — Together AI Blog
  3. OpenAI, Anthropic cut AI model costs as price-performance race intensifies — InfoWorld AI
  4. New frontier AI models, TypeSafe’s Jev AI, & NASA’s IBM collab — Mixture of Experts (IBM)
  5. Jev, an AI Model That Can’t Chat, Takes On Bigger Rivals — Bloomberg AI
  6. 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
  7. stuntd: a local Jev-compatible server on Laya that learns from your own traffic (no API key needed) — r/LocalLLaMA
  8. notjev – Turn any local LLM into a Jev-style decision engine (one token + logprobs) — r/LocalLLM

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