TypeSafe launches Jev: a 20-200x faster, 40-400x cheaper model that turns fuzzy questions into probabilities
danshipper · x · 2026-09-16
TypeSafe, a new lab from an InstructGPT/ChatGPT co-inventor, launched Jev, a model that answers plain-English questions—including fuzzy ones—with probabilities or category scores instead of text, acting like a smart if-then statement for automated workflows.
- Claimed 20-200x faster and 40-400x cheaper than chat models, with output tokens free
- Built on a new training method called RLCD; aimed at routing, invoice matching, fraud classification, and checking agent output in real time
- Every's Mike Taylor's vibe check: Jev judged an article in 0.7 seconds, cheap and fast enough to verify agent work inline
The team frames it as the shortest path to AI-driven economic revolution.
Related event: TypeSafe exits stealth with decision model Jev and RLCD training method(86 posts)→
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