ChatGPT co-inventor's startup launches Jev, a decision model claiming ultra-low hallucination
hardimanjames · x · 2026-09-16
A retweet reacting to Jev, a new model from Diogo Almeida (one of the researchers behind the instruction-following work that led to ChatGPT). Instead of autoregressive token generation, Jev maps unstructured state to type-safe probabilistic decisions in parallel, using a new RLCD training method to calibrate confidence. Claims: up to 194x faster and 445x cheaper on workflow evals, $0.042 per million input tokens with free output, competitive with frontier models on System One tasks — though not a replacement for general reasoning models.
Related event: TypeSafe exits stealth with decision model Jev and RLCD training method(86 posts)→
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