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Constrained Decoding

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TypeSafe AI launches Jev, a model built to output typed, scored decisions

TypeSafe AI has released Jev, a model designed to convert natural-language input and application state directly into typed decisions, returning choices, scores and probabilities as JSON. The company says Jev uses a new architecture, a parallel sampler, and a training method called Reinforcement Learning for Calibrated Decisions to generate probabilities without token-by-token generation. TypeSafe reports significant speed and cost improvements over general-purpose LLMs for decision-making workflows.