Jev versus text-generating models
Jev does not generate free-form text. A side-by-side video compares parallel decision-making with token-by-token text generation.
How to Evaluate Jev's Accuracy
Discusses that while Jev cannot invent answers outside a predefined schema, it can still choose wrong answers within it, sometimes with high confidence, and raises evaluation questions for low-stakes scenarios.
Jev is cool, but the question I’ve heard most over the past few days is: how do we evaluate its accuracy? 🤔 Jev cannot invent an answer outside a predefined schema, but it still can choose the wrong answer within it, sometimes even with high confidence. For low-stakes,
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This model is built for decision-making rather than text generation, outputting probabilities for each option in parallel instead of token-by-token responses. The author shares a simplified comparison of normal LLMs versus this Jev model.
