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.
JEV (System-1) called one of the freshest concepts in recent months
The author argues JEV (System-1) will change a great deal, noting current LLMs simulate System-2, and calls the JEV implementation one of the freshest concepts of recent months—seemingly just a dynamic classifier yet surprising.
Models like JEV (System-1) will, in my opinion, change a great deal. Current LLM models simulate System-2. For me, the implementation of JEV is one of the freshest concepts of the recent months. It seems like nothing particularly special (dynamic classifier) yet it's surprising
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Pricing, evaluations, and the name Jev
The launch thread explains code-and-AI workflow evaluations, the input price announced at launch, and free output tokens.
Jev Model: Decision-Making Probability Generation, 200× Faster and 400× Cheaper Than LLMs
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.
