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 Suits Domain Problem Solving: Better Combined with Logic and LLMs
The post shares many Jev ideas and notes that Jev suits domain problem solving, working better combined with logic-based approaches and LLMs than alone.
ここで大量のJevアイデアが公開中 https://render.qmuse.pub/p/muse/8079593307628562/index.html… Jevはドメイン問題解決に適している 単体でどうかというより、ロジックベース、LLM等様々に組み合わせて大きな効果を発揮するかと #JEV #AI
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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.
