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: AI Doesn't Always Need to Answer, Sometimes It Just Needs to Decide
Introduces TypeSafe AI's Jev model, contrasting it with the traditional LLM automation flow of generating text, parsing JSON, validating, and then deciding, highlighting that Jev can decide directly.
今日 AI｜Jev：AI 不一定要「回答」，有時只需要「做決定」 AI 不一定需要「回答你」，有時它只需要快速做一個決定。 TypeSafe AI 最近推出了一種很不一樣的模型：Jev。 一般 LLM 做自動化時，流程常常是： 輸入 → AI 生成文字 → 解析 JSON / 文字 → 驗證 → 才能做決定 Jev
· 0 likesOpen on X
More like this
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.
