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TypeSafe AI 发布 Jev：不生成文本的 Transformer 模型，主打低成本决策
TypeSafe AI 推出名为 Jev 的 Transformer 模型，不走 LLM 文本生成路线，而是输出概率并提供“校准决策”服务，面向软件自动化。创始人 Diogo Almeida 曾是 OpenAI 研究者并参与 RLHF 技术。Jev 不生成文本，输出 token 免费、输入按十亿 token 计费。开发者测试称，Vercel 用 Jev 替换 OpenAI 模型做命令安全分类，速度提升 5 至 18 倍且准确率更高；Bryo AI 测试中 Jev 准确率略低于 Gemini，但成本低 10 至 20 倍。
AI推荐理由 TypeSafe AI 由前 OpenAI 参与 RLHF 的研究者 Diogo Almeida 创立，发布不生成文本、只输出概率的 Transformer 模型 Jev，定位软件自动化中的低成本决策与校准输出，避开 LLM 的幻觉与冗余生成成本。文中给出开发者测试：Vercel 用 Jev 替换 OpenAI 模型做命令安全分类，速度提升 5 至 18 倍且准确率更高；Bryo AI 测试中 Jev 准确率略低于 Gemini，但成本低 10 至 20 倍。新信息在于非生成式 Transformer 的定价与决策场景，局限是来源为 AIbase 转述、缺少论文或官方基准，测试数据为开发者自述，需谨慎看待。
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TypeSafe AI Launches Jev: A Transformer Model That Does Not Generate Text, Focused on Low-Cost Decision Making
AIbase基地
Published inAI News · 2 min read · Sep 20, 2026
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TypeSafe AI has released a new Transformer model called Jev, attempting to bypass the text generation paradigm of large language models (LLMs), offering probabilistic outputs and "calibrated decision" services for software automation. Diogo Almeida, a former researcher at OpenAI and participant in RLHF technology, founded TypeSafe AI two years ago after leaving OpenAI. He believes that optimizing models around human language is not suitable for computer automation scenarios.
Jev does not generate text but instead outputs probabilities, thus avoiding the hallucination and redundant generation costs of traditional LLMs. Its output tokens are free, while input is billed by the billion tokens. Developer tests show that Vercel improved speed 5 to 18 times and achieved higher accuracy by replacing OpenAI models with Jev for command security classification; in Bryo AI's test, Jev's accuracy was slightly lower than Gemini, but the cost was 10 to 20 times lower.
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