Karina Nguyen 借 Revolut 迁移案例称企业应把自己变成巨型 RL 环境

Karina· @karinanguyen · X·2026-11-04 03:08· 20 分钟前AI 评分68

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Karina Nguyen 转发并评论 Revolut 将约 2000 名工程师迁到自托管 GLM 编码、把 Claude Code 和 Cod列入例外清单的消息，称每家公司都应把自己变成巨型 RL 环境，构建从每次交互中学习并逐步接管公司运营的自我改进 AI。引用内容称其用 56 块 Nvidia B200 跑出每百万 token 约 30 美分的混合成本，约为此前付给 Anthropic 和 OpenAI 的十分之一，工程交付周期缩短 70%。

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every company should turn itself into a giant RL env, building self-improving AI that learns from every interaction and progressively starts running the company itself

引用Guillermo Flor@guilleflorvs

BREAKING: Revolut moved ~2,000 engineers onto self-hosted GLM for coding and pushed Claude Code and Codex to the exception list. Per David Abitbol, who leads AI ops there: 56 Nvidia B200s, a blended 30 cents per million tokens, roughly a tenth of what they paid Anthropic and OpenAI. Engineering lead time improved 70%. Here's the part that matters: the gains showed up when tokens stopped being rationed. Engineers quit saving AI for the hard tickets and pointed it at everything. Frontier models become the exception, open weights become the default. That's a pricing problem for every lab heading to IPO. h/t @OliverMolander Would you move your team off frontier APIs if the bill dropped 90%?

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来源：Karina · x.com

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