Dwarkesh 对谈 OpenAI Noam Brown:Agent 集群、对齐与递归自我改进
Dwarkesh Patel 与 OpenAI 研究员 Noam Brown 对谈,涉及用 1 万个 AI Agent、1300 亿 token、88 小时求解 Navier-Stokes 千禧年大奖问题的工作。
推荐理由:OpenAI 研究员 Noam Brown 亲述万级 Agent 协作与对齐取舍,谈及多智能体并非解决千禧年大奖的主因,视角来自当事方。
模型推理能力的进展:思维链、推理模型、数学与逻辑基准的突破与争议。
当前仅显示精选新闻Dwarkesh Patel 与 OpenAI 研究员 Noam Brown 对谈,涉及用 1 万个 AI Agent、1300 亿 token、88 小时求解 Navier-Stokes 千禧年大奖问题的工作。
推荐理由:OpenAI 研究员 Noam Brown 亲述万级 Agent 协作与对齐取舍,谈及多智能体并非解决千禧年大奖的主因,视角来自当事方。
陶哲轩联合25位菲尔兹奖得主发布题为《数学领域中人工智能的严重失衡》的联合声明,批评AI公司把攻克数学难题当作基准测试来推进,认为这与数学界的目标严重脱节。声明指出,近几个月大语言模型的数学能力大幅提升,但AI主导的解题成果往往仓促发布,来不及严谨论证、提炼新方法和规范引用前人工作,引发成果归属与抄袭争议。声明认为这属于更广泛的人工智能对齐问题的一部分,2026年菲尔兹奖获得者邓煜也在签署人之列。
推荐理由:声明全文与25位签署人名单完整呈现,读者可了解数学界对AI以解题跑分推进研究的具体担忧。
OpenAI 首席产品官 Tibo 宣布暂停 200 美元档 Pro 20X 的新增订阅,以保障现有用户流畅访问 GPT-6 Astra,目前订阅页面仅剩每月 100 美元的 5X 档。
推荐理由:从订阅档位定价与算力成本的对照,可以看出重度用户行为如何击穿包月套餐的毛利假设。

推荐理由:6 款开源模型从 0.9B 覆盖到 375B,并公开中间 checkpoint 与训练日志,便于观察完整训练过程。
推荐理由:文中给出同一套指数下的横向对比和每任务成本,可据此判断轻量模型与旗舰 Pro 之间的性价比差距。
推荐理由:原文给出 DeepSeek-V4.1-Flash 的参数结构、上下文长度和开源协议,读者可据此评估其部署与成本价值。
DeepSeek 发布多模态 MoE 模型 DeepSeek-V4.1-Flash,具备 1M token 上下文窗口,全局 KV 缓存占用约 890 字节每 token,约为 DeepSeek-V4-Flash 的 1/4。
推荐理由:DeepSeek-V4.1-Flash 把全局 KV 缓存压到 890 字节每 token,长上下文推理的部署成本变化构成主要看点。
🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models. 1/6
推荐理由:DeepSeek 新架构家族最小模型亮相,配图给出它在四个基准上与其他模型的对比数据,可据此了解该型号的定位与表现。
OpenRouter 发布 Fusion 复合推理系统,调用模型可将提示词并行发给 1 至 8 个专家模型,由 judge 对比共识与分歧后生成结构化分析,再写出最终答案。
推荐理由:原文给出成本、延迟和适用场景的量化说明,读者可据此判断多模型研讨是否值得接入现有工作流。
OpenAI 发布 GPT-6 Astra,称其为面向商务的最强模型,具备高级推理、电脑使用能力,以及更强的写作和设计判断。
推荐理由:官方宣布新模型并点出推理、电脑操作与写作设计判断等方向,可据此了解其在商务场景的定位。
纽约大学数学教授 Tristan Buckmaster 宣布三项证明成果,并质疑 OpenAI 在其成果公开前就基于其工作推进,抢先公布了纳维-斯托克斯存在性与光滑性问题的完整证明。
推荐理由:原文给出了双方时间线与算力成本,读者可据此观察 AI 在数学研究中的成果归属与数据使用争议。
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
推荐理由:Hugging Face 联创从数学品味角度提出,AI 在数学上的前沿成果多是反例式搜索,尚不足以判定领域已被解决。
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
推荐理由:OpenAI 称一组智能体在 88 小时内给出纳维-斯托克斯方程证明,读者可据此了解大规模智能体协同与 Lean 形式化核验的用量。
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
推荐理由:OpenAI 称一组智能体用比 GPT-6 Astra 更强的下一代模型给出 Navier-Stokes 问题的解法,可据此看智能体在前沿数学中的角色。
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
推荐理由:原文给出智能体搜索的耗时与 token 消耗,可了解大规模智能体协作做数学研究的具体形态。
I would like to clarify a few things: 1) The screenshot is my reaching out to Levent to coordinate our releases. I hope it’s clear from the message that we came in with the best possible intentions. 2) I never ever asked for Levent to be removed from authorship of his own work (as indicated by my text). I was surprised to learn during the call with Tristan that they had only solved Euler and not Navier-Stokes; after learning this we brainstormed possible paths forward. One option we discussed was that Tristan could be the lead author on a rewrite of OpenAI’s Navier-Stokes proof. It is in that context that I said “it would be simpler if Levent was not an Anthropic employee” because I felt it would be inappropriate for an Anthropic employee to author OpenAI’s work. Importantly it was admitted that internal Anthropic models had been used in their proof of Euler blowup; I therefore felt I could not consider Levent to be an independent academic. Another option I wanted to propose (but got cut short) is to offer access to our internal model so that they could try to finish their proof and bridge the gap between Euler and NS. Again I did not know how to navigate giving access to internal OpenAI IP to an Anthropic employee. 3) To reiterate it plainly: as my text clearly indicates, and as I said during our call, OpenAI's intention was to do everything possible to celebrate their mathematical achievements and the heroic efforts that they made on Euler. In the call I was immediately met with a litany of slander, including direct threats that if we were to announce Navier-Stokes he would immediately go to the press with a barrage of unfounded accusations. I refuted all these accusations but he replied “there is nothing you can do, I simply do not trust you”. I was confused why one would turn an incredible source for celebration (of their achievements!) into such bickering, which is when I said that I did not understand why one would risk their career [over unfounded accusations]. Genuinely, at that moment, I was trying to care for him and do a last ditch attempt to get a chance to give them all the credits that they deserve. I deeply apologize for this extremely poor choice of words, it is the opposite of what I was trying to convey. (I should say that I retracted them on the spot by the way.) 4) Overall, on a personal level, it was incredibly difficult to have these conversations. Levent refused to attend any of the meetings despite my repeated asking. As Sholto Douglas said, there will need to be coordination between Anthropic and OpenAI in the future; I felt I was doing a proxy negotiation with Anthropic while the Anthropic employee refused to directly participate.
推荐理由:作者以本人身份回应 Navier-Stokes 归属争议,并用内部模型与 GPT-6 Astra 的对比图说明成果不依赖外部提示词。
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
推荐理由:OpenAI 官方宣布用下一代模型的智能体群产出纳维-斯托克斯千年问题证明,读者可以关注智能体做数学研究的这一路径。
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
推荐理由:OpenAI 称一组智能体借助下一代模型给出 Navier-Stokes 方程解,可了解这一数学难题的 AI 攻关方式与外界反应。
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
推荐理由:转述 OpenAI 关于千禧年数学难题证明的说法,读者可借此了解其下一代模型与智能体协作的定位。
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
推荐理由:材料给出了智能体攻关与 Lean 形式化验证的完整流程,读者可据此了解这一宣称结果如何被产出并接受机器核验。