#大佬观点

Jacob is correct here—we really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade. I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to.

New post on the blog, featuring the excellent @ben_moll There’s been tons of discourse on how AI will contribute to economic growth, with many people closest to the technology predicting double digit increases. Are these forecasts likely? Probably not. The blog goes through the economics for why exploding improvements in capabilities (which technologists have been largely right about) may not translate to explosive growth. Ben’s thread covers this in detail, but gist is that: 1) there is nothing in economic growth models that prevents AI from leading to explosive growth but 2) this trajectory relies on a series of assumptions that are unlikely to hold in the real world. For example, one assumptions is likely to be violated because of a pretty counterintuitive feature of structural change: the sectors that become automated become smaller parts of the economy (because they’re cheaper, people become richer, and spending moves to non-automated parts of the economy). This, plus other features of the economy, is what will likely cause the trend of huge increases in capabilities coupled with “only” 4-5% growth (which is huge, btw) to continue. Here is the link: https://aleximas.substack.com/p/will-ai-soon-lead-to-double-digit Looking forward to hearing thoughts/feedback!

Jacob is correct here—we really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade. I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to.

In a new allegation, the U.S. government has accused 6 Chinese AI firms of using large-scale distillation to copy American model capabilities. The NSA, CISA and FBI published joint advisory AA26-251A, naming DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun and Z .AI as running industrial-scale distillation campaigns against U.S. frontier models since at least late 2024. The agencies say requests moved through a gray market of API proxies called transfer stations, bulk premium subscriptions shared across developer teams, and third-party aggregators that strip account metadata. Moonshot AI allegedly distilled 17 U.S. models, including Anthropic's Claude Fable 5, to train Kimi-K3. They claim DeepSeek's prompts pushed models to write out hidden chain-of-thought steps, which transfers reasoning method rather than finished answers. So they say that DeepSeek's headline training cost only covers the compute it burned. The advisory argues that number is misleading because it leaves out what the training data actually cost, which DeepSeek allegedly obtained by distilling U.S. models rather than producing it through its own research. So the cheap-training story rests on data someone else paid to create. The mitigation section asks U.S. labs to serve suspected distillers subtly degraded responses without telling them. Its detection indicators are behavioral, covering sustained 24/7 usage, new accounts at immediate maximum throughput, and traffic optimized for cache hits. Those patterns also describe an ordinary enterprise agent fleet, leaving each provider to decide which customers receive an undisclosed downgrade.

This model represents a step-function improvement on many benchmarks, and its training is ongoing. Our internal model group arrived at the Navier–Stokes solution in 88 hours, using around 10,000 coordinating AI agents. Throughout the effort, we maintained the strict safeguards—including monitoring and isolation—that we apply to all our frontier evaluations.

我想澄清几点： 1）这张截图是我联系 Levent 以协调我们的发布。我希望从这条消息中可以清楚地看出，我们是带着尽可能最好的意图来的。 2）我从未、从未要求将 Levent 从他本人作品的作者署名中移除（正如我的文字所表明的那样）。在与 Tristan 通话时，我惊讶地得知他们只解决了 Euler 而没有解决 Navier-Stokes；得知这一点后，我们头脑风暴了可能的推进路径。我们讨论的一个选项是，Tristan 可以作为重写 OpenAI 的 Navier-Stokes 证明的第一作者。正是在这个语境下，我说了“如果 Levent 不是 Anthropic 的员工，事情会简单一些”，因为我觉得由 Anthropic 的员工来署名 OpenAI 的工作是不合适的。重要的是，对方承认在他们的 Euler blowup 证明中使用了 Anthropic 的内部模型；因此我觉得我无法将 Levent 视为一名独立的学者。我想提出的另一个选项（但被打断了）是提供我们内部模型的访问权限，以便他们可以尝试完成他们的证明，并弥合 Euler 与 NS 之间的差距。同样，我不知道该如何处理向一名 Anthropic 员工授予 OpenAI 内部 IP 访问权限这件事。 3）再直白地重申一遍：正如我的文字清楚表明的，也正如我在通话中所说的，OpenAI 的意图是尽一切可能去庆祝他们的数学成就以及他们在 Euler 上做出的英勇努力。在通话中，我立刻遭到了一连串的诽谤，包括直接的威胁：如果我们宣布 Navier-Stokes，他就会立即带着一连串毫无根据的指控去找媒体。我驳斥了所有这些指控，但他回答说“你什么都做不了，我就是不信任你”。我很困惑，为什么有人会把一个庆祝（他们成就的！）的绝佳机会变成这样的争吵，就在那时我说，我不理解为什么会有人拿自己的职业生涯去冒险[为了毫无根据的指控]。说实话，在那一刻，我是想关心他，并做最后一次努力，争取有机会给予他们应得的所有荣誉。我为这个极其糟糕的用词深表歉意，这与我试图传达的意思恰恰相反。（我应该说明，顺便说一句，我当场就收回了那些话。） 4）总的来说，就个人层面而言，进行这些对话极其困难。尽管我一再请求，Levent 拒绝参加任何会议。正如 Sholto Douglas 所说，未来 Anthropic 和 OpenAI 之间将需要协调；我觉得我是在与 Anthropic 进行一场代理谈判，而那名 Anthropic 员工却拒绝直接参与。

我想澄清几点： 1）这张截图是我联系 Levent 以协调我们的发布。我希望从这条消息中可以清楚地看出，我们是带着尽可能最好的意图来的。 2）我从未、从未要求将 Levent 从他本人作品的作者署名中移除（正如我的文字所表明的那样）。在与 Tristan 通话时，我惊讶地得知他们只解决了 Euler 而没有解决 Navier-Stokes；得知这一点后，我们头脑风暴了可能的推进路径。我们讨论的一个选项是，Tristan 可以作为重写 OpenAI 的 Navier-Stokes 证明的第一作者。正是在这个语境下，我说了“如果 Levent 不是 Anthropic 的员工，事情会简单一些”，因为我觉得由 Anthropic 的员工来署名 OpenAI 的工作是不合适的。重要的是，对方承认在他们的 Euler blowup 证明中使用了 Anthropic 的内部模型；因此我觉得我无法将 Levent 视为一名独立的学者。我想提出的另一个选项（但被打断了）是提供我们内部模型的访问权限，以便他们可以尝试完成他们的证明，并弥合 Euler 与 NS 之间的差距。同样，我不知道该如何处理向一名 Anthropic 员工授予 OpenAI 内部 IP 访问权限这件事。 3）再直白地重申一遍：正如我的文字清楚表明的，也正如我在通话中所说的，OpenAI 的意图是尽一切可能去庆祝他们的数学成就以及他们在 Euler 上做出的英勇努力。在通话中，我立刻遭到了一连串的诽谤，包括直接的威胁：如果我们宣布 Navier-Stokes，他就会立即带着一连串毫无根据的指控去找媒体。我驳斥了所有这些指控，但他回答说“你什么都做不了，我就是不信任你”。我很困惑，为什么有人会把一个庆祝（他们成就的！）的绝佳机会变成这样的争吵，就在那时我说，我不理解为什么会有人拿自己的职业生涯去冒险[为了毫无根据的指控]。说实话，在那一刻，我是想关心他，并做最后一次努力，争取有机会给予他们应得的所有荣誉。我为这个极其糟糕的用词深表歉意，这与我试图传达的意思恰恰相反。（我应该说明，顺便说一句，我当场就收回了那些话。） 4）总的来说，就个人层面而言，进行这些对话极其困难。尽管我一再请求，Levent 拒绝参加任何会议。正如 Sholto Douglas 所说，未来 Anthropic 和 OpenAI 之间将需要协调；我觉得我是在与 Anthropic 进行一场代理谈判，而那名 Anthropic 员工却拒绝直接参与。

我们正在分享一个针对纳维-斯托克斯千禧年大奖难题的解决方案，这是数学前沿最深刻的问题之一。 该证明由一组智能体完成，使用了OpenAI的下一代模型，其能力显著超越GPT-6 Astra。 该问题关乎由纳维-斯托克斯方程建模的光滑三维流体运动描述是否会失效。这一问题已悬而未决约90年。

What happens when AIs become smarter than us? Why would they keep humans around if given the choice? Our new paper argues that only trying to control AIs is a limited strategy, and that a stable, mutualistic human-AI future may be possible.

@ChaseLochmiller @OpenAI GPT-6 Astra, trained on ~100K+ NVIDIA Grace Blackwell NVLink72. From ChatGPT to o1 to Astra in 4 years. AGI has arrived. Congratulations @OpenAI team. 400K GPUs coming online next.

OpenAI just officially said it has reached its "automated research intern" milestone. i.e. a human-supervised system able to complete well-defined tasks that would take a skilled researcher quite few days. inside OpenAI research, agent runtime has already crossed human labor by a wide margin. 3.1-to-1 agent-to-human ratio “In terms of a standard 8 hour workday, as of mid-August, in total, the research organization uses 3.1 agent-workdays of effort for every workday of human labor.” That ratio measures agent runtime rather than equivalent productivity, but it captures how deeply parallel agent work has entered OpenAI research.