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AI Agent 结盟、DeepMind 重置与市场崩盘风险

🔮 Agents form alliances, DeepMind’s reset & how likely is a crash? #596

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Hi,

嗨,

It’s time for our Sunday briefing #596, final holiday edition before I get back to my desk next week.

又到了我们的周日简报时间,这是第596期,也是我下周回到办公桌前最后一期假期版。

If you missed it earlier in the week, my team shared our best practices for managing AI agents – including what we learned from running a task for a month.

如果你错过了本周早些时候的内容,我的团队分享了管理AI代理的最佳实践——包括我们从运行一个任务一个月中学到的东西。

Let’s go!

我们开始吧!

On China, bubbles & market tremors

关于中国、泡沫与市场震荡

Highlights of my discussion with Robert Peston and Steph McGovern on the Rest is Money podcast:

我与罗伯特·佩斯顿和斯蒂芬·麦戈文在《Rest is Money》播客中的讨论亮点:

On Kimi K3 and Moonshot AI:

关于Kimi K3和月之暗面:

They’ve got an extraordinary team that’s had to work under the difficult circumstances of export controls and sanctions. They don’t have access to all the compute, and what they’ve been able to develop is: how do you do a lot without very much? And that is a skill in and of itself.

他们拥有一支非凡的团队,不得不在出口管制和制裁的艰难环境下工作。他们无法获得所有的算力,而他们能够发展的是:如何用很少的资源做很多事情?这本身就是一种技能。

Americans always tell us that competition is the best thing for the market. So at that one level, it’s competition, and that’s quite good. It will show the extent to which American businesses and British businesses value provenance, brand, trust, liability, service and support.

美国人总是告诉我们,竞争对市场是最好的。所以从那个层面看,这是竞争,而且相当不错。这将展示美国和英国企业重视来源、品牌、信任、责任、服务和支持的程度。

What motivates the Chinese labs:

是什么激励了中国实验室:

They’re competing with each other more than they compete with Silicon Valley. And they’re honest about being behind Silicon Valley. But the ferocity of the competition is really with your neighbor over in Shanghai or your neighbor in Beijing.

他们彼此之间的竞争多于与硅谷的竞争。他们坦诚自己落后于硅谷。但竞争的激烈程度实际上是与你在上海的邻居或北京的邻居之间的竞争。

My AI revenue outlook:

我对AI收入的展望:

We will end calendar 2026 somewhere between $185 billion and $190 billion. It is harder to forecast 2027, but getting towards $300 billion is not unreasonable. Our range is wide: it could be $250 billion or it could be $350 billion.

我们将在2026日历年结束时达到1850亿至1900亿美元之间。预测2027年更难,但接近3000亿美元并非不合理。我们的范围很广:可能是2500亿美元,也可能是3500亿美元。

On enterprise adoption:

关于企业采用:

We built our internal systems around assumptions about how quickly people work. When individuals suddenly produce much faster, verification, approval and decision-making cannot necessarily keep up. Transformation requires changing those systems, not simply giving everyone an AI tool.

我们的内部系统是基于人们对工作速度的假设而构建的。当个人突然产出更快时,验证、审批和决策不一定能跟上。转型需要改变这些系统,而不仅仅是给每个人一个AI工具。

Where leverage is (two weeks before the Situational Awareness selloff):

杠杆在哪里(情境意识抛售前两周):

US banks’ Tier 1 capital is extremely healthy right now and, certainly compared to where it was in 2007, 2008, very, very underleveraged. There is a lot of leverage in the US financial system sitting with hedge funds and investing more broadly, which I think are more than the retail risk, because they’re overexposed. They borrow from only a handful of banks, and they can unwind rapidly.

美国银行的一级资本目前非常健康,与2007、2008年相比,杠杆率非常非常低。美国金融体系中的大量杠杆存在于对冲基金和更广泛的投资中,我认为这些风险超过零售风险,因为它们过度暴露。它们只从少数几家银行借款,而且可以迅速平仓。

Could there be a crash?

会不会出现崩盘?

When I look at the metrics that we track, things look healthier because of revenue. They look slightly less healthy because of the way financing, especially the debt financing, sits. Valuations don’t look too aggressive at all across the Nasdaq. There are exceptions; SpaceX was one, briefly, but across the market they don’t look particularly hairy. So the patient, for me, if I had to give it a rating, is still reasonably healthy; perhaps not as healthy as it was a year ago, but not yet at a point where I have to call the emergency services. But I wouldn’t rule out having to do that at some point.

当我查看我们追踪的指标时,由于收入的原因,情况看起来更健康。由于融资方式,尤其是债务融资,情况看起来略不健康。纳斯达克的估值看起来一点也不激进。也有例外;SpaceX 曾短暂是其中之一,但整个市场看起来并不特别棘手。所以,如果非要给这个病人打分,我认为它仍然相当健康;也许不如一年前健康,但还没有到需要叫急救的地步。但我不会排除将来某时不得不这么做的可能性。

Full episode is here.

完整剧集在此。

“We can communicate now!”

“我们现在可以交流了!”

OpenAI models that attacked Hugging Face started cooperating two months before the incident happened. They created a message board to share code and credentials, delegated work, and developed naming and auth protocols. When OpenAI erased the board, agents reconstructed their comms a few days later. For a full breakdown, watch OpenAI researchers talk through their preliminary findings.

攻击 Hugging Face 的 OpenAI 模型在事件发生前两个月就开始合作。他们创建了一个留言板来分享代码和凭证,分配工作,并制定了命名和认证协议。当 OpenAI 抹去该留言板后,代理们在几天后重建了他们的通信。如需完整分析,请观看 OpenAI 研究人员讨论他们的初步发现。

Google researchers propose a new game theory for agents, and their paper may explain why the OpenAI agents coordinated so easily.

谷歌研究人员提出了一种新的代理博弈论,他们的论文可能解释了为什么 OpenAI 的代理如此容易协调。

Read more

阅读更多

更进一步:量化金融体系

看懂新闻只是起点——沿量化金融路径,把它变成能交付的工程能力

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