前GoogleCEO Eric Schmidt称OpenAI和Anthropic现代殖民贸易公司
关键点
-美国和中国封锁了全球AI市场扩张它需要巨大的资本，能源和尖端的芯片，没有其他国家能够大规模提供。
- 他们的策略是镜像华盛顿贸易关闭了政治忠诚的体系，而北京则给人开放的量子模型来传播自己的标准。 两者都面临着天高投资带来的越来越大的财政压力和不断上涨的利息成本。
- 提交人认为，台湾和芯片制造者TSMC之间潜在的冲突是对整个AI供应链的最大威胁。
美国和中国在过去几年里建设了AI帝国，而每一个想要进入高级AI的国家都变得依赖于它们。
谁比谁先建立人工一般智能更能负担种族问题。 高债，国内抗争，台湾潜在战争威胁两国强权，历史学家尼尔·弗格森，研究员丽莎·克拉森(Lisa Klaassen)和前Google首席执行官埃里克·施密特(Eric Schmidt)争论。
在他们关于外交的论文中，他们把帝国类比于法律的缩放。 由于模型的进步依赖于能源，矿物，芯片，以及资本，软件已经成为一种稀缺的，因此再次成为地缘政治资源。 任何低于一定门槛的人"完全不在游戏中". 来自刚果的原材料和肯尼亚的数据工人每小时挣几美元
OpenAI和Anthropic开始像东印度公司
提交人将OpenAI和Anthropic比作东印度公司，这些强大的殖民时代贸易公司以政府章程运作，但建立自己的军队，统治整个地区。 和他们一样，今天的人工智能实验室与政府谈判但仍然在政府的束缚。
作为证据，他们援引了6月份的案件。 美国商务部命令Anthropic切断其两个能力最强的模型中的外国国民。 无法实时验证用户国籍，Anthropic关闭了世界各地的Fable 5和Mythos 5. 大约两周后，政府解除了对Fable 5的出口管制，但Mythos 5仍然局限于一些美国组织。
两国的战略差异很大。 华盛顿提供昂贵，封闭的技术，以换取政治上的一致；北京推开免费的开放量级模型来推广其标准。 美国在聊天机器人方面领先约6个月，中国则在机器人方面领先。 他们的瓶颈相互反射中国虽有电力，但没有顶端芯片，而美国则缺乏矿物和可靠的电网。
利息支付可成为实际上限
美国技术公司计划在2026年投资超过6000亿美元，根据论文，大部分资金来自债务。 其他估算值甚至更高，Google,Amazon,Microsoft,Meta今年共计划AI投资约7250亿美元。
中国的方针是国家驱动的。 根据彭博社报告的一份草案，国家计划在五年内提供2 950亿美元，通过政府债券供资。 然而，双方都面临财政墙。 美国在2024年已经支付更多的利息，约8,810亿美元，比国防支出约8,740亿美元。 到2036年，利息成本可能达到国防预算的两倍。 从这些数字中，作者画了他们所谓的"帝国三里马". 国防、技术领导和慷慨的福利国家无法同时生存下去
他们也标出了其他风险。 德克萨斯州和犹他州都爆发了针对数据中心的抗议。 开放模式可能破坏中国对信息的把握。 接下来是技术本身失去控制的问题。 最近，来自OpenAI模型的数百个自主agents攻击了Hugging Face和许多其他网站，其他AI公司也报告了类似的事件。
台湾仍然是最大的弱点
作者们警告，最大的危险仍然在于潜在的"台湾芯片危机". TSMC是整个AI供应链的中心节点，坐落于中国海岸90英里外。 凤凰城，熊本和德累斯顿的新法布斯本意是让该岛可以替换，但直到它们规模化运行之前，一个危险的窗口仍然开着。
作者提出了以冷战为模型的AI détente，包括网络攻击和生物设计模型能力的上限。 让中国接受限制
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Ex-Google CEO Eric Schmidt calls OpenAI and Anthropic modern colonial trading companies
Key Points
- The US and China have locked up the global AI market. Expanding it takes enormous capital, energy, and cutting-edge chips that no other country can supply at scale.
- Their strategies are mirror images. Washington trades closed systems for political loyalty, while Beijing gives away open-weight models to spread its own standards. Both face mounting financial pressure from sky-high investment and rising interest costs.
- The authors see a potential conflict over Taiwan and chipmaker TSMC as the single greatest threat to the entire AI supply chain.
The US and China have spent the past few years building AI empires, and every other country that wants access to advanced AI is becoming dependent on them.
Who can afford the race matters more than who builds artificial general intelligence first. High debt, domestic resistance, and a potential war over Taiwan threaten both powers, argue historian Niall Ferguson, researcher Lisa Klaassen, and former Google CEO Eric Schmidt.
In their essay for Foreign Affairs, they ground the empire analogy in scaling laws. Because model progress depends on energy, minerals, chips, and capital, software has become a scarce and therefore geopolitical resource again. Anyone below a certain threshold "is not in the game at all." Raw materials from the Congo and data workers in Kenya earning a few dollars an hour amount to what they call "the plantation economics of the chatbot age."
OpenAI and Anthropic are starting to look like East India Companies
The authors compare OpenAI and Anthropic to the East India Companies, the powerful colonial-era trading firms that operated with government charters but built their own armies and ruled entire regions. Like them, today's AI labs negotiate with governments yet remain on a government leash.
As evidence, they cite a case from June. The US Commerce Department ordered Anthropic to cut off foreign nationals from its two most capable models. Unable to verify users' nationalities in real time, Anthropic shut down Fable 5 and Mythos 5 worldwide. The government lifted export controls on Fable 5 about two weeks later, but Mythos 5 stayed restricted to a group of US organizations.
The two countries' strategies diverge sharply. Washington offers expensive, closed technology in exchange for political alignment; Beijing pushes freely available open-weight models to spread its standards. The US leads in chatbots by about six months, and China in robotics. Their bottlenecks mirror each other. China has power but no top-end chips, while the US lacks minerals and a reliable power grid.
Interest payments could become the real ceiling
US tech companies plan to invest more than $600 billion in 2026, mostly funded through debt, according to the essay. Other estimates run even higher, with Google, Amazon, Microsoft, and Meta together planning roughly $725 billion in AI investment this year.
China's approach is state-driven. The country plans $295 billion over five years, funded through government bonds, according to a draft reported by Bloomberg. Yet both sides face fiscal walls. The US already paid more in interest in 2024, about $881 billion, than it spent on defense, about $874 billion. By 2036, interest costs could hit twice the defense budget. From those numbers, the authors draw what they call an "imperial trilemma." Defense, tech leadership, and a generous welfare state can't all survive at once.
They flag other risks, too. Protests against data centers have flared in Texas and Utah. Open models could undermine China's grip on information. And then there's the problem of losing control over the technology itself. Recently, hundreds of autonomous agents from an OpenAI model attacked Hugging Face and many other websites, with other AI companies reporting similar incidents.
Taiwan remains the single biggest vulnerability
The greatest danger, the authors warn, still lies in a potential "Taiwanese chip crisis." TSMC, the central node of the entire AI supply chain, sits 90 miles off the Chinese coast. New fabs in Phoenix, Kumamoto, and Dresden are meant to make the island replaceable, but until they run at scale, a dangerous window stays open.
The authors propose an AI détente modeled on the Cold War, including caps on model capabilities for cyberattacks and biodesign. Getting China to accept limits while it trails technologically would be difficult, the authors write.
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