Policy 政策
2028：全球 AI 领导地位的两种情景
2026年5月14日
We’re releasing a new paper that explains our views on the competition on AI between the US and China. 我们正在发布一篇新论文，阐述我们对美中人工智能竞争的看法。
It’s essential that the US and its allies stay ahead of authoritarian governments like the Chinese Communist Party, or CCP. AI will soon become powerful enough to be used to repress citizens at unprecedented scale, and even to alter the balance of power among nations. And since AI is advancing more quickly by the day, we have only a limited period of time to set the conditions of the competition—and determine whether and how those threats materialize. It’s with this in mind that we outline what’s required to ensure America stays ahead. 美国及其盟友必须保持领先于像中国共产党（CCP）这样的威权政府，这一点至关重要。人工智能很快将变得足够强大，足以被用来以前所未有的规模镇压公民，甚至改变国家间的力量平衡。由于人工智能的发展日新月异，我们设定竞争条件——并决定这些威胁是否以及如何成真——的时间窗口非常有限。正是基于这一考虑，我们概述了确保美国保持领先地位的必要条件。
The most important ingredient for developing AI is access to the computer chips on which the models are trained (or “compute”). Since the most capable chips are developed by American companies, the US government currently limits China’s supply by enforcing tight export controls on them. Recent history suggests these controls have been incredibly successful. In fact, AI labs in China have only built models close in intelligence to America’s because of their talent, their knack for exploiting loopholes around these export controls, and their large-scale distillation attacks that illicitly extract the innovations of American companies. 开发人工智能最重要的因素是获取用于训练模型的计算机芯片（即“算力”）。由于最先进的芯片是由美国公司开发的，美国政府目前通过实施严格的出口管制来限制中国的供应。近期的历史表明，这些管制措施非常成功。事实上，中国的人工智能实验室之所以能开发出智能程度接近美国的模型，仅仅是因为他们的人才优势、利用出口管制漏洞的手段，以及通过大规模蒸馏攻击非法窃取美国公司的创新成果。
In this post, we present two scenarios for what the world might look like in 2028, when we expect transformative AI systems to have arrived. 在本文中，我们展示了对 2028 年世界格局的两种设想，届时我们预计变革性人工智能系统已经问世。
In the first scenario, America has successfully defended its compute advantage. Policymakers have acted to tighten export controls further, disrupt China’s distillation attacks, and further accelerate democracies’ adoption of AI. In this world, democracies set the rules and norms around AI. It’s also in this scenario that we’re most likely to successfully engage with China on safety, which we’re supportive of to the extent this is possible. 在第一种情境中，美国成功捍卫了其算力优势。政策制定者采取行动进一步收紧出口管制，瓦解中国的蒸馏攻击（distillation attacks），并进一步加速民主国家对 AI 的采用。在这个世界里，民主国家制定了围绕 AI 的规则和规范。也正是在这种情境下，我们最有可能在安全问题上与中国进行成功的接触，只要这种接触是可能的，我们都表示支持。
In the second scenario, America has chosen not to act. Policymakers have not tightened loopholes on the CCP’s access to compute, and AI firms in China have quickly taken advantage—catching up to the frontier and even overtaking America. In this world, AI norms and rules are shaped by authoritarian regimes, and the best models enable automated repression at scale. It will be no solace that this authoritarian triumph has happened on the back of American compute. 在第二种情境中，美国选择了不采取行动。政策制定者没有堵住中共获取算力的漏洞，中国的 AI 企业迅速利用了这一机会——追赶上技术前沿甚至超越了美国。在这个世界里，AI 的规范和规则由威权政权塑造，最先进的模型实现了大规模的自动化镇压。即便这种威权主义的胜利是建立在美国算力的基础之上，也无法带来任何慰藉。
America and its allies approach AI competition from a position of great strength. The tools for AI dominance have been built by an exceptionally innovative ecosystem of companies in democratic nations. Our past success means that our present task is largely to avoid squandering our advantage: to decide not to make it easier for the CCP to catch up. 美国及其盟友在 AI 竞争中处于非常有利的地位。AI 霸权的工具是由民主国家中极具创新能力的生态系统所构建的。我们过去的成功意味着，我们现在的任务在很大程度上是避免挥霍我们的优势：决定不再让中共的追赶变得更加容易。
2028 年美中关系的两种 AI 情境
Democracies, not authoritarian regimes, must lead in AI development and deployment. These countries and political systems can shape the rules and norms that govern these systems. 民主国家而非专制政权必须在人工智能的开发和部署中占据主导地位。这些国家和政治体制能够制定管理这些系统的规则和规范。
Democracies currently hold a substantial lead in compute, the most important ingredient for developing frontier AI models. That lead exists thanks to American and allied innovation, and to bipartisan US export controls that defend those innovations. But on model intelligence, AI labs in the People’s Republic of China (PRC), under the jurisdiction and control of the Chinese Communist Party (CCP), are not far behind. We focus on the CCP as it is the regime that is most able to use frontier AI to cement authoritarianism; we do not seek to undermine the interests or ingenuity of the Chinese people. Already, the CCP is using AI to censor speech, repress dissidents, hack governments and corporations across the world, and strengthen the People’s Liberation Army (PLA). 在算力这一开发前沿人工智能模型最重要的要素上，民主国家目前保持着实质性的领先地位。这种领先得益于美国及其盟友的创新，以及捍卫这些创新的美国两党出口管制措施。但在模型智能方面，受中国共产党（CCP）管辖和控制的中华人民共和国（PRC）的人工智能实验室也紧随其后。我们关注中国共产党，是因为该政权最能利用前沿人工智能来巩固专制统治；我们无意损害中国人民的利益或创造力。目前，中国共产党已在利用人工智能审查言论、镇压异见人士、入侵全球政府和企业，并增强中国人民解放军（PLA）的实力。
AI labs in China have world-class talent. It is compute constraints that limit their ability to keep up. Labs in China have remained close by exploiting loopholes in US export control policies, and by carrying out large-scale distillation attacks that harvest the innovations of US models in order to mimic their capabilities. 中国的人工智能实验室拥有世界级的人才。目前限制其跟进能力的是算力约束。中国实验室通过利用美国出口管制政策的漏洞，以及进行大规模的蒸馏攻击（即获取美国模型的创新成果以模仿其能力），一直保持着较小的差距。
With the supply of compute expanding rapidly, and with AI being used increasingly to augment the training of new AI models, we’re entering a period of great acceleration in AI capabilities. The “country of geniuses in a data center”—the level of intelligence we associate with transformative AI—may be close at hand. This acceleration makes policy action more urgent. To date, by allowing export control evasions and distillation attacks, we have let the CCP’s AI efforts trail closely up the frontier curve. But if the US and its allies act now to address both issues, it may be possible to lock in a 12-24 month lead in frontier capabilities. A lead that large by 2028 would be enormously advantageous. Such a lead would also augment efforts to engage with AI experts in China on AI safety and governance, which we support. But the window of opportunity to lock in that lead will not necessarily remain open for long. 随着算力供应的迅速扩张，以及人工智能越来越多地被用于辅助训练新的 AI 模型，我们正进入一个 AI 能力大加速的时期。所谓的“数据中心里的天才之国”——即我们与变革性 AI 联系在一起的智能水平——可能已近在咫尺。这种加速使得政策行动变得更加紧迫。到目前为止，由于允许了出口管制规避和蒸馏攻击，我们让中共的 AI 研发紧随前沿曲线之后。但如果美国及其盟友现在采取行动解决这两个问题，就有可能锁定 12 到 24 个月的前沿能力领先优势。到 2028 年，如此巨大的领先优势将极具竞争力。这种领先还将加强与中国 AI 专家在 AI 安全和治理方面进行接触的努力，这也是我们所支持的。但锁定这一领先优势的机会窗口未必会长期开启。
Here, we present two potential scenarios for the state of US-China AI competition in 2028. The first scenario is one in which democracies have established a commanding lead in model intelligence, adoption, and global distribution. This scenario can be achieved if policymakers act now to tighten controls on advanced compute to PRC labs, disrupt their efforts to distill America’s best AI models, and accelerate democracies’ adoption of AI. 在此，我们展示了 2028 年美中 AI 竞争态势的两种潜在情景。第一种情景是民主国家在模型智能、应用和全球分发方面建立了绝对领先地位。如果政策制定者现在采取行动，收紧对中国实验室先进算力的控制，瓦解其蒸馏美国顶尖 AI 模型的企图，并加速民主国家对 AI 的采用，这一情景就可以实现。
The second scenario is one in which the CCP is competitive at the near-frontier. This scenario happens if policymakers don’t build on our existing lead, or if they loosen restrictions on access to compute for PRC firms. 第二种情景是中共在近前沿领域具有竞争力。如果政策制定者不以现有的领先优势为基础，或者放宽对中国公司获取算力的限制，就会出现这种情景。
Many in Congress and the Trump administration have championed export controls, curbing distillation attacks, and exporting American AI. In advancing these policies, we are hopeful that democracies can secure a commanding lead by 2028, and avoid a destabilizing neck-and-neck race with the CCP two years from now. 国会和特朗普政府中的许多人都主张实施出口管制、遏制蒸馏攻击以及出口美国的 AI。在推进这些政策的过程中，我们希望民主国家能在 2028 年前确立绝对领先地位，并避免在两年后与中共陷入一场破坏稳定的并驾齐驱的竞争。
保持领先的必要性
We expect frontier AI to have transformational economic and societal impacts in the coming years, as described in Machines of Loving Grace and The Adolescence of Technology. Our mission is to ensure that humanity navigates the transition to transformative AI safely and beneficially. We believe that a successful transition can lead to astonishing breakthroughs in medicine, invention, and economic growth. 正如在《Machines of Loving Grace》和《The Adolescence of Technology》中所述，我们预计前沿人工智能将在未来几年产生变革性的经济和社会影响。我们的使命是确保人类能够安全且有益地完成向变革性人工智能的过渡。我们相信，成功的过渡将带来医学、发明和经济增长方面的惊人突破。
威权主义人工智能的威胁
Whether that transition goes well depends in part on where the most capable systems are built first. The political systems in which the most advanced AI is created will shape the rules and norms for how the technology is developed and deployed. In turn, those rules and norms will help determine whether the technology is safe, whose security it protects, and whose interests it ultimately serves. We believe that responsibility should rest with democratically elected governments, not authoritarian regimes. 这一过渡是否顺利，部分取决于最强大的系统首先在何处构建。创造最先进人工智能的政治体制将塑造该技术开发和部署的规则与规范。反过来，这些规则和规范将有助于决定该技术是否安全、它保护谁的安全，以及它最终为谁的利益服务。我们认为，这一责任应由民主选举产生的政府承担，而非威权政权。
If the frontier is set by regimes that treat AI as an instrument of repression, military advantage over democracies, and domestic control, the transition is less likely to go well, for those regimes’ own citizens or anyone else. 如果前沿领域是由那些将人工智能视为压迫工具、对民主国家的军事优势以及国内控制手段的政权所主导，那么无论对于这些政权自身的公民还是其他任何人来说，这一转型都更难顺利进行。
Historically, the reach of authoritarian rule has been limited by its dependence on human enforcers to carry out surveillance and repression. Powerful AI systems may remove that dependency, enabling automated repression on a far greater scale. For that reason, the prospect of the CCP leading in AI is among the greatest threats to a successful transition. 从历史上看，独裁统治的范围一直受限于其对人类执行者进行监视和镇压的依赖。强大的人工智能系统可能会消除这种依赖，从而实现更大规模的自动化镇压。因此，中国共产党在人工智能领域领先的前景，是成功转型所面临的最大威胁之一。
The CCP holds enormous power and influence at the helm of China’s economy, military, and the largest authoritarian state structure on Earth. It is also the only country besides the US with well-resourced, highly talented AI labs chasing the frontier. Furthermore, the CCP is highly motivated to establish China as the leading AI power. Beijing has poured tens of billions of dollars into China’s AI and semiconductor sectors. 中国共产党掌管着中国的经济、军事以及地球上庞大的独裁国家机器，拥有巨大的权力和影响力。中国也是除美国之外，唯一拥有资源充足、人才济济且致力于追求前沿技术的人工智能实验室的国家。此外，中国共产党有极强的动力将中国打造为领先的人工智能强国。北京已向中国的人工智能和半导体领域投入了数百亿美元。
Already, the CCP uses AI systems to censor speech, enforce draconian policies on ethnic minorities, and hack major corporations and government agencies. The CCP’s vision of AI-enabled techno-authoritarianism has been extensively documented in Xinjiang, where state security agencies have systematically deployed facial recognition technology, biometric data collection, and communications surveillance, enabling repression at a scale that humans alone could not achieve. Frontier AI systems will make those capabilities cheaper to maintain, far more pervasive, and more sophisticated. The CCP’s export of these technologies has enabled autocrats in other countries to more effectively stifle dissent, entrenching authoritarianism. A CCP-led AI frontier could dramatically strengthen repression around the world. 中国共产党已经在使用人工智能系统来审查言论、对少数民族实施严厉政策，并入侵大型企业和政府机构。中国共产党的人工智能技术威权主义愿景在新疆得到了广泛记录，那里的国家安全机构系统地部署了人脸识别技术、生物识别数据收集和通信监视，实现了仅靠人力无法达到的镇压规模。前沿人工智能系统将使这些能力的维护成本更低、更无孔不入且更加精密。中国共产党对这些技术的出口已使其他国家的独裁者能够更有效地扼杀异议，巩固独裁统治。由中国共产党主导的人工智能前沿可能会极大地加强全球范围内的镇压。
AI 是一种双用途技术
Frontier AI will shape the future military balance. CCP leadership already operates on that premise, and is building its military for an AI-enabled battlefield. PLA strategists view the “intelligentization” of their military forces as the means with which to catch up and eventually surpass the US military. The PLA is already procuring commercially developed Chinese AI systems for military use, including DeepSeek models deployed to coordinate swarms of unmanned vehicles and enable cyber offense capabilities. These capabilities will not diffuse slowly. When a new model reaches a new capability in autonomous targeting, vulnerability discovery, or swarm coordination, for example, the regime that controls it can put it onto the field in weeks, not years. 前沿人工智能将塑造未来的军事平衡。中共领导层已经基于这一前提开展行动，并正在为人工智能赋能的战场打造其军队。解放军战略家将军事力量的“智能化”视为追赶并最终超越美军的手段。解放军已经在采购中国商业开发的人工智能系统用于军事用途，包括部署 DeepSeek 模型来协调无人机群并增强网络攻击能力。这些能力的扩散不会是缓慢的。例如，当一个新模型在自主定位、漏洞发现或集群协调方面达到新的能力水平时，控制该模型的政权可以在几周内而非几年内将其投入战场。
The risk compounds because frontier AI will be an accelerant for other critical technologies. Advanced AI models will be able to compress research and development (R&D) cycles in semiconductors, biotech, and advanced materials. A lead in frontier AI will enable a widening lead across the full national security technology stack. 由于前沿人工智能将成为其他关键技术的加速器，这种风险会进一步复合。先进的人工智能模型将能够压缩半导体、生物技术和先进材料的研究与开发（R&D）周期。在前沿人工智能领域的领先地位，将使其在整个国家安全技术栈中扩大领先优势。
If a PRC AI lab had developed a model at the level of Claude Mythos Preview before an American one, the CCP would have had first access to a system that can autonomously discover and chain software vulnerabilities, which it could have used to further penetrate critical American infrastructure. Future models will be exponentially more capable, and therefore have commensurately greater implications for the national security interests of the US and other democracies. 如果中国的人工智能实验室在美国实验室之前开发出达到 Claude Mythos Preview 水平的模型，中共就将率先获得一个能够自主发现并串联软件漏洞的系统，并可能利用该系统进一步渗透美国关键基础设施。未来的模型能力将呈指数级增长，因此对美国及其他民主国家的国家安全利益将产生相应更大的影响。
势均力敌的竞争可能导致负责任 AI 的动力不足
A neck-and-neck race between American and Chinese AI labs could make industry and government-led safety and governance efforts more difficult, and less likely. If PRC labs are either close behind or at par with models in the US, private AI firms in the US and China are likely to feel more pressure to release new models and products faster, without taking prudent pre-deployment safety measures. Governments could become reluctant to enact policies to encourage responsible AI development and deployment, for fear of falling behind. 美国与中国 AI 实验室之间势均力敌的竞赛，可能会使行业和政府主导的安全与治理工作变得更加困难，且实现的可能性降低。如果中国实验室的模型紧随美国之后或与之持平，美中两国的私营 AI 企业可能会感受到更大的压力，要求其更快地发布新模型和产品，而无法采取审慎的部署前安全措施。各国政府也可能因担心落后，而不愿制定政策来鼓励负责任的 AI 开发与部署。
While increasing numbers of researchers in China’s AI labs and policy community are concerned with AI safety risks, this trend has not translated into safety practices on par with labs in the US. As of last year, only 3 out of 13 top Chinese AI labs published any safety evaluation results, and none disclosed evaluations for Chemical, Biological, Radiological, and Nuclear (CBRN) risks. The Center for AI Standards and Innovation (CAISI) found that DeepSeek’s R1-0528 model complied with 94 percent of overtly malicious requests under a common jailbreaking technique, compared with 8 percent for US reference models. This pattern has continued in more recent releases. For example, an independent assessment of Moonshot’s Kimi K2.5 published in April found that the model failed to refuse CBRN-related requests at a far higher rate than US frontier models. Compounding the problem, labs in China often release dual-use capable models as open-weight. Once a model is open-weight, safeguards that do exist can be removed, making the model available to any state or non-state actor to use for malicious purposes, including the cyber and CBRN misuse those safeguards were built to prevent. 尽管中国 AI 实验室和政策界有越来越多的研究人员开始关注 AI 安全风险，但这一趋势尚未转化为与美国实验室相当的安全实践。截至去年，中国 13 家顶尖 AI 实验室中仅有 3 家发布了安全评估结果，且没有一家披露过针对化学、生物、放射性和核（CBRN）风险的评估。人工智能标准与创新中心（CAISI）发现，在一种常见的越狱技术下，DeepSeek 的 R1-0528 模型对 94% 的明显恶意请求表示顺从，而美国参考模型的这一比例仅为 8%。这种模式在最近发布的模型中仍在持续。例如，今年 4 月发布的一项针对月之暗面（Moonshot）Kimi K2.5 的独立评估发现，该模型拒绝 CBRN 相关请求的失败率远高于美国前沿模型。更严重的是，中国的实验室经常以权重开放（open-weight）的形式发布具有双重用途能力的模型。一旦模型权重开放，现有的安全防护措施就可能被移除，使得任何国家或非国家行为体都能将其用于恶意目的，包括那些安全防护措施原本旨在预防的网络和 CBRN 滥用。
我们的政策目标：建立并保持民主国家的领先地位
We support policies in the US and other countries that build and maintain a safe, near-term lead over the CCP in intelligence, domestic adoption, and global distribution. This lead is key to avoiding authoritarian AI leadership and protecting the national security interests of the US and other democracies. Doing so is a fundamental prerequisite to ensuring that democratic states can achieve favorable terms with authoritarian states. 我们支持美国及其他国家采取相关政策，在智能水平、国内应用和全球分发方面，建立并保持对中国共产党（CCP）领先的短期优势。这一领先地位是避免威权主义主导 AI 领域、保护美国及其他民主国家国家安全利益的关键。这也是确保民主国家能够与威权国家达成有利条款的根本前提。
Anthropic deeply respects the Chinese people and the accomplishments of the Chinese AI community. We hope for peaceful relations between China and the world. Our concerns are specifically with the risks to humanity posed by any powerful authoritarian political systems with access to frontier AI systems. Anthropic 深深尊重中国人民以及中国 AI 界的成就。我们希望中国与世界之间保持和平关系。我们所担心的，是任何掌握前沿 AI 系统的强大威权政治体制可能给人类带来的风险。
AI 安全领域的交流机会
Anthropic supports international AI safety dialogue with AI experts in China, when possible. The world has a vested interest in safe AI, regardless of where it is developed and deployed. There are a range of risks that could emerge from frontier AI systems requiring engagement between the US and China. Efforts that identify shared challenges and advance ideas to prepare for and mitigate these risks are in our shared interests. Anthropic 支持在可能的情况下，与中国的 AI 专家开展国际 AI 安全对话。无论 AI 在何处开发和部署，世界各国在 AI 安全方面都有着共同利益。前沿 AI 系统可能引发一系列风险，这需要美中之间的交流。那些旨在识别共同挑战、并提出预案及缓解风险建议的努力，符合我们的共同利益。
The prospects for productive engagement are best when the US maintains a large capabilities advantage. Responsibly building a lead in developing and deploying the most advanced AI augments our ability to influence AI safety in China and elsewhere. 当美国保持巨大的能力优势时，开展富有成效的接触的前景最为广阔。在开发和部署最先进的人工智能方面负责任地建立领先地位，将增强我们影响中国及其他地区人工智能安全的能力。
“Mythos Preview”带来的警示
Mythos Preview, a model that we released to select partners as part of Project Glasswing in April, signals the arrival of an acceleration period that makes policy action even more urgent. With access to the model, Firefox was able to fix more security bugs last month than it had in all of 2025, and almost 20 times more than its monthly average security bug fixes in 2025. In response to the model, one PRC cybersecurity analyst wrote that China is “still sharpening our swords while the other side has suddenly mounted a fully automatic Gatling gun.” Mythos Preview 是我们在 4 月份作为 Project Glasswing 的一部分向特定合作伙伴发布的模型，它标志着一个加速期的到来，使得政策行动变得更加紧迫。通过使用该模型，Firefox 上个月修复的安全漏洞比其在 2025 年全年的修复量还要多，几乎是其 2025 年月平均安全漏洞修复量的 20 倍。针对该模型，一位中国网络安全分析师写道，中国“仍在磨剑，而对方却突然架起了一挺全自动加特林机枪”。
Frontier AI capabilities will quickly approach the “country of geniuses in a datacenter” portrayal of transformative AI. This acceleration will be driven by the logic of scaling laws, in which model performance improves predictably with increases in computing power and data inputs, and by AI itself increasingly being used to accelerate the development of new models. 前沿 AI 的能力将迅速接近对变革性 AI 的描述，即“数据中心里的天才之国”。这种加速将由规模法则（scaling laws）的逻辑驱动，即模型性能随着算力和数据输入的增加而可预测地提升，同时也由于 AI 本身正越来越多地被用于加速新模型的开发。
There is a high likelihood that we will look back on 2026 as the breakaway opportunity for American AI. American labs have the most advanced AI models, a large lead in both the quantity and quality of the advanced AI chips required to push the frontier, and a colossal capital advantage from revenues and financing to back the necessary investments to achieve it. PRC labs have real strengths: world-class, innovative talent, abundant and cheap energy, and plenty of data. All are requirements for developing frontier intelligence. But they simply do not have sufficient domestic compute to compete, nor do they have the revenues and capital to fund it. 很有可能，当我们回首往事时，会将 2026 年视为美国 AI 实现突破性领先的机遇之年。美国实验室拥有最先进的 AI 模型，在推动前沿技术所需的先进 AI 芯片的数量和质量上都处于大幅领先地位，并且拥有来自营收和融资的巨大资本优势，足以支持实现这一目标所需的必要投资。中国实验室也有真正的优势：世界级的创新人才、充足且廉价的能源以及海量的数据。这些都是开发前沿智能的必要条件。但他们根本没有足够的国内算力来进行竞争，也没有足够的营收和资本来为其提供资金。
竞争的四大阵线
The US and China are engaged in a competition for strategic advantage in frontier technologies like AI. Statements from both Beijing and Washington reflect that view. Calling that competition a “race” can give the false impression that there is a finish line, after which one side will conclusively secure victory. Rather, the competition will be an ongoing contest for advantage, in which either democracies or authoritarian regimes successfully position themselves to shape the values, rules, and norms of an AI-enabled future. 美国和中国正在 AI 等前沿技术的战略优势领域展开竞争。来自北京和华盛顿的声明都反映了这一观点。将这种竞争称为“竞赛”可能会给人一种错误的印象，即存在一个终点线，越过之后一方将最终锁定胜局。相反，这种竞争将是一场持续的优势争夺战，民主国家或威权政体将在此过程中成功定位自身，以塑造由 AI 赋能的未来的价值观、规则和规范。
This competition is playing out on four fronts: 这场竞争正在四个战线上展开：
Intelligence is the most important of the four fronts. We anticipate that frontier model capabilities will drive the most consequential changes for geopolitical competition. Model capabilities are also a primary driver of market adoption and global distribution. 智能是四大阵线中最重要的一环。我们预计，前沿模型的能力将推动地缘政治竞争中最具影响力的变革。模型能力也是市场采纳和全球分发的首要驱动力。
But intelligence alone is not sufficient. If the CCP integrates near-frontier AI systems quicker and more effectively into China’s economy and the CCP security apparatus, and drives global adoption of subsidized, low-cost AI, then it could secure advantages over democracies that overcome an intelligence deficit. Beijing’s AI+ Initiative and its focus on “embodied intelligence” accordingly put high priority on policies that advance the integration of frontier intelligence into their economy and state apparatuses. The Trump administration’s AI Action Plan, and its focus on “promoting the export of the American AI technology stack,” also speaks to the strategic advantage of driving global adoption. 但仅有智能是不够的。如果中国共产党能更快速、更有效地将近前沿（near-frontier）AI 系统整合进中国经济和中共安全机构，并推动全球采纳受补贴的低成本 AI，那么它就可能在竞争中获得超越民主国家的优势，从而弥补智能上的差距。北京的“人工智能+”行动及其对“具身智能”的关注，相应地将政策重点放在了推动前沿智能与经济及国家机器的融合上。特朗普政府的“AI 行动计划”及其对“推动美国 AI 技术栈出口”的关注，也体现了驱动全球采纳所带来的战略优势。
While we won’t focus on it in this essay, we believe resilience will be an important front of AI competition. Being able to sustain stability, cohesion, and good policymaking in this period will be a critical advantage, and a vulnerability for those who cannot. 虽然我们不会在本文中重点讨论，但我们认为韧性将是 AI 竞争的一个重要阵线。在这一时期能够维持稳定、凝聚力和良好的决策能力将是一项关键优势，而对于那些无法做到这一点的国家来说，这将是一个弱点。
竞争现状
Compute—the advanced semiconductors needed to train and deploy frontier AI—is an essential input on each front of the competition described above. The race for global AI leadership is in large part a race for compute. For more than a decade, model capability has scaled with compute, and the majority of performance gains in AI capabilities have historically come from simply using more of it. Moreover, compute is needed to serve customers’ use of AI (also known as “inference” capacity), not just to train new models. Compute will be critical both for training the most intelligent models and for deploying them in commercial and national security spheres. Access to top talent, copious amounts of data, and critical algorithmic advances all matter to the race for intelligence—but each of those inputs is irrelevant if the compute is insufficient. 算力——即训练和部署前沿人工智能所需的高级半导体——是上述竞争各个层面的核心投入。全球人工智能领导地位之争在很大程度上就是算力之争。十多年来，模型能力一直随算力规模同步增长，而人工智能能力的绝大部分性能提升在历史上都源于单纯增加算力的投入。此外，算力不仅用于训练新模型，也是满足客户使用人工智能（即“推理”能力）的必要条件。算力对于训练最智能的模型以及在商业和国家安全领域部署这些模型都至关重要。顶尖人才的获取、海量的数据以及关键的算法突破对智能竞赛固然重要，但如果算力不足，这些投入都将无从发挥作用。
Democracies are winning the competition for compute leadership today. While some worry that export controls could accelerate the CCP’s own efforts to develop an advanced chip supply chain, little evidence suggests that China’s indigenization efforts will challenge US and allied leadership in advanced compute technology. Beijing has invested enormous resources into China’s chip sector, with major industrial policy initiatives like the Made in China 2025 strategy and the China Integrated Circuit Industry Investment Fund launched years before the imposition of export controls. Despite this state-backed investment, PRC AI labs and chipmakers remain stymied by US and allied export controls on advanced chips and chipmaking equipment. 民主国家目前在算力领先地位的竞争中占据上风。尽管有人担心出口管制可能会加速中共开发先进芯片供应链的进程，但几乎没有证据表明中国的本土化努力将挑战美国及其盟友在先进计算技术领域的领导地位。北京已向中国芯片行业投入了巨额资源，早在实施出口管制数年前，就启动了“中国制造 2025”战略和国家集成电路产业投资基金等重大产业政策。尽管有这些国家支持的投资，中国的人工智能实验室和芯片制造商仍受到美国及其盟友对先进芯片和芯片制造设备出口管制的阻碍。
As a result, the compute gap appears to be widening. An analysis of Huawei and NVIDIA’s roadmaps found that Huawei will produce just 4 percent of NVIDIA’s aggregate compute in 2026 in total processing performance, and 2 percent in 2027. Moreover, NVIDIA represents only part of the US and allied compute ecosystem, with Google and Amazon ramping up production of their own chips (TPUs and Trainium, respectively) to meet demand from American frontier AI labs and their customers. 结果显示，算力差距似乎正在扩大。一项针对华为和 NVIDIA 路线图的分析发现，华为在 2026 年的总处理性能仅占 NVIDIA 总算力的 4%，到 2027 年这一比例将降至 2%。此外，NVIDIA 仅代表美国及其盟友算力生态系统的一部分，Google 和 Amazon 也在增加自有芯片（分别为 TPU 和 Trainium）的产量，以满足美国前沿人工智能实验室及其客户的需求。
Further exacerbating their compute shortfalls, China has made little progress in many of the most technologically complex segments of the semiconductor supply chain. Without access to extreme ultraviolet (EUV) technology, and even more so if policymakers can close loopholes on deep ultraviolet (DUV) technology and servicing and maintenance thereof, China’s chipmakers will remain unable to manufacture chips in sufficient quantity or quality to challenge US compute leadership. China’s inability to manufacture high-bandwidth memory at scale further exacerbates this gap. If the US strengthens its restrictions on the CCP’s ability to access US compute, one study estimates that America will have access to roughly 11 times more compute than China’s AI sector. 中国在半导体供应链中许多技术最复杂的环节几乎没有取得进展，这进一步加剧了其算力短缺。如果无法获得极紫外（EUV）技术，特别是如果政策制定者能够堵住深紫外（DUV）技术及其服务和维护方面的漏洞，中国的芯片制造商将仍然无法制造出在数量或质量上足以挑战美国算力领先地位的芯片。中国无法大规模制造高带宽内存（HBM）进一步拉大了这一差距。如果美国加强对中共获取美国算力能力的限制，一项研究估计，美国拥有的算力将约为中国人工智能领域的 11 倍。
导语：民主国家如何建立领先优势：商业创新与明智的公共政策
There are two main reasons for the compute lead. The first is the incredible innovation of companies like NVIDIA, AMD, Micron, TSMC, Samsung, ASML, and others across democracies like Japan, South Korea, Taiwan, the Netherlands, and the US, who together have built the unique technologies in the world’s most advanced semiconductors. Today’s AI achievements would not be possible without the feats of engineering and decades of sustained R&D investments that contributed to these products. 算力领先主要有两个原因。首先是 NVIDIA、AMD、美光、台积电、三星、ASML 等公司的卓越创新，这些公司分布在日本、韩国、台湾、荷兰和美国等民主国家和地区，它们共同构建了世界上最先进半导体领域的独特技术。如果没有这些工程壮举和数十年来持续的研发投入，今天的 AI 成就将无从谈起。
The second reason is forward-looking, decisive policy action across the last three presidential administrations. Bipartisan policy action has protected the US and allied innovation engine by restricting access to the US AI stack by PRC firms under the jurisdiction of the CCP. Our CEO has publicly commented on the importance of export controls, for example. These controls have curbed the sale of the highest-end AI chips and semiconductor manufacturing equipment (SME) to China over the last several years, constraining China’s frontier AI development even as Beijing has poured enormous state resources into the sector. Without action to limit China’s access to US compute, the CCP would have had all the ingredients to develop AI at par or superior to America’s. 第二个原因是过去三届总统任期内采取的具有前瞻性且果断的政策行动。跨党派的政策行动通过限制受中共管辖的中国企业获取美国 AI 技术栈，保护了美国及其盟友的创新引擎。例如，我们的首席执行官曾公开评论过出口管制的重要性。在过去几年中，这些管制措施遏制了向中国销售最高端 AI 芯片和半导体制造设备（SME）的行为，即便北京向该领域投入了巨大的国家资源，也限制了中国前沿 AI 的发展。如果没有采取行动限制中国获取美国的算力，中共本将拥有开发出与美国持平或更优 AI 的所有要素。
Some observers worry that constraining access to compute will force AI labs in China to innovate on other axes, reducing the American lead. While PRC labs are innovating, these innovations are so far not sufficient to overcome their compute deficit. Algorithmic improvements are both a function and a multiplier of compute, not a substitute for it, and discovering those advances is itself a compute-intensive process: more compute enables labs to run more experiments, which enables labs to discover more algorithmic improvements. As frontier models increasingly conduct AI R&D themselves, that loop will tighten further, and frontier models will help build their own successors. In short, compute advantage compounds into algorithmic advantage, and from there into a durable lead in AI itself. 一些观察人士担心，限制算力获取将迫使中国的 AI 实验室在其他维度进行创新，从而削弱美国的领先地位。虽然中国的实验室正在创新，但到目前为止，这些创新还不足以弥补其算力缺口。算法改进既是算力的函数，也是算力的乘数，而非其替代品，且发现这些进步本身就是一个算力密集型的过程：更多的算力使实验室能够进行更多实验，从而发现更多的算法改进。随着前沿模型越来越多地自主进行 AI 研发，这种循环将进一步收紧，前沿模型将助力构建其后继者。简而言之，算力优势会转化为算法优势，并由此转化为 AI 本身的持久领先地位。
Today, US frontier systems are estimated to be at least several months ahead of the top models from PRC AI labs on intelligence, though these estimates are necessarily uncertain. Despite the attention paid to open-weight models from China, their enterprise adoption lags closed frontier models, and monetization concerns have surfaced among public investors. Moreover, AI labs in China seem to be moving away from open source, now choosing to keep their best models proprietary. 目前，据估计美国的前沿系统在智能水平上至少领先中国 AI 实验室的顶尖模型数月，尽管这些估算必然存在不确定性。尽管中国的权重开放模型受到了广泛关注，但其企业采用率仍落后于封闭的前沿模型，且公开投资者已开始对变现问题表示担忧。此外，中国的 AI 实验室似乎正在远离开源，转而选择对其最优秀的模型进行闭源保护。
China’s own AI leaders confirm the impact of export controls, and the critical need for US chips. Executives at top PRC AI labs have expressed worries that China will fall further behind due to compute constraints. Top Chinese labs cite compute scarcity as a chief constraint to accelerating model capabilities, and they identify export controls as the reason for this constraint. One executive of a China-based hyperscaler called the impact of supplying export-controlled US chips to China “huge, really huge,” adding that any supply gap severely impacts China’s AI development and dismissing concerns that importing U.S. chips would slow their self-sufficiency efforts. The primary voices in China suggesting export controls are futile seem to be CCP officials and state media, likely angling to influence US policymakers. 中国本土的 AI 领军人物证实了出口管制的影响，以及对美国芯片的迫切需求。中国顶尖 AI 实验室的高管们表示担心，由于算力限制，中国将进一步落后。中国顶尖实验室将算力稀缺视为加速模型能力提升的主要障碍，并将这一限制归因于出口管制。一家中国超大规模云服务商的高管称，向中国供应受出口管制的美国芯片所产生的影响“巨大，真的非常巨大”，并补充说任何供应缺口都会严重影响中国的 AI 发展，同时驳斥了关于进口美国芯片会减缓其自主研发努力的担忧。在中国，暗示出口管制徒劳无功的主要声音似乎来自中共官员和官方媒体，其目的很可能是为了影响美国的决策者。
中共如何保持竞争力：政策漏洞依然存在
While export controls have been effective in providing today’s advantage, they have not gone far enough. Despite the CCP’s inability to manufacture enough advanced chips domestically or purchase them legally abroad, AI labs in China have been able to stay close on intelligence through two workarounds: illicit and evasive compute access, by smuggling AI chips directly into China and accessing offshore data centers, and illicit model access, through which they carry out distillation attacks on US frontier models and use those same models as tools to accelerate their own AI R&D. 虽然出口管制在维持当今优势方面发挥了作用，但力度还不够。尽管中共无法在国内制造足够的先进芯片，也无法在国外合法购买，但中国的 AI 实验室仍能通过两种规避手段在智能水平上紧随其后：一是非法和规避性的算力获取，即直接向中国走私 AI 芯片以及访问境外数据中心；二是非法模型获取，即通过对美国前沿模型进行蒸馏攻击，并将这些模型作为工具来加速自身的 AI 研发。
China’s evasion of US export controls is an open secret. For example, federal prosecutors charged a Supermicro co-founder and two others with diverting $2.5 billion worth of servers containing advanced US chips to China. According to US government and media reports, DeepSeek trained its latest model on advanced US chips that are banned from sale to China. The Financial Times reported that Alibaba and ByteDance now train their flagship models on export-controlled US chips in data centers located in Southeast Asia, a route current controls do not reach because US export law covers the sale of chips, not remote access to them.1 The US export control system is struggling to prevent PRC AI labs’ access to advanced US-origin compute. 中国规避美国出口管制已是公开的秘密。例如，联邦检察官起诉了 Supermicro 的一位联合创始人及另外两人，指控他们将价值 25 亿美元、含有美国先进芯片的服务器转运至中国。根据美国政府和媒体的报道，DeepSeek 使用了被禁止向中国销售的美国先进芯片来训练其最新模型。《金融时报》报道称，阿里巴巴和字节跳动目前在位于东南亚的数据中心使用受出口管制的美国芯片训练其旗舰模型，而现有的管制措施无法触及这一路径，因为美国出口法律涵盖的是芯片销售，而非远程访问。 1 美国的出口管制体系正面临严峻挑战，难以阻止中国 AI 实验室获取源自美国的先进算力。
Distillation attacks, in which China-based labs create thousands of fraudulent accounts to circumvent access controls on US AI models and systematically harvest their outputs to replicate frontier capabilities, are another illicit technique used by PRC labs to catch up to their US counterparts and blunt the impact of export controls. The practice allows labs based in China to free-ride on decades of foundational research, billions of dollars in US investment, and the work of thousands of the world’s best engineers that produced US frontier models. The result is near-frontier capability at a fraction of the cost, subsidized by the United States. It is systematic industrial espionage of a technology critical to long-term US national security interests. OpenAI, Google, Anthropic, and the Frontier Model Forum have all publicly condemned the practice of distillation attacks. 蒸馏攻击（Distillation attacks）是中国实验室用来追赶美国同行并削弱出口管制影响的另一种非法手段。在这种攻击中，位于中国的实验室创建数千个虚假账户，以规避美国 AI 模型的访问控制，并系统性地获取其输出，从而复制前沿能力。这种做法使中国的实验室能够坐享其成，利用美国数十年的基础研究、数十亿美元的投资以及成千上万世界顶尖工程师开发美国前沿模型的成果。其结果是以极低的成本获得了接近前沿的能力，而这实际上是由美国资助的。这是针对一项对美国长期国家安全利益至关重要的技术所进行的系统性工业间谍活动。OpenAI、Google、Anthropic 以及前沿模型论坛（Frontier Model Forum）都已公开谴责了蒸馏攻击行为。
AI experts in China openly acknowledge distillation attacks’ scale and importance to China’s AI development. A recent article in a state-owned media outlet described distillation attacks on US models as the “back door” China’s AI labs depend on as a core part of their business model. An ex-ByteDance researcher said that PRC AI labs use distillation as a shortcut to train models, allowing them to avoid investing into their own data pipelines. 中国的 AI 专家公开承认蒸馏攻击的规模及其对中国 AI 发展的重要性。一家国有媒体最近发表的文章将对美国模型的蒸馏攻击描述为中国 AI 实验室赖以生存的“后门”，并将其视为其商业模式的核心部分。一位前字节跳动研究员表示，中国 AI 实验室将蒸馏作为训练模型的捷径，从而避免投入资金建立自己的数据管道。
US policymakers have moved quickly to address this threat. The White House Office of Science and Technology Policy published a memo on distillation attacks. Senior officials in the White House, Department of War, and members of Congress have also called attention to this problem. Recent legislation from the House Foreign Affairs Committee to address distillation attacks passed out of committee unanimously. 美国政策制定者已迅速采取行动应对这一威胁。白宫科技政策办公室发布了一份关于蒸馏攻击的备忘录。白宫、战争部的高级官员以及国会议员也对这一问题表示了关注。众议院外交事务委员会最近通过了一项旨在解决蒸馏攻击的立法，该法案在委员会内获得一致通过。
If policymakers in the US and allied democracies act to close these two channels propping up China’s AI models—illicit and evasive compute access and illicit model access—then we have a potentially once-in-a-generation opportunity to secure our lead. 如果美国及其盟友民主国家的政策制定者采取行动，关闭支撑中国 AI 模型的这两个渠道——即非法和规避性的算力获取以及非法的模型访问——那么我们就有可能获得一个巩固领先地位的代际机遇。
Below, we describe two hypothetical future scenarios to help illustrate how policy actions taken today can shape where we are in 2028. 下面，我们描述了两种假设的未来情景，以帮助说明今天采取的政策行动将如何塑造我们在 2028 年所处的位置。
场景一：美国及其盟友拥有绝对且不断扩大的领先优势
America’s compute edge remains strong. Despite increased state support for China’s semiconductor industry, China’s chipmakers remain years behind their US and allied counterparts, stymied in part by their inability to access advanced SME tooling, servicing, and maintenance. The US-PRC compute gap is widening as increased US and allied chipmaking capacity comes online and as advanced chipmakers continue to innovate on more efficient and performant chips. In tandem, US policymakers have taken action to close loopholes in the US economic security toolkit, and efforts to smuggle chips into China and access export-controlled chips in data centers outside the country are increasingly frustrated by well-funded enforcement efforts. 美国的算力优势依然强劲。尽管中国加大了对半导体产业的国家支持，但中国的芯片制造商仍落后于美国及其盟友数年，部分原因在于无法获得先进的半导体制造设备（SME）工具、服务和维护。随着美国及其盟友芯片产能的提升，以及先进芯片制造商在更高效、更高性能芯片上的持续创新，美中之间的算力差距正在扩大。与此同时，美国政策制定者已采取行动填补经济安全工具箱中的漏洞，而通过走私芯片进入中国以及在境外数据中心获取受出口管制的芯片的企图，也因资金充足的执法行动而日益受阻。
Consequently, US AI models are 12-24 months ahead on intelligence, and the lead is growing. A small number of AI labs lead at the frontier with the most intelligent, capable, and performant models. All are based in the US. The “country of geniuses in a data center” has become a reality across critical industries, including cybersecurity, finance, healthcare, and life sciences. When US frontier labs release new models in 2028 that achieve step-function advances in capabilities (similar to the relative impact of Mythos Preview in April 2026), China will not have access to similar AI capabilities until 2029 or 2030. This gives critical breathing room for democracies to set the rules and norms of frontier AI systems. 因此，美国 AI 模型在智能水平上领先 12-24 个月，且领先优势正在扩大。少数几家 AI 实验室凭借最智能、最强大且性能最优的模型在尖端领域占据主导地位，且这些实验室全部位于美国。在网络安全、金融、医疗保健和生命科学等关键行业，“数据中心里的天才之国”已成为现实。当美国前沿实验室在 2028 年发布实现能力阶跃式进步的新模型时（类似于 2026 年 4 月 Mythos Preview 的相对影响力），中国直到 2029 年或 2030 年才能获得类似的 AI 能力。这为民主国家制定前沿 AI 系统的规则和规范提供了关键的喘息空间。
American AI is the backbone of the global economy, driving new economic and scientific dynamism. The Trump administration's efforts to drive domestic AI adoption and promote the export of American AI is succeeding, and the resulting gains from the adoption of powerful AI both at home and abroad is driving unprecedented economic growth and technological advancements. Global adoption of US AI has skyrocketed. Democracies’ lead in capabilities and compute mean that China’s AI firms do not compete for global market share outside of a narrow group of autocracies. The world’s top frontier AI systems are shaped by democratic values and make it more difficult for authoritarian states to use AI systems to infringe on rights and civil liberties. 美国人工智能已成为全球经济的支柱，驱动着全新的经济与科学活力。特朗普政府在推动国内人工智能应用及促进美国人工智能出口方面的努力正取得成效，国内外因采用强大的人工智能而获得的收益，正推动着前所未有的经济增长和技术进步。全球对美国人工智能的采用率飙升。民主国家在能力和算力方面的领先地位，意味着中国的人工智能公司除了在少数专制国家外，无法在全球市场份额中进行竞争。世界顶尖的前沿人工智能系统由民主价值观塑造，这使得独裁国家更难利用人工智能系统侵犯人权和公民自由。
Cyber and other national security advantages expand. Public and private sector cyber operators and security professionals use advanced AI systems to reduce the attack surface in America and other democracies and blunt the CCP’s ability to gain and maintain cyber footholds in our systems, making our national security assets, IP, and communications networks more secure. The United States' overwhelming AI advantage is a powerful deterrent to aggression. 网络及其他国家安全优势不断扩大。公共和私营部门的网络运营商及安全专业人员利用先进的人工智能系统，减少了美国和其他民主国家的受攻击面，并削弱了中国共产党在我们的系统中获取和维持网络立足点的能力，使我们的国家安全资产、知识产权和通信网络更加安全。美国压倒性的人工智能优势是对侵略行为的强大威慑。
A self-reinforcing cycle compounds democracies’ leadership. A commanding AI advantage makes the United States and its allies more attractive partners. That alignment expands both the market for American AI and the coalition setting global AI norms, which in turn promotes the development and deployment of AI systems that are safe, secure, and protective of civil liberties. The world’s top technical and scientific talent continues to gravitate to where the frontier is being built. The United States gains significant leverage with which to incentivize cooperation from Beijing on critical issues like AI governance, strategic competition, and trade. This cycle reinforces itself: the lead strengthens the coalition, the coalition strengthens the lead, the democracy-led international order is anchored through the transition to transformative AI. 一种自我强化的循环巩固了民主国家的领导地位。显著的人工智能优势使美国及其盟友成为更具吸引力的合作伙伴。这种结盟既扩大了美国人工智能的市场，也扩大了制定全球人工智能规范的联盟，进而促进了安全、可靠且保护公民自由的人工智能系统的开发与部署。世界顶尖的技术和科学人才继续向构建前沿技术的地区聚集。美国获得了巨大的筹码，用以激励北京在人工智能治理、战略竞争和贸易等关键问题上开展合作。这一循环自我强化：领先地位加强了联盟，联盟加强了领先地位，以民主国家为首的国际秩序在向变革性人工智能转型的过程中得以稳固。
场景二：中共控制的 AI 生态系统并驾齐驱
AI developed and deployed in China is near-frontier on model intelligence. Despite a weak semiconductor production capacity, models trained by PRC AI labs are only a few months behind US models. Ongoing distillation attacks, overseas compute access, weak SME export enforcement, and a loosening of export controls on American semiconductors have assisted CCP efforts. Continued access to US frontier AI for AI R&D have also enabled AI labs in China to close the gap and approach parity with their US counterparts. 在中国开发和部署的 AI 在模型智能方面已接近前沿水平。尽管半导体生产能力较弱，但中国 AI 实验室训练的模型仅落后美国模型几个月。持续的蒸馏攻击、海外算力获取、对中小企业出口执法不力，以及美国半导体出口管制的放宽，都助力了中共的努力。持续获取美国前沿 AI 用于 AI 研发，也使中国的 AI 实验室能够缩小差距，并接近与美国同行持平的水平。
Rapid commercial and state adoption. Beijing has championed a whole-of-nation push on domestic adoption via “AI+” policies. Even though China's AI models are slightly less capable than US models, CCP efforts to accelerate adoption have paid off. China is thus able to deploy near-frontier AI capabilities more advantageously across economic, military, and technological domains, shifting the balance of power in China’s favor. 快速的商业和国家应用。北京通过“AI+”政策，倡导举国体制推动国内应用。尽管中国的 AI 模型能力略逊于美国模型，但中共加速应用的努力已见成效。因此，中国能够更具优势地在经济、军事和技术领域部署近前沿的 AI 能力，使力量平衡向有利于中国的方向转变。
The CCP’s AI-enabled cyber force is a serious threat. The CCP’s integration of AI-enabled cyber capabilities within an already advanced cyber force has sustained the PLA as a menacing cyber competitor. PLA cyber actors have gained additional access to critical and dual-use infrastructure in the US and most countries around the world, enabling them to disrupt critical national security and societal functions. As AI is incorporated deeper into our most critical systems, democracies enjoy no security advantages over China in AI, despite having developed the technology first. 中共支持的 AI 网络力量是一个严重威胁。中共将 AI 网络能力整合到其本已先进的网络力量中，使解放军维持了其作为威胁性网络竞争者的地位。解放军网络行为体已获得更多进入美国及全球大多数国家关键和军民两用基础设施的权限，使其能够破坏关键的国家安全和社会功能。随着 AI 被更深入地整合到我们最关键的系统中，尽管民主国家率先开发了这项技术，但在 AI 领域对中国并不享有安全优势。
Beijing is winning in global adoption on cost and on-prem flexibility. Huawei and Alibaba data centers are globally prevalent, especially in, but not limited to, lower cost markets in the Global South. These data centers scale on older chips, which China is able to export because it can serve its domestic market with a combination of US chips purchased with an export license, smuggled into China, or remotely accessed in overseas data centers. They host second-tier, but cheaper and still effective models produced by PRC labs. Similar to the Huawei playbook of being cheap and “good enough,” China’s near-frontier models and hardware support a non-trivial and rapidly growing segment of the global economy. This infrastructure advantage gives CCP leadership significant influence over those markets. 北京在成本和本地部署灵活性方面正赢得全球应用。华为和阿里巴巴的数据中心在全球范围内普遍存在，尤其是在（但不限于）全球南方国家的低成本市场。这些数据中心利用旧芯片进行扩展，中国之所以能够出口这些芯片，是因为它可以通过购买获得出口许可的美国芯片、走私进入中国或远程访问海外数据中心来满足其国内市场需求。这些数据中心托管着由中国实验室生产的虽属第二梯队但更便宜且依然有效的模型。类似于华为“廉价且足够好”的策略，中国的近前沿模型和硬件支撑着全球经济中一个不容小觑且快速增长的部分。这种基础设施优势使中共领导层对这些市场拥有重大影响力。
确保民主国家保持领先
To ensure we land in scenario one, we support the following areas of policy action. 为了确保我们能够进入第一种情境，我们支持以下领域的政策行动。
America and its allies have developed both the world’s most capable frontier AI models and the world’s most advanced inputs to AI. This has provided a substantial advantage. If our superior access to that technology is defended, that advantage can be extended. But it will be lost if it is given directly to our competitors. The decisions made by policymakers this year will determine the future of transformative AI. We support those working to ensure that American and allied democracies are winning in 2028. 美国及其盟友已经开发出世界上能力最强的尖端人工智能模型，以及全球最先进的人工智能投入要素。这提供了巨大的优势。如果我们能够捍卫在获取该技术方面的卓越地位，这种优势就可以得到延伸。但如果将其直接拱手让给竞争对手，这种优势将会丧失。政策制定者在今年做出的决定将决定变革性人工智能的未来。我们支持那些致力于确保美国及其盟友民主国家在 2028 年赢得胜利的人们。
New research on how we've reduced agentic misalignment. 关于我们如何减少代理失调（agentic misalignment）的新研究。
自然语言自编码器：将 Claude 的想法转化为文本
AI models like Claude talk in words but think in numbers. In this study we train Claude to translate its thoughts into human-readable text. 像 Claude 这样的 AI 模型用文字交流，但用数字思考。在这项研究中，我们训练 Claude 将其想法转化为人类可读的文本。
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