I would like to clarify a few things.
我希望先就若干要点予以澄清。
First, the obvious one: we do not have or want government guarantees for OpenAI datacenters. We believe that governments should not pick winners or losers, and that taxpayers should not bail out companies that make bad business decisions or otherwise lose in the market. If one company fails, other companies will do good work.
首先，也是最显而易见的一点：OpenAI 的数据中心既未获得，也无意寻求政府担保。我们认为，政府不应充当裁判来决定企业的成败，纳税人的辛苦钱更不该为企业的失策或市场失利买单。即便某家公司倒下，仍会有其他公司接续努力，继续创造出色成果。
What we do think might make sense is governments building (and owning) their own AI infrastructure, but then the upside of that should flow to the government as well. We can imagine a world where governments decide to offtake a lot of computing power and get to decide how to use it, and it may make sense to provide lower cost of capital to do so. Building a strategic national reserve of computing power makes a lot of sense. But this should be for the government’s benefit, not the benefit of private companies.
我们认为，较为明智的做法，是由政府亲自建设并掌握自己的人工智能基础设施，并确保所有增益反哺公共利益。我们不难想象这样的场景：政府大规模包购算力，自主决定其用途；为实现此举，提供更低的融资成本亦合情合理。建立国家级的战略算力储备意义重大，但这应当着眼于国家与公众的利益，而非私营企业的私利。
The one area where we have discussed loan guarantees is as part of supporting the buildout of semiconductor fabs in the US, where we and other companies have responded to the government’s call and where we would be happy to help (though we did not formally apply). The basic idea there has been ensuring that the sourcing of the chip supply chain is as American as possible in order to bring jobs and industrialization back to the US, and to enhance the strategic position of the US with an independent supply chain, for the benefit of all American companies. This is of course different from governments guaranteeing private-benefit datacenter buildouts.
迄今为止，我们仅在一个领域讨论过贷款担保——支持在美国本土建设半导体晶圆厂。在这方面，我们与其他企业一道积极响应政府号召，并乐于投身其中（尽管尚未正式提出申请）。此举的核心在于最大限度实现芯片供应链的本土化，让就业与制造能力重回美国，并借由独立自主的供应链巩固国家战略地位，惠及所有美国企业。需特别指出的是，这与政府为纯粹谋取私利的数据中心扩建提供担保，性质截然不同。
There are at least 3 “questions behind the question” here that are understandably causing concern.
在这个问题背后，至少还潜藏着三个更深层的“隐含疑问”，难免令人忧虑。
First, “How is OpenAI going to pay for all this infrastructure it is signing up for?” We expect to end this year above $20 billion in annualized revenue run rate and grow to hundreds of billion by 2030. We are looking at commitments of about $1.4 trillion over the next 8 years. Obviously this requires continued revenue growth, and each doubling is a lot of work! But we are feeling good about our prospects there; we are quite excited about our upcoming enterprise offering for example, and there are categories like new consumer devices and robotics that we also expect to be very significant. But there are also new categories we have a hard time putting specifics on like AI that can do scientific discovery, which we will touch on later.
首先，人们关心的一个核心问题是：“OpenAI 将如何承担已签约的庞大基础设施成本？”我们预计到今年年底，公司的年化营收规模将超过 200 亿美元，并有望在 2030 年增至数千亿美元。未来八年，我们计划投入约 1.4 万亿美元以履行相关承诺。要实现这一目标，收入必须持续成倍增长，而每一次翻番都意味着艰巨的努力！尽管如此，我们对前景仍充满信心。即将推出的企业级产品令人振奋，面向终端消费者的新型设备和机器人等领域也被视为重要增长引擎。此外，还有一些尚难量化的新赛道——例如能够推动科学发现的人工智能——我们将在后文进一步阐述。
We are also looking at ways to more directly sell compute capacity to other companies (and people); we are pretty sure the world is going to need a lot of “AI cloud”, and we are excited to offer this. We may also raise more equity or debt capital in the future.
But everything we currently see suggests that the world is going to need a great deal more computing power than what we are already planning for.
我们也在积极探索向其他企业乃至个人更直接地销售算力的途径。我们笃信，世界对“AI云”服务的需求必将激增，对此我们满怀期待，并将不遗余力地提供卓越的解决方案。展望未来，我们亦可能通过增发股权或发行债券等方式进一步筹集资本。
然而，一切迹象都表明，全球对计算能力的渴求将远远超出我们现行的规划与准备。
Second, “Is OpenAI trying to become too big to fail, and should the government pick winners and losers?” Our answer on this is an unequivocal no. If we screw up and can’t fix it, we should fail, and other companies will continue on doing good work and servicing customers. That’s how capitalism works and the ecosystem and economy would be fine. We plan to be a wildly successful company, but if we get it wrong, that’s on us.
其次，对于“OpenAI是否打算成为‘大而不能倒’，政府是否应替市场选定输赢”这一疑问，我们的回答斩钉截铁：绝不。如果我们犯错而无力补救，就应自行承担失败的后果；届时，其他公司仍会继续创新，服务客户，生态与经济体系自有其韧性。我们立志成为一家卓越且长青的企业，但若终有失手，也当由我们自行负责。
Our CFO talked about government financing yesterday, and then later clarified her point underscoring that she could have phrased things more clearly. As mentioned above, we think that the US government should have a national strategy for its own AI infrastructure.
昨日，我们的首席财务官就政府融资议题发表了看法；随后她进一步澄清，坦言自己的措辞尚可更为精准。如上文所述，我们认为美国政府应为自身的人工智能基础设施制定一项国家级战略。
Tyler Cowen asked me a few weeks ago about the federal government becoming the insurer of last resort for AI, in the sense of risks (like nuclear power) not about overbuild. I said “I do think the government ends up as the insurer of last resort, but I think I mean that in a different way than you mean that, and I don’t expect them to actually be writing the policies in the way that maybe they do for nuclear”. Again, this was in a totally different context than datacenter buildout, and not about bailing out a company. What we were talking about is something going catastrophically wrong—say, a rogue actor using an AI to coordinate a large-scale cyberattack that disrupts critical infrastructure—and how intentional misuse of AI could cause harm at a scale that only the government could deal with. I do not think the government should be writing insurance policies for AI companies.
几周前，Tyler Cowen 问我，联邦政府是否应在人工智能领域充当“最后保险人”——所指并非产能过剩，而是类似核能行业那样的系统性风险。我当时答道：“我确实认为政府最终可能扮演最后保险人的角色，但我的理解与您的提法并不完全相同；我并不期待政府会像对核能那样亲自承保相关风险。”我们讨论的场景与数据中心扩建无关，更不是关于企业纾困。我们关注的是，当某些事态出现灾难性失控——比如不法分子操纵 AI 发动大规模网络攻击，致关键基础设施瘫痪——其带来的危害之巨，恐怕唯有政府具备应对能力。简言之，我并不认为政府应为 AI 企业订立保险单。
Third, “Why do you need to spend so much now, instead of growing more slowly?”. We are trying to build the infrastructure for a future economy powered by AI, and given everything we see on the horizon in our research program, this is the time to invest to be really scaling up our technology. Massive infrastructure projects take quite awhile to build, so we have to start now.
第三，“为什么要现在就投入如此巨额资金，而不选择循序渐进的增长？”我们正在为一个由人工智能驱动的未来经济奠筑基础设施。从当前的研发前景来看，此刻正是大规模加码、迅速扩展技术的最佳窗口。如此宏大的基础设施工程周期漫长，唯有立即动手，方能抢得先机。
Based on the trends we are seeing of how people are using AI and how much of it they would like to use, we believe the risk to OpenAI of not having enough computing power is more significant and more likely than the risk of having too much. Even today, we and others have to rate limit our products and not offer new features and models because we face such a severe compute constraint.
根据我们对用户使用人工智能方式及需求规模的观察，与“算力过剩”相比，“算力不足”对 OpenAI 构成的风险更大也更迫在眉睫。即便是如今，我们与同行都不得不给产品设定调用上限，推迟发布新功能和新模型，只因算力缺口之严峻。
In a world where AI can make important scientific breakthroughs but at the cost of tremendous amounts of computing power, we want to be ready to meet that moment. And we no longer think it’s in the distant future. Our mission requires us to do what we can to not wait many more years to apply AI to hard problems, like contributing to curing deadly diseases, and to bring the benefits of AGI to people as soon as possible.
在这个人工智能凭借海量算力得以实现重大科学突破的时代，我们必须为那一刻做好万全准备——而它已不再遥远。我们的使命敦促我们全力以赴，不能再虚掷岁月；要尽早将人工智能投入诸如攻克致命疾病等艰巨难题，并让通用人工智能（AGI）的福祉尽速惠及全人类。
Also, we want a world of abundant and cheap AI. We expect massive demand for this technology, and for it to improve people’s lives in many ways.
此外，我们期望迎来一个人工智能既丰富充裕又成本低廉的时代。我们相信，这项技术必将激发巨大的需求，并将在生活的诸多层面切实增益人类福祉。
It is a great privilege to get to be in the arena, and to have the conviction to take a run at building infrastructure at such scale for something so important. This is the bet we are making, and given our vantage point, we feel good about it. But we of course could be wrong, and the market—not the government—will deal with it if we are.
能置身此局、怀抱笃定，着手兴建如此宏大的关键基础设施，实乃莫大殊荣。此即我们押下的赌注，而凭借当下的视角，我们对未来深具信心。然人非圣贤，亦难免失算；倘若果真如此，评判与处置当由市场，而非政府。