首页人物观点我想澄清几件事。首先，最显而易见的一点：我们并没有、也不希望获得任何政府对 OpenAI 数据中心的担保。我们相信政府不应当“选边站”，不应决定谁赢谁输，也不应让纳税人为企业的错误商业决策或市场失败买单。如果一家企业倒下，其他公司依然会做出出色的工作。我们认为合理的方向是：政府可以建设并拥有自己的 AI 基础设施，但其收益也应归政府所有。可以想象一个未来——政府购买并掌握大量算力，自主决定其用途；在这种情况下，为其提供较低的融资成本可能是合理的。建立国家战略级算力储备确实非常有意义，但这应该是为了国家利益，而不是私企的利益。我们唯一讨论过“贷款担保”的领域，是美国半导体晶圆厂建设。我们和其他公司响应了政府号召，愿意在这方面提供帮助（虽然我们并未正式申请）。其核心理念是：让芯片供应链尽可能“美国化”，以创造就业、推动再工业化，并以独立供应链强化美国的战略地位——这将惠及所有美国企业。这显然与“政府为私营数据中心建设提供担保”完全不同。目前有至少三个“问题背后的问题”，引发了公众的合理关切。第一，“OpenAI 要如何为庞大的基础设施支出买单？” 我们预计今年的年化营收将超过 200 亿美元，并在 2030 年前增长到数千亿美元级别。未来 8 年，我们计划投入约 1.4 万亿美元。显然，这需要持续的营收增长，每次翻倍都不容易！但我们对前景充满信心——例如，我们即将推出的新企业服务令人振奋，此外像AI 消费设备和机器人等领域也将成为重要增长点。还有一些新兴领域，如能进行科学发现的 AI，其商业潜力目前难以量化。我们也在考虑将算力直接出售给其他公司或个人——我们非常确定，世界将需要大量“AI 云计算”，而我们乐于提供此类服务。未来我们可能还会发行新股或筹集债务资金。但从我们目前的观察来看，全球对计算能力的需求远超我们现有的规划。第二，“OpenAI 是否在变成‘大到不能倒’，政府是否会因此偏袒？” 我们的回答是明确的否定。如果我们犯错而无法修复，就该失败。其他公司会继续创新、服务客户——这正是资本主义的运作方式，整个生态和经济体系会继续良性发展。我们当然希望成为一家极度成功的公司，但如果失败，那是我们的责任。我们的 CFO 昨天谈到政府融资问题，之后也澄清，她的措辞本应更精确。如前所述，我们认为美国政府应制定自己的 AI 基础设施国家战略。几周前，经济学家 Tyler Cowen 问我：联邦政府是否会成为 AI 的“最后保险人”（类似于核能风险）。我回答说：“我认为政府最终确实会成为最后的保险人，但我理解的方式与你不同；我不认为政府会像核能那样真的去‘承保’。” 这完全与“数据中心建设”无关，也不是在谈“救助企业”，而是在讨论AI 可能带来的灾难性风险——例如，被恶意行为者用于发动大规模网络攻击、破坏关键基础设施。这种情况下，只有政府有能力应对。但我并不认为政府应该为 AI 企业提供保险。第三，“为什么现在要花这么多钱，而不是慢慢扩张？” 我们正在构建未来 AI 经济的基础设施。根据我们的研究趋势，现在正是扩大技术规模的关键时机。大型基础设施建设周期长，因此必须尽早开始。从用户使用 AI 的趋势来看，我们认为： 👉 算力不足的风险远大于算力过剩的风险。即便在今天，我们和其他公司都不得不限制产品速率、延迟新功能，因为算力极度紧缺。在一个 AI 能推动重大发现（如科学突破）但需要巨量算力的世界中，我们希望提前做好准备。而我们认为这已不是遥远的未来。我们的使命要求我们不要再等待多年才让 AI 投入应对现实难题，比如攻克致命疾病，并尽快让 AGI（通用人工智能）惠及大众。我们还希望创造一个AI 丰富且低成本的世界。我们预计这项技术将有巨大的需求，并以多种方式改善人们的生活。能身处这一关键舞台，参与如此规模的基础建设，是一种极大的荣幸。我们坚信这是值得的赌注，并对自己的视角与判断充满信心。但我们也清楚：如果我们错了，应该由市场——而非政府——来决定结果。 I would like to clarify a few things. 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. 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. 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. There are at least 3 “questions behind the question” here that are understandably causing concern. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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.

我想澄清几件事。首先，最显而易见的一点：我们并没有、也不希望获得任何政府对 OpenAI 数据中心的担保。我们相信政府不应当“选边站”，不应决定谁赢谁输，也不应让纳税人为企业的错误商业决策或市场失败买单。如果一家企业倒下，其他公司依然会做出出色的工作。我们认为合理的方向是：政府可以建设并拥有自己的 AI 基础设施，但其收益也应归政府所有。可以想象一个未来——政府购买并掌握大量算力，自主决定其用途；在这种情况下，为其提供较低的融资成本可能是合理的。建立国家战略级算力储备确实非常有意义，但这应该是为了国家利益，而不是私企的利益。我们唯一讨论过“贷款担保”的领域，是美国半导体晶圆厂建设。我们和其他公司响应了政府号召，愿意在这方面提供帮助（虽然我们并未正式申请）。其核心理念是：让芯片供应链尽可能“美国化”，以创造就业、推动再工业化，并以独立供应链强化美国的战略地位——这将惠及所有美国企业。这显然与“政府为私营数据中心建设提供担保”完全不同。目前有至少三个“问题背后的问题”，引发了公众的合理关切。第一，“OpenAI 要如何为庞大的基础设施支出买单？” 我们预计今年的年化营收将超过 200 亿美元，并在 2030 年前增长到数千亿美元级别。未来 8 年，我们计划投入约 1.4 万亿美元。显然，这需要持续的营收增长，每次翻倍都不容易！但我们对前景充满信心——例如，我们即将推出的新企业服务令人振奋，此外像AI 消费设备和机器人等领域也将成为重要增长点。还有一些新兴领域，如能进行科学发现的 AI，其商业潜力目前难以量化。我们也在考虑将算力直接出售给其他公司或个人——我们非常确定，世界将需要大量“AI 云计算”，而我们乐于提供此类服务。未来我们可能还会发行新股或筹集债务资金。但从我们目前的观察来看，全球对计算能力的需求远超我们现有的规划。第二，“OpenAI 是否在变成‘大到不能倒’，政府是否会因此偏袒？” 我们的回答是明确的否定。如果我们犯错而无法修复，就该失败。其他公司会继续创新、服务客户——这正是资本主义的运作方式，整个生态和经济体系会继续良性发展。我们当然希望成为一家极度成功的公司，但如果失败，那是我们的责任。我们的 CFO 昨天谈到政府融资问题，之后也澄清，她的措辞本应更精确。如前所述，我们认为美国政府应制定自己的 AI 基础设施国家战略。几周前，经济学家 Tyler Cowen 问我：联邦政府是否会成为 AI 的“最后保险人”（类似于核能风险）。我回答说：“我认为政府最终确实会成为最后的保险人，但我理解的方式与你不同；我不认为政府会像核能那样真的去‘承保’。” 这完全与“数据中心建设”无关，也不是在谈“救助企业”，而是在讨论AI 可能带来的灾难性风险——例如，被恶意行为者用于发动大规模网络攻击、破坏关键基础设施。这种情况下，只有政府有能力应对。但我并不认为政府应该为 AI 企业提供保险。第三，“为什么现在要花这么多钱，而不是慢慢扩张？” 我们正在构建未来 AI 经济的基础设施。根据我们的研究趋势，现在正是扩大技术规模的关键时机。大型基础设施建设周期长，因此必须尽早开始。从用户使用 AI 的趋势来看，我们认为： 👉 算力不足的风险远大于算力过剩的风险。即便在今天，我们和其他公司都不得不限制产品速率、延迟新功能，因为算力极度紧缺。在一个 AI 能推动重大发现（如科学突破）但需要巨量算力的世界中，我们希望提前做好准备。而我们认为这已不是遥远的未来。我们的使命要求我们不要再等待多年才让 AI 投入应对现实难题，比如攻克致命疾病，并尽快让 AGI（通用人工智能）惠及大众。我们还希望创造一个AI 丰富且低成本的世界。我们预计这项技术将有巨大的需求，并以多种方式改善人们的生活。能身处这一关键舞台，参与如此规模的基础建设，是一种极大的荣幸。我们坚信这是值得的赌注，并对自己的视角与判断充满信心。但我们也清楚：如果我们错了，应该由市场——而非政府——来决定结果。 I would like to clarify a few things. 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. 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. 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. There are at least 3 “questions behind the question” here that are understandably causing concern. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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.

Sam AltmanCo-founder & CEO, OpenAI

2025/11/06 19:36 UTC

观点原文

我想澄清几件事。

首先，最显而易见的一点：我们并没有、也不希望获得任何政府对 OpenAI 数据中心的担保。我们相信政府不应当“选边站”，不应决定谁赢谁输，也不应让纳税人为企业的错误商业决策或市场失败买单。如果一家企业倒下，其他公司依然会做出出色的工作。

我们认为合理的方向是：政府可以建设并拥有自己的 AI 基础设施，但其收益也应归政府所有。可以想象一个未来——政府购买并掌握大量算力，自主决定其用途；在这种情况下，为其提供较低的融资成本可能是合理的。建立国家战略级算力储备确实非常有意义，但这应该是为了国家利益，而不是私企的利益。

我们唯一讨论过“贷款担保”的领域，是美国半导体晶圆厂建设。我们和其他公司响应了政府号召，愿意在这方面提供帮助（虽然我们并未正式申请）。其核心理念是：让芯片供应链尽可能“美国化”，以创造就业、推动再工业化，并以独立供应链强化美国的战略地位——这将惠及所有美国企业。这显然与“政府为私营数据中心建设提供担保”完全不同。

目前有至少三个“问题背后的问题”，引发了公众的合理关切。

第一，“OpenAI 要如何为庞大的基础设施支出买单？”

我们预计今年的年化营收将超过 200 亿美元，并在 2030 年前增长到数千亿美元级别。未来 8 年，我们计划投入约 1.4 万亿美元。显然，这需要持续的营收增长，每次翻倍都不容易！但我们对前景充满信心——例如，我们即将推出的新企业服务令人振奋，此外像AI 消费设备和机器人等领域也将成为重要增长点。

还有一些新兴领域，如能进行科学发现的 AI，其商业潜力目前难以量化。

我们也在考虑将算力直接出售给其他公司或个人——我们非常确定，世界将需要大量“AI 云计算”，而我们乐于提供此类服务。未来我们可能还会发行新股或筹集债务资金。

但从我们目前的观察来看，全球对计算能力的需求远超我们现有的规划。

第二，“OpenAI 是否在变成‘大到不能倒’，政府是否会因此偏袒？”

我们的回答是明确的否定。如果我们犯错而无法修复，就该失败。其他公司会继续创新、服务客户——这正是资本主义的运作方式，整个生态和经济体系会继续良性发展。

我们当然希望成为一家极度成功的公司，但如果失败，那是我们的责任。

我们的 CFO 昨天谈到政府融资问题，之后也澄清，她的措辞本应更精确。如前所述，我们认为美国政府应制定自己的 AI 基础设施国家战略。

几周前，经济学家 Tyler Cowen 问我：联邦政府是否会成为 AI 的“最后保险人”（类似于核能风险）。我回答说：“我认为政府最终确实会成为最后的保险人，但我理解的方式与你不同；我不认为政府会像核能那样真的去‘承保’。”

这完全与“数据中心建设”无关，也不是在谈“救助企业”，而是在讨论AI 可能带来的灾难性风险——例如，被恶意行为者用于发动大规模网络攻击、破坏关键基础设施。

这种情况下，只有政府有能力应对。但我并不认为政府应该为 AI 企业提供保险。

第三，“为什么现在要花这么多钱，而不是慢慢扩张？”

我们正在构建未来 AI 经济的基础设施。根据我们的研究趋势，现在正是扩大技术规模的关键时机。大型基础设施建设周期长，因此必须尽早开始。

从用户使用 AI 的趋势来看，我们认为：

👉 算力不足的风险远大于算力过剩的风险。

即便在今天，我们和其他公司都不得不限制产品速率、延迟新功能，因为算力极度紧缺。

在一个 AI 能推动重大发现（如科学突破）但需要巨量算力的世界中，我们希望提前做好准备。而我们认为这已不是遥远的未来。

我们的使命要求我们不要再等待多年才让 AI 投入应对现实难题，比如攻克致命疾病，并尽快让 AGI（通用人工智能）惠及大众。

我们还希望创造一个AI 丰富且低成本的世界。我们预计这项技术将有巨大的需求，并以多种方式改善人们的生活。

能身处这一关键舞台，参与如此规模的基础建设，是一种极大的荣幸。

我们坚信这是值得的赌注，并对自己的视角与判断充满信心。

但我们也清楚：如果我们错了，应该由市场——而非政府——来决定结果。

I would like to clarify a few things.

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.

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.

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.

There are at least 3 “questions behind the question” here that are understandably causing concern.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

AIOpenAIFounder

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