All things AI w @altcap @sama & @satyanadella. A Halloween Special. 🎃🔥BG2 w/ Brad Gerstner
发布时间 2025-10-31 23:17:31 来源
I think this has really been an amazing partnership through every phase. We had no idea where I was going to go when we started, as Satya said. But I don't think this is one of the great tech partnerships ever. And certainly without Microsoft and particularly Sauts' early conviction, we would not have been able to do that. What a week, what a week. Great to see you both. Sam, how's the baby? Baby is great. That's the best thing I've ever. Every cliche is true and it is the best thing ever. Hey Satya, with all your time. And the smile on Sam's face when he talks about, it's just his baby. It's just so different. I got it and compute. I guess when he talks about computing his baby.
我认为这真的是一个在每个阶段都很棒的合作关系。正如Satya所说，当我们开始时，我们不知道会走向何方。但我不认为这是科技界有史以来最伟大的合作之一。毫无疑问，如果没有微软，特别是Sauts早期的信念，我们不可能做到这一点。这真是了不起的一周，太高兴见到你们俩。Sam，宝宝怎么样？宝宝很好，这是我经历过的最棒的事情。每一个老套的话都是对的，这是最棒的事情。嘿，Satya，无论如何，看到Sam谈论他的宝宝时脸上的笑容，真的是与众不同。我明白他在谈论他的“计算宝宝”时的感觉。
Well, Satya, have you given any dad tips with all this time you guys have spent together? I said just enjoy it. I mean, it's so awesome that you know, we had our babies or what our children are so young. And I wish I could redo it. So in some sense, it's just the most precious time. And as they grow, it's just so wonderful. I'm so glad to see him is. I'm happy I'm doing it older, but I do think sometimes man, I wish I had the energy of when I was like 25. That part's harder. No, not about it. What's the average age at Open AI Sam? Any idea? It's young. It's not crazy young. Not like most Silicon Valley startups. I don't know, maybe low 30s average. Are babies trending positively or negatively? Babies trending positively. Oh, that's good. That's good.
好吧，Satya，你在这段时间有没有给过一些当爸爸的建议？我说只要好好享受就行。我是说，看到我们的孩子还这么小，这真是太棒了。我真希望能够重新经历一次，所以从某种意义上说，这是最珍贵的时光。看着他们长大是多么美好。我很高兴自己在年纪大一点的时候体验这段经历，但有时我会想，要是我还有25岁时的精力就好了。那部分确实比较困难，这没有疑问。OpenAI的平均年龄是多少呢？有概念吗？挺年轻的，但也不是特别年轻，不像硅谷的大多数初创公司。我猜大概是30岁出头的平均年龄。婴儿的趋势是正面还是负面呢？婴儿的趋势是正面的。哦，那很好，那很好。
Yeah. Well, you guys such a big week. You know, I was thinking about I started at Nvidia's GTC, you know, just hit five trillion dollars. Google, Meta, Microsoft, Sacha, do you had your any just today? You know, and we heard consistently not enough compute, not enough compute, not enough compute. We got rate cuts on Wednesday, the GDP is tracking near 4%. And then I was just saying to Sam, you know, the presidents cut these massive deals in Malaysia, South Korea, Japan, sounds like with China. You know, deals that really incredibly provide the financial firepower to reindustrialize America. 80 billion for new nuclear vision, all the things that you guys need to build more compute.
好的。你们这一周真是不简单。我想到Nvidia在他们的GTC大会上，市值刚刚达到5万亿美元。谷歌、Meta、微软和萨蒂亚都参与了今天的会议。我们反复听到的是计算资源不够、不够、不够。星期三有降息，而GDP增长接近4%。然后我跟Sam说，总统在马来西亚、韩国、日本，听说也在中国达成了一些大规模的协议。协议提供了惊人的财政支持来实现美国的再工业化。为了建造更多的计算能力，还将投入800亿美元用于新的核能愿景。
But certainly wasn't, what wasn't lost in all of this was you guys had a big announcement on Tuesday that clarified your partnership. Congrats on that. And I thought we'd just start there. I really want to just break down the deal in really simple plain language to make sure I understand it and others. But, you know, we'll just start with your investment, Sacha. You know, Microsoft started investing in 2019 is investing the ballpark at $1314 billion into open AI. And for that, you get 27% of the business ownership in the business on a fully diluted basis. I think it was about a third and you took some dilution over the course of last year with all the investment. So does that sound about right terms of ownership?
当然，这其中没有被忽略的一点是，你们在星期二发布了一个重大公告，进一步明确了你们的合作伙伴关系，恭喜你们。我想从这里开始讨论。我真的希望能够用简单明了的语言来解释这项协议，以便我和其他人能更好地理解。我们先从你的投资说起，Sacha。微软自2019年开始投资，向OpenAI投资了大约1314亿美元，以此获得公司27%的所有权，以全面稀释后的计算来看。我想投入后稀释了大约三分之一，所以去年的所有投资过程中你们的股份也有一些稀释。这样的所有权比例听起来是否正确？
Yeah, it does. But I would say before even our stake in it, Brad, I think what's pretty unique about open AI is the fact that as part of open AI's process of restructuring one of the largest non-profit data. And the biggest non-profit gets created. I mean, let's not forget that in some sense, I say at Microsoft, we are very proud of the fact that we were associated with the two of the largest non-profit, the Gates Foundation and now the Open AI Foundation. So that's, I think, the big news. We obviously were thrilled. It's not what we thought. And as I said to somebody, it's not like when we first invested our billion dollars, that this is going to be the 100-bagger that I'm going to be talking about to VCs about. There we are, but we are very thrilled to be an investor and an early backer.
是的，确实如此。但在我们参与其中之前，Brad，我想说开放AI的独特之处在于它在重组过程中成立了一个最大的非营利性数据组织。而且最大的非营利组织就此诞生。我们不能忘记，从某种意义上讲，我在微软时，我们很自豪地与两个最大的非营利组织有联系，一个是盖茨基金会，现在是开放AI基金会。我认为这是个重要的消息。我们显然感到非常激动。这并不是我们最初的预期。正如我对某人所说，当我们首次投资十亿美元时，我们并没有想过这会成为让风险资本家们惊叹的百倍回报投资。但是如今我们身处其境，我们仍然很高兴能成为投资者和早期支持者。
And it's great. And it's really a testament to what Sam and team have done quite frankly. I mean, they obviously had the vision early about what this technology could do and they ran with it and just executed in a masterful way. I think this is really an amazing partnership through everything. We had kind of no idea where I was looking to go when we started, as Satya said, but I don't think I think this is one of the great tech partnerships ever and without, certainly without Microsoft, in particularly, SOTUS, early conviction. We would not have been able to do this. I don't think there were a lot of other people that would have been willing to take that kind of a bet given what the world looked like at the time.
这真是太棒了。这确实充分证明了Sam和他的团队所做的工作。坦白说，他们显然早早就对这项技术的潜力有了远见，然后开始全力以赴地投入，并以一种高超的方式执行。我认为这真的是一个令人惊叹的合作伙伴关系。正如Satya所说，当我们开始时，我并不知道会走向何方，但我认为这是有史以来最伟大的科技合作之一。特别是没有微软的坚定支持，尤其是他们在早期的坚定信念，我们是无法做到这一点的。在当时的情况下，我认为很少有人会愿意承担这样的风险。
We didn't know exactly how the tech was going to go. Well, not exactly. We didn't know at all how the tech was going to go. We just had a lot of conviction in this one idea of pushing on deep learning and trusting that if we could do that, we'd figure out ways to make wonderful products and create a lot of value. And also, as Satya said, create what we believe will be the largest nonprofit ever. And I think it's going to do amazingly great things. It was, I really like this structure because it lets the nonprofit grow in value while the PBC is able to get the capital that it needs to keep scaling. I don't think the nonprofit would be able to be this valuable if we didn't come up with the structure, if we didn't have partners around the table that we're excited for it to work this way. But, you know, I think it's been six, more than six years since we first started this partnership.
我们起初并不确切知道这项技术的发展方向。说实话，我们完全不知道它会走向何方。我们只是对推动深度学习这一想法充满信心，并相信如果能做到这一点，我们就能找到方法来创造出精彩的产品并创造大量的价值。而且，正如Satya所说，我们相信这会成为有史以来最大的非营利组织，并将实现非凡的成就。我非常喜欢这种结构，因为它让非营利组织可以在价值上成长，同时公共利益公司能够获得需要的资本来不断扩大规模。我认为，如果我们没有设计出这种结构，并且没有激动地参与其中的合作伙伴，非营利组织就不会有如此大的价值。但你知道，自从我们第一次开启这一合作，至今已经过了六年以上了。
And the pretty crazy amount of achievement for six years. And I think much, much more to come. I hope that Satya makes a trillion dollars on the investment, not 100 billion. You know what I'm saying? Well, as part of the restructuring, you guys talked about it. You have this nonprofit on top and a public benefit court below. It's pretty insane. The nonprofit is already capitalized with $130 billion, $130 billion of open AI stock. It's one of the largest in the world out of the gates. It could end up being much, much larger. The California Attorney General said they're not going to object to it. You already have $130 billion dedicated to making sure that AGI benefits all of humanity. You announced that you're going to direct the first $25 billion to health and AI security and resilience, Sam.
在六年的时间里取得了非常惊人的成就，我认为未来还有更多值得期待。我希望Satya能够通过这项投资赚到一万亿美元，而不是仅仅一千亿。你明白我的意思吧？在重组的过程中，你们谈到了这个问题。你们在上面设立了一个非营利组织，下面是一个公共福利公司。这真是非常疯狂。非营利组织已经拥有价值1300亿美元的资本，主要是OpenAI的股票，这是全球最庞大的初创资本之一，并且可能会变得更庞大。加利福尼亚总检察长表示他们不会对此提出异议。你们已经有1300亿美元专注于确保AGI（通用人工智能）能够惠及全人类。你们宣布将首批250亿美元用于健康、AI安全以及韧性建设，Sam。
First, let me just say, you know, as somebody who participates in the ecosystem, kudos to you both. It's incredible. This contribution to the future of AI. But Sam, talk to us a bit about the importance of the choice around health and resilience. And then help us understand how do we make sure that you get maximal benefit without it getting weighted down as we've seen with so many nonprofits with its own political biases? Yeah. First of all, the best way to create a bunch of value for the world is hopefully what we're we've already been doing, which is to make these amazing tools and just let people use them. And I think capitalism is great. I think companies are great. I think people are doing amazing work getting advanced AI into the hands of a lot of people and companies that are doing incredible things.
首先，我想说，作为生态系统的一员，向你们致敬。你们为AI的未来做出了不可思议的贡献。但是，Sam，请和我们谈谈在健康和复原力选择方面的重要性。然后帮我们理解一下，如何确保你们能够获得最大的收益，而不是像我们在许多非营利组织中看到的那样，因为自身的政治偏见而受到拖累？
首先，创造价值的最佳方式就是希望我们已经在做的事情，那就是制作这些了不起的工具并让人们使用。我认为资本主义很好，公司也很好。我认为很多人正在做着出色的工作，把先进的AI带给许多人和正在做着不可思议事情的公司。
There are some areas where the, I think, market forces don't quite work for what's in the best interest of people and you do need to do things in a different way. There are also some new things with this technology that just haven't existed before, like the potential to use AI to do science at a rapid clip, like really truly automated discovery. And when we thought about the areas we wanted to first focus on, clearly if we can cure a lot of disease and make the data and information for that broadly available, that would have a wonderful thing to do for the world. And then on this point of AI resilience, I do think some things may get a little strange and they won't all be addressed by companies doing their thing.
在某些领域，我认为市场力量并不能完全满足人们的最佳利益，因此需要采用不同的方法。在这项技术中也存在一些新事物，以前从未出现过，比如利用人工智能来快速推动科学进步，实现真正自动化的发现。当我们考虑优先关注的领域时，很明显，如果我们能够治愈许多疾病，并使这些数据和信息广泛可用，那将是为世界做的一件好事。关于人工智能的韧性问题，我确实认为某些事情可能会变得有些奇怪，而这些问题并不全都能通过企业自身的行动来解决。
So as the world has to navigate through this transition, if we can fund some work to help with that, and that could be cyber defense, that could be AI safety research, that could be economic studies, all of these things, helping society through this transition smoothly. We're very confident about how great it can be on the other side, but I'm sure there will be some choppyness along the way. Let's keep us through the deal. So models and exclusivity, Sam, open AI can distribute its models, it's leading models on Azure, but I don't think you can distribute them on any other leading the big clouds for seven years until 2032. But that would end earlier if AGI is verified, we can come back to that, but you can distribute your open source models, Sora agents, codecs, wearables, everything else on other platforms.
因此，当世界在经历这个过渡阶段时，如果我们能够资助一些工作来帮助这一过程，那可以包括网络防御、人工智能安全研究、经济研究等各个方面，帮助社会顺利度过这一转型期。我们对未来的美好充满信心，但我确信在这个过程中会有一些波动。我们要坚持完成这项任务。
关于模型和独占权，Sam，OpenAI 可以在 Azure 上分销其领先的模型，但我认为在七年内，直到2032年，你不能在其他主要云服务上分销这些模型。不过，如果人工通用智能（AGI）得到验证，这个期限可能会提前结束，我们可以再讨论这个问题。此外，你可以在其他平台上分销你的开源模型、Sora 代理、Codecs、可穿戴设备等其他产品。
So Sam, I assume this means no chat GPT or GPT 6 on Amazon or Google. So we have a cat, first of all, we want to do lots of things together to help create value for Microsoft, we want them to do lots of things to create value for us, and there are many, many things that will happen in that category. We are keeping what Satya termed once, and I think it's a great phrase of stateless APIs on Azure exclusively through 2030, and everything else we're going to distribute elsewhere, and that's obviously in Microsoft's interest too. So we'll put lots of products, lots of places, and then this thing we'll do on Azure and people can get it there or be awesome. I think that's great.
好的，Sam，我猜你是说亚马逊或谷歌上没有Chat GPT或GPT-6。我们有一个合作，首先，我们希望能一起做很多事情来为微软创造价值，同时也希望他们为我们创造价值，并且在这方面会有很多事情发生。我们将继续在Azure上独家保留Satya曾经提到的无状态API，到2030年，而其他方面的内容则会在其他地方进行分发，这显然也符合微软的利益。我们会将很多产品放在很多地方，而这项功能会在Azure上实现，大家可以在那里使用或进行优化。我觉得这很好。
And then the rev share, there's still a rev share that gets paid by open AI to Microsoft on all your revenues that also runs until 2032, more until AGI is verified. So let's just assume for the sake of argument, I know this is pedestrian, but it's important that the rev share is 15%. So that would mean if you had 20 billion in revenue that you're paying 3 billion to Microsoft, and that counts as revenue to Azure. Such as that, does that sound about right? Yeah, we have a rev share, and I think as you characterized it, we're either going to AGI or till the end of the thumb. And I actually don't know exactly where we counted, quite honestly, whether it goes into Azure or something else. That's a good question. It's a good question for Amy.
翻译如下：
然后是收入分成问题，OpenAI 需要向微软支付一部分收入分成，这个安排会持续到 2032 年，或者直到 AGI（人工通用智能）被验证为止。假设为了讨论方便，虽然这可能有些简单化，但重要的是，假设收入分成是 15%。那么如果你的收入达到了 200 亿美元，你需要支付 30 亿美元给微软，而这笔收入会被算作 Azure 的收入。这样说起来，听起来对吗？是的，我们有收入分成协议，正如你所描述的，不是到 AGI 实现，就是到约定期限结束。我其实不太清楚这些收入是否会计入 Azure 或其他地方，这倒是个好问题，可以问问 Amy。
Given that both exclusivity and the rev share end early in the case, AGI is verified. It seems to make AGI a pretty big deal. And as I understand it, if open AI claimed AGI, it sounds like it goes to an expert panel. And you guys basically select a jury who's got to make a relatively quick decision whether or not AGI has been reached. So you said on yesterday's earning call that nobody's even close to getting to AGI, and you don't expect it to happen anytime soon. You talked about this spiky and jagged intelligence. Sam, I've heard you perhaps sound a little bit more bullish on, you know, when we might get to AGI.
考虑到在这种情况下，独占性和分成协议都提早结束了，AGI（人工通用智能）已经得到了验证。这似乎让AGI变得非常重要。据我了解，如果OpenAI宣称达到了AGI，就会交由一个专家小组审查。你们基本上会选一个陪审团，他们需要快速做出决定，判断是否真的达到了AGI。但是你在昨天的财报电话会议中表示，目前没有人接近实现AGI，而且你也不认为这会很快发生。你还谈到了这种不规则和间歇的智能。山姆，我听说你可能对何时能实现AGI表示得稍微乐观一些。
So I guess the question is to you both, do you worry that over the next two or three years, we're going to end up having to call in the jury to effectively make a call on whether or not we've hit AGI? I realize you've got to try to make some drama between us here. You know, I think putting a process in place for this is a good thing to do. I expect that the technology will take several surprising twists and turns and we will continue to be good partners to each other and figure out what's. Well said, I think, and that's one of the reasons why I think this process we put in place is a good one and at the end of the day, I'm a big believer in the fact that intelligence capability-wise is going to continue to improve.
所以我想问你们两个一个问题：你们会担心在未来两三年内，我们会不会最终需要召集一个评审团来判断我们是否达到了通用人工智能（AGI）的水平？我理解你可能想通过这些提问制造些紧张气氛。我认为为此制定一个流程是一件好事。我预计科技将会发生一些令人惊讶的变化，我们会继续成为彼此的好伙伴，一起找出解决方案。说得好，我认为这也是为什么我觉得我们所制定的流程是一个好的选择。归根结底，我坚信智能能力会持续提高。
Our real goal, where frankly is that, which is how do you put that in the hands of people and organizations so that they can get the maximum benefits and that was the original mission of open AI that attracted me to open AI and Sam and team and that's kind of what we plan to continue on. Brad, to say the obvious if we had super intelligence tomorrow, we would still want Microsoft's help getting this product out into people's hands and we want them like yeah. Of course, of course, yeah, no again, I'm asking the questions, I know that around people's minds and that makes a ton of sense to me, obviously, Microsoft is one of the largest distribution platforms in the world.
我们的真正目标是这样的，说实话，就是如何把这些技术放到个人和组织手中，使他们能够获得最大的收益。这也是 OpenAI 最初的使命，这个使命吸引我加入了 OpenAI 和 Sam 以及他的团队。这也是我们计划继续努力的方向。Brad，很明显，如果我们明天就有了超级智能，我们仍然会需要微软的帮助，将这个产品推向用户手中。是的，当然，当然。我提这些问题是因为我知道大家都在想这些，而这对我来说也非常合理。显然，微软是全球最大的分发平台之一。
You guys have been great partners for a long time, but I think it dispels some of the myths that are out there, but let shift gears a little bit. Obviously, open AI is one of the fastest growing companies in history, such as you said on the pod a year ago, this pod that every news phase shift created a new Google and the Google of this phase shift is already known and it's open AI. And none of this would have been possible had you guys not made these huge bets with all that said, open AI's revenues are still reported $13 billion in 2025 and Sam on your live stream this week. You talked about this massive commitment to compute right 1.4 trillion over the next four or five years with, you know, big commitments 500 million to Nvidia 300 million to AMD and Oracle 250 billion to Azure.
你们一直以来都是很好的合作伙伴，长期以来我们有很多合作，但我认为这也帮助打破了一些现存的误解。让我们换个话题。显然，OpenAI是历史上发展最快的公司之一，就像你一年前在播客上说的那样，每次技术领域发生重大变化时都会创造出一个新的谷歌，而这次变化的“谷歌”显然是OpenAI。如果不是因为你们敢于做出如此巨大的投资，这一切都不可能实现。当然，OpenAI的收入仍被预计在2025年达到130亿美元。在你本周的直播中，你谈到了一项巨大的计算投资承诺：在接下来的四到五年里，总额达1.4万亿美元，其中包括向Nvidia投资5亿美元，向AMD投资3亿美元，以及向Azure投资2500亿美元。
So I think this single biggest question I've heard all week and hanging over the market is how you know, how can the company with 13 billion in revenues make 1.4 trillion of spend commitments, you know, and and you've heard the criticism Sam. We're doing well more revenue than that second of all Brad, if you want to sell your shares, I'll find you a buyer. I just enough like, you know, people are, I think there's a lot of people who would love to buy open AI shares. I don't I don't think you want to. Including myself. Including myself. Talk with a lot of like breathless concern about our compute stuff or whatever that would be thrilled to buy shares.
我觉得本周听到的最大问题就是，市场上一直在讨论的，就是一家年收入130亿的公司是如何承诺花费1.4万亿的。你也听到了批评意见，Sam。即便我们的收入超过这一数字，但如果你想出售你的股份，Brad，我会帮你找到买家。我认为有很多人都想购买OpenAI的股份，包括我自己在内。对于我们计算能力的一些忧虑，有不少人兴致勃勃，想要购买股份。
So I think we could sell, you know, your shares or anybody else's to some of the people who are making the most noise on Twitter, whatever about this very quickly. And we do plan for revenue to grow steeply revenue is growing steeply we are taking a forward bet that it's going to continue to grow and that not only will try to be T keep growing, but we will be able to become one of the important AI clouds that our consumer device business will be a significant important thing that AI that can audit made science will create huge value. So, you know, there are not many times that I want to be a public company, but one of the rare times it's appealing is when those people are writing these ridiculous open AI is about to go out of business and, you know, whatever.
我觉得我们可以很快把你的股份或其他人的股份卖给那些在推特上讨论这个话题最激烈的人。我们确实计划收入会大幅增长，目前收入增长迅速，我们押注它会继续增长。不仅如此，我们希望Try to be T能够继续增长，而我们也能够成为重要的人工智能云之一，我们的消费设备业务将成为一个重要的板块，能够自动化科学的AI将创造巨大的价值。尽管有很多次我并不想成为一家上市公司，但当那些人写这些“Open AI即将倒闭”之类的荒谬言论时，成为上市公司是极少数让人心动的时刻之一。
I would love to tell them they could just short the stock and I would love to see them get burned on that. But, you know, I we carefully plan we understand where the technology where the capability is going to grow, go and how the products we can build around that in the revenue we can generate we might screw it up like this is the bet that we're making and we're taking a risk along with that. A certain risk is if we don't have the compute we will not be able to generate the revenue or make the models at these at this kind of scale. Exactly.
我很想告诉他们可以去做空这支股票，也很期待看到他们因此遭受损失。但你知道，我们是经过仔细规划的，我们了解技术和能力的增长方向，并且计划在此基础上开发产品和产生收益。当然，我们也有可能会搞砸，因为这是我们正在下注并承担风险的事情。其中一个确定的风险是，如果我们没有足够的计算能力，我们将无法在这样的规模上产生收益或建立模型。没错。
And so let me just say one thing Brad as both a partner and an investor there is not be the single business plan that I've seen from open AI that they're put in and not beaten it. So in some sense, this is the one place where you know in terms of their growth and just even the business it's been unbelievable execution quite frankly. I mean obviously open AI everyone talks about all the success in the usage and what have you. But even I would say all up the business execution is being just pretty unbelievable.
让我这么说，布拉德，作为合作伙伴和投资者，我看过的所有来自OpenAI的商业计划，没有一个是不被他们超越的。从某种意义上说，在增长和商业执行方面，他们的表现真是令人难以置信。显然，大家都在谈论OpenAI在使用上的成功，但即使从整体来看，他们的商业执行也确实非常了不起。
I heard Greg Brockman say on CNBC a couple of weeks ago right if we could 10X our compute we might not have 10X more revenue but we'd certainly have a lot more revenue. Simply because of lack of compute power things like yeah it's just it's really wild when I just look at how much we are held back and in many ways we have you know we've scaled our compute probably 10X over the past year. But if we had 10X more compute I don't know if we'd have 10X more revenue but I don't think of you that far. And we heard this from you as well last night Sasha that you were compute constrained and growth would have been higher even if you add more compute.
几周前，我在CNBC上听到Greg Brockman说，如果我们能将计算能力提高10倍，可能不会带来10倍的收入增长，但收入肯定会增加很多。这只是因为计算能力的不足。当我看到我们受到的限制时，实在是觉得不可思议。在过去的一年里，我们的计算能力已经扩大了大约10倍。但是如果我们再增加10倍的计算能力，我不清楚收入会不会增加10倍，但也不会离这个目标太远。昨晚我们也从Sasha那儿得知，你也因为计算能力的限制，导致增长没有达到本可以实现的水平。
So help us contextualize Sam maybe like how compute constrained do you feel today and do you when you look at the build out over the course of the next two to three years. Do you think you'll ever get to the point where you're not compute constrained. We talk about this question of is there ever enough compute a lot I think the answer is the only the best way to think about this is like a. Energy or something you can talk about demand for energy at a certain price point but you can't talk about demand for energy without talking about. At different you know different demand at different price levels if the price of compute per like unit of intelligence or whatever you want to think about it fell by a factor of 100 tomorrow you would see usage go up by much more than 100 and there be a lot of things that people would love to do with that compute that just make no economic sense at the current cost but there would be new kind of demand so I think the the.
要帮助我们理解一下Sam的观点，现在你觉得计算资源是否受到了限制？当你展望未来两到三年的发展时，你认为会有一天不再受到计算资源的限制吗？我们经常讨论这个问题，是否有足够的计算资源。我认为最好的理解方式就像是对待能源一样。你可以在某个价格点讨论能源需求，但不能不谈论不同价格水平下的不同需求。如果明天每单位智能的计算成本下降100倍，使用量将会增加远超100倍，人们会想用这些计算资源做很多事情，而这些事情在现有成本下没有经济意义，但会产生新的需求。因此，我认为这个问题的.......
Now on the other hand is the models get even smarter and you can use these models to cure cancer discover novel physics or drive a bunch of human robots to construct a space station or whatever crazy thing you want. Then maybe there's huge willingness to pay a much higher rate cost per unit of intelligence for a much higher level of intelligence that we don't know yet but I would bet there will be so I. I think when you talk about capacity it's it's like a you know cost per unit and you know capability per unit and you have to kind of without those curves it's sort of made up now it's it's not a super well specified problem yeah I think the one thing that you know Sam you talked about which I think is the right ways to think about is that if intelligence is what a log of compute.
另一方面，如果模型变得更加聪明，你可以利用这些模型来治愈癌症，发现新的物理现象，或者驾驶许多人形机器人去建造空间站，或者做任何你想象中的疯狂事情。那么，也许人们愿意为更高水平的智能支付更高的费用，虽然我们现在还不知道这种情况是否会发生，但我敢打赌它会发生。所以，我认为在谈论能力时，就像是在谈论每单位的成本和每单位的能力。如果没有这些曲线，现在我们所讨论的问题并不是非常明确。是的，我认为Sam所提到的一个正确的思考方式是，把智能看作是计算的对数。
Then you try and really make sure you keep getting efficient and so that means the tokens per dollar per watt and the economic value that the society gets out of it is what we should maximize and reduce the costs and so that's where if you sort of where the jeven's paradox point is that which is you keep reducing it commoditizing in some sense intelligence so that it becomes the real driver of GDP growth all around. Unfortunately, it's something closer to a log of intelligence he was log of compute but we may figure out better scaling laws and we figure out. We heard from both Microsoft and Google yesterday both said their cloud businesses would have been growing faster if they have more GPUs you know I asked Jensen on this pod if there was any chance over the course of the next five years we would have a compute glut and he said it's virtually nonexistent chance in the next two to three years.
然后，你需要努力确保效率的持续提升。这意味着，我们应该最大化每个美元、每瓦特能处理的计算量，以及社会从中获得的经济价值，同时尽量降低成本。这就是所谓的杰文斯悖论所在，也就是说，通过不断降低成本，将某种程度的智能商品化，使得智能成为推动全球GDP增长的真正动力。不幸的是，目前的情况更接近于智能的增长是计算的对数增长，但我们可能会找到更好的扩展法则。昨天我们从微软和谷歌都了解到，他们表示云业务本可以增长得更快，如果他们拥有更多的GPU。我在播客里问过黄仁勋，他认为未来五年内是否会出现计算资源过剩的情况，他说在接下来的两到三年里，这种情况几乎不可能发生。
And I assume you guys would both agree with Jensen that while we can't see out five six seven years certainly over the course of the next two to three years for the for the reasons we just discussed that it's almost a nonexistent chance that you have excess compute. I think the cycles of demand and supply in this particular case you can't really predict right I mean even the point is what's the secular trend the secular trend is what Sam said which is at the end of the day because quite frankly the biggest issue we are now having is not a compute glut but it's a power and it's sort of the ability to get the bills done fast enough close to power. So if you can't do that you may actually have a bunch of chips sitting in inventory that I can't plug in in fact that is my problem today right it's not a supply issue of chips it's actually the fact that I don't have warm shelves to plug into and so how some supply chain constraints emerge tough to predict because the demand is just going you know is tough to predict right I mean I wouldn't it's not like seven I would want to be sitting here saying oh my god we're less short on computers because we just want to get the money.
我想你们都会同意Jensen的观点：虽然我们无法预测五六七年后的情况，但基于我们刚才讨论的原因，在未来两到三年里，几乎没有可能出现计算资源过剩的情况。需求和供应的周期在这种情况下确实难以预测。关键在于长期趋势，而这个长期趋势正如Sam所说，就是目前我们面临的最大问题实际上不是计算资源过剩，而是电力问题，以及能否快速完成相关项目来接近电力资源。如果无法做到这一点，可能会有很多芯片闲置未用，这也是我当前面临的问题——并不是芯片供应不足，而是我没有足够的设备来使用这些芯片。因此，如何应对某些供应链的限制很难预测，因为需求是难以预料的。我不想在这里说我们缺少计算机，因为我们只是想获得资金。
So that's not that good at being able to project out what the demand would really look like so I think that that's and by the way the worldwide side red wanted it's one thing to sort of talk about one segment in one country but it's about you know really getting it out to everywhere in the world and so there will be constraints and how we work through them is going to be the most important thing it won't be a linear path for sure. There will come a glut for sure and whether that's like in two to three years or five to six so I can't tell you but like it's going to happen at some point probably several points along the way like this is there is something deep about human psychology here and bubbles and also as Satya said like there's it's such a complex supply chain weird stuff gets built the technological landscape shifts in big ways so you know if a very cheap form of energy comes online soon at mass scale and a lot of people are going to be extremely burned with existing contracts they've signed it if we can continue this unbelievable reduction in cost per unit of intelligence let's say it's been averaging like 40 x for a given level per year you know that's like a very scary exponent from an infrastructure build out standpoint now again we're taking the bet that there'll be a lot more demand is that gets cheaper but I have some fear that it's just like man we keep going with these breakthroughs and everybody can run like a personal agenda laptop and we just did an insane thing here some people are going to get really burned like has happened in every other tech infrastructure cycle at some points along the way.
所以，这并不是非常擅长预测需求实际会是什么样的。因此，我认为这是一方面。另外，就全球来看，想要在一个国家讨论某个特定的细分市场是一回事，但真正要将其推向全世界，就会面临各种限制。解决这些限制将是最重要的，这个过程肯定不会是线性的。在两到三年或五到六年后，供应过剩肯定会出现，我不能确切告诉你什么时候，但在某个时点肯定会发生，这其中涉及到人类心理和市场泡沫。就像Satya说的，供应链非常复杂，技术环境也在发生巨大的变化，比如如果一种非常便宜的能源大规模上线，很多已经签署合同的人都会因此受到损失。如果成本继续以每年平均40倍的速度下降，从基础建设的角度来看，这是个可怕的指数增长。不过，我们假设随着成本降低，需求会大幅增加，但我担心的是，我们不断突破，这样发展下去，每个人都能运行属于自己的项目，结果可能会导致一些人受损，就像历史上其他技术基础设施周期那样，沿途的某些时点总会发生这种情况。
I think that's really well said and you have to hold those two simultaneous truths we had that happen in 2000 2001 and yet the internet became much bigger and produce much greater outcomes for society than anybody estimated in that period of time. Yeah, but the one thing that Sam said is not talked about enough which is the come that for example the optimizations that open a eyes done on the inference stack for a given GPU I mean I it's kind of like it's you know we talk about the Moore's law improvement on one end but the software improvements are much more exponential than that. Someday we will make incredible consumer device that can run a GPT five or GPT six capability model completely locally at a low power draw and this is like so hard to wrap my head around that will be incredible and you know that's the type of thing I think that scares some of the people who are building obviously these large centralized a few stacks and such you talked a lot about the distribution both to the edge as well as having inference capability distributed around the world.
我认为你说得非常好，我们必须同时接受这两种事实：我们在2000年和2001年经历了那些事情，但互联网却变得比任何人在那时预估的都要大，并为社会带来了更大的成果。不过，Sam提到的一点却没有被充分讨论，那就是，例如OpenAI在特定GPU上的推理堆栈优化。我觉得，这有点像是，一方面我们谈论摩尔定律的进步，但另一方面软件的改进要比那更呈指数增长。有一天，我们将能够制造出一种令人难以置信的消费设备，它能在极低的能耗下完全本地运行如GPT-5或GPT-6能力模型。这种可能性让人难以想象，但非常令人惊叹。我想，这种前景令那些正在建立大型集中的AI架构的人感到担忧。你也谈到了将推理能力分布到边缘设备以及全世界的这种分布。
Yeah, I mean the way at least I've thought about it is more about really building a fun jubble fleet I mean when I look at sort of in the cloud infrastructure business one of the key things you have to do is have two things one is an efficient like in this context and a very efficient token factory and then high utilization that's that's it there are two simple things that you need to achieve and in order to have a high utilization you have to have multiple workloads that can be scheduled even on the training I mean if you look at the AI pipelines there's pre training. There's mid training there's post training there's RL you want to be able to do all of those things so thinking about fun jability of the fleet is everything for a cloud provider.
是的，我的意思是，我考虑这件事情的时候，更多的是想着如何打造一个有趣的可用资源池。就是说，在云基础设施业务中，你必须做到两件关键的事情：一个是建立高效的代币工厂，另一个是确保资源的高利用率。仅此而已，这就是你需要实现的两个简单目标。
为了实现高利用率，你必须有多种工作负载，这样才能进行适当的调度，即使是在训练过程中也是如此。看看AI的处理流程，有预训练、中期训练、后期训练和强化学习（RL），你希望能够处理所有这些阶段。所以，对于云服务提供商来说，考虑如何让资源池更具可用性是至关重要的。
Okay, so Sam you referenced you know and Reuters was reporting yesterday that opening I may be planning to go public late 26 or 20. No, no, we don't we don't have anything that specific I'm a realist I assume it will happen someday but that was I don't know why people write these are like big and wide. Great. Well, I'm not going to do this or anything like that I just assume it's where things will eventually go but it does seem to me if you guys were you know are doing an excess of $100 billion of revenue in 28 or 29 that you at least would be in. What what I'm about 27.
好的，Sam，你提到过，昨天路透社报道说某个项目可能计划在2026年底或2020年公开。我不是特别清楚具体情况，但作为一个现实主义者，我认为这可能有一天会发生，但我不知道为什么有人会写这些宽泛而夸张的言论。好的，我不会去做这些事情，我只是认为这可能是未来的发展方向。不过在我看来，如果你们到2028或2029年的收入超过1000亿美元，至少需要在2027年做到这一点。
Yeah 27 even better you are in position to do an IPO and the rumored trillion dollars again just to contextualize for listeners if you guys want public at 10 times. 100 billion in revenue right which would be I think a lower multiple than Facebook went public at a lower multiple than a lot of other big consumer companies went public at that would put you to a trillion dollars if you floated 10 to 20% of the company that raises 100 to 200 billion dollars which seems like that would be a good path to fund a lot of the growth and a lot of the stuff that we just talked about so you're you're not opposed to it you're not.
好的，27岁更好，你有机会进行首次公开募股（IPO），而传闻中的一万亿美元估值再次提供了背景信息给听众。如果你们公司以十倍的收入，即1000亿美元的收入上市，这实际上比Facebook上市时的倍数要低，也比许多其他大型消费公司上市时的倍数要低。这样的话，如果你们公司发行10%到20%的股份，就能筹集到1000亿到2000亿美元，这似乎是一个很好的方式来资助公司增长和我们刚刚谈到的很多事情。所以你并不反对这个计划，不是吗？
But you guys are on the company with revenue growth which is what I would like us to do. But well I've also said I think that this is such an important company and you know there are so many people including my kids who like to trade their little accounts and they use chat GPT and I think having retail investors have an opportunity to buy one of the most important and largest. So honestly that that is probably the single most appealing thing about it to me that would be really nice.
你们公司的收入增长正是我希望我们公司做到的。我也说过，我认为这是一个非常重要的公司。你知道，有很多人，包括我的孩子们，都喜欢用他们的小账户进行交易，他们还使用ChatGPT。我认为让普通投资者有机会购买这家最重要、最大型的公司之一，这是非常有吸引力的地方，对我来说这真的很好。
One of the things I've talked to you both about shifting gears again is part of the big beautiful bill you know senator crews had included federal preemption so that we wouldn't have this state patchwork 50 different laws that Myers the industry down and kind of needless compliance and regulation. Unfortunately got killed at the last second by senator blackburn because frankly I think AI is pretty poorly understood in Washington and there's a lot of doom or is I think that is game traction in Washington.
我之前和你们两位都谈过要转换策略的话题，这涉及到一项重要的法案。你们知道，参议员克鲁兹在其中加入了联邦优先权的条款，以避免出现50个州各自为政的情况，这种情况会让行业陷入困境，并带来不必要的合规和监管要求。但遗憾的是，这一条款在最后一刻被参议员布莱克本阻止了。坦白说，我认为人工智能在华盛顿的认知程度不高，并且有很多末日言论在华盛顿获得了关注。
So now we have state laws like the Colorado AI act that goes into full effect in February I believe that creates this whole new class of litigants anybody who claims any unfair impact from an algorithmic discrimination and a chatbot so somebody could claim harm for countless reasons. Sam how worried are you that you know having this state patchwork of AI you know poses real challenges to you know our ability to continue to accelerate and compete around the world. I don't know how we're supposed to comply with that California.
现在我们有了一些州法律，例如科罗拉多州的人工智能法，它将在我认为是明年二月全面生效。该法律创造了一个新的诉讼群体，即任何声称受到算法歧视和聊天机器人不公平影响的人。因此，人们可以因为无数原因而声称受到了伤害。Sam，你有多担心这样的州法律拼凑会对我们持续推动创新和国际竞争的能力带来真正的挑战。我不知道我们该如何遵循加州的规定。
Sorry Colorado law I would love them to tell us and you know we'd like to be able to do it but that's just from what I've read of that that's like I literally don't know what we're supposed to do. I'm very worried about a 50 state patchwork I think it's a big mistake I think it's there's a reason we don't usually do that for these sorts of things I think it'd be bad.
抱歉，科罗拉多州的法律。我希望他们能告诉我们怎么做，我们也希望能够这样做，但根据我读到的内容，我真的不知道我们应该怎么做。我非常担心出现一个50个州各自为政的局面。我认为这是一个很大的错误，我觉得这就是我们通常不这样做的原因。我认为这可能会带来不好的结果。
Yeah I mean I think the fundamental problem of you know this patchwork approaches quite frankly I mean between open AI and Microsoft will figure out a way to navigate this right I mean we can figure this out the problem is anyone starting a startup and trying to kind of this is sort of it just goes to the exact opposite or I think what the intent. It's obviously safety is very important on making sure that the fundamental you know concerns people have a address but there's a way to do that at the federal level so I think the you if we don't do this again you know you will do it and then that'll cause its own issue so I think if US leads it's better as you know as one regulatory framework for sure.
是的，我的意思是，我认为根本的问题在于，这种零散的方法，说实话，我的意思是OpenAI和微软之间会找到解决办法，对吧？我们可以解决这个问题。问题在于任何创办初创公司并尝试……这基本上就与本意完全相反。我认为，显然安全性是非常重要的，确保解决人们的根本担忧也非常重要，但可以在联邦层面做到这一点。所以我认为，如果我们不这样做，其他国家就会这么做，然后这会引发自己的问题。所以我认为，美国要是能引领这一领域是更好的，至少确保有一个统一的监管框架。
And to be clear it's not that one is advocating for no regulation it's simply saying let's have you know agreed upon regulation at the federal level as opposed to 50 competing state laws which certainly fire bombs the AI startup industry and I think it makes it makes it super challenging even for companies like yours who can afford to defend all these cases yeah that would just say quite frankly my hope is that this time around even across EU and the United States that that would be the dream right quite frankly for any European. Start up I don't think that's going to happen. What is that that would be great I don't I wouldn't hold your breath for that one that would be great.
这段文字的翻译和简化表达如下：
需要说明的是，这并不是说有人主张完全不需要监管，而是建议在联邦层面达成一致的监管政策，而不是各个州有50种不同的法律，这种情况肯定会对人工智能初创行业造成打击。我认为，即使对于像你们这样有能力应对各种法律挑战的公司来说，这也是非常困难的。坦率地说，我希望这一次即使在欧盟和美国之间也能实现这样的梦想。对于任何欧洲初创公司来说，这都是理想的状况，但我认为这不会实现。尽管如此，这将是个好主意，不过不要对此抱太大期望。
Now but I really think that if you think about it right if you sort of if anyone in Europe is thinking about there you know what how can they participate in this AI economy with their companies this should be the main concern there as well so therefore that's I hope there is some enlightened approach to it but I agree with you that you know today I wouldn't bet on that. I do think that with sacks as the a is are you at least have a president that I think might fight for that in terms of coordination of of AI policy using trade as a lever to make sure that you know we don't end up with overly restricted European policy but we shall see.
现在，但我真的认为，如果你仔细考虑的话，如果欧洲的任何人正在思考如何参与人工智能经济，他们的公司也应该关注这一点。这应该是他们主要关心的问题。因此，我希望能有一些开明的方式来处理这个问题，但我同意你，现在我不太敢打这个赌。我确实认为，在萨克斯作为总统的情况下，至少可能会有人为此进行努力，通过协调人工智能政策和利用贸易作为杠杆，确保我们不会陷入过于严格的欧洲政策。不过，这个结果如何，我们还需拭目以待。
I think first things first federal preemption the United States is pretty critical you know we've been down in the weeds a little bit here Sam so I want to tell us go about a little bit you know I've heard people on your team talk about all the great things coming up and as you start thinking about much more unlimited compute chat GPT six and beyond robotics physical devices scientific research as you as you look forward to twenty twenty six what do you think surprises us the most what what what what are you most excited about in terms of what's on the drawing board.
我认为，首先要明确的一点是，美国联邦的优先权是非常重要的。因为我们在细节上谈了很多，所以我想让我们稍微放眼未来。我听过你团队的人谈论即将到来的许多伟大事物，当你开始考虑更无限的计算、ChatGPT-6及其之后的版本、机器人、物理设备和科学研究时，展望2026年，你认为什么会让我们感到最惊讶？在现有的规划和设计中，你最期待什么？
You are mean you just hit on a lot of the key points there I think codex has been in a very cool thing to watch this year and as these go from multi hour tasks to multi day tasks which I expect to happen next year what people to do to create software unprecedented rate and really in fundamentally new ways I'm very excited for that I think we'll see that in other industries to I have like a bias towards coding I understand that one better but I think we'll see that really start to transform what people are capable of. I hope for very small scientific discoveries in twenty twenty six but if we can get those very small ones we'll get bigger ones in future years that's a really crazy thing to say is that like AI is going to make a novel scientific discovery in twenty twenty six even a very small this is like this is a wildly important thing to be talking about so I'm excited for that certainly robotics and computer.
你提到的几个关键点都非常重要。今年以来，Codex 已经成为一个非常有趣的观察对象。未来，我预计这些任务会从需要花费几个小时的工作转变为需要几天的工作，以前所未有的速度和全新的方式推动软件的创造。我对此感到非常兴奋。我觉得其他行业也会发生类似的转变。虽然我对于编程比较了解，所以我对它有一定偏见，但我相信这些变化将彻底改变人们的能力。
我希望到2026年能够有一些小的科学发现。如果我们能实现这些小的发现，未来几年我们就有可能取得更大的突破。说AI将在2026年进行一个全新的科学发现，即使是一个很小的发现，这真的是一件非常重要的事情。我对此感到很激动，尤其是在机器人和计算机领域。
And new kind of computers in future years that'll be that'll be very important but yeah my personal biases if we can really get AI to do science here that is I mean that is super intelligence in some sense like if this is expanding the total sum of human knowledge that is a crazy big deal.
未来几年出现的新型计算机会变得非常重要，但就我个人偏见而言，如果我们能真正让人工智能从事科学研究，那在某种意义上就是超级智能。这意味着我们能够扩大人类知识的总和，这真的是一件大事。
Yeah I mean I think one of the things to use your codex example I think the combination of the model capability I mean if you think about the magical moment that happened with chat GPT was the UI that met intelligence that just took off right there's just you know unbelievable right form fact and some of it was also the instruction following piece of model capability was ready for chat.
是的，我的意思是，用你的Codex示例来说，我觉得模型功能的结合非常重要。就像ChatGPT的神奇时刻，它的界面与智能结合起来，立刻引起了广泛关注。这真的难以置信。部分原因也是因为模型功能中的指令跟随能力，为聊天做好了准备。
I think that that's what the codex and the you know these coding agents are about to help us which is what's that you know coding agent goes off for a long period of time comes back and then I'm then dropped into what I should steer like one of the metaphors I think we're all sort of working towards this I do this macro delegation and micro steering what is that UI meets this new intelligence capability and you can see the beginnings of that with that.
我认为这就是《法典》和那些编码代理的意义所在，它们是为了帮助我们。你知道吗，这个编码代理运行了很长时间后回来了，然后我被引导去该如何操控。就像我们都在努力实现的一个比喻——我进行宏观委托，而进行微观操纵。这个界面如何与这种新的智能能力结合，你可以在其中看到这一点的开端。
And I think that is a very important thing to do is to get the codex right the way at least I use it inside a GitHub Copaola is like you know it's now it's just a it's just a different way than the chat interface and I think that that I think it would be a new way for the human computer interface quite frankly it's probably bigger than that that might be the departure.
我认为非常重要的一点是正确地使用Codex。我在GitHub Copaola中使用它的方式有些不同，现在这只是不同于聊天界面的另一种方式。我认为这将会是人机界面的新方式。坦率地说，它可能比这更重要，或许这是一个突破。
I'm very excited that we're doing new form factors of computing devices because computers were not built for that kind of workflow very well certainly a UI like chat to be t is wrong for it but this idea that you can have a device that is sort of always with you but able to go off and do things and get micro steer from you when it needs and have like really good contextual awareness of your whole life and flow and I think that would be cool.
我非常兴奋，因为我们正在开发新的计算设备形式。传统的计算机并不太适合这样的工作流程，像聊天界面这样的用户界面确实不太合适。但是，这种设想是，你可以拥有一种设备，它总是伴随在你身边，可以在需要的时候自行运行任务，并从你那里获取微小的指导，同时对你的生活和工作流程有很好的上下文感知。我认为这将会非常酷。
And what neither of you have talked about is the consumer use case I think a lot about you know again we go on to this device and we have to hunt and pack through 100 different applications and fill out little web forms things that really haven't changed in 20 years but to just have. You know a personal assistant that we take for granted perhaps that we actually have a personal assistant but to give a personal assistant for virtually free to billions of people around the world to improve their lives whether it's you know ordering diapers for their kid or whether it's. You know booking their hotel or or making changes in their calendar I think sometimes it's the pedestrian that's the most impactful and as we move from answers to memory and actions and then the ability to interface with that through an earbud or some other device that doesn't require me to constantly be staying at this rectangular piece of glass I think it's pretty extraordinary.
你们都没有谈到的一个消费者在实际应用场景，我常常思考这个问题。我们使用这些设备，必须在上面浏览和挑选上百个不同的应用程序，并填写各种网络表单，而这些方式在过去20年里几乎没有变化。而我们理所当然地觉得自己拥有一个个人助理，但如果能够为全球数十亿人免费配备这样一个个人助理，可以极大地改善他们的生活。不论是给孩子订购尿布，还是预订酒店，或者调整日程安排。有时候，正是这些看似平凡的事情带来的影响最大。当我们从提供答案发展到记忆和行动，再到通过耳机或其他设备与之互动，而不必再时刻盯着这个矩形的屏幕时，想想这些改变是多么非凡。
I think that that's what Sam was teasing yeah yeah right I got to drop off unfortunately. Sam it was great to see you thanks for joining us congrats again on this big step forward and we'll talk to you. Let me crash. See you Sam take care. It's it. Sam well knows we're certainly a buyer not a seller but but but sometimes you know I think it's important because the world you know we're pretty small we spend all day long thinking about this stuff right and so conviction it comes from the 10,000 hours we've spent thinking about it. But the reality is we have to bring along the rest of the world in the rest of the world doesn't spend 10,000 hours thinking about this and then frankly they look at some things that appear overly ambitious right and get worried about whether or not we can pull those things off.
我觉得那就是Sam在开玩笑的部分，对吧？可惜我得先离开了。Sam，很高兴见到你，谢谢你加入我们，并再次祝贺你取得这重要进展，我们下次再聊。让我打个招呼，再见Sam，保重。Sam很清楚我们肯定是买家而不是卖家。但是，你知道，有时候我觉得这很重要，因为这个世界，你知道，我们其实很小，我们整天都在思考这些事情，坚定的信念是来自我们花费1万小时的思考。然而现实是，我们必须带动其他人参与进来，因为其他人并没有花1万小时去思考这些，然后说实话，他们看到一些看似过于雄心勃勃的事情时，会担心我们是否能实现这些目标。
So you took this idea to the board in 2019 to invest a billion dollars into open AI was it a no brainer in the board room you know did you have to expend any political capital to get it done dish dish for me a little bit. Like what that moment was was like because I think it was such a pivotal moment not just for Microsoft not just for the country but I really do think for the world. Yeah I mean it's interesting when you look back the journey when I look at it it's been you know we were involved even in 2016 and initially open AI started in fact as you was even the first sponsor I think and then they were doing a lot more reinforcement learning at that time I remember the daughter to competition I think happened on Azure and then.
所以你在2019年向董事会提议投资十亿美元到OpenAI项目中，这在董事会议上是毫无争议的吗？你是否需要动用一些政治资本来推动这件事？可以跟我稍微透露一下当时的情景吗？因为我觉得这不仅是对微软，对整个国家，更是对全世界一个关键的时刻。是的，我的意思是，当回顾这个旅程时，确实很有趣。我们从2016年就开始参与其中，最初OpenAI开始的时候，我们甚至是第一个赞助商。我记得他们那时主要在做强化学习，我还记得Dota 2的比赛是在Azure上进行的，然后……
They moved on to other things and you know I was interested in our out but quite frankly you know it speaks a little bit to your 10,000 hours or the prepared mind Microsoft since 1995 was obsessed I mean builds obsession for the company was natural language natural language I mean after all we had a coding company that's right information work company. So it's when Sam in 2019 started talking about text and natural language and transformers and scaling laws that's when I say wow like this is an interesting I mean you know this was a team that was going in the direction or the direction of travel was now clear it had a lot more overlap with our interest so in that sense it was a no brainer obviously go to the board and say hey I have an idea of taking a billion dollars and giving it to the board.
他们转向了其他事物，你知道我对我们的情况很感兴趣，但坦率地说，这有点像你的“一万小时理论”或“有准备的头脑”。自1995年以来，微软就对自然语言痴迷，毕竟我们是一家以编码为基础的信息工作公司。所以，当Sam在2019年开始谈论文本、自然语言、转换器和缩放定律时，我心想，这很有趣。换句话说，这个团队的方向变得明确了，它与我们的兴趣有更多的重合。从这个意义上说，去董事会提议拿出十亿美元是显而易见的选择。
Because the board will return 10 dollars and giving it to this crazy structure which we don't even kind of understand what is it it's a nonprofit blah blah blah and and saying go for it there was a debate bill was kind of rightfully so skeptical because and then he became like once you saw the GPT for demo like that was like the thing that bills talk about publicly where when he saw he said it's the best demo he saw after you know what Charles Simone should him at Zerox Park and but you know quite honestly not that's what you want to say of us could.
因为董事会会退回10美元，并将其交给这个我们甚至不太了解的疯狂结构，它是一个非营利组织等等。对此，曾经有过一场辩论，Bill（比尔）持怀疑态度，他的怀疑是有道理的。但是，一旦他看到了GPT-4的演示，他的态度就变了。他公开表示，这是他继Charles Simone在Xerox Park展示给他东西之后，见过的最好的演示。不过，说实话，这也正是我们想要说的。
So the moment for me was that, you know, let's go give it a shot, then seeing the early codecs inside of Copilot, inside of GitHub Copilot, and seeing just the code completions and seeing it work, that's when I would say we, I felt like I can go from one to 10, because that was the big call, quite frankly. One was controversial, but the one to 10 was what really made this entire era possible. And then obviously the great execution by the team and the productization on their part, our part, I mean, if I think about it, right, the collective monetization reach of GitHub Copilot, chat GPT, Microsoft 365 Copilot and Copilot, you add those four things, that is it, right, that's the biggest sort of AI set of products out there on the planet.
对我来说，那一刻就是，明白了吗，我们决定去尝试一下。然后在 GitHub Copilot 中看到早期的 codecs，看到代码自动补全功能的运作，那时我感觉自己可以从一步跨到十步，因为这实在是个重大决定。启动阶段是有争议的，但从一步到十步是让整个时代成为可能的关键所在。当然，还有团队的出色执行力和产品化，比如 GitHub Copilot、chat GPT、Microsoft 365 Copilot 和 Copilot 的整体商业化范围，我指的就是这些，组合在一起，它们是当今全球最大的 AI 产品集。
And that's, you know, what obviously has led us to sustain all of this. And I think not many people know that your CTO, Kevin Scott, you know, an ex-Googleer lives down here in Silicon Valley and to contextualize it, right, Microsoft had missed out on search, had missed out on mobile, you become CEO, almost had missed out on the cloud, right, you've described it caught the last train out of town to capture the cloud. And I think you were pretty determined to have eyes and ears down here so you didn't miss the next big thing. So I assume that Kevin played a good role for you as well. Absolutely. I find deep seek and open AI.
这就是我们能够坚持到现在的原因。而且，我认为很多人可能不知道，你们的首席技术官凯文·斯科特，他曾是谷歌员工，现在住在硅谷。放在具体背景下看，微软以前错过了搜索、失去了移动平台的机会，后来你成为了CEO，差点也要错过云计算，你形容就好像搭上了离站的最后一班车来抓住云端的机遇。我感觉你非常有决心在硅谷留意下一件大事，所以我猜凯文对你帮助很大。没错，我对深入探索和开放的人工智能很感兴趣。
Yeah, I mean, if it's in fact, I would say Kevin's conviction. And Kevin was also skeptical. Like that was the thing. I always watch for people who are skeptical who change their opinion. Because to me, that's a signal. So I'm always looking for someone who's a non-believer or something and then suddenly changes and then they get excited about it. I have all the time for that because I'm then curious why. And so Kevin started with it. All of us were kind of skeptical, right? No, I mean, in some sense, it defies the, you know, we're all having gone to school and said, God, you know, there must be an algorithm to crack this versus just let's scale in laws and throw compute. But quite frankly, Kevin's conviction that this is worth going after is one of the big things that drove this.
是的，我是说，如果事实如此，我会说这是Kevin的信念。而且Kevin开始也是持怀疑态度的。这就是问题所在。我总是关注那些怀疑但后来改变立场的人。因为对我来说，那是一个信号。所以我一直在寻找那些原本不相信某事的人，然后突然改变并对此感到兴奋。我对这样的人或者事物总是充满好奇，因为我想知道他们为什么改变立场。因此，最初Kevin也是这样。我们所有人都还有些怀疑，对吧？在某种意义上，这违背了我们上学时学到的“肯定有算法能解决这个问题”的思维，而不是单纯靠扩大规模和增加计算资源。但是，说实话，Kevin坚持认为这值得一试，这是推动这件事发展的主要原因之一。
Well, we talk about, you know, that investment that it's now worth 130 billion, I suppose could be worth a trillion someday, as Sam says. But it really in many ways understates the value of the partnership, right? So you have the value in the rev share billions per year going, going to Microsoft. You have the profit you make off the $250 billion of the Azure compute commitment from OpenAI. And of course, you get huge sales from the exclusive distribution of the API. So talk to us how you think about the value across those domains, especially how this exclusivity has brought a lot of customers who may have been on AWS to Azure.
我们谈论的那个投资现在价值1300亿，未来可能如Sam所说，价值达到一万亿。但是，这在很多方面其实低估了这种合作关系的价值。比如，每年数十亿的收入分成都会流向微软。您还从OpenAI对Azure计算承诺的2500亿美元中获利。当然，您还能从API的独家分销中获得巨额销售额。所以，请告诉我们您如何看待这些领域的价值，特别是这种独家合作如何吸引了许多原本可能使用AWS的客户转向Azure。
Yeah, no, absolutely. I mean, so to us, if I look at it, you know, aside from all the equity parts, the real strategic thing that comes together and that remains going forward, is that stateless API exclusive video on Azure that helps quite frankly both OpenAI and us and our customers. Because when somebody in the enterprise is trying to build an application, they want an API that stateless, they want to mix it up with compute and storage, put a database underneath it to capture state and build a full workload. And that's where, you know, Azure coming together with this API.
是的，没错，绝对是这样的。我的意思是，对我们来说，如果撇开所有的股份部分来看，真正具有战略意义并将继续发展的，是在Azure上的无状态API独家视频，这实际上对OpenAI和我们，以及我们的客户都有帮助。当企业中的某个人尝试构建一个应用程序时，他们需要一个无状态的API，希望将其与计算和存储结合，在其下方放置一个数据库以捕获状态，从而构建一个完整的工作负载。这就是Azure与这个API结合的地方。
And so what we're doing with even Azure Foundry, right? Because in some sense, let's say you want to build an AI application, but the key thing is how do you make sure that the e-vals or what you're doing with AI are great. So that's where you need even a full app server in Foundry. That's what we have done. And so therefore, I feel that that is the way we will go to market in our infrastructure business. The other side of the value capture for us is going to be incorporating all this IP. Not only we have the exclusivity of the model in Azure, but we have access to the IP.
我们在处理 Azure Foundry 时采用的策略是什么呢？假如你想构建一个 AI 应用程序，关键在于确保你的评估或是使用 AI 的结果是优秀的。这就是为什么我们需要在 Foundry 中拥有一个完整的应用服务器。这就是我们目前正在做的。因此，我认为这将是我们在基础设施业务中推向市场的方式。对于我们来说，捕获价值的另一面是整合所有这些知识产权。不仅我们在 Azure 上拥有模型的独家使用权，我们还可以接触到这些知识产权。
I mean, having a royalty free, let's even forgetting all the know how and the knowledge side of it. But having royalty free access all the way till seven more years gives us a lot of flexibility, business model wise. It's kind of like having a frontier model for free. In some sense, if you're an MSFT shareholder, that's kind of where you should start from is to think about we have a frontier model that we can then deploy, whether it's in GitHub, whether it's in M365, whether it's in our consumer copilot, then add to it our own data, post train it. So that means we can have it embedded in the weights there.
我的意思是，免版税地获取这一技术，再让我们暂时不考虑技术知识层面的问题，能够在未来七年内免版税地使用这项技术，给了我们在商业模式上的极大灵活性。这有点像免费获得了一个前沿模型。从某种意义上说，如果你是微软（MSFT）的股东，你应该从这点出发去思考：我们拥有一个前沿模型，可以部署在GitHub、M365或我们的消费者助手中，然后添加我们自己的数据进行后期训练。这意味着我们可以将其嵌入到模型的权重中。
And so therefore, we are excited about the value creation on both the Azure and the infrastructure side, as well as in our high value domains, whether it is in health, whether it's in knowledge work, whether it's encoding or security. You've been consolidating the losses from OpenAI. You know, I think you just reported early in yesterday. I think you consolidated four billion of losses in the quarter. Do you think that investors are, I mean, they may even be a attributing negative value, right? Because of the losses, as they apply, they're multiple of earnings such, whereas I hear this and I think about all of those benefits we just described, not to mention the look through equity value that you own in a company that could be worth a trillion unto itself.
因此，我们对在Azure和基础设施方面，以及在我们高价值领域的价值创造感到非常兴奋，无论是健康领域、知识工作、编码还是安全。您一直在合并OpenAI的损失。我想，您昨天刚刚报告过，我认为您在这个季度合并了40亿美元的损失。您认为投资者可能会因此而对这项投资持负面看法吗？因为这些损失会影响他们对收益的评估。然而，我听到这些时，会想到我们刚刚描述的所有这些好处，更不用说您在一个可能自身价值达到万亿美元的公司中的股权价值了。
Do you think that the market is kind of misunderstanding the value of OpenAI as a component of Microsoft? Yeah, that's good one. So I think the approach that Amy is going to take is full transparency because at some level, I'm no accounting expert. So therefore, the best thing to do is to give all of the transparency. I think this time around as well, I think that's why the non-gap gap so that at least people can see the EPS numbers because the common sense where I look at it, Brad is simple. If you've invested, let's call it $13.5 billion, you can of course, lose $13.5 billion, but you can't lose more than $13.5 billion. At least the last time, I check, that's what you have at risk. You can also say, hey, the $135 billion that is, today, our equity stake is sort of illiquid. What have you? We don't plan to sell it.
你认为市场对OpenAI作为微软的一个组成部分的价值有些误解吗？是的，这个问题很好。我认为，Amy将采取的做法是完全透明，因为在某种程度上，我不是会计专家。因此，最好的办法就是提供所有的信息透明。我认为这次也是如此，这也是为什么要有非GAAP差异，这样至少人们可以看到每股收益（EPS）的数据。简单从常识来看，Brad，如果你投资了135亿美元，你当然有可能损失135亿美元，但你不会损失超过135亿美元。至少在我上次查看时，这是你的风险所在。你也可以说，我们今天持有的价值135亿美元的股权有点不易变现。不管怎样，我们不打算出售它。
So therefore, it's got risk associated with it, but the real story I think you are pulling is all the other things that are happening. What's happening with Azure growth? Would Azure be growing if we had not sort of had the OpenAI partnership to your point? The number of customers who came from other clones, clouds, for the first time. This is the thing that really we benefited from. What's happening with Microsoft 365? In fact, one of the things about Microsoft 365 was, what was the next big thing after E5? Guess what? We found it in Copilot. It's bigger than any suite. Talk about penetration and usage and the pace. It's bigger than anything we have done in our information work, which we mean added for decades. We feel very, very good about the opportunity to create value for our shareholders.
所以，这确实存在一定风险，但我认为你想关注的是其他正在发生的事情。Azure 的增长情况如何？如果没有与 OpenAI 的合作，Azure 会增长吗？有很多客户是第一次从其他云平台转过来的，这对我们来说是一个巨大的收益。至于 Microsoft 365 的情况，其中一个焦点是，在 E5 之后的下一个大举措是什么？我们找到了，那就是 Copilot。它的规模超过任何一个套件。谈到渗透率、使用率和发展速度，它比我们在信息工作领域多年来做过的任何事情都大。我们对为股东创造价值的机会感到非常乐观。
Then at the same time, we fully transparent so that people can look through the what are the losses. Who knows what the accounting rules are, but we will do whatever is needed and people will then be able to see what's happening. A year ago, Sacha, there were a bunch of headlines that Microsoft was pulling back on AI infrastructure. Fair or unfair, they were out there. You know. Perhaps you guys were a little more conservative, a little more skeptical of what was going on. Amy said on the call last night, though, that you've been short power and infrastructure for many quarters. She thought that you would catch up, but you haven't caught up because demand keeps increasing. I guess the question is, were you too conservative knowing what you know now?
同时，我们会保持完全透明，这样人们就可以查看损失情况。会计规则如何尚未可知，但我们会根据需要采取行动，这样人们就能看到发生了什么。一年前，有很多报道说微软在削减人工智能的基础设施。无论这些报道是公平还是不公平，它们确实存在。或许你们当时在对局势的判断上比较保守和怀疑。然而，Amy在昨晚的电话中提到，你们已经好几个季度在电力和基础设施方面处于短缺状态。她认为你们会赶上，但由于需求不断增加，你们并没有赶上。所以问题是，就目前了解到的情况而言，过去是否太过保守了？
What's the roadmap from here? It's a great question because the thing that we realized, and I'm glad we did, is that the concept of building a fleet that truly was fungible, fungible for all the parts of the life cycle of AI, fungible across geographies, and fungible across generations. Right. So because one of the key things is when you have, let's take even what Jensen and Tim are doing. Right. I mean, they're at a pace. In fact, one of the things I like is the speed of light. Right. We now have GB 300s bringing, you know, that we're bringing up. So you don't want to have ordered a bunch of GB 200s that are getting plugged in only to find the GB 300s are in full production.
从这里开始的路线图是什么？这是个很好的问题，因为我们意识到（也很庆幸我们意识到了）打造一个真正具有可替换性的舰队这一概念十分重要。这个舰队需要在AI生命周期的所有部分、不同地理位置及不同世代之间都具有可替换性。这一点非常关键。比如说，看看Jensen和Tim正在做的事情，他们的速度极快。我非常欣赏这种“光速”的方式。现在我们正在投用GB 300s。因此，你不希望在刚装上大量GB 200s后，才发现GB 300s已经全面量产了。
So you kind of have to make sure you're continuously modernizing. You're spreading the fleet all over. You are really truly fungible by workload. And you're adding to that the software optimizations we talked about. So to me, that is the decision we made. And we said, look, sometimes you may have to say no to some of the demand, including some of the open AI demand, right? Because sometimes, you know, Sam may say, hey, give me a dedicated, you know, big, you know, whatever multi gigawatt data center in one location for training, make sense from an open AI perspective, doesn't make sense from a long term infrastructure build out for Azure.
所以，你必须确保不断进行现代化改造。你要将资源分散在各个地方，并且能够根据工作负载灵活调整。此外，还要加入我们之前提到的软件优化。因此，对我来说，这是我们做出的决定。我们也表明，有时候你可能需要拒绝某些需求，包括一些来自OpenAI的需求。比如有时候，可能会有请求说，“嘿，给我一个专用的、多千兆瓦的数据中心，用于某个地点的训练”，从OpenAI的角度看这样做可能有意义，但从Azure的长期基础设施建设来看就不合理。
That's where I thought they did the right thing to give them flexibility to go procure that from others. While maintaining, again, a significant book of business from open AI, but more importantly, giving ourselves the flexibility with other customers, our own one P. Remember, like one of the things that we don't want to do is be short on is, you know, we talk about Azure. In fact, some of times our investors are overly fixated on the Azure number. But remember, for me, the high margin business for me is co-pilot. It is security co-pilot. It's GitHub co-pilot. It's the healthcare co-pilot.
我认为他们这样做是对的，他们给予了灵活度，让其他公司参与采购。与此同时，我们仍然保留与OpenAI的重要业务关系，更重要的是，也让我们在与其他客户和我们自身业务中保留了灵活性。请记住，我们不希望缺少的是，正如我们常提到的Azure。有时我们的投资者过于关注Azure的数据。但对我来说，高利润业务是各种“协作助手”，包括安全协作助手、GitHub协作助手和医疗保健协作助手。
So we want to make sure we have a balanced way to approach the returns that the investors have. And so that's kind of one of the other misunderstood perhaps in our investor base in particular, which I find pretty strange and funny because I think they they want to hold Microsoft because of the portfolio we have. But man, are they fixated on the growth number of one little thing called Azure? On that point, Azure grew 39% in the quarter on a staggering $93 billion run rate. And, you know, I think that compares to GCP that grew at 32% and AWS closer to 20%. But could Azure because you did give compute to one P and because you did give compute to research.
我们希望确保对投资者的回报有一个平衡的方式。因此，我觉得我们的投资者群体中有一些被误解的地方，这让我觉得既奇怪又有趣，因为他们想持有微软的股份是因为我们强大的投资组合。然而，他们却非常关注其中一个小部分——Azure的增长。在这一点上，Azure在这个季度增长了39%，达到了惊人的930亿美元运行率。我认为这相比于谷歌云的32%增长和亚马逊AWS接近20%的增长都是不错的表现。Azure的增长是否与您提供给一方的一些计算能力或提供给研究方面的计算能力有关呢？
It sounds like Azure could have grown 41% 42% had you had more compute to all. Absolutely. Absolutely. There's no question. There's no question. So that's why I think the internal thing is to balance out what we think again is in the long term interests of our shareholders. And I know to serve our customers well. And also not to kind of, you know, one of the other things was, you know, people talk about concentration risk, right? We obviously want a lot of open AI. But we also want other customers. And so we're shaping the demand here. You know, we are in a supply, you know, you know, we're not demand constrained, we're supply constrained. So we're shaping the demand such that it matches the supply in the optimal way with the long term view.
听起来，如果 Azure 有更多的计算资源，其增长率可能达到 41% 或 42%。绝对如此，毫无疑问。这就是为什么我们认为内部需要平衡，以符合股东的长期利益。我知道我们也要好好服务客户。同时，我们不想面对集中风险的问题，大家都谈论这个。我们显然希望在 OpenAI 上有所作为，但我们也希望拥有其他客户。所以我们在调整需求。我们处于供应限制状态，而不是需求限制状态。因此，我们需要根据供应情况来优化需求，以实现长期目标。
To that point, Sacha, you talked about 400 billion. It's an incredible number of remaining performance obligations last night. You said that, you know, that's your book business today. It'll surely go up tomorrow as sales continue to come in. And you said you're going to, you know, you're need to build out capacity just to serve. That backlog is very high. You know, how diversified is that backlog to your point? And how confident are you that that 400 billion does turn into revenue over the course of the next couple of years? Yeah. That 400 billion has a very short duration. It's an Amy expert. It's the two year duration on average.
关于这个话题，Sacha，你提到了4000亿。昨晚提到的这个剩余履行义务的数字令人难以置信。这就是你们目前的业务现状。随着销售的继续，这个数字在未来肯定会增加。你还说你需要扩大产能以满足需求。积压订单非常多。那么，关于你的问题，这些积压订单的多样化程度如何？你对这4000亿在未来几年内转化为收入有多大信心？是的，这4000亿的平均履行期限很短，大约是两年。
So that's definitely our intent. That's one of the reasons why we're spending the capital outclear with high certainty that we just need to clear right backlog. And to your point, it's pretty diversified both on the one P and the three P. Our own demand is quite likely pretty high for our one first party. And even amongst third party, one of the things we're now are seeing is the rise of all the other companies building real workloads. That are scaling. And so given that, I think we feel very good. I mean, obviously, it's that's one of the best things about RPOs. You can be planned for quite frankly.
所以这确实是我们的意图。这也是我们投入大量资金的原因之一，我们非常确定需要清理积压的问题。正如你所说，我们的业务在第一方和第三方之间是相当多样化的。我们的第一方业务需求可能很高。而在第三方中，我们现在看到的是其他公司建立实际工作负载的兴起，并且这些工作负载正在扩大。因此，鉴于此，我们感到很有信心。坦白说，这也是RPO（可承诺收入）最好的优势之一，你可以提前规划。
And so therefore, we feel very, very good about building. And then this doesn't include obviously the additional demand that we're already going to start seeing, including the 250, you know, which will have a longer duration and will build accordingly. Right. So there are a lot of new entrants, right, in this race to build out compute Oracle, Core, we've crucible, et cetera. And normally we think that will compete away margins, but you've somehow managed to build all this out while maintaining healthy operating margins at Azure.
因此，我们对建设感到非常乐观。而且，这还不包括我们已经开始看到的额外需求，包括那250个，您知道的，那将会有更长的持续时间，并相应地进行建设。对吧。在这场计算能力扩展的竞争中，有很多新参与者，比如Oracle、Core、Crucible等等。通常情况下，我们会认为这会导致利润率竞争走低，但你们却设法在扩建的同时，保持了Azure运营利润的健康。
So I guess the question is for Microsoft, how do you compete in this world that is where people are leveraging up, taking lower margins, while balancing that profit and risk? And do you see any of those competitors doing deals that cause you to scratch your head and say, oh, we're just setting ourselves up for another boom and bust cycle? I mean, at some level, the good news for us has been competing even as a hyperscaler. Every day, you know, there's a lot of competition, right, between us and Amazon and Google on all of these, right?
我想问题是对于微软来说，在这个充满竞争的世界中，你们如何在提高杠杆、降低利润率的情况下，平衡利润和风险进行竞争？你们有没有看到一些竞争对手在进行交易时让你们感到困惑，觉得他们可能会让自己陷入新的繁荣和萧条周期中？对于我们来说，好消息是，即使作为一家超级扩展企业，每天在与亚马逊和谷歌的竞争中，我们依然能很好地竞争。
I mean, it's sort of one of those interesting things, which is everything is a commodity, right, compute storage. I remember everybody saying, wow, how can they be able to margin except at scale, nothing is a commodity. And so therefore, yes, so we have to have a cost structure, our supply chain efficiency, our software efficiencies all have to kind of continue to compound in order to make sure that there's margins, but scale. And to your point, one of the things that I really love about the OpenAI partnership is it's gotten us to scale, right?
我的意思是，这有点像那些有趣的事情，其中一切都是商品，对吧，比如计算存储。我记得每个人都在说，哇，除了在大规模下，怎么可能会有利润，其实没有什么是真正的商品。因此，是的，我们必须拥有一个合适的成本结构，我们的供应链效率以及软件效率都必须不断复合，以确保在规模上的利润。至于你提到的一点，我非常喜欢与OpenAI的合作，因为它让我们达到了规模化的水平，对吧？
This is a scale game. When you have the biggest workload there is running on your cloud, that means not only are we going to learn faster on what it means to operate with scale, that means your cost structure is going to come down faster than anything else. And guess what, that will make us price competitive. And so I feel pretty confident about our ability to, you know, have margins and this is where the portfolio helps. I've always said, you know, I'm being forced into giving the Azure numbers, because at some level, I never thought of allocating,
这是一场规模游戏。当你的云端运行着最大的工作负载时，这不仅意味着我们将更快地学习如何在规模上运作，还意味着你的成本结构将比其他任何东西更快地降低。你猜怎么着，这将使我们具有价格竞争力。因此，我对我们的能力很有信心，也就是能够保持利润率，这正是我们的产品组合所帮助的。我一直都说，我被迫提供Azure的数字，因为在某种程度上，我从未想过要进行分配。
I mean, my capital allocation is for the cloud, from whether it is Xbox cloud gaming or Microsoft 365 or for Azure, it's one capital outlay. And then everything is a meter as far as I'm concerned from an empty perspective. It's a question of, hey, the blended average of that should match the operating margins we need as a company. Because after all, otherwise why we're not a conglomerate, we're one company with one platform logic. It's not running five, six different businesses, we're in these five, six different businesses only to compound the returns on the cloud and AI investment.
我的意思是，我的资金分配主要用于云业务，无论是Xbox云游戏、Microsoft 365，还是Azure。这些都是一个资本投入。而在我看来，剩下的都是取决于使用量的问题。关键在于，整体的平均收益应该符合我们公司所需的运营利润率。毕竟，我们不是一个多元化企业，而是一家有着统一平台逻辑的公司。我们进入这五六个不同领域的目的，都是为了加倍云计算和人工智能投资的回报。
Yeah, I love that line. Nothing is a commodity at scale. You know, there's been a lot of ink and time spent even on this podcast with my partner Bill Gurley talking about circular revenues, including Microsoft, stasher credits, right open AI that were booked as revenue. Do you see anything going on like the AMD deal, you know, where they traded 10% of their equity and, you know, for a deal or the Nvidia deal? Again, I don't want to be overly fixated on concern, but I do want to address head on what is being talked about every day on CMBC and Bloomberg. And there are a lot of these overlapping deals that are going on out there. Do you, do you, when you think about that in the context of Microsoft, does any of that worry you again as to the sustainability or durability of the AI revenues that we see in the world?
是的，我喜欢那句话。在大规模下，任何东西都不会是商品化的。你知道，我和我的合伙人Bill Gurley在这个播客上花了很多时间和精力讨论循环收入，包括微软的情况，比如被计入收入的Stasher积分，以及OpenAI。你有没有注意到类似于AMD的交易，他们用10%的股权来进行交易，或者是Nvidia的交易？我不想过于担心，但我确实想直接面对每天在CNBC和彭博社上讨论的话题。现在有很多这样的重叠交易正在进行。当你在微软的背景下考虑这些问题时，这些AI收入的可持续性或持久性会让你担心吗？
Yeah, I mean, first of all, our investment of, let's say, that 13 and a half, which was all the training investment, that was not booked as revenue. That is the, that is the reason why we have the equity percentage. That's the reason why we have the 27% or 135 billion. So that was not something somehow that made it into Azure revenue. In fact, if anything, the Azure revenue was purely the consumption revenue of chat GPT and anything else. And the APIs, they put out that they monetized and be monetized. To your aspect of others, to some degree, it's always been there in terms of vendor financing, right? So it's not like a new concept that when someone's building something and they have a customer who is also building something, but they need financing for whether it is, it's sort of, they're taking some exotic forms, which obviously need to be scrutinized by the investment community. But that said, when the financing is not a new concept, interestingly enough, we have not had to do any of that, right? I mean, we may have, really either invested in OpenAI and essentially got an equity stake in it for return for compute, or essentially sold them great pricing of compute in order to be able to sort of bootstrap them. But others choose to do so differently.
当然，首先，我们投资的约135亿美元，都是用于培训的投资，并未记录为收入。这就是我们拥有股权比例的原因，也是为什么我们有27%或1350亿的原因。因此，这些资金并没有直接计入Azure的收入。事实上，Azure的收入主要来自于ChatGPT和其他产品的使用收入，以及公开的收费API。因此，这些投资没有影响到Azure的收入。
至于您提到的其他方面，在某种程度上，供应商融资一直都存在。这不是什么新概念，当有人在开发项目时，如果他们的客户也在开发项目，但需要融资时，会采取一些复杂的融资形式，这显然需要得到投资界的审查。不过，即使融资本身不是新鲜事，我们实际上并没有需要这样做。我们可能在OpenAI中进行了投资，并因此获得了一部分股权作为计算资源的回报，或者是以优惠的计算资源价格支持他们的启动。但其他公司可能有不同的选择。
And I think circularity ultimately will be tested by demand because all this will work as long as there is demand for the final output of it. And up to now, that has been the case. Certainly, certainly. Why wouldn't a shift, you know, as you said, over half your business to software applications, you know, I want to think about software and agents, you know, last year on this pod, you made a bit of a stir by saying that much of the application software, you know, was this thin layer that sat on top of a crud database? The notion that business applications exist, that's probably where they're all collapse, right, in the agent era. Because if you think about it, right, they are essentially crud databases with a bunch of business logic.
我认为循环性最终会受到需求的考验，因为只要对其最终产品有需求，这一切才会有效。到目前为止，确实是这样。当然，当然。为什么不把你一半以上的业务转向软件应用呢？我想谈谈软件和代理的问题。去年在这个播客上，你提到很多应用软件只是一个覆盖在简单数据库上的薄层，这引起了一些轰动。在代理时代，关于商业应用程序存在的概念，可能在这一点上它们都会崩溃。因为如果你想想看，它们本质上就是带有大量业务逻辑的简单数据库。
The business logic is all going to these agents. Public software companies are now trading at about 5.2 times forward revenue. So that's below their 10-year average of seven times, despite the markets being at all time highs. And there's lots of concern that SaaS subscriptions and margins maybe put at risk by AI. So how today is AI affecting the growth rates of your software products, of, you know, those core products? And specifically, as you think about database, fabric, security, office 360. And then second question, I guess, is what are you doing to make sure that software is not disrupted, but is instead super powered by AI?
业务逻辑正在转移到这些代理商。目前，上市软件公司的交易价格大约是预期收入的5.2倍。这低于它们过去十年的平均水平7倍，尽管市场处于历史高点。很多人担心人工智能可能会威胁到SaaS订阅和利润率。因此，目前人工智能是如何影响你们的软件产品增长率的，尤其是那些核心产品？具体来说，对于数据库、数据模式、安全性、Office 360等产品，你们是怎么看待的？第二个问题是，你们在做些什么以确保软件不会被人工智能颠覆，而是更加增强？
Yeah, I think that's right. So the last time we talked about this, my point really, there was the architecture of SaaS applications is changing, because this agent here is replacing the old business logic tier. And so because if you think about it, the way we built SaaS applications in the past was you had the data, the logic tier, and the UI, all tightly coupled. And AI, quite frankly, doesn't respect that coupling, because it requires you to be able to decouple. And yet, the context engineering is going to be very important. I mean, take, you know, something like Office 365. One of the things I love about our Microsoft 365 offering is it's low RPU, high usage. Right? I mean, if you think about it, right? Outlook or Teams or SharePoint, you pick Word or Excel, like people are using it all the time, creating lots and lots of data, which is going into the graph. And our RPU is low. So that's sort of what gives me real confidence that this AI tier, I can meet it by exposing all my data.
是的，我认为这是对的。上次我们讨论这个话题时，我的主要观点是，SaaS应用程序的架构正在发生变化，因为这里的智能代理正在取代旧的业务逻辑层。想想看，以前我们构建SaaS应用程序的方式是数据、逻辑层和用户界面紧密耦合。而AI实际上并不遵循这种耦合，因为它需要你能够解耦。然而，情境工程将变得非常重要。举个例子，比如Office 365。我喜欢Microsoft 365的一点是，它的每用户平均收益（RPU）低，但使用率高。想一想，无论是Outlook、Teams、SharePoint，还是Word或Excel，人们一直在使用它们，创造了大量数据，这些数据被传入图谱中。而我们的每用户平均收益很低。这让我对AI层有信心，因为我可以通过公开我的所有数据来适应它。
In fact, one of the fascinating things that's happened, Brad with both GitHub and Microsoft 365 is thanks to AI, we're seeing all time highs in terms of data that's going into the graph or the repo. I mean, think about it, the more code that gets generated, whether it is Codex or Clod or wherever, where is it going? GitHub. More power points that get created, Excel models that could create it, all these artifacts and chat conversations, chat conversations are new docs. They're all going to the graph and all that is needed again for grounding. So that's what you turn it into a forward index, into an embedding. And basically, that's semantics is what you really go ground any agent request.
其实，Brad，令人着迷的是，在 GitHub 和 Microsoft 365 中，由于人工智能的发展，我们看到进入数据图表或代码仓库的数据量达到了历史新高。想想看，无论是 Codex、Clod 还是其他任意生成的代码，它们都被上传到哪里？GitHub！更多的演示文稿、Excel 模型，还有各种文档和聊天对话——这些聊天对话已经成为新的文档形式——它们都进入了数据图表，而这些都是系统的基础。这些数据最终被转换成前向索引或嵌入；实际上，这个过程是为了赋予语义，以便为任何智能代理的请求提供准确的基础信息。
And so I think the next generation of SaaS applications will have to sort of, if you are high RPU low usage, then you have a little bit of a problem. But if you are we are the exact opposite, we are low RPU high usage. And I think that anyone who can structure that and then use this AI as in fact, an accelerant because I mean, right, if you look at the M365 Copa price, I mean, it's higher than any other thing that we sell. And yet it's getting deployed faster and with more usage. And so I feel very good or coding, right, who would have thought in fact, think GitHub, right? What GitHub did in first or 15 years of its existence or 10 years of its existence, it was basically done in the last year, which is because coding is no longer a tool, it's more a substitute for wages.
所以我认为下一代的SaaS应用需要有所调整。如果你的应用是高ARPU（每用户平均收益）但使用率低，那可能会有一点问题。但我们正好相反，我们是低ARPU高使用率。我认为，任何能够做到这一点并利用AI加速发展的人都会获得成功。看看M365的Copa价格，它比我们销售的任何其他产品都高。但它的部署速度和使用率都是最高的。所以我对编码感到很乐观，想想GitHub吧。在其存在的前10到15年间完成的事情，在过去的一年里就基本上完成了。这是因为编码不再仅仅是一个工具，而更像是工资的替代品。
And so it's a very different type of business model. I kind of think about the stack and where value gets distributed. So until very recently, right, clouds largely ran pre compiled software. You didn't need a lot of GPUs and most of the value accrued to the software layer, to the database, to the applications like CRM and Excel. But it does seem in the future that these interfaces will only be valuable, right, if they're intelligent, right? If they're pre compiled, they're kind of dumb. The software's got to be able to think and to act and to advise. And that requires, you know, the production of these tokens, you know, dealing with the ever changing context.
这是一种截然不同的商业模式。我常常思考这个体系以及价值的分配。在直到最近为止的时间里，云服务主要运行的是预编译的软件，你并不需要太多的GPU，大部分的价值都集中在软件层面，比如数据库以及像CRM和Excel这样的应用程序上。但未来这些界面似乎只有在智能化的情况下才会真正有价值。如果它们是预编译的，那么就显得有些愚钝。软件必须能够思考、行动和提供建议。要做到这一点，就需要生成这些符号（tokens）并处理不断变化的环境。
And so in that world, it does seem like much more of the value will accrue to the AI factory, if you will, to, you know, gents in producing, you know, helping to produce these tokens at the lowest cost and to the models. And maybe that the agents or the software will accrue a little bit less of the value in the future than they've accrued in the past. Well, steel man for me, why that's wrong. Yeah, so I think there are two things that are necessary to try and to drive the value of AI. One is what you describe first, which is the token factory. And even if you unpack the token factory, it's the hardware silicon system.
在这样的世界里，看起来更多的价值会聚集在“AI工厂”上，比如说，它帮助以最低成本生产这些"代币"以及相关模型。而这些软件代理或者说代理工具在未来可能会积累比过去更少的价值。那让我来反驳一下为什么这种说法不对。我认为推动AI价值的增长需要两个要素。首先是你所说的“代币工厂”，即使我们把“代币工厂”拆分来看，它也包括硬件、芯片等系统。
But then it is about running it most efficiently with the system software, with all the fungibility, max utilization. That's where the hyperscalers role is, right? What is a hyperscaler? Is hyperscaler? Like everybody says, if you sort of said, hey, I want to run a hyperscaler. Yeah, you could say, oh, it's simple. I'll buy a bunch of servers and wire them up and run it. It's not that, right? I mean, it was that simple, then there would have been more than three hyperscalers by now. So the hyperscaler is the know how of running that max utel and the token factories. And it's not the end, by the way, it's going to be heterogeneous, obviously, gents in super competitive.
然后，这就是如何通过系统软件以最高效的方式运行它，包括灵活性和最大化利用率。这就是超大规模经营者的角色，对吧？那么，什么是超大规模经营者呢？是否每个人都在谈论这个概念？如果有人说，他们想运营一个超大规模的系统。你可能会说，这很简单，我只要买一堆服务器，把它们接在一起运行就行了。但实际上并不是这样。如果真有这么简单的话，那现在就会有超过三家超大规模经营者了。超大规模经营者的关键在于如何管理最大化的利用率以及代币工厂。这还不是终点，因为这将是一个异构并且高度竞争的领域。
Lisa is going to come, you know, Hawks going to produce things from Broadcom. We will all do our own. So there's going to be a combination. So you want to run ultimately a heterogeneous fleet that is maximized for token throughput, inefficiency, and so on. So that's kind of one job. The next thing is what I call the agent factory. Remember that a SaaS application in the modern world is driving a business outcome. It knows how to most efficiently use the tokens to create some business value. In fact, GitHub Copilot is a great example of it, right? Which is, you know, if you think about it, the auto mode of GitHub Copilot is the smartest thing we've done, right?
丽莎会来，你知道的，Hawks会从博通（Broadcom）生产东西。我们都会做我们自己的部分，所以这将是一个组合。你希望最终运行一个由不同设备组成的车队，以最大化代币吞吐量、效率等。这是其中一个任务。下一个事情是我称之为“代理工厂”（agent factory）的东西。记住，一个现代世界的SaaS应用程序是在推动业务成果。它知道如何最有效地使用代币来创造一些业务价值。事实上，GitHub Copilot 就是一个很好的例子，对吧？如果你想想看，GitHub Copilot 的自动模式是我们做过的最聪明的事情。
So it chooses based on the prompt, which model to use for a code completion or a task handoff, right? That's what you and you do that, not just by, you know, choosing in some round robin fashion, you're doing because of the feedback cycle you have, you have the e-vals, the data loops and so on. So the new SaaS applications, as you rightfully said, are intelligent applications that are optimized for a set of e-vals and a set of outcomes that then know how to use the token factories output most efficiently. Sometimes latency matters, sometimes performance matters and knowing how to do that trade in a smart way is where the SaaS application value is.
所以，这个系统根据提示选择使用哪个模型来进行代码补全或任务交接，对吧？这就是你们所做的，并不是简单地以轮询的方式选择，而是基于反馈循环、e-val评估、数据循环等来进行选择。正如你所说，新的SaaS应用程序是智能化的应用，它们针对一系列e-val评估和预期结果进行了优化，这样就能够最有效地利用token工厂的输出。有时候，延迟很重要，有时候，性能很重要，知道如何在两者之间进行聪明的权衡，就是SaaS应用程序的价值所在。
But overall, it is going to be true that there is a real marginal cost to software this time around. It was there in the cloud era too, and we were doing, you know, CD-ROMs, there wasn't much of a marginal cost, you know, with the cloud there was, and this time around it's a lot more. And so therefore, the business models have to adjust and you have to do these optimizations for the agent factory and the token factory separately. You have a big search business that most people don't know about, you know, but it turns out that that's probably one of the most profitable businesses in the history of the world because people are running lots of searches, billions of searches, and the cost of completing a search if your Microsoft is many fractions of a penny, right, doesn't cost very much to complete a search.
总体来说，这次软件确实存在一个实际的边际成本。在云时代也存在这样的成本，而在我们使用CD-ROM的时候，边际成本并不高；云计算时代则有了一些，而这次的成本要高得多。因此，商业模式需要进行调整，你必须分别优化代理工厂和令牌工厂。你拥有一个大规模的搜索业务，多数人可能并不知情，但事实证明这可能是世界历史上最赚钱的业务之一，因为人们进行大量的搜索，数以十亿计，而如果你是微软，完成一次搜索的成本只是几分钱的一小部分，因此完成搜索的成本并不高。
But the comparable query or prompt stack today when you use a chatbot looks different, right? So I guess the question is assume similar levels of revenue in the future for those two businesses, right? Do you ever get to a point where kind of that chat interaction has unit economics that are as profitable as search? I think that's a great point because see, search was pretty magical in terms of its ad unit and its cost economics because there was the index which was a fixed cost that you could then amortize in a much more efficient way. Whereas this one, you know, each chat to your point, you have to burn a lot more GPU cycles both with the intent and the retrieval.
今天，当你使用聊天机器人时，相应的查询或提示堆栈看起来与以往不同，对吧？因此，我猜想问题是，假设这两项业务未来的收入水平相似，你是否能达到一个点，即聊天互动的单位经济效益能像搜索一样盈利？我认为这是个很好的问题，因为搜索在广告单元和成本经济方面相当神奇，因为有一个固定成本的索引，可以以更高效的方式摊销。然而，在聊天方面，你需要耗费更多的GPU循环来处理意图和检索。
So the economics are different. So I think you knew that's why I think a lot of the early sort of economics of chat have been the freemium model and subscription on the even on the consumer side. So we are yet to discover whether it's agentic commerce or whatever is the ad unit, how it's going to be litigated. But at the same time, the fact that at this point, you know, I kind of know, in fact, I use search for very very specific navigational queries. I used to say I use it a lot for commerce, but that's also shifting to my, you know, copilot look at the copilot mode in edge and being or copilot.
所以这里的经济模式不太一样。我想你知道这也是为什么很多早期的聊天经济模式采用了免费增值模式和订阅制，甚至在消费者端也是如此。我们还不确定未来会是代理商务还是其他形式的广告单元，以及它将如何发展。但与此同时，事实上此时此刻，我其实知道，我使用搜索主要是用于非常具体的导航查询。我以前常说我经常用它来购物，但这也正在转向我的助手模式，比如在Edge和Bing中的助手模式。
Now they're blending in. So I think that yes, I think that is going to be a real litigation. Just like we talked about the SaaS disruption, we're in the beginning of the cheese being a little moved in consumer economics of that category. Right. I mean, and given that it's the multi trillion dollar, this is the thing that's driven all the economics of the internet, right? When you move the economics of search for both you and Google and it converges on something that looks more like a personal agent, a personal assistant chat, you know, that could end up being much, much bigger in terms of the total value delivered to humanity, but the unit economics, you're not just tamerizing this one time fixed index.
现在他们正在融入其中。所以我认为，是的，我认为这将成为一个真正的诉讼。就像我们之前讨论的SaaS颠覆一样，我们正处于消费者经济中某个类别的局势略有变动的初期阶段。对吧，我的意思是，考虑到这是个数万亿美元的市场，它推动了互联网的所有经济活动。你和谷歌的搜索经济在改变，当它趋于类似个人代理或个人助手聊天的形式时，这可能在对人类提供的总价值方面变得更大更重要，但单元经济不是只是简单地将这种一次性的固定指数化。
That's right. And so that's right. The consumer. Yeah, the consumer category, because you are pulling a thread on something that I think a lot about, right? Which is what, during these disruptions, you kind of have to have a real sense of where is, what is the category economics? Is it winner take all and both matter? Right. The problem in consumer space always is that there's finite amount of time. And so if I'm not doing one thing, I'm doing something else. And if your monetization is predicated on some human interaction in particular, if there was truly a gentick stuff, even on consumer, that could be different.
没错。正如你所说，消费者这个类别确实如此。因为你提到了一些让我深思的事情。在这些变化中，你必须真正了解类别经济的现状。是不是赢家通吃，两者都很重要？消费者领域的问题在于时间是有限的。如果我不在做一件事情，那么我就在做另一件。而如果你的盈利模式特别依赖于某种人际互动，那么即使在消费者方面，如果存在真正的独特因素，那也可能会有所不同。
Whereas in the enterprise, one is it's not winner take all. And two, it is going to be a lot more friendly for agentic interaction. So it's not like, for example, the first seat versus consumption. The reality is agents are the new seats. And so you can think of it as the enterprise monetization is much clearer. The consumer monetization, I think, is a little more murky. You know, we've seen a spade of layoffs recently with Amazon announcing it's a big layoffs this week. You know, the Mag 7 is at little job growth over the last three years, despite really robust top lines. You know, you didn't grow your head count really from 24 to 25. It's around 225,000.
在企业环境中，首先，这并不是一个赢家通吃的局面。其次，这将更加有利于代理的互动。这与第一排座位和消费的关系不同。实际上，代理就像是新的座位。因此，可以认为企业的盈利模式更为清晰，而消费领域的盈利则相对不那么明确。我们最近看到了一波裁员，亚马逊本周宣布了大规模裁员。尽管这几年的总体业务表现强劲，但“Mag 7”公司在过去三年中的就业增长却很有限。比如，你的员工数量并没有从24万增长到25万，而是大约保持在22.5万左右。
You know, many attribute this to normal getting fit. You know, just getting more efficient coming out of COVID. And I think there's a lot of truth to that. But do you think part of this is due to AI? Do you think that AI is going to be a net job creator? And do you see this being a long term positive for Microsoft productivity? Like it feels to me, like the pie grows, but you can do all these things much more efficiently, which either means your margins expand or it means you reinvest those margin dollars and you grow faster for longer.
你知道，很多人将这归因于恢复正常的健身状态。你知道，就是说在疫情过后，效率提高了。我认为这在很大程度上是正确的。但是，你认为这部分是因为人工智能吗？你认为人工智能会成为净就业岗位的创造者吗？你是否认为这对微软的生产力来说是一个长期的积极因素？在我看来，整体市场在增长，但你可以用更高效的方法完成所有这些事情，这要么意味着你的利润率扩大，要么意味着你将这些利润再投资，从而实现更长久的快速增长。
I caught the golden age of margin expansion. I'm a firm believer that the productivity curve does and will bend or in the sense that we will start seeing some of what is the work and the work flowing particular change, right? There's going to be more agency for you at a task level to get to job complete because of the power of these tools in your hand. And that I think is going to be the case. So that's why I think we are even internally, for example, when you talked about even our allocation of tokens, we want to make sure that everybody at Microsoft standard issue, right? All of them have Microsoft 365 to the tilt in the sort of most under limited way and have get up co-pilot so that they can really be more productive.
我赶上了利润扩张的黄金时代。我坚信生产力曲线确实会弯曲，或者说我们将开始看到工作流的某些变化。得益于手中这些工具的强大功能，你将在任务层面上拥有更多自主权以完成工作。我认为这将成为现实。因此，我认为即便在公司内部，例如在谈到我们如何分配令牌时，我们想确保每位员工都能使用微软标准配置。也就是说，他们都能够充分使用Microsoft 365和GitHub Co-Pilot，从而真正提高工作效率。
But here is the other interesting thing that Brad will be learning is there's a new way to even learn, right? Which is, you know, how to work with agents, right? So that's kind of like when the first when word Excel PowerPoint all showed up in office, kind of we learn how to rethink. So let's say how we did a forecast, right? I mean, think about it, right? In the 80s, the forecast were inter-office memos and faxes and what have you? And then suddenly somebody said, oh, here's an Excel spreadsheet. Let's put in an email, send it around people, enter numbers and there was a forecast.
但这里还有一件有趣的事情，布拉德将会学习一种新的学习方式，对吧？这就是如何与智能助手合作，对吗？这有点像当初 Word、Excel 和 PowerPoint 刚进入办公室时，我们学会了重新思考。例如，当时我们是如何做预测的，对吧？想想看，在80年代，预测是通过内部备忘录和传真等方式进行的。但突然间，有人说，哦，这里有个 Excel 电子表格，我们可以把它放在电子邮件里，发给大家填写数字，于是就有了一个预测。
Similarly, right now, any planning, any execution starts with AI, you research with AI, you think with AI, you share with your colleagues and what have you. So there's a new artifact being created and a new workflow being created. And that is the rate of the pace of change of the business process that matches the capability of AI. That's where the productivity efficiencies come. And so organizations that can master that are going to be the biggest beneficiaries, whether it's in our industry or quite frankly in the real world.
同样地，现在任何计划和执行工作都是从人工智能开始的。你用人工智能进行研究，用人工智能思考，与同事分享信息等等。因此，一种新的方式和新的工作流程正在形成。这种业务流程的变化速度正好匹配人工智能的能力，这也是生产效率提高的源泉。因此，那些能够掌握这种模式的组织将成为最大的受益者，无论是在我们的行业中，还是在现实世界中。
And so is Microsoft benefiting from that? You know, so let's think about a couple of years from now, five years from now, at the current growth rate will be sooner, but let's call five years from now, your top line is twice as big as what it is today, Sacha. How many more employees will you have if you're if you grow revenue by like one of the best things right now is these examples that I'm hit with every day from the employees of Microsoft. There was this person who leads our network operations, right? I mean, if you think about the amount of fiber we have had to put for like this, you know, this two gigawatt data center we just built out in fair water, right?
微软是否从中受益呢？让我们想想几年后的情况，五年后，如果按照当前的增长速度，可能会更快一些，但我们就先说五年后，你们的营收将是现在的两倍，萨提亚（注：假定萨提亚为微软负责高管）。如果你们的收入增长速度如同现在这样的好情况，你们会有多少员工呢？目前我每天都会收到微软员工带来的很多例子，其中一个是负责我们网络运营的人。想想我们为了这个新建在法尔沃特的两千兆瓦的数据中心需要铺设的光纤数量，对吧？
And the amount of fiber there, the AI, and whatever, it's just crazy, right? So and it turns out this is a real world asset. There are I think 400 different fiber operators we're dealing with worldwide. Every time something happens, we're literally going and dealing with all these DevOps pipelines. The person who leads it, she basically said to me, you know what, there's no way I'll ever get the head count to go do all this. Not forget, even if I even approved the budget, I can't hire all these folks. So she did the next best thing. She just built herself a whole bunch of agents to automate the DevOps pipeline of how to deal with the maintenance.
这里有大量的光纤、人工智能等等，真的很疯狂，对吧？结果发现这是一个真实世界的资产。我们在全球范围内大约处理400家不同的光纤运营商。每当出现什么情况时，我们都需要处理所有这些DevOps流水线。负责这个项目的人基本上对我说，她不可能获得足够的人手来完成所有这些工作。即便预算获批，她也雇不到这么多人。因此，她采取了次优方案：她自己建立了一整套代理，用于自动化处理DevOps流水线中的维护工作。
That is an example of your to your point, a team with AI tools being able to get more productivity. So if you are question, I will say we will grow a head count. But the way I look at it is that head count we grow will grow with a lot more leverage than the head count we had, pre AI. And that's the adjustment, I think structurally or seen first, right? Which is one, you call it getting fit. I think of it as more getting to a place where everybody is really not learning how to rethink how they work. And it's the how, not even the what, even if the what remains the constant, how you go about it has to be relearned.
这就是一个例子，说明你的观点：一个拥有AI工具的团队可以提高生产力。所以如果你有疑问，我会说我们的员工人数会增长。但在我看来，我们增加的员工人数将比AI出现前的员工更具杠杆效应。这是结构上的调整，我想这是首先会看到的变化。你可以称之为“变得更有能力”，而我认为这是在大家真正学习如何重新思考工作方式的阶段。重点在于“如何工作”，而不是“工作内容”，即使工作的内容保持不变，你处理的方式也必须重新学习。
And it's the unlearning and learning process that I think will take the next year or so. Then the head count growth will come with max leverage. Yeah, no, it's a, I think we're on the verge of incredible economic productivity growth. It does feel like when I talk to you or Michael Dell that most companies aren't even really in the first any, maybe the first batter in the first inning in reworking those workflows to get maximum leverage from these agents. But it sure feels like over the course of the next two to three years. That's where a lot of gains are going to start coming from.
这将是一个需要大约一年左右时间的"去学习和再学习"的过程。然后，我们的人力增长将达到最高的杠杆效应。我觉得我们正处在经济生产力极大增长的边缘。当我与你或迈克尔·戴尔交流时，确实觉得大多数公司在重新设计工作流程以从这些代理中获得最大杠杆这方面，甚至还处在起步阶段的第一局。但确实感觉在未来两到三年内，这将是许多收益开始涌现的领域。
And again, I, you know, I certainly am an optimist. I think we're going to have net job gains from all of this. But I think for those companies, they'll just be able to grow their bottom line, their number of employees slower than their top line. That is the productivity gain to the company aggregate all that up. That's the productivity came to the economy. And then we'll just take that consumer surplus and invest it in creating a lot of things that didn't exist before. 100%. 100%. Even in software development, right? One of the things I look at it is no one would say we're going to have a challenge in having, you know, more software engineers contribute to our sort of society because the reality is you look at the IT backlog in any organization. And so the question is, all these software agents are hopefully going to help us go and take a whack at all of the IT backlog we have.
当然，我是一个乐观主义者。我相信我们最终会实现净就业增长。不过，我认为对于某些公司来说，他们将能够让员工人数的增长速度低于收入的增长速度。这就是公司整体的生产力提升，累积到经济上就是一种生产力的提高。然后我们会将这些消费者盈余投资于创造大量以前不存在的事物。绝对的，百分之百！即使在软件开发领域也是如此。没有人会说，我们在增加更多软件工程师来为社会做贡献方面面临挑战。因为实际上，你看看任何组织的IT积压情况。所以问题在于，希望所有这些软件代理能够帮助我们解决我们面临的所有IT积压问题。
And think of that dream of evergreen software that's going to be true. And then think about the demand for software. So I think that to your point, it's the levels of abstraction in which knowledge work happens will change. We will adjust to that. The work and the workflow. That will then adjust itself even in terms of the demand for the products of this industry. I'm going to end on this, which is really around the reindustrialization of America. Now I've said, if you add up the $4 trillion of CAPEX that you in these in so many of the big large US tech companies are investing over the course of the next four or five years, it's about 10 times the size of the Manhattan project on an inflation adjusted or GDP adjusted basis.
考虑到那个关于 "常青软件" 的梦想即将成为现实，再想想对软件的需求。我认为，从你的观点来看，知识工作发生的抽象层次会有所变化，我们会适应这一点。工作和工作流程也将进行调整，这也会在一定程度上影响对该行业产品的需求。我想以此结束，实际上这与美国的再工业化有关。正如我之前所说，如果将美国许多大型科技公司在未来四五年间投资的4万亿美元资本支出相加，则相当于曼哈顿计划规模的10倍（按通胀或GDP调整的标准）。
So it's a massive undertaking for America. The president has made it a real priority of his administration to recut the trade deals. And it looks like we now have trillions of dollars. South Koreans committed $350 billion of investments just today into the United States. And when you think about what you see going on in power in the United States, both production, the grid, etc. What you see going on in terms of this reindustrialization. How do you think this is all going? And maybe just reflect on where we're landing the plane here, your level of optimism for the few years ahead. Yeah, I know. I feel very optimistic because in some sense, Brad Smith was telling me about the economy around Wisconsin data center.
这对于美国来说，是一个巨大的任务。总统将重新谈判贸易协定作为其政府的优先事项之一。而且看起来我们现在拥有数万亿美元。就在今天，韩国人承诺在美国投资3500亿美元。当你考虑到美国在能源方面的所作所为，包括生产、电网等，你还能看到在再工业化方面的进展。你怎么看待这一切？或许可以思考一下我们将如何收尾，你对未来几年的乐观程度如何。是的，我感到非常乐观，因为从某种意义上来说，布拉德·史密斯告诉我关于威斯康星数据中心周边经济的情况。
It's fascinating. Most people think of a data center that is sort of like, yeah, it's going to be one big warehouse and there is fully automated. A lot of it is true. But first of all, what went into the construction of that data center and the local supply chain of the data center? That is in some sense the reindustrialization of the United States as well. Even before you get to what is happening in Arizona with the TSMC plans or what was happening with micron and their investments in memory or intel and their fabs and what have you right? There's a lot of stuff that we will want to start building. Doesn't mean we won't have trade deals that make sense for the United States with other countries.
这很有趣。大多数人想到数据中心时，通常会觉得它像一个大型的自动化仓库，这在很大程度上是事实。但是，首先要考虑的是该数据中心的建设过程和本地供应链。从某种意义上来说，这也是美国再工业化的一部分。甚至在亚利桑那州的台积电计划或美光的内存投资以及英特尔的晶圆厂计划之前，就有很多我们想要开始建设的东西。这并不意味着我们不会与其他国家签订对美国有利的贸易协定。
But to your point, the reindustrialization for the new economy and making sure that all the skills and all that capacity from power on down, I think is sort of very important for us. And the other thing that I also said, Brad, it's important and this is something that I've had a chance to talk to President Trump as well as Secretary Lutnik and others is it's important to recognize that we as hyperscalers of the United States are also investing around the world. So in other words, the United States is the biggest investor of compute factories or token factories around the world, but not only are we attracting foreign capital to invest in our country so that we can reindustrialize.
但是按照你的观点，重塑新经济的工业化，并确保从电力到各项技能和能力，这对我们来说非常重要。另外，我也曾和布拉德说过，我们与特朗普总统、卢特尼克部长等人讨论过，认识到我们作为美国的超大规模公司也在全球范围内进行投资是很重要的。换句话说，美国是全球计算工厂或代币工厂的最大投资者，同时我们也在吸引外国资本来投资我们的国家，从而实现再工业化。
We are helping whether it's in Europe or in Asia or elsewhere in Latin America and in Africa with our capital investments bringing the best American tech to the world that they can then innovate on and trust. And so both of those, I think, are really bone well for the United States long term. I'm grateful for your leadership. Sam is really helping lead the charge at Open AI for America. I think this is a moment where I look ahead, you know, you can see 4% GDP growth on the horizon. We'll have our challenges. We'll have our ups and downs. These tend to be stairs, you know, stairs up rather than a line straight up into the right.
我们正在帮助世界各地的发展，无论是在欧洲、亚洲、拉丁美洲还是非洲，通过我们的资本投资，将最好的美国技术带给世界，各国可以在此基础上创新并且信赖。我认为，这对美国的长期发展非常有利。我很感激你的领导。山姆正在Open AI引领美国的发展。这是一个值得展望的时刻，未来我们可能会看到4%的GDP增长。当然，我们也会面临挑战，会经历起伏。这增长往往像是拾阶而上，而不是一路直线攀升。
But I for one see a level of coordination going on between Washington and Silicon Valley between big tech and the reindustrialization of America that gives me cause for incredible hope. Watching what happened this week in Asia led by the president and his team and then watching what's happening here is super exciting. So thanks for making the time. We're big fans. Thanks, thanks, Sasha. Thanks so much, Brad. Thank you. As a reminder to everybody, just our opinions, not investment advice.
但我个人看到华盛顿和硅谷之间、科技巨头与美国再工业化之间存在某种协调，这让我感到非常乐观。看到总统和他的团队在亚洲领导的事情，再看看这里发生的情况，真是令人振奋。所以感谢你抽出时间。我们是你的忠实粉丝。谢谢你，Sasha。非常感谢，Brad。感谢你们。提醒大家一下，这只是我们的观点，不是投资建议。