BG2 w/ Bill Gurley & Brad Gerstner | NVDA, Chips, AI Compute Build Out, AI Impact on Big Tech | E03

Would you rather have an assistant with the intelligence of like Einstein, but they have no access to the internet and they don't know anything about your history? Or would you like to have an assistant that's just above average intelligence knows everything about you and they can use the internet? Okay, you would choose that. Hey, great to have you here in person. I remember when you were right up this hill. Yeah. You guys were over here. So I had a couple thoughts this morning. First, I got to take a ride in full self-driving 12. How was that? It was mind boggling. I think this is going to be a bit of a chat, cheapy-tea moment for full self-driving, but what it really just reminded me of the magic of this moment. Tesla rebuilding their models for how they do self-driving around imitation learning and all this interesting stuff going on over there. I think they probably made more progress in the last 12 months than in the last seven years in terms of what's going on there. And it's going to be rolled out here. It's already rolled out to 5,000 people. And so people are going to start experiencing that. And I think we're having more and more of these moments because this substrate we're going to talk a lot about today, AI, and just the compute like what it unlocks.

你更想要一个助理，拥有爱因斯坦一样聪明的智能，但他们无法上网，并且对你的历史一无所知吗？还是你想要一个智能略高于平均水平的助理，了解你的一切，并且可以使用互联网？好的，你会选择哪个？嘿，很高兴你亲自来到这里。我记得你曾经就在这个山坡上。是的，你们就在这里。今天早上我有一些想法。首先，我有机会体验了全自动驾驶12. 这是怎样的体验？让人难以置信。我觉得这可能会成为全自动驾驶的一个重要时刻，因为这让我回想起了特斯拉重建他们的自动驾驶模型，采用模拟学习和其他有趣的技术。我认为在过去12个月里，他们在那方面取得的进展可能比过去7年还要多。现在这项技术已经被推向市场，已经面向5000人开放。所以人们将开始体验这项技术。我认为我们会有越来越多这样的时刻，因为我们今天将要讨论的基础是人工智能，以及这种计算力所能带来的一切。

The second in prepping for this pod was how bad you make my head hurt. I was thinking about this. What I love about this pod is it's a forcing function. You and I talk all the time. You're always challenging me. We're always comparing notes. But now with a little bit of structure around it, every couple of weeks, we have to think about some topics. Today, we're going to talk a lot about think AI and compute and chips and its impact on big businesses. And honestly, I liken it to an athlete. And they say, in order to be the best I can possibly be, maybe Kobe, I want to practice against the best. No, but like, listen, the reality is, it's like running 10 miles a day to get ready for a big game. Like, if you're in this business and you're not exhausted with the analysis you're doing, the thinking you're doing, particularly at moments like these to try to gather this data and try to gather edge, then you're probably not going to end up on top of the heap. Yeah, I agree. And I think that having a topic or an idea that you want to fully flush out and be able to talk about causes you to place a few phone calls, you know, read a few PDFs. And before you know it, you actually realize you've learned something you didn't know, you know, five days earlier. It's a, you know, I think the little, you know, pull the screen back a little bit. I mean, you and I talked, you know, we're interacted five, 10 times a day over the course of last week on these topics. And then we turn over a rock and we find more data, more information, we share that with one another leads to another conversation, you know, and the combined networks allow us to ask a lot of the smartest people in the world the questions we need to be asking to try to figure out this moment. So it's been a lot of fun, but, but it does give me a bit of a headache. Hopefully a good one.

为了准备这一期的节目，第二个问题是你让我头痛得厉害。我在想这个问题。我喜欢这个节目的原因是它是一种迫使函数。你和我总是在交谈。你总是在挑战我。我们总是比较笔记。但现在，有了一点结构，每隔几周，我们必须考虑一些话题。今天，我们将大谈AI、计算和芯片以及它们对大型企业的影响。老实说，我把它比喻为一名运动员。他们说，为了成为可能的最佳，也许像科比，我想要和最强的对抗。不，但是，现实是，就像每天跑10英里来为一场大比赛做准备一样。如果你从事这个行业，而你对自己正在做的分析和思考感到疲惫，尤其是在这种时刻努力收集数据和获取优势的时候，那么你可能最终不会成为佼佼者。是的，我同意。我认为有一个你想要完全拓展并能够谈论的话题或观点会导致你打几个电话，阅读几份PDF文件。然后不知不觉中，你会发现自己学到了之前不知道的东西，你知道，五天前。我认为，稍微拉开屏幕一点点。我和你在上周针对这些话题进行了五到十次的互动交流。然后我们翻开一个石头，发现了更多的数据、更多的信息，我们彼此分享，这导致了另一场谈话，而合并的网络让我们能够向全世界一些最聪明的人提出我们需要问的问题，以试图弄清这个时刻。这很有趣，但是，它确实让我头疼了一阵。希望是一种好的头痛。

So, so we remain, we remain kind of in an earning season. Yeah. And so what, what, what happened in the past few weeks that you think is super important. Yeah. Well, we have a lot of, we have a few stocks that have run a lot, meta, Nvidia up 30, 40%, even with the pullback that we had today. But the truth is the NASDAQ hasn't really moved that much. I mean, I think we're up three or four percent through today. If you look at the median stock, I think it's up about 1%. In fact, I think we have a chart here just on the dispersion that we see in the NASDAQ, you know, and so remember last year was, was like this risk on moment, a mean reverting moment for all of technology.

因此，我们仍然处在一个赚钱的季节。是的。过去几周发生了什么，你认为非常重要？是的，我们有很多股票涨幅很大，meta，NVIDIA上涨了30%至40%，即使今天出现了回调。但事实上，纳斯达克指数并没有大幅上涨。我认为截至今天，我们仍然只上涨了3%至4%。如果看看中位数股票，我认为涨幅大约是1%。事实上，我认为我们这里有一个关于纳斯达克的差异的图表，你知道，去年是这种技术的风险增加时刻的反弹时刻。

And this year we're, we're, we're really starting to see the winners and the losers. We have some software companies that reported after the bell to tonight that are down a lot because they're not seeing the AI pull forward that maybe an Amazon or a Microsoft. So that's my first takeaway. My second takeaway is, you know, against these higher prices for some of these companies, you know, the backdrop looks a little bit more challenging. So we had a CPI print that came out last week that ran a little hotter than people expected.

今年我们真的开始看到赢家和输家。有一些软件公司在今晚报告后出现了大幅下跌，因为他们没有像亚马逊或微软那样看到人工智能带来的推动。这是我的第一个观点。我的第二个观点是，对于某些公司的高价，背景看起来更具挑战性。上周发布的消费者物价指数 (CPI) 涨幅超过人们的预期。

The 10 years back up to four, three, remember, at the end of the year, I think I had gotten down to three, five. And then we had what I thought was a really provocative tweet at the end of the week from Larry Summers, where he said the next move by the Fed could be higher. Now, why is this so provocative? Well, the market is betting for sure. The only debate about the soft landing has been when is the Fed going to cut? Right? And so you have summers come out and say, Hey, I think the next move could be higher. That would be a shock to the market. Was he being provocative or do you think there's real data that suggests that that the soft landing is in a foregone conclusion?

在过去的10年里，最多回到了四个，三个，记得吗，年底的时候，我觉得我已经下降到了三点五。然后在周末，我看到了一条我认为非常引人注目的推特，来自拉里·萨默斯，他说联邦储备系统的下一步可能是加息。现在，为什么这么具有挑衅性呢？因为市场肯定在押注。关于柔软着陆的唯一争论是联储何时会降息？因此，萨默斯出来说，嘿，我觉得下一步可能是加息。这对市场来说将是一个震惊。他是在挑衅还是你认为真的有数据表明柔软着陆是板上钉钉的结论？

Well, listen, Larry was was spot on right in 2022. Okay. I think last year he he was a little bit too aggressive as to where he thought rates were going to have to go. At the end of 22, I think he said maybe they could have to go to six or seven percent. But I'm humble in the face that the future is unknown and unknowable. Like, we don't know. That's the truth of the matter. So as investors, we have to try to distribute this these probabilities. And so if I go back and look at this, real rates, right? So real rates, this is the restrictiveness that we have in the economy. So this is effectively the interest rates we have less the expected inflation rate in the future. There is high as they've been since the fall of 2007.

嗯，听着，拉里在2022年的判断完全正确。好的。我觉得去年他可能有点过于激进，预测利率可能会达到什么水平。到了22年底，他说可能会达到六七个百分点。但面对未知和不可知的未来，我保持谦逊。就像，我们不知道。这就是事实。所以作为投资者，我们必须尽量分配这些可能性。所以如果回顾一下，实际利率，对吧？实际利率，这反映了我们经济上的严格程度。实际上，这就是我们的利率减去未来预期通胀率。自2007年秋季以来，实际利率已经达到了如此高的水平。

And the last time they were higher than that was in the summer, August of 2000. Okay. Now, what was the what was going on August of 2000 and the fall of 2007? Well, the the economy was on a heater and the Fed was trying to slow it down. Okay. So that's the level that the Fed currently has its foot on the brakes. And every month that inflation comes down, if it does, okay, then the restrictiveness goes up, right? So the Fed, if inflation is coming down, then the Fed does nothing and its foot goes harder on the brake. So that's why Paul has said we have to cut rates just to stay equally restrictive.

他们上次超过这个水平是在夏天，2000年8月。那么，2000年8月和2007年秋天发生了什么事情？嗯，经济正在热火朝天，美联储试图放慢它。好的。所以现在美联储把刹车踩在这个水平上。每个月如果通胀下降，那么紧缩性就会增加，对吧？如果通胀下降，那么美联储就不会采取任何措施，刹车就会踩得更重。所以保罗说我们必须降息，才能保持同样的紧缩性。

So for Larry to be right, we would really have to see a reversal in inflation, which I don't think many people forecast or see. But I think the important takeaway is this, as investors, I know, and you're already probably saying, God, how do Brad side track me on macro? I don't want to talk about this. You know, I often think about that famous saying, if you don't do macro macro, does you? But when I think about when I think about it in this moment, it's just to say stocks have run up a bunch at the start of this year. Okay. The backdrop has gotten a little less predictable. There's now this tug of war that's going on. So I think we're going to have to see both of those things play out.

所以要让Larry的观点成立，我们实际上需要看到通胀出现逆转，而我认为很少有人预测或看到这一点。但我认为重要的要点是，作为投资者，我知道，你可能已经在说，天啊，布拉德怎么又扯到宏观经济上了？我不想谈论这个。你知道，我经常想起那句名言，如果你不关心宏观经济，宏观经济就不会关心你。但当我在此刻考虑这个问题时，我的意思只是股市在今年年初已经上涨了很多。背景变得有点不可预测。目前正发生一场拉锯战。所以我认为我们必须看到这两个因素都得到解决。

And then of course, this week, the monster that comes tomorrow bill is Nvidia. In fact, that CNBC is screaming every day, whichever way Nvidia goes, so goes the market. Now, I don't think it's quite like that. But one of the things that I was thinking about in regard to this is because we were making a bet that AI was for real, that training workloads were going to be large, and that these inference workloads were going to kick in. As investors, we often take what we call this private equity approach to the public markets, which is, let's get the big trends, the phase shifts, the super cycles, right?

当然了，这周最受关注的公司就是明天将公布业绩的英伟达了。实际上， CNBC每天都在炒作，无论英伟达的股价往哪个方向走，市场也会跟着一起动。我不认为事情完全是这样的。但是我在想的一件事是，我们做出了一个赌注，认为人工智能是真实存在的，训练工作量会很大，而这些推理工作量会逐渐出现。作为投资者，我们经常采取所谓的私募股权方法来对待公开市场，也就是看重大趋势、阶段性转变、超级周期，对吧？

I think about you had me over to benchmark. This is years ago. And you said, Brad, will you come and talk about booking.com and the case you do at Columbia Business School in the old Graham and Dodd class that I teach with Chris Begg on occasion. And the thing I tried to teach the students in that class is why did all the analysts on Wall Street miss booking.com, misspike price line. Now, remember, price line was a billion dollar company in the public markets. Today, it's $120 billion, $120 bagger in the public markets. I mean, there aren't many venture capitalists that ever get $120 bagged, let alone a public market investor. And the takeaway in the class is everybody and all the analysts on Wall Street were so focused on how many hotels were they going to add in the quarter, right? And there'd be a lot of volatility around the number of hotels added in the quarter. Nobody really took the time horizon to say in five, 10, 15 years, how much more the offline world is going to book their hotels online and how much bigger that's going to be. So often the short term trading, they would get the long term conviction right, but they would end up trading out of the position.

我记得你曾邀请我来做benchmark。那是很多年前的事了。你说，布拉德，你愿意来谈谈booking.com以及你在哥伦比亚商学院的老格雷厄姆和多德课堂上教授的案例吗，我偶尔会和克里斯·贝格一起教授。在那堂课上，我试图教给学生们的是为什么所有的华尔街分析师都错过了booking.com，错过了priceline。请记住，priceline在上市市场是一家百亿美元的公司，今天市值为1200亿美元，在上市市场是一个120多倍的增长。很少有风险投资家如此成功，更别说一位上市市场的投资者了。课堂的收获是所有的华尔街分析师都太过关注他们在季度内会增加多少家酒店，对于每个季度增加的酒店数量会有很大的波动。但没有人真正花时间去考虑未来五、十、十五年内，离线世界会有多少人在线预订酒店，这市场规模会有多大。往往在短期交易中，他们可以做到对长期趋势的判断，但最终会错失机会。

So I look at Nvidia tomorrow, and the honest to God truth is we have no edge on a quarter or on day to day trading of these things. I think we do believe that the, and we're going to talk about this later, the amount of compute that's going to have to be built in the world is way bigger than people than consensus estimates, you know, currently forecast. But I think tomorrow it's going to be really interesting. What could really move? I mean, they're sold out, right? And their productions known. So it's just pricing that could be different. Correct. Well, I think there's so every, every hedge fund, every long, only person, they track all this data, right? So the co-woss data, you know, the order books, the H 100 data. And I think what people are seeing, and there's been some tweets about this, is that the lead times on Nvidia H 100s are going down. So what might you think if the lead times are going down, you would say, Oh, the demand must be going down, or the supply must be going up, catching up with demand. And you know, we've all been trained that every supply constraint is ultimately met with a glut, right? So everybody's just the wall of worry around Nvidia's. When does the glott come? We've pulled forward all this training demand. It's dark fiber like in the year 2000.

所以我明天会看Nvidia，老实说，我们对于这些股票的季度或每日交易并没有任何优势。我认为我们确实相信未来要建设的计算量要比人们普遍的预估要大得多。但我觉得明天会很有趣。可能会有什么改变呢？他们的产品全部售罄，生产也是公开的。所以只是定价可能会有所不同。没错。我认为每家对冲基金，每个持有长期头寸的人，他们都跟踪所有这些数据，对吧？所以关注数据，订单簿，H100数据。我认为人们看到的是，有些推文也提到了，Nvidia H100的交货时间在缩短。所以如果交货时间在缩短，你会怎么想？你可能会说，哦，需求一定正在下降，或者供应正在赶上需求。我们都被培训过，每次供应限制最终都会导致供过于求，对吧？所以每个人都在考虑Nvidia的担忧，瓦里关于何时会出现供过于求？我们已经提前消化了所有这些培训需求。就像2000年的黑光纤一样。

I think those things are not accurate. But of course, I have no idea what this means as to tomorrow. So I think there are just tons of questions about AI chips inference, how much of it's going to be going on. I know we're going to hit on a bunch of that today. So, you know, we stirred the pot last week, a little bit or two weeks ago, by questioning the consensus view on Google, which is that they're going to be a big AI winner. I think we called it the $2 trillion question. I tweeted about it. You know, Mark Suster chimed in and said, you know, I'll take the side that they're going to be an AI loser. You know, but why don't we dive in a little bit? You had this good idea. Hey, let's look at these large cap tech companies through the lens. Are they winner or they loser from AI? So let's start with Google. Yeah. And I wanted to back up a little bit and borrow a framework from one of my, one of my close friends and and someone that I think a lot of people have listened to and learned from around investing, Mike Mobison. And years ago, shortly after I first met him, he was teaching a class at Columbia and they started him in the sky. Paul Johnson started talking about an acronym they titled cap competitive advantage period. And what they would do is they would take a company's market cap and they'd look at the trends in the company and they would back into the number of years into the future that Wall Street was telling you this company was going to have a competitive advantage. And by by by basically counting the number of years it would take in free cash flow to build into the market cap. And what the point did he made is that, you know, different businesses have different amount of durability.

我认为这些事情不准确。但当然，我不知道这对明天意味着什么。所以我认为有很多关于AI芯片推理的问题，它们将会发生多少。我知道今天我们将会涉及很多这方面的问题。所以，你知道的，我们上周或两周前引发了一些争议，质疑了关于谷歌的共识观点，即他们会成为一个 AI 大赢家。我认为我们称之为 2 万亿美元的问题。我在推特上谈到过。你知道，马克·萨斯特也表示自己会赌他们会是 AI 大输家。但是让我们深入了解一下吧？你提出了一个好主意。嘿，让我们通过这个视角来看看这些大型科技公司，它们是 AI 的赢家还是输家？所以让我们从谷歌开始。是的。我想再退一步，借用我一个密友的一个框架，也是一个我认为很多人都听过并从他那里学到东西的投资人 Mike Mobison。几年前，我第一次遇见他后不久，他在哥伦比亚大学教授一门课，他和他的同事保罗·约翰逊开始谈论一个他们制定的缩写 cap 竞争优势期。他们会拿一个公司的市值，看公司的趋势，然后反推出华尔街告诉你这家公司还会有竞争优势的多少年。通过基本上计算将来市值需要多少年才能构建出自由现金流。他的观点是，你知道，不同的企业拥有不同程度的持久性。

And so, you know, Coca-Cola might only have a 3% growth rate, but it might have a 40 or 50 P.E. because everyone is willing to bet that 75 years from now you'll still see Coca-Cola on the show. Yeah. Yeah. Right. Whereas, you know, you look at a company that all of a sudden faces the innovators deliver faces disruption. And this cap can close super fast and it has dramatic impacts on the market cap of the company. I remember when Blackberry first got in trouble, the the the valuation just retrenched so aggressively that many people got fooled into thinking it was a value because it was trading at 10 times earnings. Yeah. Same way. Yeah. And and and what was happening is the people in the know were saying this company's competitive advantage just became quickly undurable. Yes. I'm not sure undurables are what you understand the point that I'm making. Oftentimes because we have a lot of high growth stocks in Silicon Valley and so they get assigned big multiples. Multiples are a byproduct of a couple things, how fast you're growing because we're trying to forecast those free cash flows into the future, but also to the second point, the durability because we have to assign a discount rate.

因此，你知道，可口可乐的增长率可能只有3％，但它可能有40或50倍的市盈率，因为每个人都愿意打赌75年后你仍然会在节目中看到可口可乐。是的。是的。对。然而，你知道，有些公司突然面临创新者带来的冲击。这个差距可以迅速缩小，并且对公司的市值产生戏剧性影响。我记得当黑莓第一次遇到麻烦时，估值急剧下降，以至于很多人被骗以为它是一种价值，因为它的市盈率只有10倍。是的。同样的。是的。然而，正在发生的是知情人士表示这家公司的竞争优势迅速变得不可持续。是的，我不确定你理解我所表达的观点。通常情况下，因为硅谷有很多高增长股票，所以它们被赋予很大的倍数。倍数是几个因素的副产品，包括你的增长速度，因为我们试图预测未来的自由现金流，但也包括第二点，就是稳定性，因为我们必须分配一个折现率。

What's the probability that we're actually going to be able to collect those annuities sometime in the future. And so, the less confidence we have about the future, the higher the discount rate. And so, even though you may have high growth, we have to discount it a lot. And Mike has gone on, I think, to talk about optionality, especially around tech companies. Sometimes you have a platform position that increases the optionality. You're going to be able to move into other fields and therefore, that would also be a positive. But other people have questioned why these tech companies have high multiples at all because they're so susceptible to tech disruption, in which case you could argue the other side. But anyway, the reason I thought this would be an interesting way to talk about some of the large companies and AI, I don't think there's a single person out here that is arguing that AI is not some kind of fundamental phase transition, Clay Christensen's disruptive wave or whatever. And in fact, I think the number one way you could probably commit Harry Carrey as a public company would be to, on your earnings call, say, we think AI is full of shit, like we don't want anything to do with it.

有多大的概率我们未来能够真正收到那些年金？因此，我们对未来的信心越低，贴现率就越高。因此，即使你可能有高增长，我们仍然必须大幅贴现。Mike已经进行了讨论，我认为他特别谈到了科技公司的期权性。有时候你拥有一个平台位置，增加了期权性。你将能够进入其他领域，因此，那也会是一个正面因素。但其他人质疑为什么这些科技公司的市盈率如此高，因为它们是如此容易受到技术颠覆的影响，这种情况下你可以提出另一个观点。但无论如何，我认为这是一个讨论一些大型公司和人工智能的有趣方式的原因，我认为这里没有一个人会辩称人工智能不是某种基础性的阶段性转变，克雷·克里斯滕森的颠覆性浪潮或者其他什么。事实上，我认为你可能会被公开上市公司以一个方式奉献烈士的，那就是在你的收益电话上说，我们认为人工智能是胡说八道，我们不想碰它。

And so, everyone's forced to have an answer. And I think, you know, one example that's pretty obvious to everyone is Microsoft, I think it became very clear to a lot of investors when they learned about an LLM and what it was capable of. And the fact it could help write code, and then it could help you write a paper, you know, and it could help you with creative endeavors. People looked at the Microsoft portfolio of assets, especially where they make money around the office suite, right? And said, and the developer community, where they also, you know, control a lot of the IDEs that are used to program. And they said, oh, this is easy. Microsoft will be enhanced by this. And we should also add their their adaptness at moving quickly with the open AI relationship and being they were in there in front of this early. Absolutely. And so all three of those things you go, oh, this, they're in that winter. And lo and behold, you know, their stock went up and they had multiple expansion.

因此，每个人都被迫给出一个答案。我想，你知道的，一个很明显的例子是微软，当很多投资者了解到LLM及其所能做的事情时，他们意识到了这一点。它能帮助编写代码，然后帮助你写论文，还可以帮助你进行创造性的努力。人们看着微软的资产组合，特别是他们在办公套件研发方面赚钱的地方，以及开发者社区，他们还控制很多用于编程的集成开发环境。他们说，哦，这很简单。微软将受益于这一点。我们也应该补充说，他们在与OpenAI的合作关系上迅速行动的能力，并且他们非常早就参与其中。绝对正确。还有这三件事情，你可以看出，哦，他们就在那个冬季。然后，事实证明，他们的股价上涨了，扩张了多个倍。

Yeah, I mean, I think that the first question we ask as investors is, is this thing real? And what do we mean by real? What I mean by is the juice worth the squeeze. It costs me something to have AI if I'm a customer, right? And is the productivity gains that I'm getting as a business worth it, right? So, you know, I was talking about Tesla, you know, start off the conversation. Well, if if this model and this compute and all of this capability allows me to develop full self driving and to win the automotive market because of that, then of course, the juice is worth the squeeze. I think if co-pilot allows my engineers to be 30, 40, 50% more productive, then I'm replacing human beings with machines. Of course, that's worth the squeeze. And so I would say that as we sit here in the early, but I would even say it another way in the Microsoft case, if you're not using their tool and you're programming without it, you're falling behind. Right. And so it becomes, you know, a tool that you have to have to remain competitive.

是的，我的意思是，我认为作为投资者，我们首先要问的问题是，这个东西是真实的吗？那么我们所说的真实是什么意思？我所指的是果汁是否值得榨取。作为一个客户，拥有人工智能对我来说是有成本的，对吗？作为企业，我所获得的生产力增益是否值得，对吗？所以，你知道，我之前谈起了特斯拉，开始这个对话。如果这个模型和这个计算以及所有的功能使我能够开发完全自动驾驶，并通过这个赢得汽车市场，那当然果汁是值得榨取的。我认为如果辅助驾驶允许我的工程师们提高30%、40%、50%的生产率，那么我正在用机器代替人类。当然是值得榨取的。因此，我认为正如我们现在处在早期阶段一样，但我想用另一种方式说，在微软的案例中，如果你不使用他们的工具，而你的编程是在没有它的情况下进行的，你会落后。因此，它变成了一个你必须拥有以保持竞争力的工具。

Yeah. And so, you know, to me, I, we really try to look at it through the lens of, is this company like, if we look at their existing business, is their existing business enhanced or attacked because of AI? And then what new business opportunities do they have? And if we go back to Google for a second here, because I think we it's kind of this iconic study because the consensus view was that they were going to be a a huge winner in AI. And let let's step back for a second here. 20 years ago, right, the idea that you were going to be able to ask any questions, immediately get information for free, like Google gives us, right, was just beginning. And the gains to humanity caused by the revolution that Google really led around information discovery and how efficient and how quick they provided information discovery really just it changed the world in every respect. It moved humanity forward back to Ridley's idea of ideas having sex, right? Like it just allowed us to have more ideas, collect more information, exchange more information.

是的。所以，对我来说，我们真的试图通过这种视角来看待它，即这家公司是否因为人工智能而得到增强或遭受攻击？然后他们有什么新的商业机会？如果我们回到谷歌这里，因为我觉得这是一个标志性的案例，因为普遍的看法是他们将成为人工智能的巨大赢家。20年前，你能够随时提问并免费获得信息的概念，就像谷歌给我们的一样，刚刚开始。由谷歌引领的信息发现革命对人类带来的收益，以及他们提供信息发现的效率和速度，实际上改变了世界的每一个方面。像里德利提出的思想相互交融的观点一样，它让我们可以更多地产生想法，收集更多信息，交换更多信息。

I asked the team to do a little analysis like as investors like, where do we think the right multiple should be for Google? And like, what what are the things that are inputs into that? So if you think about this, Google does about 10 billion queries a day, right? So, you know, a couple, a couple queries are more than a query for every human on the planet. And it has the most efficient system in the world for doing that. I think if you pull up this tweet from Vivek, it'll show that that the number of queries that are asked of Google has slowed down a lot, right? So they're growing at about 4% a year. Monetization is up a lot, 13% more ads on the page. We've talked about that. And so you have a 17% keg or around search.

我要求团队进行一些像投资者那样的分析，我们认为 Google 的正确倍数应该是多少？还有，那些是这种倍数的输入因素？如果你考虑一下，Google 每天大约处理100亿个查询，对吧？所以，你知道，几个查询就已经超过了地球上每个人的查询。而且它拥有全球最高效的系统来做到这一点。我认为如果你查看 Vivek 的推文，它将展示 Google 被询问的查询数量已经大大减少了，对吧？所以它们每年大约增长4%。货币化水平提高了很多，网页上的广告增加了13%。我们已经谈论过这个问题。所以你有一个17%的搜索成长率。

And so the first thing that we just say is that the basing engagement, even before AI had slowed down a lot, because you're already at 10 billion queries a day. So next we took a crack at a chart that says, how many of those queries are going to become chat GPT-like queries? Okay. And so the black line here is kind of the number of queries that are information retrieval queries on Google. And the blue line is the actual and the forecast by us for the chat GPT-like equivalent queries that are going to occur. Now, what where do we get that information? Well, first we know a little something about the number of queries on chat GPT, right? And we know that open AI and Google are working on these search integrated experiences. I think they call it SGE, where they're going to have answers like perplexity in line with search. I think that Microsoft is now doing this with the rebranded co-pilot.

因此，我们首先要说的是，在人工智能放慢之前，基础的参与已经大大减少，因为每天已经有100亿次查询。接下来我们尝试了一下一个图表，显示有多少查询会变成类似于Chat GPT的查询？黑线代表谷歌的信息检索查询数量，蓝线代表我们预测的即将发生的类似于Chat GPT的等效查询数量。那我们获取这些信息的来源是什么呢？首先，我们对Chat GPT的查询数量有一些了解，对吧？我们知道OpenAI和谷歌正在开展与搜索整合体验相关的工作，我认为他们称之为SGE，他们将提供类似于搜索的困惑性答案。我认为微软现在也在做这个，他们重新命名为co-pilot。

So a lot of the information retrieval searches are going to be replaced with these chat GPT-like searches. And this is where it starts to get interesting because two things kick in, Bill. Number one, it costs a hell of a lot more, right? To provide answers than it did to provide 10 blue links. So if you say like, what's it cost to provide 10 blue links? It's about a third of a penny or less per query. Now, what is it cost to do that for 750 tokens today? And of course, this will go down over time, but it's 10 X more, right? It's four cents per query. And then if you look at the refinement of queries that's really going on. So a lot of times, Bill, what they do is they'll send back these 10 blue links and then they'll use that as they're prompt, right? To re query the engine. This could be up to 50 X more expensive to serve an answer, a high quality answer to the consumer versus 10 blue links. So your cost goes up a lot.

因此，很多信息检索搜索将被类似于聊天GPT的搜索所取代。这就是开始变得有趣的地方，因为有两件事情开始起作用，比尔。首先，成本大大增加了，对吧？提供答案比提供10个蓝色链接要花费更多。如果你问提供10个蓝色链接的成本是多少？每次查询大约是三分之一美分或更少。现在，为了今天750个令牌提供这样的服务成本是多少呢？当然，随着时间推移，这个成本会降低，但是它增加了10倍，对吧？每次查询四美分。然后，如果你看一下真正在进行的查询的精细化。很多时候，比尔，他们会发送回这些10个蓝色链接，然后他们会将其用作提示，对吧？重新查询引擎。向消费者提供高质量答案可能会比提供10个蓝色链接昂贵多达50倍。所以你的成本会大大增加。

Well, what about revenue? So I asked the question on the other side, well, we know that revenue goes down. Why? Because I'm not clicking on all these ads on the page, right? And so revenue per search likely goes down. I think if you look at that in terms of what the gross margin is to Google, right? The cost of serving going up, the revenue coming down, I don't know, you may take a 95% margin today on a business where you have 99% share, your share likely goes down over time because you have people like chat, GPT you have to compete with, but worse yet, your margin on each of those queries goes down over time. I don't know what it nets out at 50, 50%, 60%.

嗯，那么收入呢？我提出了另一个问题，我们知道收入下降了。为什么？因为我不点击页面上的所有广告对吧？所以每次搜索的收入可能下降。我认为如果你看看这对谷歌的毛利是什么意思，服务成本增加，收入下降，我不知道，你可能在你拥有99%市场份额的业务上拥有95%的毛利，但随着时间的推移，你的份额可能会下降，因为你需要和像Chat、GPT这样的竞争对手竞争，但更糟糕的是，每个查询的利润随着时间的推移会下降。我不知道最终会是什么样，也许会达到50%，60%。

Now mind you, for perplexity or co-pilot or meta, et cetera, that's a great business of 50% margin business. And you know, it reminds me what we've all said so many times, Google's margin is their opportunity. So the problem for Google is they have to do this because their competitors are forcing them to do it. Okay, but it definitely is going to be a lower margin business and they're unlikely to have the 99% share. So everybody has texted and emailed me, yeah, but they've got YouTube and they've got Gmail and they've got Gemini 1.5 and they've got all this stuff. And I stipulate all of that is true. Okay, but the business that today produces the vast majority of profits for the company. What percent? I mean, listen, I think that search and YouTube produce over 100% of the profits because they have a lot of money losing units in the business, but it's over 80% of the profits in the business. And so when you think about that, now listen, they've got great management. They can cut costs. There are lots of things they can do. I'm not saying this is going to occur overnight. But if you and I were talking with Clayton Christensen about the innovators dilemma and we were analyzing this business, this would really be case exhibit number one.

现在请注意，对于困惑、副驾驶员或元、等等，那是一个利润率达到50%的伟大业务。你知道，这让我想起我们所说过很多次的一点，谷歌的利润率就是他们的机会。所以谷歌的问题是他们必须这么做，因为他们的竞争对手逼迫他们这么做。但肯定是一个较低利润率的业务，他们不太可能拥有99%的市场份额。因此，每个人都在给我短信和邮件说，但他们有YouTube，他们有Gmail，他们有Gemini 1.5，他们有所有这些东西。我承认这都是真的。但今天为公司产生绝大部分利润的业务。百分之多少？我是说，我认为搜索和YouTube产生了超过100%的利润，因为公司中有很多亏钱的部门，但它们占据了业务中80%以上的利润。所以当你考虑这一点时，现在听着，他们有出色的管理团队。他们可以削减成本，有很多事情可以做。我不是说这会一夜之间发生。但如果你和我与克雷顿·克里斯滕森谈论《创新者的困境》，并分析这个业务，这将真正成为案例展示的首要案例。

Now, the irony of the innovators dilemma, Bill, is most of the companies that face it, they know they face it. They know they face it. So the question is, why don't they do anything about it? I think some don't. But in this case, you, I think there's no doubt that they know. Of course, they know. So the question is they're trying to thread the needle, right? Can we somehow modify this in a way where we continue to grow our quarterly earnings because just setting the platform on fire and retrenching in the public markets and doing all of that very, very difficult advantage by one thing that the searches that are going away first or Wikipedia like searches that don't have much monetization. So it doesn't, it doesn't, the revenue doesn't come apart right away, even though you might be losing search volume. And more importantly, like people start getting addicted to the answer right away, which is very different from 10 blue link.

现在，创新困境的讽刺之处在于，大多数面临这种困境的公司都知道他们面临着挑战。他们知道他们面临挑战。那么问题是，为什么他们不采取任何行动呢？我觉得有些公司确实没有采取行动。但在这种情况下，我认为他们是明知道的。当然，他们知道。所以问题是他们在试图寻找解决方案，对吧？我们能否以某种方式修改这种情况，继续增长我们的季度收益，因为只是让平台失控并在公开市场上撤退，以及做所有这些非常困难的优势，其中一个搜索就会先消失，比如没有太多盈利的维基百科搜索。因此，尽管你可能会失去搜索量，但收入不会立即受到影响。最重要的是，人们开始立即追求答案，这与10个蓝色链接截然不同。

I think like the horses out of the barn on answers, right? Like once consumers experience the magic of an answer, they're not going back to hunting and pecking for a roster for an athletic team through 10 blue links. So you're just going to use it. And all of this just reminded me of lastly of somebody tweeted out a Grantham quote this week that I thought was pretty interesting. But it's this if you pull out this tweet from, from Charlie, he says, the S&P profit margins move down to 10.6% Q423, the lowest since Q420 20. And that is the quote from Grantham, I love. Profit margins are probably the most mean reverting series in finance.

我觉得答案就像马儿从马棚里跑出来一样，对吧？一旦消费者体验到了答案的神奇之处，他们就不会再回去费劲地在10个蓝色链接中搜索运动队名单。所以你只需要使用它。所有这些让我想起了有人在本周发推特引用了一个格兰瑟姆的话，我觉得很有趣。他说，如果S&P的利润率下降到10.6%Q423，那将是自Q42020以来最低的。这是我喜欢的格兰瑟姆的话。利润率可能是金融领域中最具均值回归特性的系列数据。

And if profit margins don't mean revert, then something has gone badly wrong with capitalism. Right. I mean, what's happening here with Google? It's not that this is anomalous. Right. When there are big pools of profits like exists in Google search, capitalism has a way to redistribute those people would give it up. Like I agree, like Apple and Microsoft had given up 100% prior to this new reality. That's why that's why Sacha says you if you're in technology, if you run a company like Microsoft, all the money is made in the two to three years around a phase shift. You cannot miss a phase shift. If you miss it, then you miss all the value capture for the next decade.

如果利润率不回归到均值，那么资本主义出现了严重的问题。对。我的意思是，谷歌发生了什么？这并不是个例外。对。当像谷歌搜索这样巨大的利润池存在时，资本主义有一种重新分配这些利润的方式。就像我同意的，像苹果和微软在这种新现实之前都放弃了100%。这就是为什么萨查说，如果你从事科技行业，如果你经营一家像微软这样的公司，所有的钱都是在一个阶段性转变的两三年内赚得。你不能错过一个阶段性转变。如果你错过了，那么你就错过了未来十年的所有价值获取。

And I might argue with AI, it's going to be even bigger value capture and disruption. And it's going to last longer than a decade. One other thing we don't know yet that I just be issuing your thoughts on is, what's the business model for this? Because right now, the premium versions of perplexity and chat GBT have a dollar amount, their subscription. This kind of looks like the Netflix type situation. So is it subscription or is it free? Do you want ads around your answers or not? Well, I mean, listen, remember the disruptors. They don't have to generate a lot of margin on this because they are no money on it today.

我可能会和人工智能争论，它会带来更大的价值捕获和颠覆。并且它会持续比十年更长时间。 还有一件我们还不知道的事情，我想征求你的看法，那就是，这个业务模式是什么？因为现在，谜团和聊天GBT的高级版本都需要付费订阅。这有点像Netflix类型的情况。所以是订阅还是免费？你想让你的答案周围有广告吗？嗯，我是说，记住那些颠覆者。他们不必在这上面赚很多利润，因为他们今天在这上面不赚钱。

So what do they have to do? They have to cover their costs. Yeah. And these disruptors want to see Google dance, as Sacha said. So the prize prize when he said I was too. But listen, listen, the fire in the belly is exactly what you need. I think Sacha has founder level fire in the belly about this moment in time. And I think he has it not just because he wants to see the stock price go up. I think he has it because people like Sacha, they're post money. And what they care about right now is moving humanity forward.

所以他们要做什么？他们必须覆盖他们的成本。是的。而这些颠覆者想要看到谷歌跳舞，正如Sacha所说的。所以当他说我也是最在意的奖励。但是听着，听着，内心的激情正是你所需的。我认为Sacha对这一时刻有着创始人级别的激情。而他之所以有这种激情，不仅仅是因为他想看到股价上涨。我认为他之所以有这种激情，是因为像Sacha这样的人，他们已经过了为金钱奔波的阶段。而他们现在所关心的是推动人类前进。

And they understand that they've worked their entire careers to get to this place where we go from computers acting like calculators that are modestly beneficial to now computers helping us answer and solve the most perplexing and fundamental questions that we face. And so I suspect that they're going to underprice this. If I were perplexity, I would I wouldn't have any ads in a thing, right? No need to put ads in it. And I would attack and I would try to get share, right? And so it would be surprising to me if we don't see meta AI and Microsoft and by dance and perplexity

他们明白他们为了达到这个地步而全心全意工作，我们从计算机只是像计算器一样谦逊地帮助我们，到现在计算机帮助我们回答和解决我们面临的最困扰和基本的问题。所以我怀疑他们会低估这一点。如果我是困惑，我不会在里面放广告，对吧？没必要在里面放广告。我会进攻，努力获取份额，对吧？所以如果我们没有看到meta AI和微软、字节跳动和困惑这些公司，那对我来说会很惊讶。

and all the others who are providing answer engines, chat GPT, coming at them below margin. Okay. Now, let's ask let's answer the question that I'm talking about the shorter term while everybody is fighting to gain share, they'll price it so they cover their costs or maybe not maybe Microsoft's willing to eat it, you know, here for a while. And I continue like I as of right now and I've played with all of them on the consumer side, I don't think anyone has a pro I perplexity came out as a lot faster.

现在让我们来谈谈我所说的短期问题，当每个人都在为获得市场份额而奋斗时，他们会定价以覆盖成本，或者也许微软愿意承担这一成本，你懂的，在这里一段时间。就我目前的情况来说，我已经玩过所有消费者端的产品，我认为没有一个产品能像pro I perplexity那样快。

That was pretty cool. But when I just look at the quality of the answers, I don't I mean, on different searches, one might be better than the other, but I don't see anything that's so holistically notable. Like I remember when Google search came out like where I was, I remember trying it versus off the list and yeah, and it was like you could tell like, Oh, this is better, right? And I don't see that right. I had that I did have that feeling of chat GPT versus a traditional Google search. Oh, yeah. I mean, you're saying among the answer.

这真的很酷。但是当我只看答案质量时，我并不是指，不同的搜索可能有好有坏，但我没有看到什么特别值得注意的综合性特点。就像我记得谷歌搜索刚出来的时候，我记得我尝试过它和其他搜索引擎，确实，你可以感觉到这更好一些，对吧？但现在我没有感受到这一点。我没有感受到聊天GPT与传统谷歌搜索之间的差距。哦，是的。你是说在答案中。

Now you have you have four or five, right? Right. I leave I leave back, you know, companies competing in this consumer AI space in there. I don't see anyone yet. Now, I as I said on our last part, I think if you get this memory, right? It could change. And since we did that, um, open AI published a release that says we're working on it. We're working on it. Here comes memory. But the promise is where I think pretty thin relative to people again, because I think this is so important. You and I are in agreement that this could be the next 10x moment with GPT like experiences for consumers.

现在你有四个还是五个，对吧？对。我留下，你知道，在这个消费者人工智能领域有公司在竞争。我还没有看到谁。现在，就像我在上一部分说的，我觉得如果你得到这个记忆，对吧？它可能会改变。自从我们做了那件事之后，嗯，Open AI发布了一份声明，说我们正在努力做这件事。我们正在努力。记忆即将到来。但是承诺相对于人们来说我觉得很薄，因为我觉得这很重要。你和我都同意这可能是消费者GPT体验的下一个10倍时刻。

So just double click again on on what you're understanding is a memory and why you think your sensibilities are that it's so important. So I think there's two elements to this. And one of them is a is a user expectation thing. And then the second one is a technical observation on the latter. Let me let me get to that in a second.

所以再次双击你认为是一个记忆的东西，以及你为什么认为你的感受力如此重要。我认为这有两个要素。其中一个是用户的期望，另一个是技术观察。让我稍后详细说明。

But on the user expectation thing, you know, it's funny. I always go back to the movie her, which I thought was just incredible. But like, you I think want to be able to talk to this thing and have it remember everything that you ever told it. And if you had one that knew all of your emails, all of your contacts could remember your to do this, could when you're about to meet someone that could bring up the last four times you met with them and the reminders you left yourself at that point in time, like you're talking to, you know, we talk about the programmers 30% productivity increase.

但关于用户的期望，你知道，有点有趣。我总是想起那部电影《她》，我觉得它太不可思议了。但就像你一样，我想要能够与这个东西交谈，并让它记住你告诉它的一切。如果你有一个可以记住你所有的电子邮件、所有的联系人，可以记住你的待办事项，当你即将见到某人时，可以提醒你上次见他们的四次情况以及那个时刻你给自己留下的提醒，就像你在与别人交谈一样，你知道，我们谈论程序员30%的生产率增长。

This could be a human 30 or 40%. Like if you have this thing in your head that just remembers everything. So that's and by the way, and I said this last time, I think most people have just extrapolated AGI into infinity and think it's going to do all these things. But it's not doing it right now. And and you know this because you and I've been talking about this for a couple of months now, if you talk to the people that are at the tops of these firms and you say, Hey, why can't this thing remember everything I want? And they go, Oh, that's that's a hard problem.

这可能只是人类的30到40%。就好像你的脑海里有一个记住一切的东西。所以，顺便说一下，我上次也说过，我认为大多数人只是把人工智能延伸到无限远，认为它会做所有这些事情。但现在它并没有这样做。你可以知道这一点，因为你和我已经谈论了几个月了，如果你和这些公司的高层人员交谈，你会问：“嘿，为什么这个东西不能记住我想记住的一切？”他们会说：“噢，那是一个困难的问题。”

Exactly. And it turns out that just because of the way this thing works, it would literally have to retrain every night on each every individual user and training costs are super expensive. Right now it's trained on the internet. It's regurgitating the internet. It's not training on everything in your database. And so there are people, including open AI and all I think every want this is another one of those things I think they're all aware of this. But they don't know how to do it technically.

事实上，由于这个系统的工作方式，它必须每晚重新对每个用户进行训练，而训练成本非常昂贵。目前它是在互联网上进行训练的，只是在重复互联网的内容，而不是在您的数据库中进行全面训练。因此，包括Open AI在内的许多人都意识到了这一点，但他们不知道如何在技术上做到这一点。

And and and you know, I invite anyone to come on the show that thinks they know how to do it technically if they'd like to correct us or whatever I'd love or if there's a startup that thinks they know how please come see us who right? You're both funded. And you and I've talked about this. I mean, and listen, I think open AI open the kimono a little bit. I think they're further out in front than they revealed.

我想说的是，我邀请任何认为自己在技术方面擅长的人来参加节目，如果他们想要指正我们或者有任何想法的话，我很乐意接受，或者如果有创业公司觉得他们擅长，请来找我们聊聊对吧？你们两个都有资金支持。而且我们已经谈过这个话题了。听着，我认为OpenAI已经有了一些进展，比他们透露的更为领先。

But you know, again, I come back to this idea that I'm really lucky out here. My my assistant Brit. She's been with me for 15 years. She knows me longitudinally. My likes, my dislikes, my family, everything about my kids, everything about hotels I've stayed at, rooms I want to stay in, etc. So my expectation of her is that she can take offload a lot of that because she has all that prior history, right?

但你知道，我再次回到这个想法，我在这里真的很幸运。我的助手布里特。她和我在一起已经15年了。她对我非常了解。我的喜好，讨厌的事情，我的家人，我的孩子，我住过的酒店，我想要住的房间，等等，她都知道。所以我对她的期望是，她可以帮我承担很多工作，因为她有所有这些先前的经历，对吧？

And very human had that. Exactly. You think about the productivity unlock for humans. If you give that for free to every human in their pocket, and I'm convinced it's going to happen. But one of the things I would suggest, I had a really interesting conversation with some friends about Apple. Okay. Because this is the giant, right? This is the thing in everybody's pocket. Nobody's talking about them. But they they have so much information about me. Okay.

每个人都有这样的经历。不错。你考虑过给人类带来的生产力释放。如果你免费把它放在每个人的口袋里，我相信这是会发生的。但我想提出一个建议，我和一些朋友进行了一次非常有趣的关于苹果公司的谈话。因为这是一个巨头，对吧？这是每个人口袋里的东西。但没有人在谈论他们。但他们对我有这么多信息。

They have my contact list. They have my emails. They have my text. They have all these applications. And so one of the things I'll just drop out there, I think a little provocative about what they may be doing. Because I've read a bunch of stuff on Twitter about how they're building their large language model of their own. My sense is they're not doing that. Okay. My sense is, in fact, that if you think about it in the context of my assistant, right? So here's the metaphor I give to you.

他们拥有我的联系人列表。他们拥有我的电子邮件。他们拥有我的短信。他们拥有所有这些应用程序。所以我想就有一件事情我会提出来，我认为会有点具有挑衅性，关于他们可能在做什么。因为我在Twitter上读到了一些关于他们如何建立自己的大型语言模型的东西。我觉得他们并没有在做那个。好的。实际上，我觉得，如果你在考虑它与我的助手的背景，如果你想象一下，对吧？所以这里是我给你的比喻。

Would you rather have an assistant with the intelligence of like Einstein, but they have no access to the internet and they don't know anything about your history? Or would you like to have an assistant that's just above average intelligence knows everything about you and they can use the internet? Okay. You would choose that, right? You would choose the and so think about what Apple is going to do. Maybe more like a small language model, like really understand all the language, really understand everything about me, really understand how I interact with all these applications.

你更愿意拥有一个像爱因斯坦一样聪明的助手，但他们没有网络访问权限，也不知道你的历史吗？还是你更希望拥有一个智力略高于平均水平的助手，他们知道你的一切并且能够使用互联网？好的。你会选择后者，对吧？你会选择那个，所以想想苹果可能会做什么。也许更像一个小型语言模型，真正理解所有语言，真正理解我所有的一切，真正理解我如何与所有这些应用程序互动。

And then when I have a deep problem I need to solve, they can sub agent it out, right? They can send me down the path of chat GPT or send me down the path of Gemini or send me to meta AI for an answer engine if I want to go down that path. But I think that there's this layer on the top that's just a different architecture, a different way of thinking about this. That's going to be more like my assistant Brit that's just steering everybody in the right directions.

然后，当我有一个需要解决的深层问题时，他们可以将其代理出去，对吗？他们可以引导我走向聊天GPT的路径，或者引导我走向Gemini的路径，或者引导我走向元AI寻找答案引擎。但我认为，顶层存在一种不同的架构，一种不同的思考方式。那将更像是我的助手Brit，它只是在指导所有人朝着正确的方向前进。

I think Apple is superbly positioned to do this. But of course you don't want it to just you also want to be able to tell it things that you just to remember this or mark this down or attach this to a note. And we've talked in the past about how an LLM could be a user interface disruption. And so you could imagine a small business starting with a CRM that is only voice, right? And you say this customer this, you know, and you just talk to it and you want it to remember. But that has to be architect. Think about this. You know, Brett Taylor's new business Sierra, we're looking at a bunch of businesses in this space. Again, you and I are talking about it in the consumer landscape. Remember everything longitudinally about me. But what is a CRM? It's remembering everything longitudinally about your other, your customers. Well, one thing I want to do just to wrap this up because I think that you and I are analysts and you know, I think oftentimes in our business people talk about it. Is this company good or is this company bad? And I think one of the things you and I think about a lot is distribution of probabilities. And is it reflected in valuation?

我认为苹果公司具备出色的优势来做到这一点。但当然，你不仅希望它能仅仅做出这一些，你还想要能够告诉它一些事情，比如让它记得这个或者记下来这个或者把这个附加到一个记录中。我们过去曾谈论过一个LLM可能会对用户界面造成打扰。因此你可以想象一个小企业从一个仅仅具有语音功能的CRM开始，对吧？你说这个顾客这个，你知道，然后你只要跟它交流，你希望它能记住。但这需要进行架构设计。思考这个。你知道，布雷特·泰勒的新公司Sierra，我们正在关注这一领域的一系列企业。再次，你和我正在讨论消费者市场。纵向记住我所有的信息。但CRM是什么？它是在纵向记住你的其他客户。有一件事我想要做的就是总结一下，因为我认为你和我是分析师，而且在我们的行业里，人们经常谈论一个公司是好还是坏。我认为你和我经常考虑的一件事是概率的分布。这是否反映在估值中？

So if you pull up this chart we did, which is the man comparison, it shows the growth rates and the multiples applied to Microsoft, Amazon, Nvidia and Google. And here all we did was take consensus numbers. So these are not altimeters numbers. Our numbers are higher for some and lower for others. But one of the things I just want to point out is at the top, this is the 23 through 25 expected growth rates, 14% for Microsoft, 12% for Amazon, 42% for Nvidia and 11% for Google. So Google's already expected out of those four to be growing at the slowest rate. But then what's interesting if you come down here to the price to earning ratio, right? You'll see that Google is trading at the lowest PE, right? 21 times 24 and 20 or 18 times 2025 expected.

所以，如果你查看我们制作的这份图表，这是关于这几家公司的比较，显示了微软、亚马逊、英伟达和谷歌的增长率和市盈率。这里我们只是使用了共识数据。因此这些不是我们的数据。我们的数据有些高一些，有些低一些。但我想指出的一点是在顶部，这是2023年到2025年的预期增长率，微软为14%，亚马逊为12%，英伟达为42%，谷歌为11%。因此，在这四家公司中，谷歌已被预期为增长速度最慢的。但很有趣的是，如果你看下面的市盈率，你会发现谷歌的PE最低，分别是21倍、24倍和2025年预期的20倍或18倍。

So all the things that you and I just talked about Bill about growth rate and durability of free cash flows into the future, I would argue a lot of these are already discounted in the stock, right? People are already placing those bets. And so one might take the other side of that and say, yeah, Brad, yeah, Bill, I know all those things to be true, but they can cut a lot of costs and do a lot of things and that could cause the multiple to go up. But if you go to the line under that to the peg ratio, because this is one a lot of people want to ignore on a on a price to earnings multiple, for example, in videos a lot higher. But if you actually look at it on a peg ratio, this year, it's it's a much less expensive company. If you look at on 25 peg ratios, it's just a little bit different. So there are two ways in which to look at future price to earnings multiples. One's growth adjusted, right? That tries to take growth out of the equation and just look at it in terms of strict valuation.

所以我们刚才和比尔谈到的关于增长率和未来自由现金流的持久性的所有事情，我认为很多这些已经在股票中折扣了，对吗？人们已经下了这些赌注。因此有人可能持相反意见说，是的，布拉德，是的，比尔，我知道所有这些都是真的，但他们可以削减很多成本，做很多事情，这可能会导致多个增加。但如果您去查看其下面的PEG比率，因为这是很多人想忽视的一个地方，例如，视频多是很高的，但实际上如果您以PEG比率来看，今年这家公司是一个更不昂贵的公司。如果您看25个PEG比率，情况会有些不同。因此，有两种方式来看待未来的市盈率。一种是增长调整的，对吧？它试图将增长排除在外，只看待严格的估值。

So my big takeaway from this bill is we're not here to pick on Google. We're just to say this is an important case study to watch about innovators dilemma. And it's clear to me that investors are already discounting it, that they have some of these headwinds coming. And I think there may be an opportunity. So, you know, I said the other day, if they manage to thread this needle, trust me, I'll climb on board that bus because I think there are tremendous costs they can cut out of that business. There's a lot of fitness they can drive into that business. And the real question is, how are they going to drive down the costs of serving these inferences? And how are they going to monetize this in a way that by the way, we, you know, it's funny because I think they have other assets like when you talked about Apple, you said they have the handset. Well, you know, Google controls the entire Android market, which is a big market.

因此我对这项法案的主要看法是我们不是要针对谷歌，我们只是说这是一个重要的案例研究，关于创新困境。显然，投资者已经在对此进行折价，他们已经预见到一些困难要来了。我认为可能会有机会。所以，你知道，前几天我说过，如果他们成功地解决了这个难题，相信我，我会加入他们的行列，因为我认为他们可以削减大量成本。他们可以给业务带来很多活力。真正的问题是，他们将如何降低服务这些推论的成本?以及他们将如何以某种方式将此货币化，顺便提一下，我觉得他们还有其他资产，就像你提到了苹果，你说他们有手机。很明显，谷歌控制着整个Android市场，这是一个庞大的市场。

They have a competitor to Microsoft's office suite. Now, they have historically not invested a lot in that it's not a big driver of their revenue. They could they could all of a sudden triple down, you know, they were ahead in type ahead. If you remember, like, I, my kids use those products and I was always on the Microsoft and I can remember, like it was finishing sentences for my kids. I was like, what was that? Right. That was inside of Gmail. Yeah, first. Yes. And so they have assets that that they could bring to the bear. And I, and I think, you know, everything you said about Apple is true. Like having the physical control, the physical device seems real to me like meta, like the notion that my AI would live in my WhatsApp as a person.

他们有一个竞争对手，可以与微软的办公套件相匹敌。历史上，他们在这方面并没有投入太多，因为这并不是他们收入的主要来源。但他们突然可以做出三倍的努力，你知道的，在自动填写方面他们领先。如果你记得的话，我的孩子们使用那些产品，我总是在用微软，我记得，就像它在为我的孩子们完成句子。我觉得那是什么来着？对，那是在Gmail里。对，首先。是的。所以他们拥有可以利用的资产。我认为，关于苹果的一切都是真实的。拥有物理控制，物理设备对我来说似乎是真实的，就像我的人工智能会在我的WhatsApp里作为一个个人存在的观念。

I like that doesn't feel intellectually perfect to me. Like it being in the phone. Yes. Feels perfect to me. Like this thing's with me all the time. But let's talk about two things in that regard. So we talked about you talked about memory being a 10 X chat GPT moment. So you said GPT was one of these 10 X moments to you compared to blue links. If we got memory, that would probably feel 10 X like by the way, why you're there. I have to say one thing that relates to to valuation. Yeah. One thing that drives durability going back to our competitive advantage period is switching costs. If I start relying on one of these things as my memory, and I don't have a way to pull that out and jump to something else, I'm stuck.

我喜欢这种不完美的智力感觉。就像在手机里一样。是的。对我来说感觉完美。就像这个东西一直和我在一起。但让我们谈谈这方面的两件事。所以我们谈到了你谈到了记忆是一个10倍的GPT时刻。所以你说GPT对比蓝色链接是你其中一种10倍的时刻。如果我们有了记忆，那可能会感觉像10倍一样。顺便说一下，你为什么在这？我必须说一件与估值相关的事情。是的。驱动耐久性的一件事情回归到我们的竞争优势时期是切换成本。如果我开始依赖其中一件事情作为我的记忆，而我没有办法将其提取出来并切换到其他东西，那我就会被困住。

Yes. Like I am hooked, locked, stuck. Right. Which means I'm very, very positive for the person that gets there. So I think I'm looking for memory as a 10 X moment. The other 10 X moment I'm looking for here, Bill, is actions, right? Going from answers to actions. And so let's talk about that for a second. Yeah. You know, this company, Rabbit's been making some waves. They have their version one out. Yeah. I saw, I think Tony Fiddell tweeted the other day, can't wait to get his hands on one. There's a bunch of cool demos online. We've spent some time with the company. And now the thing that they have or that they talk about is a huge differentiator is what they call a large action model, not a large language model, large action model. And basically think of it like cursor control, Bill. So if I say, and in fact, we did this demo upstairs when they were visiting, I said, book an Uber going from, but it was able to do it.

是的。就像我被抓住、锁住、困住了一样。对。这意味着我对那个能实现这个目标的人非常非常积极。所以我认为我在寻找记忆作为一个10倍的时刻。这里我追寻的另一个10倍时刻，比尔，是行动，对吧？从答案到行动。那就让我们谈一谈。是的。你知道吗，这家公司，Rabbit已经引起了一些轰动。他们的第一个版本已经发布了。对，我看到了，我想是托尼·菲戴尔（Tony Fiddell）前几天发推说迫不及待想要拥有一台。还有很多酷炫的演示视频在线上。我们花了一些时间研究了这家公司。现在他们所拥有的或者谈论的一个巨大的区别是他们所谈论的大动作模型，而不是大语言模型。基本上可以把它想象成光标控制，比尔。所以如果我说，事实上，当他们来访时，我们在楼上进行了这个演示，我说叫一个优步从…但它能够做到。

It literally had trained on the behavior, cursor behavior of people using these apps. And it was able to book that without any other intervention by me. So I took to doing some research and said, could Apple do this? Because Apple knows exactly what pixel I'm using on the screen to hit a book button on booking.com or on Uber or whatever the case may be. Now remember, Caparti talked about this when he went to open AI the first time he worked on a project that he called World of Bits. And World of Bits, the iconic thing he tried to do there. And I think this was maybe five or six years ago was to book a hotel. Could he get an AI to book a hotel? And he said, at the time it was damn near impossible, he had to write all these very specific algorithms, had to try to figure out what every booking page looked like. And he said recently on Lex Freeman, maybe a year ago, he said, I think if I tried to do it now using the general capabilities that exist today, it would be a lot easier.

它实际上已经在训练人们在使用这些应用程序时的行为，包括光标行为。它能够在我没有任何其他干预的情况下完成订票。所以我开始做一些研究，想知道苹果是否也能做到这一点？因为苹果知道我在屏幕上点击booking.com或Uber等按钮时所使用的像素。现在记住，卡帕尔蒂在第一次参观开放AI时谈到了这个问题，他当时致力于一个名为World of Bits的项目。在那里，他试图做的标志性事情是预订一家酒店。他能让AI来预订酒店吗？他说，当时这几乎是不可能的，他不得不编写所有这些非常具体的算法，不得不设法弄清楚每个预订页面的外观。他大约一年前在Lex Freeman上说，他认为如果现在尝试使用当今存在的一般功能来做这件事，会变得更容易一些。

So I think that Apple's working on this clearly startups like rabbit are looking on working on it. I think that is another 10x moment that's in front of us, which is we go from answers where I'm just asking it for information to actions. And once it can start booking my hotel booking, reserving my restaurant. And then I just say, same thing, do it again. Right? Because it has a little bit of memory about my prior action. Those are really powerful. And there's a there's an element of this that's just a fancier version of screen scraping, right? There's a there's a there's a hackiness to this to this notion. And I have often said, you know, why in the world are we writing in the self-driving world, are we writing, you know, millions and millions of line of code to infer the state of a traffic light? Like, why don't we just broadcast the state of the traffic light? And it would be it would be three orders of magnitude less code. But guess what? I think we we literally are going to bypass. I think if we had done that, that also would have been intensive, right? Because then we had to wire everything up to be morning.

所以我认为苹果正在努力解决这个问题，像rabbit这样的初创公司也在研究这个问题。我认为，我们面前又有一个10倍的时刻，从我只是问问题得到答案，到可以执行行动。一旦它开始帮我预订酒店、预订餐馆，然后我只需说同样的事情，再做一次。因为它对我的先前操作有点记忆。这些都非常强大。这个元素只是屏幕抓取的更高级版本，对吧？这个概念有一种巧妙的精明。我经常说，你知道，在自动驾驶的世界中，我们为什么要写数百万行代码来推断交通灯的状态呢？为什么我们不直接广播交通灯的状态呢？这样会省下几个数量级的代码。但猜猜看？我认为我们可能会绕过这个问题。因为如果我们那样做了，也会很耗费资源，对吧？因为我们必须把一切连接起来才能运行。

Well, here's where I think the world's going. We met with these robotics companies, we meet with Tesla, et cetera, imitation learning. Okay, they're not even going to know what the stop sign is or the traffic light is or the dog in the street. They're not going to write C plus plus for every one of those specific incidents. They're literally going to watch the behavior of the five star human drivers for enough hours. And they're going to imitate it. All right, but you're missing my point back on the on the on the internet side, which is is telling having the having the AI, um, like move my cursor around and click and fill out things is is not the most efficient way to do this. You would you would have API. API is of course with these different services and and and a way to interact. And that's going to be a an interesting evolution. And there's a number of startups working on this too, on different ways to try and drive action and to, you know, some of them will will sit on top of browsers and do that or some of them might try and sit on top of your phone. Of course, Google and Apple will stop them from doing that. I totally agree with that. It's funny. I was asking our analysts, right? 10 billion queries a day on Google today. I say, do the number of queries in the future go up or go down? Right. And I had somebody, uh, if I saw our event at perplexity, said to me, well, the number of queries probably goes down because you don't have to ask it so many times. It'll just give you an answer. And I said, what about the positive reflexivity? Once I get the answer, I've got more questions. Right. Like as long as it's fast and it's producing the that information, I actually think actions and memory will unlock more interactions because it's so much more valuable to me. I'll start using it more and more for these future things. And I don't know. It'd be interesting to see there, you know, for a while, we've had the elections of the world or whatever, you know, do integrations, right? And so the maybe the possibility exists that if I'm an Uber customer and open table customer that that that eventually, I will tell them my favorite front end and they'll come to some agreement there so that they can pass my registration information through and that that all happened seamlessly. But there's a lot of work to do to make all that happen. Right. I mean, I think there's a lot of agent to agent interaction that will go on. Um, an AI agent representing both of these parties. But what's interesting about the action model, you know, the - hackiness that you talk about, right? I imagine this will get solved by startups in some pretty hacky ways to begin, but then it will ultimately likely be solved at scale in more elegant ways, whether it's APIs or agent to agent interactions, etc. But we're starting to see real experimentation. And I've had some of the early prototypes of actions actually coming to pass. And that feels to me like the next two big breakthroughs are going to be this memory. And by the way, I said this last time and it's a subtle point. But I don't think Google, you know, it's another issue in the in the disruption. I don't think Google has treated its partners well in the search ecosystem. And so there's a lot of, of angst there and a lot of mistrust. And so if open AI or perplexity came along and said, would you integrate and pass tokens? They might say yes. I think they're going to be more reluctant to do that with Google. I mean, at a minimum, we know they would probably like more competitors. In the game of sending them leads, right? So I mean, I think just the fact that you're a smaller player that you can be another source of competition. And they're not so dependent on Google for upstream traffic is probably an advantage to you.

嗯，这就是我认为世界正在变化的地方。我们与这些机器人公司见面，与特斯拉见面，等等，模仿学习。好的，它们甚至不会知道停车标志是什么，交通灯是什么，街上的狗是什么。他们不会为每一个具体的事件写C plus plus。他们实际上会观察五星级人类驾驶员的行为足够多的小时数。然后他们会模仿它。好了，但你忽略了我的观点，在互联网方面，那就是告诉AI，像移动我的光标，点击和填写东西，这不是最有效的方法。你会有API。API当然是这些不同的服务，以及与之交互的一种方式。这将是一个有趣的演变。有许多初创公司也在研究这一点，期望通过不同的方式来驱动行动，并有些公司会在浏览器的顶部安排一些或者有些公司也尝试将其放在手机的顶部。当然，谷歌和苹果都会阻止他们这样做。我完全同意这一点。有趣的是，我询问了我们的分析师，现在每天在谷歌上有100亿次搜索查询。我说，未来的搜索查询数量会增加还是减少？我曾经在某个困扰的事件看到有人对我说，好吧，搜索查询的数量可能会减少，因为你不必多次提问，它会直接给你答案。我说，积极的反应呢？一旦我得到答案，我就会有更多问题。就像只要它快速而且提供那些信息，我实际上认为行动和记忆会释放出更多的互动，因为对我而言这非常有价值。我将开始越来越多地用于这些未来的事情。我不知道。在某种程度上，我们已经看到世界上的一些选举或者其他的整合，对吧？所以也许存在这样的可能性，如果我是Uber的客户和open table的客户，最终我会告诉它们我更喜欢的前端，并且他们会达成某种协议，这样他们可以顺利传递我的注册信息，并且所有事情都能无缝进行。但是有很多工作要做才能让一切顺利进行。我认为会有很多代理对代理的互动。一个代表这两方的AI代理。但有趣的是，你提到的行动模型的 - 欺骗性，对吧？我想这将通过一些非常巧妙的方式来解决，但最终可能会以更优雅的方式在规模上得到解决，不管是API还是代理对代理的互动等。但我们开始看到真正的实验。我看到了一些早期的行动原型实际上成为现实。对我来说，下一波两大突破可能是记忆。顺便说一句，上次我说了这一点，这是一个微妙的观点。但我认为谷歌，在颠覆中的另一个问题是，我认为谷歌没有在搜索生态系统中善待其合作伙伴。所以有很多焦虑和很多不信任。如果open AI或perplexity过来说，你是否愿意整合并传递令牌？他们可能会说是的。我认为他们对于与谷歌做这样的事情可能更加犹豫。至少，我们知道他们可能想要更多的竞争对手。在给他们导入信息的游戏中。所以我认为，你是一个较小的参与者，你可以成为另一个竞争来源。他们对于自己的上游流量不再那么依赖谷歌可能对你有利。

Well, I know we're going to want to move to the topic of chips here in a second. But before we get there, we touched on Microsoft, we touched on Google, we touched on Apple, just by way of comparison. And people have heard me talk about meta a little bit in this in this regard. So again, the way we approach the analysis for all large cap tech, we said, is their existing business get better or worse because of AI? And then do their new business opportunities get bigger. Okay. So in the case of meta, unlike Google, Google has this massive super profitable business that's under assault by answers and actions. In the case of meta, we've seen their core business get better as a result of AI. Why? Because you're targeting videos now on reels, you're targeting. And then it happened pre-level. That was already happened. It was starting to happen. But the big difference really, I think between bite dance and meta was that yaming at bite dance adopted an approach around AI and GPUs before meta did. And I think I think Mark really made that transition about three years ago. You can see it in their cap X spend. But the big question was, obviously, he had to spend the money before he got the results. And so investors like us were kind of holding our breath and we're saying, would this lead to better engagement? Well, now we know it's lead led to massively better engagement. And I'm not talking just on reels. This is on the core big blue Facebook product. This is on WhatsApp. This is on Instagram. So they have these big platforms that are benefiting from both more engagement and the targeting of ads. Remember, this stock was at 90 bucks and everybody said, Facebook's dead because Apple attacked Apple pushed through their changes that disabled their ability to really track people into it. And basically because of AI, they've been able to backfill that monetization completely. Nobody thought no investors thought that was going to be the case 18 months ago. So their core business got a lot stronger. Now, as we look ahead, think about the new business opportunities that are in front of them. And I'm just talking about the things that Mark talked about on the call. Number one, they've got tens of millions of business customers that now they're literally creating these customer service agents for AI agents for every single WhatsApp business. Now, we don't see that as much here in the US, even though WhatsApp is the fastest growing messaging platform in the US. But if you go to a place like India or Brazil, people are transacting. Some of the biggest AI engines, right? AI bot companies are being built on WhatsApp as a platform in Brazil and in India, where they have tens of millions of customers already using them. So these have become platform companies that are enabling vertical and horizontal bots. And they're going to build their own. They're going to build it for celebrities. They're going to build shopping agents that assist me buying things on Instagram. You know, I always see all these things I like on Instagram, but it's a pain to actually buy the things on Instagram. The one click never got that easy. Now, I think you're going to see shopping agents that assist in doing that. And then just think about this content creation bill, whether you're an advertiser, just think what we saw this week with Sora. Text a video. I mean, now think of this in the context of an advertiser trying to drive a motor or creator or a creator, right? So my sons are creators creators on these platforms. This is going to unleash monster amounts of creation in the world at lower costs. And so all of that, I think, benefits their core business. You have these new businesses that they get to move into that I just mentioned.

好的，我知道我们马上就要转到讨论芯片这个话题。但在我们到那里之前，我们提到了微软、谷歌和苹果，只是为了做一个比较。人们听到我有关meta的一点话。因此，我们对所有大型科技公司的分析方法是，他们现有的业务因为人工智能而变得更好还是更糟，然后他们的新业务机会会变得更大。在meta的情况下，与谷歌不同，谷歌有这个正在受到问答和行动侵害的超级利润丰厚的业务。而对于meta，我们看到他们的核心业务因为人工智能而变得更好。为什么呢？因为你现在在reels上定位视频，你在定位。在此之前，这已经发生过。这已经开始发生了。但我认为拜特舞蹈和meta之间真正的区别是，拜特舞蹈在meta之前采用了人工智能和GPU的方法。我认为马克大约三年前开始做出这个转变。你可以从他们的资本支出中看出来。但最大的问题是，显然，在获得结果之前，他必须先花钱。因此，像我们这样的投资者有点屏住呼吸，我们说，这会带来更好的参与度吗？现在我们知道，这确实带来了大幅提高的参与度。我不仅指的是reels。这也发生在核心的脸书大蓝产品上。 WhatsApp上也是如此。Instagram上也是如此。因此，他们拥有受益于更多参与度和广告定位的大平台。请记住，这支股票曾经到90美元，每个人都说脸书完蛋了，因为苹果攻击了，苹果推出了他们的变革，使他们无法真正跟踪人们。但基于人工智能的原因，他们已经完全弥补了这种盈利。18个月前，没有投资者认为这会发生。他们的核心业务变得更加强大。现在，展望未来，想想他们面前的新商机。我只想说说马克在电话会议上谈到的事情。第一，他们有数以百万计的企业客户，现在他们为每个WhatsApp企业客户创建这些客户服务代理AI代理。现在我们在美国看不到这种情况，尽管WhatsApp是在美国增长最快的消息平台。但如果你去印度或巴西之类的地方，人们正在进行交易。一些最大的人工智能引擎公司正在WhatsApp上构建平台。在巴西和印度，他们已经有数以百万计的客户使用他们的产品。因此，这些已成为让垂直和水平机器人能够实现业务的平台公司。他们将建立自己的平台。他们将为名人建立平台，他们将建立购物代理，帮助我在Instagram上购买东西。你知道，我在Instagram上总是看到很多我喜欢的东西，但实际上在Instagram上买东西很痛苦。一键购买从来没有那么容易。现在，我认为你会看到购物代理来帮助实现这一点。然后想想这个内容创造法案，无论你是广告商，想象一下我们本周在Sora上看到的东西。文本视频。现在想象一下一个广告商试图推动一个运动或创作者。我的儿子们是这些平台上的创作者。这将在世界上以更低成本释放大量创作。因此，我认为所有这些都会使他们的核心业务受益。他们有这些我刚提到的新业务可以发展进入。

Then, of course, I thought another interesting thing from Morning Brew. I think the pod that Mark was on last week, he talked about the meta AI glasses that all my analysts have, right? He said, you know, most people, they looked at Mark taking the video, reviewing the Vision Pro from his couch and they see, you know, that got a lot of glamour on Twitter. But the fact of the matter is Mark said the way you want to think of VR and AR really is as your desktop or your laptop. But the meta AI glasses, he said, think of as your phone, right? Because I'm going to be able to text. I'm going to be able to call. I'm going to be able to listen to music. I'm going to be able to order my Uber. I'm going to be able to do all these things from those glasses. And I don't have to pull out this rectangular thing or I keep it in my pocket or whatever. I think that's why you're seeing such incredible demand for those. And of course, the form factors will change and it'll evolve over time. But that's an entirely new line of business. So this is a company that's spending $20 billion a year on these other businesses that haven't been generating a lot of return. And I think now the market's starting to assign some value to those businesses. But we should be fair, right? Because YouTube benefits from those same of course dynamics that you talked about. And if you're talking about units of being the phone or the Apple and Google already have a huge install base like what forward is a magnitude to the number of Rayman glass.

然后，当然，我还从《Morning Brew》中找到了另一个有趣的事情。我觉得上周马克参加的那个播客里，他谈到了我所有分析师都有的元AI眼镜，对吧？他说，你知道，大多数人看到马克在沙发上拍视频，审查Vision Pro，他们会觉得那在推特上很有魅力。但事实是，马克说，你应该把虚拟现实和增强现实想象成是你的桌面或笔记本电脑。但元AI眼镜，他说，应该当作是你的手机，对吧？因为我可以发短信，打电话，听音乐，叫Uber，做这些事情都可以从这些眼镜里进行。我不必拿出这块长方形的东西，或者把它放在口袋里什么的。我觉得这就是为什么你看到这些眼镜有如此惊人的需求。当然，外观形态会不断改变和发展。但这确实是一个全新的业务领域。所以这家公司每年要在这些其他未产生很多回报的业务上花费200亿美元。我觉得现在市场开始给这些业务一些价值。但我们应该公平对待，对吧？因为YouTube也受益于你谈到的这些动态。而且如果你说单位是手机，那苹果和谷歌已经有了庞大的用户群，像雷曼眼镜的数量相比已经高出一个数量级。

Yeah, no, no, no, for sure. But I think the question is from where you are today. Right. And so like I'll stipulate YouTube will be a better business in the future. Content targeting will be better. Ad targeting will be better. Right. And as long as Google is able to backfill the core of search like we just discussed, then it's going to be worth more in the future. There's no doubt about it. And of course, in terms of just their basic research and development around AI, what they did with Gemini 1.5, etc. I mean, like these, they have incredible talent and resources. The only liability is they have an incumbent business that is a monopoly business with monopoly profit. So that we can move on. Let's do a fast drive by. I'm going to do one on Apple and then you do Amazon. Okay. As a reminder to everybody, just our opinions, not investment advice. So for me, you know, Apple, you could argue they have the best asset in the world in this phone. And if you look at the user base of this compared to the Android user base, you know, it's just perfect, right? And they've been doing Siri for a while. And so you connect those two things, you say shit, like they put a L and M on top of this, they could get to all the data. Well, sir, you could give a permission to read your emails. So you could literally get to all the data. So that's a massive positive. Now the negative is they haven't been known for internet services. You look at Spotify, relative to Amazon music, Siri's kind of been. It's been terrible. Not evolving, right? Like it's very much like it was the day it came out. Yeah. And so it would almost require a pivot of like like Mark did on cost. And you'd almost have to see Tim come out and say, we're making a massive pivot. Like 180 degrees, we're going to be all in. Like we're putting our best engineers on this. And until that happens, I think it's a doubters camp. Yeah. Well, I mean, clearly it's been an underperformer this year. I mostly related to China market. Yeah, you have China market, but you have all these concerns in the market going just as to what's the durability or revenue going to be in the future. You clearly have. But they have the assets. Imagine if you took like five of the top AI people. I mean, I'm these companies and they were there. Like they were there the way Tony Fiddell was there early on for the iPod. Like if you had that, you know, listen, for the first time, they have real challengers, whether it's a humane or rabbit, a meta AI glasses, these other things, right? Like I'm just saying the door has been cracked on the ecosystem. Siri has not evolved, right? So they, they, I think they're the first to acknowledge that. I think they are going to try to disrupt themselves about that.

是的，不不不，肯定会这样。但我认为问题是要看你现在所处的位置。对。所以我会承认，YouTube将来会成为一个更好的生意。内容定位会更好。广告定位也会更好。对。只要谷歌能够像我们刚讨论的那样填补搜索的核心部分，那么它将在未来更值得投资。毫无疑问。当然，就基本的人工智能研究和发展而言，他们在Gemini 1.5上所做的事情等等。我是说，他们拥有令人难以置信的人才和资源。唯一的问题是，他们有一个处在垄断地位的现有业务，具有垄断性利润。所以我们可以继续下一步。让我们快速谈一下。我会讨论苹果，然后你说亚马逊。好吗？提醒大家一下，只是我们的意见，不是投资建议。对我来说，你可以说苹果在这款手机上拥有世界上最好的资产。如果你看这个用户群与Android用户群相比，你会发现这简直完美，对吧？他们已经推出Siri一段时间了。所以把这两件事联系在一起，你会说哇，如果把这两者结合起来，他们可以获得所有的数据。当然，你可以允许他们读取你的邮件。所以他们可以实际获取到所有的数据。这是一个巨大的优势。现在的问题是，他们一直不擅长互联网服务。你看看Spotify相对于亚马逊音乐，Siri一直存在问题。没有进步，对吧？就像当它第一次推出时一样。是的。所以几乎需要一个像马克在成本上做的那样的转变。你几乎需要蒂姆出来说，我们要进行一次巨大的转变。就像180度，我们全心全意投入其中。我们要把我们最优秀的工程师放在这个项目上。在那之前，我认为它还是个疑虑派的阵营。是的。嗯，我是说，明显地，它今年表现不佳。主要是与中国市场有关。是的，有中国市场，但市场对未来的收入持续性有所担忧。明显地。但他们拥有这些资产。想象一下，如果你带来了五个顶尖的人工智能专家。我是说，这些公司中的人，他们在那里。就像托尼·菲德尔早期为iPod提供技术支持一样。如果你有了那个，你知道，首次出现，他们有真正的挑战者，无论是人道主义还是兔子，还是增强现实智能眼镜等等。对吧？我只是说，生态系统的大门已经被打开了。Siri没有发展，对吧？所以，我认为他们是第一个承认这一点的。我认为他们将尝试进行自我颠覆。

I'm not sure whether we'll see a big breakthrough moment this year. I think we'll definitely see announcements this year about AI on the edge running on the phone and in all these other things. We'll start to see, they'll start to crack the door on this. To me, the big breakthrough on Apple is if they can run a five, 10 billion dollar parameter model on the phone on the edge without consuming all of my battery, which, you know, there's a lot of talk that they're going to be able to do that. They can maintain some memory about me and then they can show me the early part of actions on this device. It will unlock a huge new device cycle. Okay. And that's what drives this style. I was the one supposed to do. Okay. You do. You do. I'm going to ask you quick questions.

我不确定我们今年是否会看到一个重大突破时刻。我认为今年肯定会有关于AI在手机和其他设备端的公告。我们将开始看到他们在这方面取得突破。对我来说，苹果的重大突破是如果他们能在手机端运行一个价值五到十亿美元的模型，而不会消耗掉我的整个电池，很多人都在谈论他们可能会做到这一点。他们可以记住一些关于我的信息，然后在设备上展示出我未来可能会采取的行动的初期部分。这将开启一个巨大的新设备周期。这就是推动这种风格的内容。我本应该做的。好的，你做。我要问你几个快速问题。

So on the e-commerce side of the business, does AI help or hurt Amazon? Yeah. Okay. And how much? Yeah. I think, I think on AI, they're two, when I think about retail e-commerce, I think about it from two directions. First is Apple has been in the business of AI from a merchandising perspective, just like Alibaba has been for a long time. Think about the largest retailer in the world. Think about the way Macy's used to work. There was somebody at the store who would say, we're going to show black t-shirts today at the front of the line. And Amazon today, nobody knows why they are targeting Brad Gersner with certain things. It's a black box. Okay. So they're using it. But here's the thing I think is happening a bit to them on that front. And by the way, Andy Jassy is getting fit. They are tightening the screws on costs and all the other things.

在电子商务方面，人工智能对亚马逊是帮助还是伤害？是的。好的。到底有多大的影响？是的。我认为，我认为从人工智能的角度来看，当我思考零售电子商务时，我从两个方面思考。首先，苹果一直从商品角度进入人工智能业务，就像阿里巴巴长期以来一直在做的那样。想想世界上最大的零售商。想想梅西百货的运作方式。以前商店里有人会说，我们今天会在排队的前面展示黑色T恤。而亚马逊今天，没有人知道他们为什么对Brad Gersner进行针对性的推荐。这是一个黑匣子。好的。所以他们在使用人工智能。但我认为他们在这方面会遇到一些问题。而且顺便说一句，安迪·贾西也在进行调整。他们正在收紧成本和其他方面的控制。

But look at a company like T. Moo. Okay. The Pimdodo on China owns that quickly became the largest advertiser on Facebook. It's e-commerce sales are through the roof. Now what they're doing, I mean, it's so incredibly clever. It's full stack AI. So they don't even have inventory or merchandise. They literally go out and they collect data from customers about what they think they will want. They can assess how many of those things to build. And they literally are building it for themselves. So they vertically integrated this AI e-commerce business. And then they're pushing it out the other end. And so I think there have been a lot of people in the US who have been dismissive, but they've been shocked how big that business has come become in such a short period of time. We're starting to see this out of TikTok as well, where they're turning into an e-commerce business. I think this opportunity sits in front of meta as well. So I think there are some orthogonal challenges. But in terms of the core, I think their core continues to get better because of better targeting and AI reducing costs. Think about their customer care cost. We do have to move on.

但是看看像T.Moo这样的公司。好吧。中国的Pimdodo迅速成为Facebook上最大的广告商。它的电子商务销售量飙升。现在他们在做的事情，我是说，非常聪明。这是全栈AI。所以他们甚至没有存货或商品。他们从客户那里收集关于他们认为他们想要的东西的数据。他们可以评估需要制造多少这样的东西。然后他们实际上是为自己建立它们。所以他们垂直整合了这个AI电子商务业务。然后他们推出去。所以我认为在美国有很多人对此不屑一顾，但他们震惊于这样一个业务在短时间内变得如此之大。我们也开始看到TikTok也在转型为电子商务业务。我认为这个机会也摆在了Meta面前。所以我认为有一些正交挑战。但就核心而言，我认为他们的核心因为更好的定位和AI降低成本而持续改善。想想他们的客户关怀成本。我们必须继续前进了。

Hit AWS as quickly as possible. Yeah. So I would say AWS, at the end of the day, these companies are in the business of renting AI services to end enterprises. Right. And as much as we talk about Azure and Microsoft running the table today, here's the truth. We've seen almost no share shift from AWS to Azure as a result of open AI. And if you would have asked me 12 months ago, I would have said jury's out as to whether or not that's going to happen. It didn't happen. Amazon responded quickly enough. And here's the other thing, you know, in slutments, talk a lot about this term, data gravity, right? It turns out all my data is in AWS. So long as they have a decent AI solution, I'm going to stick with them because I don't have to move anything. And I think they delivered that solution to a podcast. And Jesse was talking about the fact that they have proprietary chips for both training and inference. And obviously, as the AWS stack grew up, they had moved into networking chips. They've moved into a lot of technologies. People wouldn't have thought about Amazon owning or designing.

尽可能快地击中AWS。是的。所以我会说AWS，归根结底，这些公司的业务是向企业租赁人工智能服务。没错。尽管我们现在多么谈论Azure和微软控制市场，但事实是，由于开放的人工智能，我们几乎没有看到AWS向Azure转移份额的情况。如果你在12个月前问我，我可能会说现在是否会发生这种情况还难以确定。但实际上并没有发生。亚马逊的反应足够快。另外一个重要的一点是，久经沙场的人们经常会谈论数据重力这个术语，对吧？结果证明，我的所有数据都存储在AWS里。只要它们有一个不错的人工智能解决方案，我就会继续选择它们，因为我不用再把东西搬迁。我认为他们把这个解决方案交付给了播客。杰西谈到了他们为训练和推理都有专有芯片。显然，随着AWS技术堆栈的壮大，他们已经涉足网络芯片市场。他们进入了许多人们不曾想到亚马逊会拥有或设计的技术领域。

Do you give them in this bigger transition? Do you give them any chance of being competitive in it from a AI silicon perspective? So I think the right way to think about it is not will they build a better GPU than Nvidia? The right way to think about it is can they supplant part of the supercomputer, right? The entire system. Are there pieces that they can pull out and plug in or workloads, specific workloads that they can serve with a lower cost infrastructure because they're doing hyper targeting silicon all the way to model? And I think the answer to that is yes. But I still think they'll be one of the largest buyers of Nvidia GPUs in the world because it doesn't replace that for a lot of really important workloads. Well, he also said that that I think would be good for the listeners to hear. And I don't want to overstate where Alexa is. And we talked about Siri earlier, but he said that as Alexa got bigger, that the training costs are tiny compared to the inference cost. And he suggested, and maybe this is me interpolating that the inference market over time is going to be much more susceptible to things that are lower power, lower cost, all the things that aren't just performance from a silicon perspective. And I totally believe that to be true. And with that, we can move to the biggest headlines of the week. We finally got here, which is this debate over the future of the compute build out needed to support AI. And to your earlier point about valuation, how unique is this revenue, how long does it last? And so we have a couple of charts, just a ban or tweets to bang through here to kind of contextualize this first, Nvidia stocks up a lot. But it's because the revenue of the profits have greatly exceeded expectations. So this chart just shows what their data center market share has grown to in the year, right? The world is shifting toward AI as a compute infrastructure and they benefited.

你们在这个更大的转变中给予他们支持吗？从AI硅片的角度来看，你们给予他们竞争的机会吗？所以我认为正确的思考方式不是他们是否能建造比Nvidia更好的GPU，正确的思考方式是他们能否取代超级计算机的一部分，整个系统。他们是否可以取出并插入或服务于特定工作负载，因为他们一直在使用超定位硅片到模型？我认为答案是肯定的。但我仍然认为他们将是全球Nvidia GPU的最大买家之一，因为对于许多非常重要的工作负载来说，它并不能完全取代。他还说了一点我认为听众会喜欢听到的。我们之前谈到了Siri，但他说随着Alexa的发展，培训成本与推断成本相比微不足道。他暗示，也许这是我在推断，随着时间推移，推断市场将更容易受到那些功耗更低、成本更低、以及不仅仅是性能方面的硅片的影响。我完全相信这个观点是正确的。有了这一观点，我们可以转向本周最重要的头条新闻。我们终于来到了这里，即关于支持AI所需的计算基础设施的未来争论。以及关于估值的早期观点，这种收入有多独特，它能持续多久？所以我们有一些图表和推文，让我们快速了解一下，以更好地了解情况，首先是Nvidia的股价上涨了很多。因为他们的收入和利润大大超出了预期。因此，这张图表显示了他们在数据中心市场份额在一年内的增长情况，世界正在朝着以AI为计算基础设施的方向发展，而他们受益于此。

One of the areas I think I tweeted about this that I think has been greatly underestimated this idea of sovereign demand. And I tweeted this week, you know, I think Jensen was over in the Middle East meeting with with several of the GCC countries over there. And I think what people still don't appreciate is there probably dozens of sovereigns who are trying to get into the Nvidia order book. And that they view it as one of their top three national priorities to build out AI capabilities. And I think the size you're talking about for some of these GCC countries is going to be competitors competitive with the hyperscalers itself. So in that context, right? When Sam Altman suggested and blew everybody's mind that he was going to raise seven trillion dollars to, you know, build chips. I don't know if he ever said it. It was it was inferted and repeated over and over again. So he threw out a big number. But I do think that we're talking trillions of dollars over the course of the next four to five years as we rebuild the world's compute infrastructure. And then finally, Masa did not want to be left out. And so he came out and said that he's going to raise a hundred billion dollars to build fabs and chips to compete within video as well. You've watched the semi industry for a long time. Okay. And and more importantly, just the dynamics of supply and demand. So just step back for a second. Right. What do you make of all of this?

我认为，一个被大大低估的领域是主权需求。我在推特上提到过这一点，本周我也发推特说，我认为Jensen在中东与几个海湾合作委员会国家会面。我认为人们仍然没有意识到可能有几十个主权国家试图进入Nvidia的订单簿中。他们将其视为他们建设人工智能能力的前三个国家优先事项之一。而这些海湾合作委员会国家的规模可能会成为超大型云服务提供商的竞争对手。在这种背景下，当Sam Altman提出并震惊了所有人，他将筹集7000亿美元来建设芯片时。我不知道他是否曾说过这个数字，但这个消息被传播了多次。他提出了一个庞大的数字。但我认为，在未来四到五年内，我们将谈论数万亿美元，因为我们需要重新建设世界的计算基础设施。最后，Masa不想被落下。所以他宣布将筹集1000亿美元来建立工厂和芯片，以与Nvidia竞争。你长期关注半导体行业。更重要的是，你关注供需的动态。所以请稍作停顿。你如何看待这一切？

Well, I have some cynicism, but that comes naturally to me. The first thing I would say is they're they're all talking about raising money from the exact same people. So if I were those people, I would just be a little careful because I think to a certain extent, there's a there's a smell of loose money. That's how I would interpret it. Because they're not they're not saying they want to raise this money. Absolutely. They're saying they want to raise it from a very specific group in the Middle East. So so that's the one thing too. I was struck when I read about sovereign server stacks, you know, there needs to be a reason, right? It would have to be about, you know, wanting to have control over certain amounts of information. It could be proprietary information to your country could be wanting to control how all of them operate in that country. Um, servers typically depreciate a bit like fish, you know, and and and that was been true of DRAM and storage and all of these had fish, right? Fish. They last a day. Like, yeah, well, I mean, it's I'm being provocative, obviously, but people have talked about with that with those like you wouldn't you wouldn't want to hoard any because what happens is, you know, the next generation comes along and goes down quickly. So I would just, you know, there was a time at which, um, Microsoft was trying to convince the world that we'd all need an NT server for every employee. And, you know, when I heard that the first time, I was like, trying to get my head to the so I don't know. I don't know if countries need server stacks, maybe. Um, like I said, it'd have to have those particular frames in mind.

嗯，我有点愤世嫉俗，但这是我天生的。我要说的第一件事是，他们都在谈论从完全相同的人那里筹集资金。所以如果我是那些人，我会小心一点，因为我认为在某种程度上，有一种松散资金的味道。这是我的解读。因为他们并不是说他们想要绝对筹集这笔钱。他们说他们想从中东的一个非常特定的群体那里筹集。所以这也是一点。 当我读到关于主权服务器堆栈的事情时，我感到震惊，你知道，必须有一个理由，对吧？它可能是关于想要控制某些信息量。这可能是您国家的专有信息，可能是想控制所有这些在该国运行的方式。服务器通常会贬值，就像鱼一样。这在DRAM和存储器等所有这些鱼上也是如此，对吧？鱼。它们只能活上一天。对，嗯，我的意思很具有挑衅性，但人们谈论说像这样的事情，你不会想囤积任何东西，因为下一代会迅速下降。所以我只是，您知道，有一个时间，微软曾试图说服世界上每个员工都需要一个NT服务器。当我第一次听到时，我就在努力理解，所以我不知道。我不知道国家是否需要服务器堆栈，也许。就像我说的，它必须要考虑到那些特定的框架。

The second thing that just struck me and this gets more to, uh, to the Altman and the masa quote is, you know, the idea that we're just going to go compete with Nvidia, like, it's pretty radical. There are already people competing with Nvidia and these competing with Nvidia. Like, like, there are other people that have somewhat of a head start. Like decades. Yeah. So you're just going to go do it. I was like, that's bold. Like it's not like chip, um, design bins. Oh, yeah, Intel obviously, but like, it's not like chip design bins to disruption or like software does. Like this is hard stuff.

刚刚让我感到震惊的第二件事，更接近奥尔特曼和马萨的引言，就是，你知道，我们只是打算与英伟达竞争，这是相当激进的。已经有人在与英伟达竞争了，并且这些人在与英伟达竞争。就像，还有其他人在某种程度上已经领先了。几十年了。是的。所以你打算去做这件事。我觉得那真是大胆。就像不是芯片设计那么简单。嗯，英特尔很明显，但是，这不像芯片设计那样会产生颠覆性变化，或者像软件那样。这是一项艰巨的工作。

Yeah. And then some of them, and once again, I don't know that there was an exact quote, but the idea that you're going to build a fab and compete, you're going to compete with TMS TSMC and Nvidia at the same time. Like, no chance. Yeah. Like, like, no chance. Cause like, let's say, let's say you got it. I mean, we all know how the math work, but say you got a 20% chance of competing with either of them. Right. Like, then you're down to four, like a pull in the soft and by the way, the time scale that you're going to need. Like, I mean, just read, well, we'll get into it in a minute.

是的。然后一些人，我再次不清楚是否有确切的语录，但是他们的想法是，你要建立一个晶圆厂来竞争，你将同时要与TSMC和Nvidia竞争。像，没有机会。是的，像，没有机会。因为，比如，假设你有20%的竞争对手，你要与他们之一竞争。对吧。那么，你只剩下四分之一的机会，还有，你需要的时间周期。像，我是说，我们马上就会深入讨论。

Cause we'll talk about like what it means to have a competitive fab around the world. But TSMC is far, far ahead of the competition. And one of the reasons AMD has a higher market cap than Intel today is specifically because they got out of the fab business and bet on TSMC. So I think, I think it's really important to tease out those two things, but there's chip design, right? And obviously Nvidia is already designing for two to three generations ahead.

因为我们会谈论全球拥有竞争力的晶圆厂意味着什么。但台积电遥遥领先于竞争对手。AMD如今市值超过英特尔的其中一个原因是因为他们退出了晶圆厂业务，并依靠台积电。所以我认为，区分这两件事情非常重要，但还有芯片设计，对吧？显然，英伟达已经在为未来两三代设计芯片。

I mean, the series B is already taking orders in the order book likely to launch in Q three of this year. And, you know, is order of magnitudes better than the H one hundreds that are out there today. And then you're, they're already designing what comes after Blackwell. And so it's not as though they're standing still and anybody who knows Jensen, he's an animal and that company is, is playing for the future. And then if you look at TSMC and, and, and I shared with you a video, maybe just pull up a little bit about kind of the findings from that.

我是说，系列B已经在订单簿中接受订单，可能会在今年第三季度推出。你知道，它要比现在市面上的H百倍更好。而且，他们已经在设计接下来的产品。所以并不是他们在原地踏步，任何了解詹森的人都知道，他是一个怪物，这家公司正在为未来打算。而且，如果你看看TSMC，我和你分享了一个视频，也许可以看一下其中的发现。

But this is from the founder of TSMC and the CEO for decades, Morris Chang talking about the competitive advantages and bill, because this really gets to the fab. Like, why are all the world's fabs in Taiwan? Okay. And why aren't the fabs in Texas anymore with Texas instruments? Or why aren't the fabs and other parts of the world? And what does that mean for the future of this build out? And I think the implication of these, of these releases is that we're going to start building a bunch of fabs in the Middle East. I think we know we're trying to build fabs in Arizona. There's some talk about building fabs in Mexico. But maybe just let's deconstruct that one. What does it mean to build a fab outside of Taiwan to make next generation AI chips?

但这是台积电的创始人和数十年来的首席执行官张忠谋谈论竞争优势和账单的内容，因为这真的涉及到晶圆厂。为什么世界上所有的晶圆厂都在台湾？为什么德州仪器的晶圆厂不再在德克萨斯州？为什么其他地方没有晶圆厂？这对未来的建设意味着什么？我认为这些释放的暗示是，我们将开始在中东建造一堆晶圆厂。我认为我们知道我们试图在亚利桑那建造晶圆厂。有一些关于在墨西哥建造晶圆厂的谈论。但也许让我们解构一下。在台湾之外建造一个晶圆厂来生产下一代人工智能芯片意味着什么？

You shared this link with me. And I, it's a talk that Morris Chang gave at MIT, I think in November, right? Very recently, he's over 90. And the first, it's like an hour long talk. And the first 60% is a history lesson. But then the last 40%, I would encourage everyone to go watch, like everyone, including every politician in the United States of America. Because Morris makes the point that the reason Taiwan is competitive has to do with the labor model that exists there. And the type of work people are willing to do and your ability to retain them.

你跟我分享了这个链接。我看了一场张忠谋在麻省理工学院的演讲，我想是在11月份，对吧？他已经九十多岁了。讲话持续了大约一个小时，前60%是历史课程。但是接下来的40%，我鼓励每个人都去看，包括美国的每一位政客。因为张忠谋指出，台湾之所以具有竞争力，与那里存在的劳工模式有关。人们愿意从事的工作类型，以及您保留他们的能力。

And he walks through his history of hiring in Texas and other parts of the US. Yeah, interesting enough. He ran a fab plant for Texas instruments in Texas. And he explains why Taiwan, like why Texas could never possibly compete with a fab plant in Taiwan. And he even, he admits that the US was a manufacturing prowess in the 50s and 60s. But the social requirements that we put on labor at that time are different than they are today.

他回顾了他在德克萨斯州和美国其他地区招聘的历史。是的，挺有趣的。他曾在德克萨斯州为德州仪器公司运营一家工厂。他解释了为什么台湾，就像德克萨斯州一样，永远无法与台湾的工厂竞争。他甚至承认，上世纪50年代和60年代美国是制造业强国。但当时我们对劳动力的社会要求与今天不同。

And so whether you look at TSMC and it turns out it's the same thing's true of a Foxconn factory in Mexico, you have people working longer hours, sometimes living in dormitories. And he mentions that on his talk. And he says the country must more likely to disrupt Taiwan would be Vietnam or India, not an advanced culture. And to think you're going to re on shore a fab and ignore Morris Chang is just kind of crazy to me.

所以无论你是看台积电还是富士康在墨西哥的工厂，都会发现工人们工作时间更长，有时甚至住在宿舍里。他在演讲中提到了这一点。他还表示，可能会对台湾造成破坏的国家更有可能是越南或印度，而不是一个先进的文化国家。而且认为重新在岸建立一家晶圆厂并忽视张忠谦的观点对我来说有点疯狂。

And I look at the requirements once again that we put on companies around labor and say to myself, it's not going to happen here. And the people will quickly react to that and say, oh, you're in favor of of forced labor or likes super hard labor. But the people that are choosing that at that point in time are choosing a better life. And to deny them that opportunity, like the individual that lives in war as that's commuting to this Foxconn plant is getting a better life. Even with his four nights a week in the dorm. And to deny him that and insist on our circuit 2023 social norms on that country is unfair. Right. From my point of view. Right. I think it denies them their chance at disruption. So when you unpack and we'll put the link to the video here, when you unpack that message, it's really that Taiwan thrived because these operators and technicians would spend their life working in the same fab on this. You're getting getting better and better at the same thing. And he talked about a 12% churn rate.

我再次查看我们对公司在劳动力方面的要求，自言自语地说，这里不会发生这种情况。人们会迅速对此做出反应，说你赞成强迫劳动或类似非常辛苦的劳动。但在那个时间点做出选择的人选择了更好的生活。而否认他们这种机会，就像那个住在战乱地区的个体为了通勤到富士康工厂而争取更好生活。即使他每周住在宿舍四晚。而否认他们这种机会，坚持我们2023年的社会规范对那个国家是不公平的。从我的观点来看，这样做否认了他们改变现状的机会。因此，当你深入挖掘并看这个视频时，真正的信息是，台湾之所以繁荣，是因为这些操作员和技术人员会一生都在同一个工厂上工作，变得越来越擅长做同样的事情。他谈到了12%的流动率。

I think when he was at the fab in Texas, and he said the problem is the second a better job would come along, they would leave for a better shot. That was it was 12 during during a recession. During a recession, implying that it was much higher. It was with the 25 when when when the times were good. And he said, you just can't run a fab plant with 25% churn among the operators. You produce really bad product. And I think the point is it's not just better life. It's also kind of these cultural norms. And so that's why he said, you know, in Vietnam and India, they have cultural norms. He believes that are more consistent with with loyalty and staying with something longer.

我认为在德克萨斯州的工作时，他说问题在于只要有更好的机会，他们就会为了更好的机会而离开。这是在经济衰退期间，暗示着离职率要高得多。在经济衰退期间，离职率更高。当时情况好的时候，离职率是25%。他说，如果操作员离职率达到25%，你就无法经营一个良好的工厂。你会生产很差的产品。我认为关键不仅仅是为了更好的生活。也包括这种文化规范。所以他说，在越南和印度，他相信那里的文化规范更符合忠诚和长期从事某事的要求。

And on top of that, that it would be an improvement in the quality of life for the people who would take these jobs. And therefore the incentive is there for them to stay in those positions. And either right or wrong. Like, I, you know, I'm not, I'm not provocative. Like, yeah, it's provocative because it says that if America is really worried about the concentration in Taiwan, they should probably be trying to help build some exactly plants in Mexico or Vietnam or that kind of thing versus bringing them here. Cause the odds of operating them here in a competitive way, globally competitive, where low. So I guess, does that make you skeptical of the chip sack? I mean, I see the Intel is back in Washington looking for another $10 billion to subsidize the work that they're doing. I mean, I get the US national security concern, particularly considering that 100% or virtually 100% of these advanced chips are being manufactured in a place that has risk, has political risk associated with it. Bill, let me ask you this.

除此之外，这将是提高那些接受这些工作的人们生活质量的一种改善。因此，他们有动力留在这些职位上。但是，无论对错。我不是，你知道，我不是挑衅性的。是的，这是挑衅性的，因为它表明如果美国真的担心对台湾的依赖，他们可能应该试图在墨西哥或越南建立一些类似的工厂，而不是把它们带到这里。因为在这里运营它们在全球竞争中的优势是很低的。所以我想知道，这让你对芯片行业感到怀疑吗？我看到英特尔正在华盛顿寻求另外100亿美元来资助他们正在进行的工作。我明白美国的国家安全担忧，特别是考虑到这些先进芯片的100%或几乎100%是在一个有风险、与政治风险相关的地方生产的。比尔，让我问你这个问题。

By the way, I am somewhat skeptical of chip sack. And then the other thing I would say to you is, like China is probably in a really good place. Yeah. They're really smart. They have all the intellectual capability of being competitive. And they probably still have this opportunity for them, you know, over time in terms of the willingness of certain part of their population to be willing to work in those types of situations. Yeah. I mean, I'll take probably the under on that. I think that the opportunity, like now there is a global imperative to diversify the source of manufacturing.

顺便说一句，我对芯片袋有些怀疑。另外，我想对你说的是，中国可能处于一个非常好的位置。是的，他们非常聪明。他们具备所有竞争的智力能力。也许他们仍然有这种机会，你知道，随着时间的推移，有一部分人口愿意在那种情况下工作。是的。我可能认为这种机会很有可能实现。我认为，现在有一个全球性的必要性来多样化制造来源。

And I think Morris Chang was having this conversation at MIT recently because he understands the global imperative. I think you are going to see plants that get built in places like Vietnam and Japan. I think you are going to see them get built in India. You're probably going to see some attempts in the Middle East. Obviously, we're trying to do some of this stuff here. I think from a United States interest, both in terms of wanting to maintain leadership in AI and wanting to diversify our political risk associated with Taiwan, it's not so important that everything is produced in the US, right? That shouldn't be our goal or objective for all the reasons that Morris Chang points out.

我认为莫里斯·张最近在MIT进行这种对话，因为他理解全球的紧迫性。我认为你会看到一些工厂建在越南和日本等地。我认为你会看到它们在印度建造。你可能会看到一些在中东的尝试。显然，我们正在尝试在这里做一些事情。我认为从美国的利益角度来看，无论是希望在人工智能领域保持领导地位还是希望多样化与台湾相关的政治风险，重要的不是所有东西都在美国生产，对吧？这不应该是我们的目标或目的，正如莫里斯·张所指出的种种原因。

But I do think it would be better if we had four or five places around the world that were load balancing the manufacturing of these chips. That's a fair point. And I think the whole re-onshoring argument conflates the national security interest with a interest in American jobs and that kind of thing. Going back quickly to these new chip companies that are going to miraculously compete with Nvidia, I would tell you, and this is maybe an older venture capitalist talking and one who's watched different partners sit on the boards of startup semiconductor companies, it ain't easy. The first silicon that comes back doesn't always work. And you might be 50 million to first silicon. You might be 100 million to first silicon.

但我认为，如果我们在世界各地有四五个地方来平衡这些芯片的制造会更好。这是一个很中肯的观点。我认为全面重新本土化的论点将国家安全利益与对美国就业的兴趣混为一谈。再回到那些将与英伟达神奇竞争的新芯片公司，我会告诉你，也许这是一位经验丰富的风险投资家在谈话，一个曾见证不同合作伙伴在初创半导体公司董事会上坐镇的人，这并不容易。第一块回来的硅片并不总是有效的。你可能要付出五千万美元才能得到第一块硅片。你可能需要付出一亿美元才能得到第一块硅片。

You've got to get in line at TSMC. How are you going to break that door down? How are you going to out compete in video for TSMC's time? How are you going to get on that place? And it's hard. And by the way, once you do get working silicon, your yields are probably crappy. That's what happens. This is physical material science type stuff. It's not software. Right. And you're going up against, again, two companies that are run in pretty exceptional ways by exceptional founders in the case of gents has been there for three decades. He's devoted his life to this TSMC seemingly has similar types of leadership. But one of the things I wanted to pivot to on this bill, because it begs the question, why is Sam throwing out this really big number? Right? Why is Masa throwing out this really big number?

你必须排队在台积电等候。你打算怎么破门而入呢？你打算如何在视频方面超越台积电的时间？你要怎样获得这个位置？这是困难的。顺便说一下，一旦你获得了工作硅片，你的产量可能会很低。这就是发生的事情。这是物质科学类型的东西。而不是软件。对。而且你将要面对的，又是两家公司，它们的运营方式都非常出色，由非凡的创始人管理，例如某家已经在那里干了三十年。他把生命都献给了这个事业，台积电似乎也有相似的领导水平。但是我想转向这个话题，因为这引出了一个问题，为什么山姆要提出这个很大的数字呢？为什么孙正义要提出这么大的数字呢？

And I think the answer, like one of the things I want to talk about is this, which is just what is the size of the market opportunity that we're talking about here? And so I have a slide we had Jensen when he was in the Middle East, he mentioned, and the quote was, and this was just from Feb 24, he said, there's about a trillion dollars worth of installed base of data centers around the world. And over the course of the next four to five years, we'll have two trillion of data centers powering software around the world, and it will all be accelerated compute. Okay. And so I asked my team to break that down a little bit. Like what, you know, how does that look like per year, right, to get to this number? So, of course, I'm doing this from outside in, we take a swag at it, and it pulls up this next line, bar chart.

我认为答案，就像我想谈论的其中一件事情，就是这个，我们现在谈论的市场机会大小是多少？所以我有一个幻灯片，我们在中东时，杰森提到过，引用是，这是从2月24日开始的，他说，全球安装基础有约一万亿美元的数据中心。在接下来的四到五年里，我们将有价值两万亿美元的数据中心为全球软件提供动力，并且所有这些都将是加速计算。好的。所以我让我的团队简单分解一下那个。比如，每年看起来会怎么样，对吧，来达到这个数字？所以，当然，我是从外部做这个，我们粗略估算一下，然后得到这个下一个条形图。

So this is the AI data center build out. In blue is the new accelerated compute, right? In green is the replacement data center that we think will go to accelerated. And then in gray is the replacement that's non accelerated compute. So this would be more like, you know, X86. And again, I'm certain this is wrong specifically, but that's what we're in the business of doing, trying to build a forecast based upon folks who are providing this information. The line running through the center that starts at 55% and goes down to 26%. That is in video's share of that global compute build out based on current consensus numbers for Nvidia. Okay.

这是AI数据中心的扩建图。蓝色部分是新的加速计算资源，对吧？绿色部分是我们认为会转移到加速计算的替代数据中心。灰色部分是非加速计算的替代数据中心，更像是X86。我不确定具体数据是否准确，但这是我们所做的工作，根据提供这些信息的人们的预测建立起来。中间的线从55%下降到26%。这代表了基于目前Nvidia的全球计算设备扩建的共识数值中，视频所占的份额。

So the consensus forecast that has the stock at $700 a share assumes, if you believe this TAM to be accurate, assumes that their share will go from 55% today to 26% in 2028. Now, I think if you just step back and you say, okay, do we think we're going to go from a trillion to data centers to two trillion to data centers just ask that at a high level? Okay. Will you and I just spent an hour plus talking about how a 10 billion queries a day are likely to move from information retrieval, right to inference as we as humans expect to get answers rather than a card catalog. We talked about enterprises, whether they're doing their engineers in code generation or whether customer service centers or whether Tesla and full self driving or whether it's sovereigns who are taking on national security issues, you know, drone fleets or whether it's proteins and life sciences or material sciences. There isn't going to be a single industry on the planet that's not employing accelerated compute in order to solve the problems of their enterprise.

因此，根据共识预测，股票价格将达到每股700美元，这意味着如果您认为总地址维护（TAM）准确，股份将从今天的55%增长到2028年的26%。现在，我认为如果你稍微退后一步，你会问自己，我们是否认为从万亿数据中心到二万亿数据中心只是从一个更高的层面来问？好的。您和我刚刚花了一个多小时讨论每天10亿次查询从信息检索转移到推理的可能性，因为我们作为人类期望获得答案，而不是打开卡片目录。我们谈到了企业，无论是他们在自己的工程师中生成代码，还是客户服务中心，还是特斯拉和全自动驾驶，或者是承担国家安全问题的主权国家，你知道，无人机舰队，还是蛋白质和生命科学，或者材料科学。地球上没有一个行业不会利用加速计算来解决其企业的问题。

So if you said to me, with that is the backdrop a year ago, I think the big question bill was, is there going to be enough productivity gains in the world to justify this compute build out? Remember, people thought, Oh, we're pulling forward all the demand for NVIDIA. This is like dark fiber in 2000. We're going to be way over supplied. We're going to have a glut. I think the evidence on the field is that that was wrong. I think the evidence on the field is that in fact, just like we talked about on the last pod, we tend to underestimate the size of these super cycles because when you have these phase shifts, everything changes. You have positive reflexivity in the world, more begets more because it's better. Right. And so I think the bigger question when I look at this chart, what I push my team on, what I'm certain of, you know, what I the rumored pricing of H 100s to be 100s is that B 100s are going to cost even more than the H 100s. And so I say to my team, like these margins have to get competed down. Right. But the feedback and something I think that's really important is that although the B 100 is more expensive, it's so much more powerful. Right. It's like this.

因此，如果你对我说，一年前，这是背景，我认为大问题是，世界上是否会有足够的生产力提升来证明这种计算建设的必要性？记得，人们曾认为，噢，我们正在提前满足所有对英伟达的需求。这就像2000年的黑暗光纤一样。我们会过度供应。我们会有过剩的情况。我认为实地证据表明这是错误的。我认为实地证据表明，事实上，就像我们在上个片段中谈到的，我们往往低估了这些超级周期的规模，因为当你有这些阶段性转变时，一切都会改变。你有正向反应在世界上，更多带来更多，因为它是更好的。对我来说，更大的问题是当我看着这张图表时，我鼓励我的团队，我确信的是，我听说的H 100s价格是100美元，而B 100s的价格会比H 100s更高。所以我对我的团队说，这些利润率必须被竞争压低。但反馈和我认为非常重要的一点是，尽管B 100的价格更高，但它的性能更强大。就像这样。

If you had an employee bill and you were paying them $100,000 and I said, Hey, you ought to hire this other guy, he costs 200,000. You said, Well, why would I hire him if he costs 200,000? I would say he does 10x the work of the guy who you pay 100,000 to. You would pay him $200,000 in a second. Right. And I think that's why Nvidia today is getting those margins. In the future, I expect that there's going to be more competition, whether it comes from this custom chips that you're talking about, whether it's from other competitors like AMD, whether it's from, you know, new startups that from masa or Sam, etc.

如果您有一个雇员，而且您支付他们$100,000，我说，嘿，你应该雇佣这个另一个人，他要价200,000。您会说，嗯，如果他要价200,000，为什么我要雇佣他呢？我会说，他的工作量是您支付100,000的那个人的10倍。您会立即支付他$200,000。对吧。我认为这就是为什么Nvidia今天能获得这些利润率。未来，我预计会有更多的竞争，无论是来自您所谈论的定制芯片，还是来自像AMD这样的其他竞争对手，或者是来自新的创业公司，比如masa或Sam等等。

But you and I just talked about the challenge to build a fab and the challenge to design those chips is non trivial. And you know, the probabilities are somewhat low. And so it's going to take time to get time. I mean, if you're starting today, like, when would you have an impact? But one question I would have for you on this is, you know, if you're right about this, I wonder about TSMC's capacity. Right. You know, and that is a limited right. So you're looking at the chart and saying, how do we get to two trillion of replacement in new if TSMC is gated in their ability to produce these?

但是你和我刚刚谈到了建立晶圆厂的挑战以及设计那些芯片的挑战并不容易。你知道，成功的可能性相当低。所以需要时间来获得成功。我的意思是，如果你今天开始做，那么什么时候会产生影响？但是我对此有一个问题，就是如果你关于这一点是对的，我想知道台积电的产能。对，你知道，它是有限的。所以你在看图表时会想，如果台积电在生产这些芯片方面受限制，我们如何能达到两万亿的替代量？

Now, Jensen gave this number. He's intimately familiar with TSMC and their ability to produce. So I said, I think he has a sense in his head about what they can get done. I think that the other limit limiting factor we're going to run up against here pretty quick. It's not going to be capital, right? It may or may not be TSMC, but the power consumption. So even for the B 100, the data center designs, like you're talking about liquid, cooling, custom design data centers, they're going to consume massive amounts of power. And I think part of the reason you're hearing about this sovereign demand from the Middle East bill is they understand that their chief competitive advantage is low cost energy, right?

现在，詹森给出了这个数字。他对台积电及其生产能力非常熟悉。所以我说，我认为他心里有一个关于他们能做到什么的概念。我认为我们很快就会遇到的另一个限制因素不是资本，对吧？可能是台积电，也可能不是，而是功耗。所以即使对于B100，像你说的那样的数据中心设计，液冷，定制设计的数据中心，它们将消耗大量的电力。我认为你之所以听到中东地区的这种主权需求的原因之一是因为他们明白他们的主要竞争优势是低成本能源。

And I don't think they're talking about building all of this just to service the needs of their country. I think they're smart enough to understand they're trying to equitize all their petrochemical well into technology. Well, they're in the future. And if I was running one of those countries, I would look at this phase shift as an opportunity to become the supplier to the world of computer aided intelligence, right? And if they can do that because they have lower cost energy and because they can recruit the likes of Sam Altman, they can recruit the likes of TSMC to their countries to set up shop there to design chips there.

我认为他们建设所有这些并不仅仅是为了满足自己国家的需求。我觉得他们足够聪明，明白他们正试图把所有石化资源转变为科技。他们走在未来的道路上。如果我是这些国家的领导人，我会把这次转变视为成为世界计算机辅助智能供应商的机会，对吗？如果他们能做到这一点，因为他们能以更低的能源成本招募像是萨姆·奥特曼这样的人才，招募像是台积电这样的公司来他们的国家设厂制造芯片。

It's not all that different than digging wells, right? Think about digging a well, you have to spend a lot of money, a lot of time, a lot of research. You're hoping you get your payback five, 10, 15 years into the future. And so I think this is a rational decision by them to build out this capability. But to your point, it's a non-zero and non-trivial undertaking to try to get it done. Now, if they do that, it's going to put them in competition with some of the hyperscalers, right? From core weave, day, W.S. to others who are in the business of renting AI capabilities out.

这其实和挖井并没有太大的不同，对吧？想想挖井，你必须花费很多钱、很多时间、做很多研究。你希望未来五年、十年、十五年能够收回成本。所以我认为他们决定建立这种能力是理性的决定。但正如你所说，要实现这一目标是一项非零且非微不足道的任务。现在，如果他们这样做，就会与一些超大型数据中心进行竞争，对吧？比如科微、Day、W.S.等其他出租人工智能能力的公司。

But I think it's good for the world because what we want to see is a lot of competition. We want to see the price of AI compute fall over time. That's going to lead to a lot more consumption. And because of the productivity gains from the end applications, again, self-driving cars are coming up with vaccines or solving complex problems or just allowing consumers to have answers instead of 10 blue links. We need the cost to come down on all this stuff. And maybe this would be a good way to wrap. But if you bring that attitude to the table, I mean, it sounds like, and I don't want to put words in your mouth, but there's no reasonable end in sight from where you sit, like on this way.

但我认为这对世界是有益的，因为我们想要看到更多的竞争。我们希望看到人工智能计算的价格随着时间降低。这将导致更多的消费。由于最终应用程序带来的生产力收益，比如自动驾驶汽车正在研发疫苗或解决复杂问题，或者只是让消费者能够得到答案，而不是看到十个蓝色链接。我们需要各种技术的成本降低。也许这是一个很好的总结方式。但如果你持有这种态度，我是说，我不想替你说话，但从你的角度来看，这种情况不会有合理的结束，是吗？

We're at the very beginning, and it's going to go for a long time. I said last week, and I think we had a little video that went out. And I said, we are going to hit a Zona disillusionment. I don't know whether it's this quarter, maybe tomorrow within video when it starts, right? We're going to hit a Zona disillusionment where you have a mismatch between supply and demand. And then all the skeptics are going to say, I told you so, the Internet's a fad. AI's a fad. Mobile's a fad. It happens in every super cycle.

我们还处在最初阶段，而且要持续很长一段时间。我上周说过，我认为我们发布了一个小视频。我说，我们将会遇到一次“低谷失望期”。我不知道是不是在这个季度，也许明天视频开始的时候会发生，是吗？我们将会遇到“低谷失望期”，在那里供应和需求之间存在不匹配。接着所有怀疑论者都会说，我告诉过你，互联网是一种潮流，人工智能也是潮流，移动技术也是潮流。这种情况在每一次超级周期中都会发生。

We're going to use that as a buying opportunity because we are absolutely convinced that the runway is longer and wider and the impact on humanity is going to be greater because the end applications are so compelling that are using AI to assist them in everything that they do. But that's really where the tug of war is in the world today, Bill. And that's what makes a market, right? You're going to have those people who are skeptics about that demand. That's what creates a wall of worry. You know, why does NVIDIA trade it 20 to 30 times earnings, right? I would say because there's a lot of skeptics and there's a lot of worry about whether or not these free cash flow is durable into the future, right?

我们将把这视为一个购买机会，因为我们绝对相信跑道更长更宽，对人类的影响会更大，因为最终的应用将会非常引人瞩目，他们正在使用AI来帮助他们做任何事情。但这真的是当今世界的拉锯战所在，比尔。这也是市场的独特之处，对吧？你会遇到那些对需求持怀疑态度的人。这就是产生焦虑的墙壁。你知道，为什么英伟达会以20到30倍的市盈率交易呢？我会说，因为有很多怀疑论者，对未来这些自由现金流的持续性存在很多担忧，对吧？

I bet to the worry is more on pricing than volume, right? And I, by the way, and it's unknowable. Like, I don't know, nobody who follows this nose. So you have to assign some probability to that future outcome. But I think you're right. It is a good place to leave it.

我觉得担心更多的是价格而不是销量，对吧？顺便一提，这是不可知的。就像，我不知道，没有人能准确预测。所以你必须对未来的结果赋予一定的概率。但我认为你说得对。这是一个适当的结论。

I wish you could be here. I know you're, you're anchored down there in Texas, speaking of Texas fabs. But this is fun to have you here in person. Good to see you. Like old times. And, and I think we're going to be talking and debating this for as long as we're doing this pod for sure. No doubt. No doubt. Good to see you.

希望你能在这里。我知道你被锚定在德克萨斯那边，说起德克萨斯的设施。但能亲自见到你真的很开心。很高兴见到你，就像以前一样。我觉得我们会一直讨论和辩论这个话题，直到我们继续录制这个节目。毫无疑问。很高兴见到你。