The SpaceX IPO, Fable 5, AI Capex Update & Market Check w/ Gavin Baker, Andrew Fox & Clark Tang
发布时间 来源
Episode 设置
摘要
Brad Gerstner sits down with Gavin Baker and Andrew Fox of Atreides Management, alongside Altimeter partner Clark Tang, to break down one of the biggest questions in tech and markets: how should investors think about the SpaceX IPO?
They unpack the major levers behind SpaceX’s next phase: Starship rapid reusability, Starlink broadband and direct-to-cell, Elon’s emerging AI compute business, xAI’s model ambitions, the Cursor acquisition, and the long-term promise of orbital data centers. The group also debates whether SpaceX is becoming a new kind of AI hyperscaler — “Elon Web Services” — and what that means for the future of compute, cloud, and frontier intelligence.
Then they dive into the latest model race: Fable 5, Mythos, ChatGPT 5.5, long-running agents, open source vs. frontier models, Nvidia vs. ASICs, the AI CapEx boom, and why the market may still be underestimating the scale of AI demand. Enjoy another episode of BG2!
Timestamps:
(00:40) Intro — SpaceX IPO in Two Days, Mythos Launches, Taiwan Takeaways
(03:05) xAI's Google & Anthropic Deals: Highest Operating Profit Per Gigawatt
(13:28) "Elon Web Services" — Nobody Had AI Compute in the SpaceX Model
(19:08) Data Centers Are Not Commodities: First-Principles Design
(26:01) Orbital Compute Economics: $5B Per Gigawatt in Space vs. $25B on the Ground
(29:25) The Most Underrated Variable: What Cursor Does for xAI's Model
(35:05) Bull & Bear Case — Can SpaceX Really 8X Revenue in 4 Years?
(37:00) Post-IPO Drawdowns, Lock-Ups & How to Size the Position
(43:56) Fable 5, Mythos & Why Snapshot Benchmarks Are Broken
(51:00) Frontier vs. Open Source: 90% of Revenue Accrues at the Frontier
(01:04:11) $1.5T in CapEx vs. $300B in AI Revenue — Does the Math Math?
(01:18:13) The Next $1 Trillion: Three Companies, Half the Time
Produced by Edward Schmidt & Dan Shevchuk
Music by Yung Spielberg
Available on Apple, Spotify, www.bg2pod.com
Follow:
Brad Gerstner @altcap https://x.com/altcap
Gavin Baker @GavinSBaker https://x.com/GavinSBaker
Clark Tang @_clarktang https://x.com/_clarktang
BG2 Pod @bg2pod https://x.com/BG2Pod
GPT-4正在为你翻译摘要中......
中英文字稿 
我认为我们都对人工智能充满了兴趣。如果你对人工智能有兴趣，那就意味着我们需要建造比大家想象中更多的计算设施，而且这些模型将比人们预期的更有价值。结合他们的核心业务，我想不出还有哪个企业家或公司是比SpaceX更好的未来投资选择。所以，我认为对大多数机构投资者来说，SpaceX是一个必买、必持有的选择。这是一个"设定然后忘记"的投资，以便在太空和人工智能的未来都有真正的投注。
▶ 英文原文 ⏱
And I think we're all pretty AI-pilled. And if you're AI-pilled, that means we've got to build a lot more compute than the world thinks and that these models are going to be a lot more valuable than people think. You combine that with their core business, I don't know another entrepreneur or another business that's a better bet on the future, right, than SpaceX. And so I think for most institutional investors, it's a must-buy, a must-own. It's set it and forget it, right, in order to have a real bet on both the space and the AI future.
好的，我们开始吧。这是硅谷一个清晨，BG2回来了。我们正在讨论所有与科技和市场相关的话题。为此，我请到了GB，来自Atreides的Gavin Baker，他还带来了他的得力助手Andrew Fox。当然，我也邀请了我的合伙人Clark Tang来一起探讨当天的一些重大问题。比如说，我们应该如何看待SpaceX的首次公开募股？有哪些重要因素需要考虑？接下来的几年会有很大的变化。
▶ 英文原文 ⏱
All right, here we go. Early morning, Silicon Valley, BG2 is back. We're chopping it up on all things tech and markets. To do that, I have none other than GB in the house, Gavin Baker from Atreides. He's brought his main guy, Andrew Fox. And, of course, I had to draft Clark Tang into the mix, my partner, to talk about some of the big questions of the day. You know, how should we be thinking about the SpaceX IPO? You know, what are the big levers? There are big numbers out there for what's going to happen over the course of the next few years.
那么，让我们把这个话题展开讲一下，帮助大家更容易理解。Mythos 昨天上线了。我想简单谈谈在超级智能竞赛中，谁更占优势，谁处于劣势？我们现在处于什么阶段？通过 Mythos 的发布，我们学到了什么？Clark 上星期和 Jensen 一起在台湾参加了 Computex 和 GTC。那么我们的收获是什么？GPU 和内存方面发生了什么变化？瓶颈在哪里？接下来我们应该怎么做？
▶ 英文原文 ⏱
So let's break that down a bit, help simplify it for folks. Mythos launched yesterday. I want to talk a little bit about, like, who's up, who's down in the race for superintelligence? Where are we? What did we learn with the Mythos launch? And Clark was in Taiwan last week with Jensen at Computex and GTC. So what was our takeaway there? What's going on with GPUs, memory? Where are the bottlenecks? And where do we go from here?
首先，Gavin，我想请你来谈谈SpaceX的IPO。这个IPO将在两天后进行。你是一个大股东，祝贺你。我们也是股东，并且计划在IPO中购入。《华尔街日报》报道称，高盛也预测，到2028年，SpaceX的营收将达到1600亿美元。我们知道这次IPO的价格是每股135美元，总市值1.77万亿美元。当我们考虑这个IPO时，有很多重要因素和变化。
▶ 英文原文 ⏱
To start everything off, you know, maybe just kick it over to you, Gavin, talking about the SpaceX IPO. The IPO is in two days. You're a big shareholder. Congratulations. We're also a shareholder. You know, we also expect to be buying in the IPO. The Wall Street Journal is reporting. You know, the Goldman Sachs are both saying $160 billion in revenue in 2028. We know that the IPO is $135 a share, $1.77 trillion. So when we think about kind of what the big levers are, there are so many moving parts in this IPO.
没有人比你更擅长于把问题分解并简化。接下来几年你认为我们应该考虑的关键因素有哪些？当然，很高兴能在这里。谢谢你的邀请。我以为我们要把它叫BGGB，但我们可以坚持用BG2。这是你的地盘。嘿，嘿，嘿。一切都可以再讨论修正。没关系，没关系。我认为有两个重要的关键因素或者变量是大家应该关注的。
▶ 英文原文 ⏱
Nobody's better than you at just breaking it down, simplifying it. What are the key levers that we ought to be thinking about that you're thinking about over the course of the next few years? Sure. So great to be here. Thank you for having me. I thought we were going to call it BGGB, but we can stick with BG2. I'm in your house. Hey, hey, hey. All subject to revision. That's okay. That's okay. So I think there's two big levers or variables that I think people should focus on.
好的，我不会对那些变量的走向发表评论。不过你们有这个图表。你们在X平台上发布了吗？我之前发布过，然后我们还添加了一个有关XAI新交易的内容。是的。所以我的老朋友克拉克做了一个很棒的分析。他展示了XAI与谷歌在云计算方面的交易每千兆瓦所产生的营业利润比Anthropic、Meta、谷歌和OpenAI都要高。
▶ 英文原文 ⏱
And, you know, I'm not going to comment on where I think those variables go. But one is, you guys have this chart. Did you post this on X? I did before, and then we also included a new addition with XAI's new deals as well. Yeah. Yeah. So Clark, who I've known for many years, did a great analysis here. And he shows that XAI's deal with Google for cloud computing generates more operating profit per gigawatt than Anthropic, than Meta, than Google, than OpenAI.
所以，你知道，你在Altimeter的同事，她计算出Colossus 1的年经常性收入（ARR）增长率是55%。你知道，如果你能够以6%、7%、8%的利率借到钱，然后投资于一个ARR为55%的项目，虽然我不是最精明的思考者，但这数学还是非常吸引人的。因此，我认为最重要的变量之一，就是他们多快能建立地面数据中心。根据Jensen的说法，我们知道Elon比任何人都更快地建立数据中心，仅需122天。
▶ 英文原文 ⏱
And so, you know, your colleague at Altimeter, also, she calculated a 55% ARR on Colossus 1. You know, if you can borrow money at 6%, 7%, 8%, and invest in something with a 55% ARR, I'm not the most sophisticated thinker, but that math, math. Right. And so I think the most important variable, one of the most important, is how quickly they bring on terrestrial data centers. We do know from Jensen that Elon brings data centers up faster than anyone, 122 days.
速度就是成本。没错。因为你每天都要为电工和水管工支付费用，这就是成本。而且，现在他们的收费可能已经达到了史上最高水平。因此，我觉得每个人都应该自己计算一下这个问题，但这确实是个巨大的变量。是的，确实是个非常大的变量。第二件事是，我们有一个图表，现在严重过时了。这真是让人惊讶。
▶ 英文原文 ⏱
Speed is literally cost. Right. Because every day you're paying electricians and plumbers, that's cost. And they're now monetizing them at arguably the highest rate. And so I think, you know, everybody should run their own math on that, but that is a massive variable. Yes. Truly massive variable. The second thing is, you know, we have a chart, and it's wildly out of date now. It's kind of freaking amazing.
这张图表，我想，这张图表是10天前的吗？但在这大约10或12天里，自从我们制作了这个显示Opus 4.7的帕累托曲线的图表以来，Opus 4.8已面世。这个图表已经过时了。现在我们还有Fable和完全疯狂的Mythos。在短短10天里，我们需要更新这个图表两次。
▶ 英文原文 ⏱
This chart is, I think, is this chart from 10 days ago? But in like the 10 or 12 days since this chart, since we made this chart, which shows the Pareto curves for Opus 4.7 for coding, for Codex from OpenAI. And now we've had Opus 4.8. It was already out of date. And now we have Fable. Totally. And Mythos, which is freaking wild. In 10 days, like we would have had to update the chart twice.
好的，但帕累托曲线展示的是在一定成本下可以获得多少智能。我确实认为所有的收入都会逐渐集中到帕累托曲线中。至少所有前沿模型的收入都会集中到帕累托曲线中。这是用于编程的帕累托曲线。让我觉得很惊讶的是，在图表中可以看到，Composer 2 的帕累托优越性，即在最低水平的智能下，只需要很少的训练。
▶ 英文原文 ⏱
Right. But what the Pareto curve shows is how much intelligence you can get for a given amount of cost. And I do think being all revenue will accrue to the Pareto curve. All at least kind of frontier model revenue will accrue to the Pareto curve. And this is Pareto curve for coding. And what I think is so impressive is that you could see in the chart that Composer 2 was Pareto dominant, or, you know, at the lowest level of intelligence with very little training.
好的。这说明，正如你所知，你对Cursor非常熟悉，我认为你比我了解得多得多。根据我的理解，Cursor和Anthropic拥有的专有编码数据的量比其他任何人都多，他们各自的专有编码数据量甚至超过了互联网上公开的数据量。因此，Cursor使用Kimi K.25，利用自己的私有数据，进行了某种强化学习和有监督的微调，开发出了一个非常优秀的模型。然后，他们花了三个星期在Colossus 2集群中，得到了一个在12天前性能优于Composer 2.5的模型。不过，这是基于他们自己的基准测试，即Cursor bench，所以这个结果可能需要谨慎对待。
▶ 英文原文 ⏱
Right. And this just reflects, and I know you know Cursor well, and I think you know Cursor a shitload better than I do. A vast amount better than I do. But my understanding is that Cursor and Anthropic have more tokens of proprietary coding data than anyone else, and they each have more tokens of proprietary coding data than exist on the public internet. And so they fed, Cursor fed, used Kimi K.25, used their own private data, did some RL, some supervised fine tuning, and they got a really good model. And then they spent three weeks in the Colossus 2 cluster, and they got a model that 12 days ago was Pareto dominant with Composer 2.5. Now it's on their own benchmark, Cursor bench, so maybe take it with a grain of salt.
我认为这表明Cursor数据在编程中非常有价值。当它经过训练，达到类似Chinchilla Optimal甚至超过Chinchilla Optimal的水平，并结合强化学习时，我觉得这暗示着XAI和SpaceX AI在编程领域有可能成为真正的参与者。一个有趣的地方是，我们回答问题的方式中，并没有提到火箭发射、Starlink或者通信领域。直到六个月前，这些还是我们的主要业务。然后，我们合并了X.AI和Cursor，并宣布了一些交易，显然他在悄悄地建立一个类似AWS的服务。
▶ 英文原文 ⏱
But I think this just suggests that the Cursor data is very valuable for coding, and when it is trained, you know, Chinchilla Optimal or Beyond Chinchilla Optimal with reinforcement learning, you know, I think it suggests that XAI and SpaceX AI has a shot of being a real player in coding. I mean, I think one of the interesting things is, you know, we, the way you answer the question, right, we didn't talk about launch, right, we didn't talk about Starlink or communications. Those, up until really six months ago, were the business. Yeah. And, you know, and then we merged in X.AI, and we merged in Cursor, and then we announced these deals where it was very clear he was kind of building AWS right under our nose, you know, in terms of this.
但我想做的是去看看Fox。让我们来分析一下。有三大业务线，对吗？我们有通信业务，比如Starlink发射业务。然后是AI计算业务。接下来，我想回到你刚刚提到的X.AI。但如果我们只关注核心业务，我们需要假设什么才能让核心业务——包括发射和Starlink——顺利进行，以实现现有的数字？好的。当然，发射业务是所有事情的基础。这是SpaceX的“皇冠上的明珠”，尤其是可重复使用性，这是其他公司很难具备的。
▶ 英文原文 ⏱
But what I want to do is go to Fox. Give us the breakdown. Three big lines of business, right? We've got the communication Starlink launch business. We've got the, you know, AI compute business, and then I want to come back to X.AI that you were just clicking on. But if we just go to the core business, what do we have to assume goes right in the core business, both with launch and with Starlink, in order to achieve the numbers that are out there? Yeah, sure. So, look, I think the thing that's foundational to everything is the launch business. Right. Right. This is the kind of crown jewel of SpaceX. It's something that no one else really has, notably reusability. Right.
很快，可快速重复使用，对吧？我认为这是实现AI经济效益的关键，使轨道计算成为非常经济上有吸引力的事情。除了我们面临电力和芯片短缺的问题，我认为快速重复使用是我们应该关注的核心。Elon经常谈到这个话题，将火箭发射的频率提高到类似于航空业的水平。Gavin之前用过这样的比喻，旧的航天工业就像是想象一下你登上一架飞机，飞往加州，下了飞机，然后飞机爆炸了。
▶ 英文原文 ⏱
And soon, rapid reusability, right? This is, I think, what you need to believe in to get to the economics in AI that make orbital compute something that's very economically attractive. Right. Outside of the idea that we are in shortage for power, shortage for chips. Right. So, I think rapid reusability is the main thing that we're watching for and I think most people should watch for. You know, Elon talks about it a lot, but getting these rockets to fly at a cadence that's comparable to an airline, right? And Gavin has used this analogy before, but the old rocket industry was kind of like, imagine boarding a plane, flying to California, getting off the plane, the plane explodes.
所以，我认为SpaceX最终想要实现的是让星舰的两个阶段都能飞行多次，而不仅仅是助推器。在需要翻新之前，让一个星舰飞行30、40或50次。这样一来，你就可以把飞行器的成本摊到多次飞行中，这显著降低了成本。但这是个非常难解决的问题，极其困难。而且你看，我觉得这个公司已经明确表示，他们计划在今年晚些时候尝试回收星舰的第二阶段。
▶ 英文原文 ⏱
So, I think what SpaceX are ultimately trying to achieve is have a Starship fly both stages, not just the booster, 30, 40, 50 times before you have to retrofit that ship. And when you do that, you're amortizing the cost of the vehicle over many flights, right? And that's what brings the cost down significantly. But that's a really hard problem to solve. Extremely difficult. And look, I think the company, you know, have been loud and clear. They're going to attempt to bring back the second stage of Starship later this year. Right.
然后让它可以重用，你知道的，明年再利用二级火箭。从那时起，加快发射频率。然而，归根结底，降低发射成本是使所有这些业务成为可能的关键，也是让它们相较于传统企业更具吸引力的原因。那么，Starship 到目前为止发射了多少次？比如说，Starship 3 刚刚发射，有多少发射呢？大家普遍预期两三年后是什么样的呢？发射频率是多少？我们是每天发射一次吗？每周或每月发射一次吗？在预期方面，我们现在处于什么阶段呢？
▶ 英文原文 ⏱
And then make it reusable, you know, refly the second stage next year. And from there, ramp up the cadence. But at the end of the day, driving down the cost of launch is what enables all of these other businesses and is what makes them so attractive relative to incumbents. So, how many times have Starship just launched, Starship 3, you know, just launched? How many launches are, you know, do you think kind of the consensus out there is assuming, you know, two or three years from now? Like, what is the launch cadence? Are we launching one of these every day? Are we launching one of these every week or every month? Like, where are we in terms of expectations?
好的，说实话，我认为目前的预期是这样的：去年，我们大约有160到165次发射，而在接下来的几年里，这个数字会增加到几百次。再之后的三年里，发射次数可能会达到数千次。我想公司有这样的愿景：数千次发射。每天进行两到三次发射。对吧？那么，这会带来什么样的可能性呢？显然，我在硅谷，甚至在移动革命进行到二十年后的今天，我在桑希尔路上的电话都接不过来。
▶ 英文原文 ⏱
Yeah, so look, I think expectations for now, you know, we're going from, you know, call it 160, 165 launches last year, up into the high hundreds of launches in the next several years. And, you know, getting into the thousands of launches probably in the next three years thereafter. Okay. I think the company of aspirations. Thousands of launches. You're launching. You're doing two or three launches a day. Right. Right. And then talk to us a little bit. What does this enable? Obviously, you know, I'm here in Silicon Valley. I can't even keep a call on Sand Hill Road two decades into the mobile revolution.
我的意思是，这简直太疯狂了。这就像第三世界。这是个严重的商业问题，但我们在这里却感到非常紧张。这真是太疯狂了。就在星木酒店附近，完全没有信号。我在想，这怎么可能呢？这简直像个笑话。这里是美国的科技中心，却连电话都接不住。好吧，当Starlink移动网络推出时，我们都要换成它，因为我可不想在山景路上丢掉电话联系。
▶ 英文原文 ⏱
I mean, it's the craziest thing. It's like a third world. It's a major business problem when you're freaking out here. It's crazy. It's crazy. Right by the Starwood, dead zone. I'm like, how can this possibly be? It's almost like it's a joke. It's the epicenter of technology in America, and you can't maintain a call. Okay, so we're all going to switch to Starlink Mobile when it comes along because I don't want to lose that call on Sand Hill Road.
请帮我详细讲解一下，从整体上看，这是未来两到三年业务收入增长的主要部分。我猜测这很大程度上是由直销连接推动的。给我讲解一下其中的一些经济状况。是的，其实这很有趣。考虑到目前覆盖的家庭比例，宽带业务仍处于非常早期的阶段。看看使用Starlink的全球家庭比例，还不到1%，这就是宽带业务的现状。
▶ 英文原文 ⏱
So walk me through a little bit, just again, high level. It's a big portion of the revenue growth expected in the business over the course of the next two to three years. My hunch is a lot of this is driven by direct-to-sell connectivity. Walk me through a little bit of those economics. Yeah, so look, it's actually interesting. The broadband business is still very early stage when you think about the percent of households that have actually been penetrated to date. You look at the percent of global households with Starlink, it's less than 1%, and that's the broadband.
你家里、车上、船上甚至飞机上都有一个基础终端。因此，我实际上认为宽带可以扩展到数亿个终端和用户。今天的用户群体已经很庞大。如果“星舰”能够快速重用，达到数亿是可能的，但这非常困难。如果没有竞争，实现数亿用户是有可能的，但只是也许。我总是说在这里看到产品经理和分析师遇到这种情况很有趣，就像我和克拉克的情况一样。
▶ 英文原文 ⏱
You kind of have a base terminal at your house, on your car, on your boat, and in airlines now as well. So I actually think broadband can scale to hundreds of millions of terminals, hundreds of millions of users. And today, the subscriber base. Hundreds of millions if they get rapid reusability of Starship, which is really hard. You know, if there's not competition, hundreds of millions, it's possible, but maybe. I always say around here, it's funny, I love seeing PM and kind of analysts in this situation. It's exactly what I do with Clark.
克拉克会说一些话，我会说，未来是一种未知概率的分布。这种概率要么更高，要么更低，所以给我一个概率的分布。我们是在谈论20%还是30%？这很搞笑。其实就是同一个事情。好吧，也许不是100%一样。我看到埃隆做过很多困难的事情，而这真的是一个非常困难的事。所以我觉得他们在快速可重复使用方面取得成功是合理的。但是我认为重要的是要承认，像轨道计算、Starlink、Starlink V3、Starlink 直连到手机这些，我们首先需要的是飞船 V3 的可重复使用，然后快速的可重复使用才能解锁很多这些可能性。
▶ 英文原文 ⏱
Clark will say something, I'll say, the future is a distribution of unknown probabilities. It's either more likely or less likely, so give me the distribution. Are we talking 20%, 30%? It's hilarious. It's the same thing. Well, no, 100% the same thing. And, like, I've watched Elon do many hard things, and this is a really hard thing. So I think it's reasonable to think that they're going to succeed with rapid reusability. But I just think it's important to acknowledge that, like, Orbital Compute, you know, Starlink, you know, Starlink V3, Starlink Direct-to-Cell, we need first reusability for Starship V3, and then rapid reusability unlocks a lot of this.
好的。当我看到银行在《华尔街日报》上发布的模型时——都已经被广泛报道和泄露了——这些模型大多在收入方面集中在连接性上，比如说Starlink、Direct-to-Cell等。预计到2028年，这些的收入将从100亿美元增加到500亿美元。所以，我并不是要求你们给出具体的数字。而是当我和Clark交流时，我只是在评估大致的规模。我们是否认为在未来三年内可以将业务规模扩大到五倍？无论是宽带还是直面消费者的需求（TAM，总可用市场）是否足够？我的看法是，答案是肯定的。
▶ 英文原文 ⏱
Right. When I see the models that the banks are putting out there, right, in Wall Street Journal, everybody's reported on these. These things have been widely leaked. They largely have the revenue on connectivity, so let's call it Starlink, Direct-to-Cell, et cetera, going from, you know, let's call it $10 billion to $50 billion by 2028. And so I'm not asking you guys to react to, you know, to tell me your specific numbers. But when I'm talking to Clark, all I'm trying to size up is order of magnitude. Do we think we can 5X the business over the course of the next three years? Is there enough TAM, both in terms of broadband and direct-to-consumer? And I think the answer to that is yes.
好的，我简单说一下：我随身携带Starlink，因为我是个视频游戏迷。无论我在世界的哪个角落，Starlink的连接都是最好的，它既快又延迟低。我认为，一旦他们实现快速重复使用，它们的每吉字节或每兆字节的成本也会是最低的。“更好、更快、更便宜”一直是成功的公式。所以，如果想达到500亿美元的市场份额，这大概只需要全球电信市场的0.3%的占有率。或许Starlink的定价会有些下降，但我就是这样看待这个问题的。
▶ 英文原文 ⏱
Yeah, here's what I'd just say very simply, is I have, I travel with Starlink. Yes. I'm a big video gamer, and very consistently, wherever I am in the world, Starlink is the best connection. Yes. It's the fastest, it's the lowest latency, and I do think once they get to rapid reusability, it's also going to be, they're going to have the cheapest cost per gigabyte or megabyte delivered. And better, faster, cheaper has been a winning formula. And so $50 billion, that's, you know, 0.3% penetration of the global telecom market. Now, maybe there's some deflation with Starlink pricing, but that's the way I'd frame it up.
是的，我喜欢押注于"更好、更快、更便宜"。克拉克，我想说过去六周里最大的惊喜之一可能是埃隆。我们在“全员投入”播客中讨论过这个话题，我们把它称为EWS（埃隆网络服务）。他与Anthropik和谷歌达成了这些巨大的交易。我认为当时甚至没有人想到SpaceX会参与AI计算领域。几个月前的模式是关注Starlink的连接性，然后是X.AI这个模型。
▶ 英文原文 ⏱
Yeah. I like betting on better, faster, cheaper. Clark, I would say probably the biggest surprise of the last six weeks is that Elon, you know, we talked about it on All In podcast, we called it EWS, Elon Web Services, right? That he struck these huge deals with Anthropik and Google. I don't even think people were thinking about SpaceX in the AI compute game, right? If you looked at the models as of a few months ago, it was connectivity, so Starlink, and then it was X.AI, the model.
不过，这整个类别的操作是将大量计算能力集中起来，而他在这方面有独特的优势，然后以非常盈利的方式进行转售。这种做法以前并不在很多人的预期中，现在却成为了预测中的重要组成部分。你记得我们和Jensen一起做的那个播客吗？当时Jensen说，Elon是独一无二的。他们所实现的成就是前所未有的。从这个角度来看，10万个GPU，相当于当前全球最快的超级计算机。这就是一个计算集群。
▶ 英文原文 ⏱
But this whole category of taking all of this compute, which he's uniquely good at standing up, right, and then reselling it in a way that's highly profitable was not in a lot of people's forecasts. Now, it's a major component of the forecast. You know, you and I did this podcast with Jensen, where Jensen said, Elon is an N of one. What they achieved is singular, never been done before. Just to put in perspective, 100,000 GPUs, that's, you know, easily the fastest supercomputer on the planet. That's one cluster.
通常来说，建造一台超级计算机需要三年的时间来规划，然后设备会被运送过来，还需要一年的时间来让其正常运作。是的，我们现在讨论的是19天。哇，确实是独一无二的例子。Elon就是这样的一个例子。他有能力获取供应、建立供应链，并以一种对他自己和现在其他人都有效的方式部署它。所以，请带我们了解一下这个过程。在我看来，这似乎是收入故事中的一个重要组成部分。
▶ 英文原文 ⏱
A supercomputer that you would build would take, normally, three years to plan, and then they deliver the equipment, and it takes one year to get it all working. Yes. We're talking about 19 days. Wow. N of one is right. Elon is an N of one. And his ability to secure supply, stand up the supply, you know, deploy it in a way that's, you know, coherent and effective for both himself and, I guess, now for others. So, walk us through kind of that. It looks to me, again, like this is a major component of the revenue story.
当然。我是说，我们之前都在MacroHard数据中心，明显能感受到建设这些地点所投入的工程技术。大家总是谈论谷歌如何制造TPU并将其出售给Anthropik以为AI创造收入。我认为这里的情况与此类似，埃隆能够迅速获取资源，快速建造这些站点，并且现在可以通过这些站点在即将到来的庞大AI市场中获利。你看看他与许多供应商建立的关系，比如与Jensen，以及那些希望XAI成为租户的不同站点，他能够以比其他很多同行更具吸引力的融资条件来达成这些交易，这些优势会随着时间的推移不断增加。
▶ 英文原文 ⏱
Totally. I mean, so, we were all at the MacroHard data center, and it was just very evident the amount of engineering that had gone into building these sites. You know, people always talk about Google and their ability to build a TPU and sell the TPU to Anthropik to generate revenues for AI. I think it's a pretty similar dynamic here with Elon able to secure power, build these sites faster than anyone else, and also be able now to monetize it to this massive AI market that's ahead of us. If you look at the relationships that he's forged with a lot of his suppliers, you know, be it Jensen, be it, you know, all of these different sites that actually want XAI as a tenant, his ability to finance these deals at very attractive financing rates relative to a lot of the other players in the space, you know, these are advantages that compound over time.
当你有足够的信誉来建立这些网站并在这些水平上实现盈利时，这对很多相关人员来说实际上是一个非常有吸引力的选择。实际上，如果你特别去看这些交易，正如Gavin你指出的，实际上，他们通过出售这些基础设施的盈利能力可能比其他行业参与者更强。显然，谷歌为此向SpaceX支付了巨额溢价。Fox，你提到了一点我认为非常重要，那就是，为了获得太空计算的优先权（谷歌肯定想要的），他们可能愿意为地面计算支付更高的价格。
▶ 英文原文 ⏱
And when you've built the credibility to stand up these sites and monetize at these levels, you know, it's actually a very attractive proposition for a lot of folks involved. And actually, you know, if you look at these deals in particular, Gavin, you pointed out, but, you know, they're actually monetizing, you know, perhaps better than other players in the space by selling this infrastructure. A lot higher Google is obviously paying SpaceX a huge premium for this compute. Fox, you said something that I thought was really important, which is, you know, it may very well be that in order to get, you know, first in line on space compute, which Google certainly wants to do, that they're willing to pay a premium for their terrestrial compute.
在我看来，这就是为什么会有溢价的一种解释，你有什么想法吗？是的，我认为其中确实包含了一些这样的因素。然而，归根结底，SpaceX能够快速建立起计算能力。他们能高效地在一个地方建立起大量的计算资源并且保持随时可用。所以，我认为这就是大部分溢价的来源。但是除此之外，显然未来人们会越来越多地进入太空，为了优先拿到这个机会，支付一点像期权费的额外费用也是合理的。我们一直在投资新兴云计算领域，因此桌上的每个人都基本上相信，我们缺乏继续推动智能前沿所需的计算能力。
▶ 英文原文 ⏱
And so to me, that's how you kind of square the circle as to why the premium, any thoughts? Yeah, look, I think there's some of that embedded there. But look, at the end of the day, SpaceX can stand up compute quickly. They can stand it up coherently and they can stand up a lot of it in one place and have it readily available. So look, I think that's most of the premium. But outside of that, certainly people are going to space over time. So pay a little call option to get first in line for space. We've all been investing in the neocloud space, so like there's a fundamental belief around this table that we lack the compute needed to continue to push the frontier on intelligence.
所以我们需要建设大量的计算能力。现在，市场上有竞争。在一方面，有那些正在扩展这种能力的大型云服务提供商。然后，还有专注于人工智能的云服务也在扩展这种能力。现在，事实上在几周内，这个领域中出现了一位巨头，它就是SpaceX。Gavin，我的问题是，他们能整合这个市场吗？因为如果我考虑一个市场，Elon有独特的能力去获取供应。他在交易方面也有独特的能力，而没有人能像他那样快速建立起一切。所以，我认为在人工智能计算市场上可能会出现一次真正的整合，一边是大型云服务提供商。
▶ 英文原文 ⏱
So we have to build a lot of compute. Okay, now there's a competition going on. On one end, you have the hyperscalers who are building out that capability. Then we have AI dedicated clouds that are building out that capability. And now literally in a matter of weeks, right, we have a, you know, a giant that's emerged in this category, which is SpaceX. The question to you, Gavin, is can they consolidate this market, right? Because if I think about a marketplace, Elon has a unique ability to get the supply. He has a unique ability to cut deals on the other side and nobody can stand it up like he can stand it up. So I think there might be a real consolidation in the AI compute market where you have the hyperscalers on the one hand.
另一方面，你知道，他可能会成为AI计算市场中最大、最强的玩家。是的，我想他们现在是在谷歌交易后，排名第四还是第五的超大规模计算公司？应该是第四吧。真是让人惊讶。在短短30天内，我们从不是AI超大规模计算公司到成为第四名。我们超过了很多公司，包括甲骨文。CoreWeave是一家庞大的企业，对吧？我们是他们的投资者，而且一直以来都是。但还有许多其他玩家，比如Nebiuses、Irons这样的公司。我想在硅谷现在可能有大约50家Neolabs正在被资助，因为计算资源的短缺。
▶ 英文原文 ⏱
And on the other hand, you know, he may emerge as the largest, strongest player in the AI compute market. Yeah, so I think they are, are they the number four or number five hyperscaler today after the Google deal? It will be number four. Kind of wild. Yeah. In 30 days, we went from not being an AI hyperscaler to being number four. And we passed a lot of companies, including Oracle. CoreWeave is a huge business, right? We're investors in, you know, and have been investors in, right? But there are a lot of other players, the Nebiuses of the world, the Irons of the world. And I would say that there are probably 50 Neolabs being funded in Silicon Valley right now, as we speak, because of the shortage in compute.
当然。在30天内完成这样的事情真是不可思议。我要说的是，有人认为这些数据中心只是普通商品。我并不同意这个观点，而且我认为在座的各位也不会同意。同样的，Elon（马斯克）能够从第一性原理重新设计火箭并使其可重复使用，他也是从第一性原理设计了一辆电动车。其他人在尝试将电动车做得像一辆内燃机车，而他从不同的角度思考。我认为，他从第一性原理的角度重新审视数据中心的设计，并设计出了与众不同的东西。
▶ 英文原文 ⏱
Absolutely. So that's kind of crazy in 30 days. That's just extraordinary. What I would say is that I think there is a belief that these data centers are commodities. And I do not share that belief. I don't think anybody around this table shares that belief. And in the same way that Elon was able to re-engineer a rocket from first principles and make it reusable, he engineered an electric car from first principles. You know, everyone else was trying to, you know, make an electric car like an internal combustion engine car. And he thought about it differently. And I think he looked at data center design from first principles, and he designed something fundamentally different.
我确实和团队交流过。我说，嘿，大家，或许关于一些对于你们而言显而易见的数据中心设计的事情，可以低调一些，因为这些对别人来说可能是新的发现。我觉得你们的做法比你们意识到的更具差异化，因为对于你们来说很合乎逻辑的事情，对其他人可能未必如此。而这就是他能够在122天内做到这些的原因。
▶ 英文原文 ⏱
And I did actually ask the team. I said, hey, guys, maybe it'd be a little less public about things that are very obvious to you about how to design a data center, but are revelations to other people. Because I think what you're doing is maybe more differentiated than you perhaps realize, because what you're doing is so logical to you, but maybe not logical to everyone else. And that's how he was able to do it in 122 days. Yeah.
我的意思是，布拉德，昨天我们与我们投资组合中的一家公司会面，我们在讨论“表后”工作。我们真的在认真考虑这件事。现在，可能只有两三家公司能够可靠地设计和建造“表后”数据中心。你知道，这一切都涉及到真正的工程技术工作。
▶ 英文原文 ⏱
I mean, to that point, Brad, yesterday we were meeting one of our portfolio companies, and we were talking about behind the meter, and we're, you know, really thinking about it. There's only maybe two or three players now that can actually reliably engineer behind the meter data center. And, you know, there's real engineering work that goes into all of this.
所以，如果你考虑一下这个问题，如果你是一个燃气燃烧公司，比如说Vernova，并且你说，我们的燃气燃烧发动机数量有限，现在我们可以把它们卖给X.AI，或者卖给这些新兴的Neo Clouds创业公司。你会选择卖给谁呢？还有另一个动态，当GPU加速销售时，每个人都开始赚更多的钱。
▶ 英文原文 ⏱
So if you think about this, if you're a gas combustion, if you're Vernova, and you say, we only have a certain number of gas combustion engines, now we can sell them to X.AI, or we can sell them to one of these startup Neo Clouds. Who are you going to sell them to? Well, and there's another dynamic. Like, everyone starts making more money when the GPUs get energized and sold faster.
所以，从字面上看，速度就是所有供应商的金钱，比如电力、土地和涡轮机。因此，我认为这是，我们会看到的。嘿，布拉德，伙计。但我们现在只是在谈论地球上的事情。地球上的事情。我确实想谈谈这一点，然后你可以再抛回给我。跟我说说，好吧，假设他们继续扩展地面基础设施，并继续为这些找到买家。
▶ 英文原文 ⏱
So literally, speed is money for all of the suppliers. Like, power, land, turbines. So I think it's, we'll see. Hey, Brad, man. But this is just, we're just talking terrestrial. Terrestrial. I do want to hit on, and then you can flip it back on me. Talk to me, okay, so let's assume, right, that they continue to build out the terrestrial landscape. They continue to find buyers for that.
请给我们讲解一下，这会带来什么样的突破，以及它与空间数据中心有何关联。因为我认为，一旦我们开始讨论万亿级容量及其以上的规模，也就是说上千个G，对吗？而今年我们只在做25或30个G，是这样来衡量的，对吧？是的，20或25个G。那么，我们一旦开始扩展规模，请告诉我们，是否需要空间数据中心来激发我们对购买IPO的兴趣呢？
▶ 英文原文 ⏱
Walk us through, you know, what this unlocks, you know, and how this is related to space data centers. Because I think, you know, once you start talking terafab capacity and beyond, so we're talking 1,000 gigs, right? And this year, what, we're doing 25 or 30 gigs, just to put it all in perspective? Yeah. Right? 20, 25 gigs. Okay, so once we start scaling up, walk us through, do we have to have space data centers in order to get excited about buying the IPO, right?
当然，世界上有一些争论。我听到杰夫·贝佐斯说，我觉得更可能是六年，但埃隆会说三年，因为如果他说六年，那可能会拖得更久。所以说三年，我们可能在四五年内实现。但是，你们认为太空数据中心对于IPO是否至关重要？你们认为实现这些的时间表是怎样的？
▶ 英文原文 ⏱
And then there's obviously this debate in the world. I heard Jeff Bezos say, you know, I think it's more like six years, but Elon's going to say three, because if he says six, then it will take even longer. So say three, and we may get it in four or five. But are space data centers integral and essential to, you know, the IPO, and what do you think the timeline is to either of you guys?
所以我认为，如果考虑那些与光标有关的变量可能对可解释人工智能（XAI）意味着什么。这方面我们已经有了一个存在的证明，一旦你真正到达帕累托前沿，收入就可以迅速增长，这就是Anthropic。此外，似乎对编程有很大的需求。
▶ 英文原文 ⏱
So I don't think, I think if you think about those variables around what cursor could mean for XAI. And we do have an existence proof that once you really get on that Pareto frontier, revenue can scale rapidly, and it's called anthropic. And there does seem to be an exhaust, there seems to be a lot of demand for coding.
我确实认为Amjad Massad发布了一些非常有趣的东西。他是Replit的创始人。他提出了一个观点，称为“苦涩教训邻近”，认为编程可能是通往AGI（通用人工智能）和ASI（超人工智能）最快的途径。因为如果你精通编程，那么你可以写代码让模型做任何事情。所以我觉得这是一个非常深刻的观点，我认为编程将继续非常重要。
▶ 英文原文 ⏱
And I do think Amjad Massad posted something very interesting. The founder of Replit. The founder of Replit. He called it bitter lesson adjacent, that coding may be the fastest path to AGI and ASI. Because if you're really good at coding, you can write code, if a model's good at coding, to do anything. So I think that's a profound point, and I think coding is going to continue to be very important.
所以，我认为，如果你考虑到那个变量，考虑到由Starlink V3支持的Starlink直连移动服务，并思考他们能多快引入陆地计算能力，我认为轨道计算对于IPO估值并不是必须的。但无疑，这是一个重要的因素。另一种说法也许是，你可能会认为我们实现人工智能自我（ASI）的速度会比实现轨道计算的速度更快。
▶ 英文原文 ⏱
So I think if you think about that variable, if you think about Starlink Direct-to-Cell, enabled by Starlink V3, and you think about how quickly they can or cannot bring on terrestrial compute, I don't think orbital compute is necessary for the IPO valuation. But it's certainly important, and it's. Well, maybe another way to say it is you may think we're going to get to ASI faster than we're going to get to orbital compute.
这可能会让我们的智商从300提升到400、500，甚至更高，并有能力将其规模扩大到达到全球GDP的10%。但也许我们应该转向下一个目标。不，不，我认为在轨道计算方面，Foxy会很出色，Art Clark可以很好地从基本原理上进行数学分析。Clark有一个很棒的图表，展示了它耗费的千兆瓦数以及每千兆瓦的成本。
▶ 英文原文 ⏱
That may take us from 300 IQ to 400 IQ, 500 IQ, and beyond, and the ability to scale it up to consume 10% of global GDP. But maybe that's where we should move next. No, no, I think on orbital compute, I think Foxy would be great, Art Clark, to lay out the math for first principles on, you know, Clark has this great chart on, you know, the gigawatts it costs, you know, the dollars per gigawatt.
好的。让我们来谈谈经济方面的理由。是的。关于是否需要围绕“轨道”进行投资的问题，我认为不需要。首先，我要说的是，根据当前对人工智能业务的预期，隐含的货币化率是多少？我记得你提到过一个传闻中的数字，人们在讨论1600亿美元这个数额。
▶ 英文原文 ⏱
Great. And walk us through the economic case. Yeah. Yeah, so, I mean, on this point of, is orbital key to investing here, I don't think it is. And the first point I'll make is, what are the implied monetization rates based on expectations today for the AI business? You know, I think you threw out the $160 billion number that's been leaked out there that people are talking about.
这句话的大意是：“根据这个数字推测，AI业务的隐含变现率大约是每吉瓦每年140亿美元。他们刚刚和Anthropic签署了一份22到23的协议，刚刚和谷歌签了50。所以，我认为你可以在地球上的AI业务上投资，并且对其前景感到兴奋。但对于Orbital（轨道项目）来说也是如此。”
▶ 英文原文 ⏱
The implied monetization rate on that number is something like $14 billion per gigawatt per year for the AI business. They just signed Anthropic at 22 to 23. They just signed Google at 50. Right. Right. So, I think you can invest behind the AI business terrestrially and still be excited about it. But with Orbital.
我认为这是一个重要的点。如果他们能获得土地和电力，我会感到很兴奋。不过，我的意思是，对于大多数投资者来说，他们更容易理解SpaceX如何在地球上取得成功。比如，他们能否获得土地、电力和芯片？对此的答案是，很有可能，可以的。而且，我们所说的是，以他们目前的盈利速度，就能达到外界传言的那些数字。这还没算上他们可能在轨道数据中心方面的进一步领先。如果可以的话，也带我们了解一下这方面的情况。
▶ 英文原文 ⏱
I think it's an important point. Excited about it if they can get the land and the power. Right. But, I mean, I think for most investors, right, they have an easier time getting their head around how SpaceX wins terrestrially. Like, can they go get land, power, and chips? The answer to that is high probability, yes. Yeah. Okay. And what we're saying is, at the rate they're monetizing that, that gets you to the numbers that are being leaked out there. Before you even have to take the leap of faith that they're going to extend the lead with Orbital data centers. But take us there on that, too.
好的，看，当谈到轨道技术（Orbital）时，我认为关键在于两级可重复使用。对，而且要实现快速的两级可重复使用。现在，Starship已经展示了他们能够成功地回收助推器。至于第二级，我们要看看今年晚些时候会发生什么。我认为他们正试图将第一级带回来，然后在明年实现其可重复使用。但当谈到轨道计算在经济层面的影响时，两级可重复使用的关键之处在于每公斤的成本大幅下降。我们这里谈论的是从Falcon火箭的每公斤约1500美元降低到250美元，甚至更低。
▶ 英文原文 ⏱
Yeah, so, look, with Orbital, I think the key thing is two-stage reusability. Yeah. And beyond that, rapid two-stage reusability. Yeah. So, today with Starship, they've shown that they can successfully re-land the booster. Mm-hmm. The second stage, we'll see what happens later this year. I think they're attempting to bring that back and then make it reusable by next year. But the thing that's important about two-stage reusability when it comes to the economics for Orbital compute, right, is the cost per kg comes down significantly. We're talking about going from $1,500 per kg on Falcon, somewhere in that range, to $250 per kg, something lower.
当你能够重复使用火箭的次数越多，价格就越低。因为你只是分摊了发射的成本。最终，你会趋近于燃料的成本假如你可以无限期地使用一枚火箭，当然，这需要很长时间才能真正做到。但到了那时候，我们讨论的价格会远低于每公斤250美元。然后你看看这些人工智能卫星的规格。你知道的，Elon做得非常棒。他前几天阐述的那个计划真是令人难以置信，因为我认为他们终于向人们展示了如何可行地设计这些卫星、卫星的重量是多少、以及一枚飞船的发射中能够装多少颗卫星。
▶ 英文原文 ⏱
And the more that you can reuse the rocket, the more that price comes down. Right. Because you're just depreciating the cost of the launch. And eventually, you asymptote to the cost of the fuel. Right. Right. Assuming you can use a rocket for forever. Yes. Right, which will take a very long time for us to really achieve that. But, and at that point, we're talking about something well south of $250 per kg. So, then you look at the specs of these AI satellites. You know, Elon did a great. Yeah, that pod was incredible that he laid out the other day, the specs on the satellites. It was really great because I think they are finally showing people, here's how you could viably design one of these satellites, and how heavy is the satellite, how many could you fit into a starship launch.
当你分析这些数字时，你会发现每次星舰发射大约能提供5兆瓦的容量。对吧？每艘星舰可以承载100公吨。因此，你可以计算出将这些卫星发射到太空中每吉瓦的成本。了解吧。将这种计算能力送入太空。而你算出的结果还未考虑诸如不合格的GPU和故障卫星等因素，这些都是会发生的事情，但得出的数学结果是，每在太空中放置一吉瓦的资本支出约为50亿美元。相比之下，在地面上，考虑到开关设备、发电机、变压器、外壳以及获得电力的成本，如今每吉瓦的资本支出约为200到250亿美元。
▶ 英文原文 ⏱
And when you back into the numbers, you get to something like 5 megawatts of capacity per starship launch. Right. There's 100 metric tons in one of those starships. So, you can back into the math of how much will it cost per gigawatt to launch these satellites into space. Right. Launch this compute into space. And the math that you get to, before you account for things like bad GPUs, bad satellites, right, these will all be things that happen, but the math you get to is it's about $5 billion per gigawatt of CapEx to put these in space. Right. For comparison, terrestrially, talk about the switch gears, the generators, the transformers, the shell, getting the power, that today is about $20 to $25 billion per gigawatt.
所以，我们在讨论的是，将数据中心的部分材料成本降低到原来的五分之一，这可是个很大的数字。简单来说，今天要在地面上建设一个千兆瓦的数据中心需要花费600亿美元。我们可以这样分开看：大约350亿美元用于购买处理训练和推理的GPU和硅芯片。而250亿美元则用于土地、主体结构、电力和冷却系统。我假设这些元素可能会因为通货膨胀而上涨。所以这250亿美元的部分可能不会下降。因为在宇宙当中，空间、电力和冷却基本上是免费的。这里我提到的“空间”是指土地。是的。
▶ 英文原文 ⏱
So, we're talking about a 5x reduction in cost on half of your bill of materials for the data center, which is a huge number. Just very simply, I mean, just to say, it costs $60 billion to put a gigawatt on the ground today. And we'll call it 35 of that is, are the GPUs and the silicon that's doing the training and the inference. And $25 billion is the land, the shell, the power, and the cooling. I would hypothesize that those elements are probably going to be inflationary. So, that $25 billion may not go down. And because space, power, cooling are effectively free in space. And when I say space, I mean land. Yes.
在太空中没有陆地，但太空里有空间，而且有很多空间。在太空中投入30亿美元建造一个千兆瓦的系统，运营成本可能更低。最初的600亿美元可能导致通货膨胀，但后来的30亿到可能会随着时间的推移而具有通货紧缩效应。不过我们需要考虑的是系统的可靠性和维护问题。只要大家都能算清楚账，只要这些卫星在太空中没出现大量故障，这笔账是可以算得过来的。此外，我们也知道GPU会过热融化，激光器会失效，特别是在数据中心进行大型训练时，这种情况时有发生。
▶ 英文原文 ⏱
There's no land in space, but there is space in space. But there's a lot of space. There's a lot of space in space. You're talking about putting a gigawatt into space for $30 billion and having lower operating costs. Now, the first $60 billion that's inflationary, and that $30 billion, that $5 billion, maybe deflationary over time. But what we need to consider is, you know, the reliability and the maintenance. And so, as long as, you know, everybody can do the math, but as long as these satellites in space aren't failing at an astronomical rate, the math, maths, and by the way, we know GPUs melt and lasers fail, we know this happens in data centers, particularly during big training runs.
是的，我的意思是，GPU会过热。因此，只要可靠性和维护成本不大幅下降，一旦我们实现了Starship V3的可重复使用和快速可重复使用，数学上的计算就是成立的。看看这件事，我们之前讨论过Starlink，我们说，很明显，我们会在Starlink上实现直接连接到手机的功能，这些假设似乎都是可以理解的。然后，当谈到建立地面数据中心时，基于这些交易，可以很容易想到，Elon会创建一个更大的，或者说Starlink或SpaceX会在这一领域建立一个更大的业务。
▶ 英文原文 ⏱
Yeah, I mean, GPUs melt. So as long as the reliability and maintenance is not dramatically lower, the math is there once we have reusability and then rapid reusability for Starship V3. When you look at this, okay, so we went through Starlink and we said, okay, like, it just stands to reason we're going to have direct to sell on Starlink, like the assumptions there are, you know, again, seem like you can get your head around. Then when it comes to building terrestrial data centers, again, not a hard one to think that based on these couple of deals that Elon's going to build a much bigger, Starlink's going to build, or SpaceX is going to build a much bigger business there.
然后，你还有这个关于空间的期权，可以进一步降低价格。有一件事我们还没讨论，那就是他们的模型，对吧？让我感到惊讶的是，六个月前，X.AI 在竞争，他们表现得相当不错，但在过去几个月里，他们做了一件非常重大的事情，就是收购了 Cursor。Cursor 拥有七八百人，从收入的角度来看已经做得非常出色。根据我们自己的预测，他们今年的收入可能高达 100 亿美元，所以他们增长得非常快，是领先的编码代理之一。但他们还有一个了不起的团队，具备真正构建前沿模型的潜力。然而，他们受制于计算能力的限制。于是，突然之间，他们被 X 收购。X 具备巨大的计算能力，现在他们可以用来训练模型。
▶ 英文原文 ⏱
And then you have this call option on space that would drop the price even further. The one thing we haven't talked about is their model, right? And I find this surprising, right? Six months ago, X.AI was competing, they were doing pretty well, but they've done something dramatic over the course of the past couple months, which is they bought Cursor, right? Cursor is 700, 800 people, was already doing incredibly well from a revenue perspective. Our own projections were that they could exit this year at up to $10 billion of revenue. So they were growing very fast, one of the leading coding agents. But they also had this incredible team with the potential, right, to really build a frontier level model. But they were compute constrained. So all of a sudden, they get bought by X. X has massive compute that they can now train on.
当我想到人工智能领域的收入时，如果我查看模型中的这一项，从100亿美元增长到1500亿美元，是的，其中很大一部分将会来自他们核心的编织类业务。但是问题是，其中有多少会是由Cursor团队打造的新团队真正推动的核心X.AI业务？关于这个问题，你有什么想法吗，Kevin？目前，Composer 2.5在12天前表现优异，它是在Kimi K2.5基础模型上训练的。现在，GROC 4.3的1.5万亿参数模型正在进行训练。根据规模定律，可以假设这可能是一个更好的基础模型。而且，Cursor的数据不仅仅在强化学习中被使用，还被注入到预训练过程中。
▶ 英文原文 ⏱
And when I think about the revenue in AI, if I look at that line item in the models, having it go from $10 billion to $150 billion, yes, a lot of that will be the core weave type business that they have. But the question is, how much of that is going to be the core X.AI business that's really powered by the new team from Cursor? So any thoughts on that, Kevin? Right now, so Composer 2.5 was Pareto dominant 12 days ago. It was trained on the Kimi K2.5 base model. Now, what's happening is the GROC 4.3, 1.5 trillion parameter model is training. One would hypothesize, based on scaling laws, that that might be a better base model. And then the cursor data is being injected into the pre-training process, not just reinforcement learning.
我们拭目以待。我认为这将是一个非常重要的数据点，一旦发布，我觉得每个人都应该记住，一旦你在那个帕累托曲线的多个位置上。如果你有计算能力，就可以快速扩展。对我来说，如果要说这故事中被忽视的部分，那就是这一点。大家很容易对与Anthropic的交易感到兴奋，因为这些是可以直观感受到的东西。大家知道这些交易能带来多少收入。我也看到关于90天终止权、这些交易能持续多久以及应该给这些收入多少估值的讨论。
▶ 英文原文 ⏱
And we'll see. And I think that is going to be a very important data point when that comes out. And I just think everyone should keep in mind that once you are at multiple places on that Pareto curve. If you have compute, you can scale really rapidly. You know, that to me is, if I had to say what the one piece that's being lost in the story, right? Like, it's easy for everybody to get excited about the deals with Anthropic because you can put your hands around that. You know how much revenue it is. I see debate about, you know, the 90-day termination and how long they'll last and what multiple do you put on those revenues.
但我认为人们忽略了一点，那就是他们在构建前沿模型方面的能力有了显著提升。硅谷以外的人可能不太了解，你知道，Michael 和 Cursor 的团队。这是他刚刚带到 SpaceX 的一个杰出团队。SpaceX 本来就已经在构建优秀的模型。而且他们有一种变现计算能力的方法，可以让你选择把所有计算能力收回内部，用于训练模型和运行模型。我怀疑，如果有意外的优势惊喜，如果我们一圈讨论下来，我会说这里是最不被关注的地方，却可能带来最大的意外惊喜。
▶ 英文原文 ⏱
But I think the thing that's getting lost is I think they've dramatically advanced their capability when it comes to building a frontier model. People outside Silicon Valley may not know, you know, Michael and the team at Cursor as well. This is an extraordinary team that he just downloaded, right, into SpaceX. SpaceX was already building good models. And what they have is they have this way to monetize compute that gives you this call option that you can pull all that compute in-house, right, to train a model and then to run the model. I suspect if there's an upside surprise, if we went around the table, I'd say this is the place that's getting the least amount of attention and could have the biggest upside surprise.
克拉克，你有没有什么想法，觉得目前对这个业务有哪些被忽视或者误解的地方？我想说，过去几周证明了埃隆和他们的团队能够部署如此多的计算能力。其实，如果你回到一年前半，他们在计算能力的竞赛中是落后的。他们没有那么多的H100，后来引入了Colossus，然后又在更大规模上引入了Colossus II。现在，我们准备进入Verirubin阶段，根据我很多次的对话，看来他们可能已经确保了Verirubin容量的20%，特别是在早期这些芯片非常稀缺的时候，他们会在这一切上占得先机，因为大家认为他们能更好地部署这些计算能力。
▶ 英文原文 ⏱
Any thoughts, Clark, on what you think is being overlooked or areas that you think are misunderstood about the business today? I would say what the last few weeks have proven is that Elon, their team can stand up all this compute. Actually, if you just, you know, went back one and a half years, you know, they were behind in the race to stand up compute. They were, you know, they didn't have that many H100s, they brought in Colossus, then they brought in Colossus II at a scale much larger than anyone else. And now, you know, as we gear for Verirubin, you know, from, you know, a lot of my conversations, it looks like they've, you know, secured maybe up to 20% of Verirubin capacity, especially in the early days of, you know, when, you know, these chips are very scarce, that they're going to have a lead on all of this because, you know, people think that they can stand up this compute better.
我认为，过去几周实际上表明，埃隆会尝试挑战行业前沿。但是，如果出于某种原因，他们采购了超出需求的容量，这一稀缺资产仍然能够以同类最佳的利润率和回报周期实现盈利。讽刺的是，我们都干这行够久了，知道这也是贝索斯建立AWS的原因。他当初不得不为黑色星期五建立额外的服务器容量，但在一年中的其他时间，这些容量基本上是闲置的。后来，他找到了一种非常出色的方式来盈利。顺便说一句，当时在2009年和2010年，当贝索斯在扩展AWS的能力时，投资者其实不太看好，因为这会消耗大量的自由现金流。
▶ 英文原文 ⏱
So I think they'll, you know, what the last few weeks have actually shown is that Elon, you know, Elon will take, you know, take a shot at hitting the frontier. But if it, you know, if for whatever reason, they, they have over-procured some capacity, this is a very scarce asset that they have shown that they can monetize at actually, you know, best in class margins and payback periods. I mean, the irony is like, you know, you and I've been doing this long enough to know, I mean, that's why Bezos built AWS, right? He had to build capacity for Black Friday. Yeah. Right. But then the rest of the year, he sat on all this capacity that he had to build and he figured out a really incredible way to monetize this. And by the way, investors at the time, 2009, 2010, when he was building out the capability around AWS, hated it because he was consuming all that free cash flow.
与此同时，他正在挖掘世界历史上最大的金矿之一。对，在最大的里算一个。在其中之一。在那个时候可能是最大的。是的，谷歌搜索可能会对此有话要说。顺便说一下，我确实觉得这件事很重要。Grok 4.3，我认为如果他们获得了光标（cursor），那可能会变得非常重要。而Grok 4.3 当时处于帕累托前沿，不到10到12天前，它还是世界上最智能的5000亿参数模型。这些变化很快，有四家公司处于前沿：XAI、SpaceX AI、Google的Gemini 3.1 Pro。剩下的领域主要由Anthropic和OpenAI主导。但是他们当时在帕累托前沿，我们现在将看看他们如何利用光标。
▶ 英文原文 ⏱
Meanwhile, he was digging the biggest gold mine in the history of the world. Right. One of the biggest. One of the biggest. Among them. Among them. At the time was probably the biggest. Yeah. Google search might want to have a discussion. By the way, I do think it is important. Grok 4.3. I think the cursor, if they acquire it, that may end up being very important. But Grok 4.3 was on the Pareto frontier and as of 10 or 12 days ago, and these things move fast, most intelligent 500 billion parameter model in the world. And they were on the frontier and there are four companies on the frontier, XAI, SpaceX AI, Google, one with Gemini 3.1 Pro. And then the rest of it was dominated by Anthropic and OpenAI. But they were on the Pareto frontier and now we'll see what they do with the cursor.
好的，我稍后再回到这个话题。顺便说一下，我想问你几个问题。好，来吧，你觉得怎么样？你认为有潜力的最大增长空间来源于模型吗？对的。你怎么看呢？我觉得这是人们最少讨论的方面。所以，当我看这家公司的IPO时的乐观和悲观情况时，悲观的人会看去年的收入，比如说是180亿美元。他们再看银行预测三年后的收入会是1600亿美元，他们会说，历史上很少有公司在三四年间将收入提高到八倍。所以，我觉得这是让人们对估值感到紧张的地方。
▶ 英文原文 ⏱
Yeah. I want to come back to that in a second. By the way, man. I want to ask you some questions. Okay, go, go, go. What do you think? So you think the biggest source of potential upside is the model? Yes. What do you think? I think that's the thing that's least talked about. Least talked about. And so, listen, when I look at the bull bear case on the IPO, right? The bears are looking at last year's revenue. Say it was $18 billion. And they're looking at the forecast from the banks of $160 billion, you know, three years from now. And they're saying, listen, not many companies in the history of the world have basically 8X their revenue over three to four years. Right? So that's where, you know, I think people get nervous about the valuation.
当我再次以分析师的身份，从基本原则出发，把每个部分分解开来看的时候，对吧？当你看Starlink的时候，这一切看起来是完全可行的。当我看到他们在地面上构建的AI计算，未来三年内也显得非常可行。当我看到他们在收购Cursor后的模型，结合他们拥有的计算能力，似乎可能带来意想不到的惊喜。所以，我想说，在IPO的时候，大家可能会觉得有风险，但我认为，当你回过头来看三年后的今天，大多数人会感叹，这一切原来如此显而易见，即使现在所有这些事情都伴随着风险。
▶ 英文原文 ⏱
When I look at this, again, when you break it down as an analyst, first principles, part by part, which is what I tried to do here. Right? When you look at Starlink, it looks totally doable. When I look at what they're building in AI compute terrestrially, looks totally doable over the course of the next three years. When I look at the model itself after the acquisition of Cursor, you know, combining those things around the compute they have, that looks to me like it could be an upside surprise. So I would say that I think that, you know, in the IPO, but I think when you look back three years from now, there's a decent chance that everybody's like, oh my God, that was super obvious. Right? Even though today, all of these things have risk associated.
回到我们最初开始的地方。我们中没有人是为了用1.77万亿的IPO来炒作。这只是作为我们公司内的分析，对其进行拆解，然后问一下：未来可能性的分布是什么？从现在开始，变得更高的概率是什么？我认为我们都被人工智能深深影响了。如果你被人工智能影响，那就意味着我们必须建立比世界想象中多得多的计算能力，并且这些模型会比人们预期的更有价值。再加上他们的核心业务，我认为没有其他企业家或企业比SpaceX更值得寄予厚望，不是吗？
▶ 英文原文 ⏱
Back to where we started. None of us are here to pump the IPO at 1.77 trillion. It's really to just break it down as we do inside our shop and to say, what is that distribution of future probabilities? What's the probability that is higher from here? And I think we're all pretty AI-pilled. And if you're AI-pilled, that means we've got to build a lot more compute than the world thinks and that these models are going to be a lot more valuable than people think. You combine that with their core business, I don't know another entrepreneur or another business that's a better bet on the future, right, than SpaceX.
因此，我认为对于大多数机构投资者来说，这是一个必须购买、必须持有的资产。这种设置好后无需过多关注的策略，旨在对这个领域和人工智能的未来做出真实的投资。从你嘴里说出的，正合我心意。我是说，听我说，我认为你可能需要耐心等待。不过，上周我们有一张图表在 Twitter 上广为流传，发布的时机相当巧妙。图表显示，从 Facebook、Twitter、阿里巴巴到 Shopify 等 20 家公司的 IPO 后平均最大跌幅超过 50%。也许，这个信息可以为我们这个部分的话题画上句号。
▶ 英文原文 ⏱
And so I think for most institutional investors, it's a must-buy, a must-own. It's set it and forget it, right, in order to have a real bet on both the space and the AI future. From your lips to God's ears. I mean, listen, again, I think that you're going to have to wait. But, you know, we had this chart last week, right, that came out. Everybody was sending around Twitter. Conveniently timed. And, you know, it shows the average max drawdown post-IPO for, like, 20 companies from Facebook, Twitter, Alibaba, Shopify is, you know, over 50%. And so maybe that, again, we'll end this section here.
你知道的，Gavin，你我做这行已经有很长一段时间了。我们知道在公司上市时，市场行情会很波动。作为一个管理者，你是怎么应对这种情况的？你会在IPO期间进行交易吗？还是会设定一个初始位置然后不去管它？从Altimeter的角度来看，我们通常会采取一种“设定初始位置然后不去管”的策略。然后根据市场在某个特定时刻的反应，我们可能会增加或减少持仓。不过，你对这张图或者你们团队有怎样的看法？你们显然在上市前持有了很多股份。
▶ 英文原文 ⏱
You know, Gavin, you and I have been doing this a long time. We know it's going to be bouncy around the IPO. You know, how do you, as a manager, try to manage that? Do you try to trade around the IPO? Do you set it kind of and forget it? I would say from an altimeter perspective, what we tend to do is we take a base position that we set and forget, right? And then we may size up or size down depending upon how the market reacts in, you know, in a particular moment. But any thoughts on this chart or, you know, how people, you guys are thinking about it in particular? You obviously own a lot going into it.
首先，我完全同意你所说的每一个字。实际上，我的想法和你的一样，就是"设定好后就不要再去想"。你提到过船上有压舱物，你可以移动它，并把它移到船的一边，以便让船迎风倾斜以加速；而当你不希望船倾覆时，就把它移到另一边。我觉得这是一个很好的比喻。我们可以用同样的方式来看待投资组合中的所有重要公司。所以，我是100%同意的。虽然这张图表看起来有点沉闷，我想说的是，其实还有关于IPO的数据。
▶ 英文原文 ⏱
First, agree with absolutely everything you said. And I actually think about it the same way. Set it and forget it. You've talked about you have ballast. You move around and you move the ballast to one side of the ship. When you want the ship to lean into the wind to go faster and you move it to the other side, we don't want the ship to tip over. I think that's a great analogy. Think about all important companies in the portfolio the same way. So, 100% agree. I mean, this chart is a bummer. What I would say is, you know, there's data on IPOs.
但我想说的是，这是一个前所未有的情况。我们从未见过如此大的IPO，也从未有过IPO如此迅速进入指数的情况。我们完全不知道投资者会卖出多少。我可以冒险猜测一下，但我不确定。埃隆，我想他并不需要流动资金。我记得他拥有多少呢？Foxy，大约50%。是的，他被锁定365天，所以我们知道他不会卖，对吧？所以，我认为这是一个前所未有的情况。正确的答案是，我不知道短期内会发生什么。
▶ 英文原文 ⏱
But what I would just say is this is a really unprecedented situation. We've never had an IPO this big. We've never had an IPO that's going to go into an index this quickly. We simply do not know how much selling there will be from investors. I would hazard a guess. I mean, I don't know. But, Elon, I don't think he needs liquidity. And I think he owns, what does he own, Foxy? 50%-ish. 50% of the company. And by the way, he's locked up for 365 days. Yes, exactly. So, we know he's not selling, right? So, I just think it's an unprecedented situation. And the right answer is, I don't know what's going to happen in the short term.
我会建议每位投资者在做决策时，就按照你说的方式来思考。我们有多种不同的杠杆和变量。用基本原则来分析每一个因素，做出自己的决定。进行尽职调查，认真思考。不过，这里涉及很多复杂的变量。而令我觉得有趣的是，以前的市销率是过去12个月收入的100倍。可是，在他们签署了一些交易后，我认为现在是39倍。这个变化很快。他们在一个月内增加了290亿美元。顺便问一下，你见过这样的情况吗？从未见过。
▶ 英文原文 ⏱
And the right answer that I would just encourage every investor in making their own decision is to just think exactly the way you articulated it. We have these different levers. We have these different variables. Think about each one of them from first principles. Make your own decision. Do your own due diligence. Be thoughtful. But there are a lot of variables here. And then it is a little funny to me that, you know, it was 100 times trailing TTM revenue. Well, after the deals they signed, I think it's at 39 times. That can change fast. So, they added $29 billion in a month. Yes. By the way, have you ever seen that happen? Never.
从未见过这样的事情。你知道，这说明了什么，首先，埃隆不仅是个伟大的工程师。他和格温以及他们的团队在商业上也非常出色。还有布雷特。他们了解到为下一阶段筹集资金所需做的事情，他们在商业中有一个长期目标。所以，对我来说，再次，在过去几周里我们从Curser看到的一切，以及他们达成的这些交易中，我不知道"Mag 7"中的任何一家公司能否如此迅速地调整他们的业务。这是一种极少见的大规模创业精神。
▶ 英文原文 ⏱
Never. And, you know, it just goes to show, first, Elon is not only a great engineer. He and Gwen and the team are great at business. And Brett. They understand what needs to be done to raise the capital, to get to the next phase. They have a long-term mission in the business. And so, to me, again, what we saw in the course of the last few weeks with Curser, what we saw with these deals that they cut, I don't know that any of the Mag 7 could have moved that quickly to adjust the business that they did. It's exceptionally entrepreneurial at scale, which we very rarely see in businesses.
有两件事情我想提一下。布拉德，我能给你一个拥抱吗？我想说的第一件事是，人们经常谈论筹集的资本总量。如果你把这里的资本加起来，比如Anthropic可能筹集的资金，OpenAI可能筹集的资金，还有SpaceX可能筹集的资金，我们姑且说是2500亿美元。这相当于「Mag 7」总市值的1%。对，就是1%。对我来说，这就像是在未来下注，我们都对此充满信心。
▶ 英文原文 ⏱
Two other things I would just say. Can I give you a hug, Brad? Two other things I would just say. Number one is, people talk a lot about the total amount of capital being raised. If you add up the capital here, right, for Anthropic, what they may raise, what OpenAI may raise, what, you know, SpaceX may raise. Let's call it $250 billion. That's 1% of the Mag 7. Okay, it's 1% of the Mag 7. Yeah. And we will as well. You know, like that to me is like a bet on the future that we all believe in.
如果要翻译成中文并且表达出易读的意思，可以这样说：
所以，如果问我们在哪些方面的看法不同于大多数人的观点？我们的独特看法是什么？我们实际上认为事情会发展得更大、更快。我们已经这样思考了几年。首先，它只占市场巨头七大（Mag 7）公司总市值的1%。然后你提到的卖出量。我这里有一个图表，我们将在这里发布。这是SpaceX股东的股票逐渐释放（Dribbles share release）的情况，所以在首次盈利发布之前，不会有太多股票被释放。我们在Cerebris首次公开募股（IPO）中也见过类似情况。这里的这个IPO也是如此。我认为银行对此很周到，知道这是一次非常大的IPO。
▶ 英文原文 ⏱
And so, if I said, where are we out of consensus? What is our variant perception? We actually think it's going to be bigger, faster. And we've thought that for a couple of years. So, first, it's only 1% of the Mag 7 market cap. And then you referenced it, the amount of selling. I've got a chart we'll post here. This is, you know, the Dribbles share release for SpaceX shareholders. You know, so there's not a lot that can be released up until after the first earnings. We saw this in the Cerebris IPO. There's a version of it here in this IPO. And so, again, I think the banks have been thoughtful here, knowing that this is a very large IPO.
我不是说这不会下跌。就像，这些东西可能会下跌。但是对我来说，从长远来看，有没有公司比这家更适合作为未来的投资？我认为他们在过去五周展示的东西，让他们可能是第一。不过我们继续说其他的。哦，不不，我想再说一下员工的问题。我觉得这里还有一个前所未有的事情，就是员工和很大程度上的投资者每六个月都能获得流动性。对，没错。
▶ 英文原文 ⏱
And I'm not saying that it won't trade down. Like, there's a possibility, you know, these things trade down. But again, for me, telescope out. Is there any company better positioned as a bet on the future? I think what they've shown over the course of the last five weeks, they're probably number one. But let's move on. No, no, can I just say one thing about the employees? I think another thing that's unprecedented here is the employees, and to a large degree the investors here, have had liquidity every six months. Exactly, exactly.
在过去大约十年间，如果你是SpaceX的员工或前员工，并且想要出售手中的股份，你大概有过接近20次机会。而且从历史记录来看，大投资者们是有机会出售的。因此，我认为很多人……这个观点很好……他们选择了持有这些股份。现在有了一个新的估值，我们拭目以待他们会做什么。但这的确是前所未有的，我们拭目以待。
▶ 英文原文 ⏱
For like the last 10 years. Yes. So if you're a SpaceX employee, or former employee, and you wanted to sell, you've had, whatever that is, close to 20 chances. And it is a matter of historical record that large investors have been able to sell. To sell, yeah. So I would think a lot of the people… That's a great point. …they've chosen to own it. Now there's a new valuation, and we'll see what they do. But just, this is utterly unprecedented, and we'll see.
是的，这确实是个很好的观点。我们实际上把这些公司称为准公共公司。你我都知道，SpaceX，我也把Anthropic和Databricks归入这一类。在过去的三年里，它们在很多方面的流动性比我们所熟知的一些上市生物科技公司还要高。确实如此。所以这里存在一个流动性的连续性。我们通常把公司简单地分为私营和上市，但实际上它们之间存在一个连续的范围。
▶ 英文原文 ⏱
Yeah, no, it's a great point. We've in fact called these companies quasi-public. You and I both know that SpaceX, and I've put Anthropic in this category as well, Databricks in this category. These things in many ways have been more liquid over the course of the past three years than some public biotech companies we know. Absolutely. And so there's a continuum of liquidity here. We treat it as a binary, private versus public, but it's really about this continuum.
你知道，我们继续讨论模型吧。你知道的，Anthropic昨天发布了Fable 5，你提到过，它基本上是一个带有一些分类器和网络安全、生物、化学以及蒸馏领域安全措施的mythos。当这些功能被触发时，它会回退至Opus 4.8。昨天Kaparthi在推特上谈到这个问题。他说这个模型在所有基准测试中都是最新的，但真正让它与众不同的是它处理长时间任务的能力。你转发了我们共同的朋友Noam Brown的帖子，你知道，ChatGPT 5.5也展现了这些能力。这让Noam认为，现在应该不太需要做这些技能评估了。这些简单的快照式基准测试已经不再那么重要了，我们应该以时间、计算或令牌为横轴。因为如果让这些前沿模型运行足够长的时间，我们现在几乎可以解决大多数问题。
▶ 英文原文 ⏱
You know, let's keep going on models. You know, Anthropic Launch Fable 5, which you referenced yesterday, which is basically mythos with some classifiers and safeguards around cyber and biology, chemistry, and distillation. When those things get triggered, it fails back to Opus 4.8. You know, there's a Kaparthi tweet about this yesterday. He said, you know, it's SOTA on all the benchmarks, but what really makes it special is long-running tasks. Okay? You retweeted our good friend, you know, Noam Brown. You know, ChatGPT 5.5 also exhibited these capabilities. You know, it led Noam, right, to suggest that it's not very relevant to do these skills. It's not very relevant to do these snapshot benchmarks anymore. Like, the x-axis has to be time or tokens or compute. Because we can solve most problems now if we just let these frontier models for a very long point in time.
所以，Gavin，这个新一代的模型是什么？对吧？Fable 5，ChatGPT 5.5。这对于超级智能的竞赛意味着什么？谁在上升？谁在下降？谁还在前沿？告诉我们你的想法。说实话，很难说Anthropic没有在提升。是的，在他们公布的营收数字之后，还有Fable 5的发布，Mythos显然更好。但我就是觉得Noam Brown昨天发布的内容，关于polynomial的帖子，实在是太深刻了。是啊。我们真的不知道这些模型有多聪明。而且我们说过……多说一点。为什么我们不知道这些模型有多聪明？因为没有人连续运行Mythos一年。没错。我们可能永远无法知道每一代模型的实际智能程度。对。但这也是因为我们没有时间在下一个模型推出之前，适当评估它们的智能水平。
▶ 英文原文 ⏱
So, Gavin, what is this new class of model? Right? Fable 5, ChatGPT 5.5. What does it mean for the race in superintelligence? Who's up? Who's down? Who's still on the frontier? Give us your thoughts. I mean, it's hard to say that Anthropic's not up. Yeah. Like, after the revenue numbers they put up, after the Fable 5 release, and Mythos is evidently even better. But I just think that Noam Brown post from yesterday, polynomial, is so profound. Yeah. And just the idea that we do not know how smart these models are. Okay. And we made… Say more about that. Why don't we know how smart they are? Because nobody has run Mythos for a year continuously. Exactly. We may never know how smart each generation of models actually is or was. Right. But because we don't have time to appropriately evaluate their intelligence before the next model comes out.
我的意思是，这是一种深刻的观点。可以想象一下，好吗？我总是说，当你想到全自动驾驶（FSD）时，试想着一个从不分心、从不疲惫、从不开车打电话、不酒驾、不对孩子大喊大叫、不需要给后座的婴儿喂奶瓶的人。当然，你会觉得，随着时间推移，这种情况会优于那些会被分心的人。我不知道……布拉德，你能在一个话题上深入思考多久？对，也许是一个小时。一个小时。就像一个小时。哦，天哪。这让我感觉很糟糕。因为我想我最多只能在一个话题上连续深入思考五分钟，不让其他想法打扰。对。不过我可以再回到这个话题。想象一下，如果阿尔伯特·爱因斯坦能够，每次能思考三个小时。对，没错。他显然是个非常杰出的天才。
▶ 英文原文 ⏱
I mean, this is a profound statement. And just imagine, okay? So I always say, like, when you think about FSD, just imagine a human being who never gets distracted, never gets tired, never talks on the phone in the car, never drinks and drives, never yells at their kids, never has to go to the backseat to give their baby a bottle. And, like, of course you would think that over time that is superior to humans who are distracted. I don't know how long… How long can you think deeply about one topic, Brad? Yeah. It could be an hour. It could be an hour. It could be an hour. It's like an hour. Oh, man. Yeah. That makes me feel terrible. Because I think I could think deeply about one topic continuously before having a stray thought enter my mind for, like, maybe five minutes. Right. Now I could come back to that. Imagine if Albert Einstein had been able, instead of, you know, maybe he could think for three hours at a time. Right, exactly. Clearly an exceptional intellect.
是的。但想象一下，如果阿尔伯特·爱因斯坦只专注于基础物理学。是的，一天24小时。他无需吃饭，也不需要睡觉或放松。不喝酒，也永远不会变老。永远不会变老。他死了，但他的智力不会减弱。是的，如果他这样思考了一年，我已经能够解决很多这些棘手的问题了。所以我认为这是一个非凡的想法。我从中得到的启发是，无论我之前对计算的看好程度如何，现在我更加看好了。对，对，对。
▶ 英文原文 ⏱
Yes. But imagine Albert Einstein had just thought about fundamental physics. Yeah. 24 hours a day. Yeah. He doesn't have to eat. He doesn't have to sleep. He doesn't have to relax. He doesn't drink. And never gets old. Never gets old. He dies. Never has diminutive intelligence. Yes. And he thought for one year. Yeah. I'd already, you know, have solved a lot of these intractable problems. Yeah. So I just think that's an extraordinary thought. And just my takeaway was, however bullish I was on compute before then, I'm just a lot more bullish. Right, right, right.
好的，所以你知道，我们所看到的是，这可能真的是让Opus 4.6取得突破的关键。它是第一个能够长时间运行的模型，能够维持上下文和记忆，并解决一些较长时间的问题。对我们来说，信号在一月份就出现了，我们意识到了那是一个重要的时刻。但随后，当你开始看到收入增长时，我们知道许多人独立投票表明这一点，它变得非常有用。所以，今年一个共识问题是，人工智能的收入是否会出现。
▶ 英文原文 ⏱
Yeah. So that is a, you know, we saw when, that was probably what really unlocked Opus 4.6. It was the first really long running model that could maintain that context, maintain that memory, solve some of these longer running problems, right. For us, the signal was in January, we knew, we felt like that was a big moment. But then when you started to see the revenue go up, we knew that lots of people were voting independently, that that was a profound moment that they became much, much more useful. So, but one of the things that the consensus going into this year, right, so the big question going into this year was, was the AI revenue going to show up?
我们何时能达到那些让企业和消费者更多使用的智能水平呢？我认为，当时在这个播客上，我和比尔的辩论中达成的共识是，开源模型和便宜的代币正在追赶前沿，或许这些模型正开始趋于饱和，人们实际上不会为高价代币买单。然而，看起来今年过了六个月的实地证据恰恰相反。前沿代币占据了绝大多数的收入份额。事实上，如果你相信长期计算能力的发展以及更多计算能力带来的好处，它们可能在某些基于蒸馏的模型上进一步扩大了领先优势。
▶ 英文原文 ⏱
Where are we going to get to these thresholds of intelligence that cause enterprises and consumers to use them more? And I think the consensus at the time, at least on this podcast, the debate with my, with Bill, was that open source models, cheap tokens were catching up on the frontier, that perhaps these models were beginning to asymptote, that people wouldn't really pay for premium tokens. And it seems to me that the evidence on the field six months into the year is just the opposite, right? That frontier tokens are capturing the vast majority of all the revenues. And that in fact, if you believe in the long running capabilities and more compute allows you to do that, they may actually be extending their lead, right, on some of these models that were built on distillation.
所以我就向桌子旁的所有人开放讨论。大家怎么看，这个观点——便宜的开源代币总是会缩小与前沿模型之间的差距——是对的吗？还是这些前沿模型在扩大领先优势？我觉得这种讨论自从我们开始训练这些模型以来就一直存在。当时的情况是，我们总是落后前沿三到六个月。但从数据看，所有的收入实际上都流向了前沿。这是因为每次我们推出前沿模型，都会产生一系列新的使用场景，以前从未能解决的问题——比如编程。而且我们过去整天都坐在桌子边，认真研究Claude，因为使用Fable 5能做的事情让人着迷，而这些事情在一天前，用Opus 4.8是无法实现的。
▶ 英文原文 ⏱
So I just opened it up to anyone around the table. What are your thoughts on whether or not, you know, have we challenged this thesis that cheap open source tokens are going to always, you know, close the gap on these frontier models? Or are they extending their leads? I think this debate, like this same debate has existed since the beginning of, since we started training these models to begin with, which was, hey, we're always kind of three, six months behind the frontier. But empirically, like you can just see all of the revenue has actually just accrued at the frontier. And I think that's because every time we release the frontier, a whole new, like slew of use cases that previously we could have never tackled before. Like coding. Like coding. But also just, you know, we've just been locked at our desks for the last day just, you know, hammering Claude because, you know, it's just fascinating the things that now we can do with Fable 5 that we just couldn't do with Opus 4.8 just a day before.
所以，有哪些事情让我觉得好奇呢？我认为现在 AI 在多代理协调方面做得非常好。Anthropic 发布了一篇博客文章，讲述了六种不同的代理协调模式。他们讨论过这些，但实际上，一旦你能够管理好所有这些代理，模型和代理之间的联系就会越来越紧密。模型可以理解你的工作范围。
举个例子，我把我们的七个模型放在一起，然后说，我想基于这些公司的各种假设，比如台积电的产能，生成一个关于我信念的总体视图，并制作一份报告。模型能够逐步推理我们的所有假设，比如，如果你相信这个，那么这件事就和另一件事不一致。它可以指出这些矛盾点。这真的是很吸引人的。
▶ 英文原文 ⏱
So what are some of those things, man? I'm curious. So I think it's really, really good at multi-agent orchestration now. So Anthropic released a blog post about like different agent, six different agent like orchestration patterns that, you know, they've talked about. But really like once you start being able to manage all these agents, the harness and the model itself is being arled with one another. They're actually being, you know, fused closer and closer together. But the model can understand the, you know, the extent of your work. So, you know, one of the things, for instance, is I just threw in like seven of our models and just said, okay, like I want to create a master view of like my beliefs, given all of these assumptions of all these companies, TSMC capacity, like, and then produce me a report on all this stuff. And, you know, the model is able to reason through all of our assumptions. Like actually, if you believe this, this thing is inconsistent with this. Right. What are the contradictions? Exactly. Yeah. It was fascinating.
我们以前从来没有这样做过，但是现在我觉得我们只是迈入多代理协调的第一步。我们会更深入地进行下去。这就是一个例子。我把过去三年的所有笔记都输入进去，系统对这些笔记进行了分析，并告诉我哪些想法是一致的，哪些信息是最终最有价值的。结果真是让人感到惊讶，看到我们能做到哪些事情。我们已经突破了极限，激发出了所有这些潜力。比如说，他们昨天在发布会上就给出了几个例子。
▶ 英文原文 ⏱
And, you know, before we never do that. But now, you know, I think we're just step one into multi-agent orchestration. We're going to do this even further. And that's one example. I've also dumped all my notes into and it's reasoned across all my notes from the last three years and said, you know, here are some of your ideas that were consistent. Here are like, you know, the sources that were actually the highest signal to what actually played out, you know? And then it was actually just super fascinating what you could do. And we've just blown through our, blown through our limits. It's unlocking all this. I mean, like they gave examples yesterday in the release.
好的。Anthropic 在 Stripe 完成了一个拥有五千万行 Ruby 代码的项目，仅用了一天就进行了重构，而不是需要很多人花费几个星期的时间。想想这对生物学和生命科学的影响，涵盖了整个领域。在我看来，这让我们回到一个基本点。首先，如果你相信长时间运行的智能体会产生这样的影响，那么在未来，我们将会在更长时间内生成和消费更多的信息。世界因此让我联想到 TerraFab 和 Space Orbital 等，因为我们可能会解锁真正的智能门槛，但要达到这个目标，我们必须让这些“马”跑很长一段时间。
▶ 英文原文 ⏱
Yeah. Anthropic did, you know, 50 million line Ruby code base at Stripe that was, you know, refactored in a day versus many weeks with many people. You think about where this is impacting biology and life sciences just across the spectrum. And to me, it really gets back to this fundamental point. Number one, if you believe this to be true about long-running agents, then we're going to produce and consume more tokens in the future as far as the eye can see. So the world, this gets me back to, you know, TerraFab and Space Orbital and all this because we may in fact unlock real thresholds of intelligence, but we're going to have to let these horses run for a long time in order to get there.
好的。我来说两点。两件事可以同时为真。第一，大部分经济价值可能会继续积累在前沿领域。对，截止目前确实是这样，包括今年的前六个月。第二，世界上大多数被使用的代币可能会是开源的。目前确实是这样。我认为这种状态可能会继续下去。
▶ 英文原文 ⏱
Yeah. I'll just say two things. Two things can be true. Mm-hmm. The majority of economic value may continue to accrue to the frontier. Right. And man, has it ever accrued to the frontier thus far. Right. And for sure the first six months this year. But the majority of tokens consumed in the world may be open source. And they are today. Yes. And I think that this current state is likely to persist.
好的。Harvey在X平台上发布了一篇很棒的博客文章。他们使用了自己的专有法律数据进行强化学习和监督微调，利用开源模型进行了精彩的实验。令人惊讶的是，现在的信息更新如此之快，可能仅仅五天后就过时了。他们还使用了一种称为路由器的工具，来决定将查询发给哪个模型以及使用哪个模型进行验证。通过这种方法，他们在成本较低的情况下，获得了比Opus 4（无论是4.7还是4.8）更好的结果。我认为这就是未来的发展方向。
▶ 英文原文 ⏱
Yeah. Harvey had a great blog post that they put out on X. And they used, and it's just amazing how everything gets out of date like in five days, you know. But they used their own proprietary legal data to do reinforcement learning and supervised fine-tuning with fireworks on an open source model. And then they used a router and a router being something that picks which model you send which query to and which model you use to check which model. And they got better outcomes than Opus 4, either 4.7 or 4.8 at a lower cost. Yes. And I think that is the future.
好的。实际上，他们仍然在大量使用Opus。但是，他们处理的大部分令牌可能是在他们自己的开源模型中。我们也听到了同样的情况。我们进行了一项针对300家公司的企业调查，以了解哪些公司在进行优化。这些公司在考虑模型路由时，会选择将某些令牌发送到特定地方。哪些公司在考虑优化？哪些公司还没有开始优化？然后，他们对Frontier Model令牌的预期使用情况如何呢？即使这些公司已经在进行优化，他们仍然预计会消耗更多令牌。
▶ 英文原文 ⏱
Yeah. And the reality is they were still consuming a lot of Opus. Yeah. But a majority of the tokens they were processing probably were in their own open source model. We hear the same thing. Yeah. We did an enterprise survey that will post of 300 companies which ones were optimizing. So these are folks who are kind of looking at model routing and saying we're going to send certain tokens over here. Which ones are thinking about optimizing? Which ones aren't optimizing yet? And then what is their expected use of Frontier Model tokens, right? And they're all expecting to consume a lot more even though they're already in the process of optimizing.
想象一下JP摩根的情况。如果他们正在进行一些后台作业，比如客户服务，他们很可能会使用开源模型。不过，我认为他们不太愿意使用中国的开源模型。所以，他们在等待美国的开源模型，这样才能真正满足他们的需求。但是我猜，对于这些企业来说，很多后台作业最终会依靠这些开源模型。这样一来，大部分的"token"（代币）可能都会用在这里。
▶ 英文原文 ⏱
Think of it in the context of JP Morgan. If they're doing some back of the house stuff, right, on customer service or whatever, they may very well use an open source model. Now I think they're loathe to use Chinese open source models. So they're waiting on kind of US open source models to, you know, be able to really deliver the bang that they need. But my hunch is for these enterprises, a lot of that back of the house stuff will get rooted there. That will probably be a majority of the tokens.
我觉得那些真正高价值的工作，比如编程，他们不想写次等的代码。我认为绝大多数的高端工作仍然会留在前沿。你不需要爱因斯坦来给你订旅行，也不需要爱因斯坦来进行KYC（用户身份验证）。但这正是我们两年前在这张桌子上讨论过的话题。然而，如果你看看收入曲线，人们当时的结论是前沿的模式不会累积大部分收入。但是我们现在看到的情况是，这些模式占据了90%的收入。
▶ 英文原文 ⏱
But I think the really high value stuff, you know, coding as an example, they don't want to write second tier code. I think the vast majority of that will continue to be on the Frontier. You don't need Albert Einstein to book you a trip. You don't need Albert Einstein to do KYC. But this is the debate we had literally at this table two years ago. However, if you just look at the revenue curves, right? What folks concluded when they said that, they said, therefore, the Frontier models will not accrue most of the revenue. And what we're seeing right now, it's 90% of the revenue.
这一直是彻底错误的，可能错误率超过90%，而且可能继续错下去。前沿技术可能占经济价值的90%，开源可能占代币的80%。我认为关于开源有件事很重要，那就是有人认为开源对人工智能不利。实际上，它可能对前沿模型不利，这就是你提到的那种悲观情况。但它对计算和硬件实际上是非常利好的。因为如果前沿模型获取的利润变少，那么在计算上花费的成本就会增加。
▶ 英文原文 ⏱
That has been decisively wrong. Probably more than 90%. And it may continue to be decisively wrong. Frontier might be 90% of the economic value. Open source might be 80% of tokens. Something that I think is very important on open source is that, you know, I think there's this belief that it's bearish for AI. It's actually, it may be bearish for the Frontier models. There's that bear case you talked about. It's actually really bullish for compute and hardware. Because if the Frontier models are capturing less of the margin, then you're going to spend more on compute.
所以，开源做得越好，对计算服务提供商就越有利。我想说的是，在西方，特别是在硅谷，以及在亚洲之间，有着非常深刻的信念差异。在硅谷，人们普遍认为一切都趋向于闭源和云计算，流量都会朝这个方向发展。而在亚洲，人们普遍相信我们会为每个工作负载找到合适的模式，并且不会过度消费。
▶ 英文原文 ⏱
So the better open source does, the better it is for compute providers. I will say, there is a very, I would say between spending time in the heart of like the West, Silicon Valley, and also spending time in Asia, there's like a very big, like a deep-seated belief in one versus the other, which is like if you spend a lot of time here, it's like all closed source, cloud, every, all traffic is going to go, you know, by way of this direction. And then you spend time in Asia, you know, the overwhelming belief is that we're going to find the right model to the right workload, and we're not going to overspend.
好的，我认为，接下来的一年很可能会成为决定方向的关键时期。我认为封闭源代码模型之所以能捕获如此多的价值，是因为这些模型真正理解了用户的意图，并且能够完成工作。在这一年里，我们首次看到代理不仅仅是回答聊天机器人的请求，而是能够实际完成有用的工作。
▶ 英文原文 ⏱
Right. And I think, you know, I would say the next year is probably going to be the most indicative of which way this falls. Because I think, I think the reason why closed source models have captured so much of the value is because the models actually get the intention and actually carry through the work. And this was the first year where we actually had agents that actually carried out user intention from just answering a chatbot request to actually producing useful work.
好的。现在，这种智能的水平已经迅速提升，我们不断把它应用到经济价值最高的任务中，比如编程、金融等知识工作。但是对于那些种类繁多的小任务，如果开源技术继续保持六个月的差距，我们可能会看到更多开源技术被用于我们的日常任务。其实，这基本上就是Jensen的观点。
▶ 英文原文 ⏱
Right. Now the, the level of this intelligent has scaled so rapidly and we continue to push against like the most economically valuable tasks, which are coding and finance and all these like knowledge work tasks. But like for the long tail of tasks, if open source continues to maintain a six month lag, we might actually see a lot more open source used for, you know, our everyday tasks that we might actually. And that's basically Jensen's argument, right?
好的。Jensen 的观点是，未来会有模型路由。目前的情况是，先进的模型在执行长时间任务上具有优势，而开源模型在这方面表现不佳，所以先进模型获得了大部分价值。但开源模型很快也将能胜任这些长时间任务，这样一来，它们也将获得大量收入。
▶ 英文原文 ⏱
Yes. Jensen's argument is you're going to have model routing. And we're just in a moment in time where the frontier models gained to the advantage, can do long running tasks, the open source models couldn't do it very well. And so they're accruing all of the value, but as soon as the open source models can do the long running tasks as well, which is not far away that they too will grab a bunch, a bunch of this revenue.
你们是Reflection的投资者吗？我不是。好的，我们也不是，但我对Misha和他们团队以及他们正在做的事情印象深刻。我非常希望一个前沿的开源码美国实验室能够取得成功。我们知道，我最近听你说过，我相信这是真的，Nvidia如果真的想做的话，他们完全有能力随时构建一个前沿的开源码模型，因为他们已经拥有一些很棒的开源码模型。
▶ 英文原文 ⏱
Are you investors in reflection? I'm not. Okay. No, nor, nor are we, but I, I'm very impressed by Misha and, and the team and what they're doing. I very much want a frontier open source us lab to win. We know that, you know, I heard you say recently, and I believe it to be true, Nvidia any day that they really wanted to, right? They already have some great open source models. They could absolutely build a frontier open source model whenever they chose to do it.
在我看来，美国是否会有一个开放源代码的前沿模式并不是问题，而只是时间的问题。在那个时刻，也就是说，假设他们获得了这些长期运行的能力，前沿实验室是否又一次实现了某些成果，使他们能够继续垄断收入。我认为，如果有人说：“哇，你打造的这个专用集成电路（ASIC）真可爱。真是太可爱了。”他们可能在问你是否愿意让开放源代码加入前沿行列。你怎么看这个提议？所以，我不确定这是否是明确的计算，但我确实认为Jensen有他的观点。可以再详细解释一下，给大家更清晰的理解。
▶ 英文原文 ⏱
And so it's not a question in my mind as to whether or not the U S is going to have a frontier open source model. It's just a question about timing. And then like at that point in time is the, you know, let's say, let's assume they get these long running capabilities. Have the frontier labs now achieve something yet again, that allows them to keep it, keep the stranglehold on the revenues. Yeah. And I just think it's, if you're, wow, that's a cute ASIC you've built there. That is so cute. Right. How would you like open source to join the frontier? Right. How would you like that? How do you like the apples? So, I mean, I'm not sure that's the explicit calculation, but I do think Jensen is. Say more. Just double click on that for everybody at home.
好的。如果他们推出一个开源模型，那对ASIC(专用集成电路)市场会有什么影响？可能你没有足够的收入或利润来支撑ASIC的开发。我确实认为Nvidia（英伟达）很有可能成为全球开源AI的主导供应商，而且我相信Jensen（黄仁勋）将会推动开源。目前，这个领域可能落后最前沿大约六个月。但我认为我们可能会看到这个差距越来越小。而且我认为Jensen有一个重大的商业决策要做。我这里看到这张图表，所以让我们来聊聊Nvidia。不过，如果他所有的客户都要和他竞争，那为什么不直接和他的客户竞争呢？
▶ 英文原文 ⏱
Yeah. If you were, if they were to put an open source model out there, how does that impact the ASIC landscape? Well, you might not have the revenue to fund, to fund that, the revenue or the margins to fund that ASIC. And I do think Nvidia is highly likely to be the world's dominant provider of open source AI. And I do think Jensen will bring open source. You know, right now it's whatever, six months behind the frontier. Yeah. We might see it creep closer and closer and closer. And I do think Jensen has a big business decision. I see this, you know, chart here. So let's, you know, chop it up about Nvidia as you say. But if all of his customers are going to compete with him. Yes. Then why not compete with his customers?
我们有所有这些NeoClouds，对吧？这是一个可以与其他云计算企业竞争的云计算业务。他有自己非常出色的模型。NemoTron 3或3.1在计算效率方面确实很棒。而且他总是谨慎地发布小模型，以避免触及Anthropic、OpenAI或谷歌的利益。但我认为这是他做出的一个选择。而且，只要经济条件发生变化，我认为英伟达可以更快地加入前沿，成为世界上最大的云计算公司之一，比人们想象得要快。很有趣，很有趣。克拉克，带我们看看这个图表。
▶ 英文原文 ⏱
And we have all these NeoClouds. Right. So that's a cloud computing business that can compete with all these cloud computing businesses. He has his own models that are really, really good. NemoTron 3 or 3.1 was actually really, really cool from a compute efficiency perspective. And he's always careful to release small models. Right. So as to not tread on anthropic open AI. Right. Google's toes. But I do think that is a choice he is making. And just, you know, if the economics change. Right. I think Nvidia can join the frontier and become one of the world's largest cloud computing companies much faster than people think. Interesting. Interesting. Clark, walk us through this chart.
是的，我想在台湾时间所得到的一个结论是，大家对下一波ASICs（专用集成电路）的发展充满了期待。但我认为，现在是一个非常明确的时刻，以前总是在讨论Nvidia和ASICs之间的竞争，要么是Nvidia，要么是ASICs，总有一个是绝对的赢家。如今，我觉得已经不是这样的趋势了。每年大家都以为Nvidia会在收入、功率、销售数量等方面大幅失去市场份额。但实际上，如果你看过去几年来的数据，Nvidia实际上很好地保持了他们的市场份额。实际上，如果考虑到Anthropic并没有真正使用Nvidia的产品，或许直到2526年Nvidia才在份额上有所失去。
▶ 英文原文 ⏱
Yeah. So I think one of the takeaways from spending time in Taiwan was there is certainly a lot of excitement around the next wave of ASICs. But I think it's like a very clear moment now where Nvidia, it used to be an argument of Nvidia versus ASICs. It's one or the other and, you know, total domination one or the other. Right. Now, I think it increasingly, every year, everyone assumed that Nvidia was going to lose share dramatically on a revenue scale, on a gigawatt scale, on a unit scale. And actually, if you actually look at the last few years, you know, they've actually maintained their share very, very handsomely. Actually, if you accounted for the fact that Anthropic was not really using Nvidia, they probably actually gained share against, if not for in 2526.
我认为非常有趣的是出现了一类新的加速器或ASICs。以MediaTek推出的新V8T和Broadcom的V8I为例，这成为了关于TPU（张量处理器）的大讨论话题。现在，关于ASICs的争论是它们会越来越多地根据实际工作负载进行定制。这是一个发展的方向，相比之下，Nvidia已经展示出它作为全球主要计算提供者的地位。对于内部工作负载来说，可能会越来越多地走向定制化，更深入到技术堆栈。我记得就在一年前，这还仅仅是Broadcom和Nvidia之间的竞争。现在看来，关于哪种加速器适合哪种工作负载、客户和商业模式，这方面的细微差别变得更多了。
▶ 英文原文 ⏱
So I think what was very interesting, though, was a new class of accelerators or ASICs, MediaTek with their new V8T versus, you know, Broadcom's V8I for TPUs actually was a big topic of discussion. And, you know, I think for ASICs, the argument now is that more and more will look custom to the actual workload. And that is like one vector that people are moving in versus Nvidia now has kind of shown itself as the predominant provider of compute to a lot of the world. And for, you know, internal workloads, perhaps they will go more and more custom and more and more down the stack. And I remember just, you know, one year ago when it was kind of a Broadcom or Nvidia battle. It seems there's a lot more nuance now to, you know, what type of accelerators will fit which workloads and fit which customers and fit which business models.
好的，我以为这是个新话题。不过，这是一个新的认识。我觉得我们大家一直以来都有这样的看法。这确实让我很震惊。我现在在外面，我和我们的一家公司的董事会开了个会。他们特别强调的一点是，我们原以为全世界对英伟达的需求会变少，但事实正好相反，英伟达正在加速发展，并且继续超越他们的竞争对手。我觉得很多人都在关注这个开放式AI的千兆瓦。你知道，英伟达有10个，博通也有10个，谁有6个呢？AMD，AMD有6个并且有权证。然后 Cerebrus，我们的一个共同投资的公司，也有一个千兆瓦。这些都是纸面上的情况。至于实际部署会怎样，让我们拭目以待。
▶ 英文原文 ⏱
And, yeah, I thought that was a new topic. New realization, though. I think we all kind of shared this view for a long time. Yeah, I was just shocked. I mean, I'm out here. I did a board meeting with one of our companies. And just, you know, their biggest one thing they emphasized is we thought the world would be consuming less Nvidia than it is. And if anything, Nvidia is accelerating and they just continue to out execute their competitors. And I think a lot of people are indexing to this open AI gigawatt. And, you know, Nvidia has 10, Broadcom has 10, who has six? AMD. AMD has six and they have warrants. And then Cerebrus, our shared portfolio company, has a gigawatt. And I just, that is what's on paper. Right. What actually gets deployed, let's see.
如果说，呃，27个里面有10个，我会非常惊讶。这个数学怎么算？让我们看看谁数学最好，那个市场份额是多少？30%。对。如果他们真的达到了那个数字，我会非常惊讶。我认为那是一个极其不可能的结果。尤其是在我们仍处于电力受限的世界中，如果你能用英伟达的芯片获得更多的每瓦特令牌（这在实际上就是收入），那就比许多替代方案要有利得多。如果你用其他芯片建厂，你可能可以省下一些钱，但收入会减少，利润率也可能更低。这就是黄仁勋一直强调的一个点，我认为这非常重要。
▶ 英文原文 ⏱
I will be very surprised if, you know, that 10 out of 27, what's that math? Let's see who's best at math. What percentage market share is that? 30%. Yeah. Yeah. I'll be very surprised if that is where they land. I think that is an extremely unlikely outcome. And especially as long as we are in a watt constrained world, if you can get more tokens per watt, which is literally revenue with Nvidia, then a lot of alternatives. Just if you build your factory with another chip, you may save some money, but you're going to have less revenue and the margins may be lower. And that's a point that Jensen keeps hammering and I think is really important.
顺便说一下，我们要给予应得的赞誉。在这个ASIC领域中，令我感到最重要、最惊讶的事情之一是Meta和微软可能有些令人失望。你知道是谁做出了一个优秀的ASIC芯片吗？对，你知道，是的，是Jalapeno公司。没错，这是一个很棒的芯片。不过遗憾的是，它需要在比Nvidia的GPU低得多的温度下运行，这意味着你需要花更多的钱来进行冷却，并且这会消耗更多的电力。他们真的做出了一个很棒的芯片。
▶ 英文原文 ⏱
And by the way, credit where credit is due. The most important, the most, one of the most surprising things to me in this ASIC landscape, I would say Meta and Microsoft have been probably disappointing. Yes. You know who made a good ASIC? Yes. Well, I know you know. Yes. Jalapeno. Yeah, exactly. It's a great chip. Yes. Now, unfortunately it needs to run at a much lower temperature than the Nvidia GPUs, which means you need to spend more money on cooling and that consumes more power. They made a great chip.
我们可以，我的意思是，我认为的问题是，对每个人来说，是否这是你时间的最高和最佳利用？对吧？我个人倾向于认为前沿公司，似乎存在一种信念，认为他们必须实现垂直整合。但是如果你像我一样相信，在接下来的两到三年里，随着这些递归循环的发展，超智能的竞赛可能会结束，那么我觉得应该专注，再专注，继续专注。你的存在是为了打造世界上最好的智能，并提供世界上最好的智能。这意味着你必须获得所有的收入，因为如果你想建设所需的计算能力以继续推动前沿发展，你就必须有收入来支持这一点。回到专注的问题，我觉得他们确实做到了。
▶ 英文原文 ⏱
We can, I mean, I think the question there and the question for everybody is going to be, is that the highest and best use of your time? Right? Like I, you know, I tend to think that the frontier companies, like there's this belief that they got to be vertically integrated. But if you believe like I do that the race to super intelligence, particularly as we get these recursive loops working, maybe over in the next two to three years, then I think focus, focus, focus, focus. You exist to build the best intelligence in the world and to deliver the best intelligence in the world. And you, that means you have to have all the revenue because if you want to build out the compute, it's going to be required to continue to push the frontier. You have to have the revenue in order to support it. You know, subject to the focus question, I think they certainly did.
这让我回到了某种现实检查。你知道的，我们刚刚讨论了测试时计算、推理时计算、长时间运行的代理。这真的是今年解锁收入的关键。这一切都让我们走向更多的资本支出。Google 刚刚筹集了800亿美元，对吧？我们现在将 MAG-5 或 MAG-7 的自由现金流，与几年前相比大幅减少了80%。摩根士丹利，你面前有这张他们的资本支出预测表，从2027年将其从9500亿美元提高到1.1万亿美元。我的意思是，我们曾经与詹森谈论过这一点，那是他两年前的预测。
▶ 英文原文 ⏱
This all brings me back to kind of a reality check though. You know, we just got done talking about test time compute, inference time compute, long running agents. This is really the thing that's unlocked the revenue this year. It all pushes us in the direction of more CapEx. Google just raised $80 billion, right? We've now taken the MAG-5 or MAG-7 free cash flow, you know, down dramatically 80% from just a few years ago. And Morgan Stanley, you've got this chart in front of you up to their 2027 CapEx forecast from $950 billion to $1.1 trillion. I mean, we were talking about this with Jensen. That was his forecast two years ago.
你知道，这显然还不包括SpaceX、CoreWeave等公司。因此，我认为到2027年的数字可能更接近1.5万亿美元。 如果我们将其与总增量推理收入进行比较，这是市场担心的事情。去年十月在我与Sam Altman的播客中提到，是否能真的承担每年1.5万亿美元的资本支出，而在推理收入上只产生X金额。今年引发热潮的是Anthropics，以巨大的收入表现登场。所以，明年AI实验室的总收入大概会达到3000亿美元。
▶ 英文原文 ⏱
You know, obviously this doesn't even include SpaceX, CoreWeave, etc. So I think the number on 2027 is likely closer to $1.5 trillion. And if we compare this to the total incremental inference revenue. So the thing that the market gets worried about, you know, back to my Sam Altman podcast, you know, in October of last year. Can we really afford to spend $1.5 trillion of CapEx a year if we're only generating X amount in inference revenue? The thing I think that lit the fuse this year was Anthropics showed up in a major way with revenue, right? And so we have, you know, the AI lab revenue, everybody combined at around $300 billion next year, right?
所以，我们不能将这个计划延展到2027年，或者说，到2027年，我们要花3000亿美元。因此，我们在3000亿美元的推理收入上花费了1.5万亿美元的资本支出。这个计算对你来说合适吗？是什么会让你感到更加担忧我们继续进行这些投资的能力呢？因为一旦我们对这点感到担忧，整个半导体行业都会受到很大影响。你认为这3000亿美元的毛利率是多少？我们可以粗略估算为50%。我猜可能比这高一点，也许是60%或70%。不过，我的意思是，这样的计算慢慢就合理了。
▶ 英文原文 ⏱
So can't, you know, roll that out to 2027, or that is 2027, $300 billion. So we're spending $1.5 trillion of CapEx on $300 billion of inference revenue. Does that math math for you? And what would cause you, you know, to get more nervous again about our ability to continue to make these investments? Because the second we get nervous about it, the entire semi-complex is going to come down a lot. Well, what do you think the gross margins are on that $300 billion? Yeah, let's call it 50%. I would guess they're probably a little bit higher than that. I might say 60 or 70. But I mean, that math starts to math.
我想说的是，我认为3000亿美元这个数字有点低。是的，我就是觉得这个数字不够高。你这个看法我完全同意。是的，我认为我们今年的推论收入远超2000亿美元。所以，我觉得这个计算结果是合理的。我觉得我们必须给我们的朋友Jensen一些肯定，因为他曾说过一些听起来很离谱的话。对，他的预测比较保守，他的估计偏低。他两年前就曾预测达到一万亿美元。也就是说，他当时的预测真的很保守。所以，我们应该认可他的成绩，并认真思考他现在所说的话。
▶ 英文原文 ⏱
And what I would just say is I think that $300 billion is low, man. Yeah. I just think it's low. From your mouth. Yeah, exactly. I think we end this year well over $200 billion in inference revenue, well over. And so I think the math really maths. And I do think we have to give Jensen, our friend, some credit because he said some things that seemed outlandish. Right. And he was conservative. He was low. He said a trillion two years ago. And I mean, he was really low. Right. And so like, let's give the guy some credit and think about what he is saying right now.
当然，当然。而且，我要说的是，Elon 一直非常积极。Sundar 也是如此。Sam 和 Dario 也是如此。你知道，Dario 在与 Dworkish 的播客中谈到数据中心的国家天才时说，到2028年，这种情况会出现。他说，到2028年，收入将达到几千亿美元的低位，所以我们可以说，到2028年，收入可能有三四千亿美元。他是很早就这么说的，所以他可能还会调整他的预测。他还提到，2030年之前，收入肯定会达到数万亿美元的规模。如果我们现在的收入增长趋势是到今年年底达到两千亿美元，那么到明年可能就是四五千亿美元，并在2029年达到数万亿美元的途径上，那么这笔账是算得上的。
▶ 英文原文 ⏱
For sure. For sure. And listen, I would say consistently Elon's been taking the over. Sundar's been taking the over. Sam, Dario. You know, Dario did the podcast with Dworkish when he was talking about country geniuses in the data center. He said that will be here by 2028. He said revenues will go into the low hundreds of billions by 2028. So let's call that, you know, three, four hundred billion of revenue by 2028. And he said that a while ago now. So he may even be revising up his number. And he said, it's hard for me to see that there won't be trillions of dollars in revenue before 2030. And if you're on that revenue trajectory, if we're on a trajectory to 200 by the end of this year, let's call it four or 500 by next year and a path to trillion plus by 2029, then the math, maths.
我们必须记住，大约一半的支出是用于培训的，可能稍微少于一半。是吧，Foxy？具体多少取决于实验室，但我认为这个比例越来越小。是的。好的。我认为只有大约百分之一的支出与收入无关，而是用于开发下一个模型。所以，我觉得从数学上来讲，这是合理的。同时，还有一种囚徒困境，如果你选择退出，这可能会是一个生存性的决策。当然。而且，在进入这一年时，关于哪些预期没有实现，大家都认为代币定价、计算的价格都将呈现通货紧缩的趋势，并且随着时间的推移会逐渐稳定下降。
▶ 英文原文 ⏱
And we got to keep in mind that half of the spending is there to, you know, for training, maybe a little less than half. What is it, Foxy? It's probably, it depends on the lab, but I would say it's increasingly less than half. Yes. Okay. And I think that's the only one percent is spending that's not revenue generating that is going to kind of make the next model. So I think the math, maths. Right. And there's still this prisoner's dilemma where if you opt out, that may be an existential decision. For sure. And I think like coming into this year, going back to this kind of what narratives were violated, you know, I think into this year, everyone expected token pricing, the price of compute, it's all deflationary and it will be kind of a smooth line deflationary over time.
我认为今年的情况正好相反，一切都归结于供需关系。在这方面，需求似乎远远超过了供给。你可以看看SpaceX和其他公司的签约情况，每瓦特的变现率正在上升。而且，这还是基于用户数量相对较少的基础上。就像WhaleRock的Alex所说，全球只有不到0.2%的人在以一种主动的方式使用人工智能。我不是技术专家，但我正在一个虚拟机实例中使用500个CPU核心和5个GPU，全天候不间断。如果有更大比例的人群开始这样使用资源，我们很可能会长期面临资源短缺的环境。所以，我认为这是对投资回报率问题的积极信号。
▶ 英文原文 ⏱
But I think this year what we've seen is the opposite. And, you know, it's all comes back to supply demand. The demand side of the equation seems to be far outstripping the supply. Right. And I think you look at the deal signed by SpaceX and others, the monetization rates per watt are increasing. And look, that is on a pretty nascent small base of users. Right. Like Alex at WhaleRock, he has this great way to frame it. Less than 0.2% of people on Earth are actually using AI in an agentic way. Right. Right. Like I'm not a technical person, but I'm consuming 500 CPU cores in a VM instance, five GPUs 24/7. I mean, if you draw that out to any meaningful percentage of the population, I mean, we're going to be in, you know, this kind of shortage environment maybe for some time. So I think that is all positive for this ROI question.
人啊，Foxy，CPU和GPU的比例是一百比一？这是什么样的工作流程？当然，当然，当然。好的，好的。是的，我在精打细算。好，很好，棒极了。我还想说，那个比例是300比1.2或1.5，现在在物理上我们只能扩展到一定的生产能力，而且实际上我们也只能在这个程度上增加支出。然而，我们现在看到的情况却相反，人们愿意为这些代币支付更多。实际上，当每千瓦时的货币化从年初最高的200亿增加到现在的300亿，甚至是逼近400亿时，这种支付意愿正在增加。
▶ 英文原文 ⏱
Man, Foxy, a hundred to one CPU to GPU ratio? What kind of a digit of workflow? Of course. Of course. Of course. Fine. Fine. Yes. I'm being smart with my spend. Good, good, good. Excellent. I will say also that ratio of 300 to one point, you know, call it 1.2, 1.5. There is also a rate that now physically we can only expand how much we can produce and how much we can actually increase that spend by. Whereas we're seeing the opposite right now on the willingness to pay for these tokens. Right. And actually like when the willingness to pay for these, when the monetization per gigawatt is actually increasing from, you know, call it like 20 billion in the best of cases for, at the beginning of the year, to now like 30 to even pushing 40.
每吉瓦。每吉瓦。所有这些都是很高的固定成本基础。但现在这一切就像是纯利润流入。对吧。而且实际上，随着规模的增加，大家愿意为这些付钱，你知道，现在所有这些都因我们讨论的内容而有所规定，比如开源的部分有多少、不是开源的有哪些、以及所有不同的流转。对吧。但实际上，随着我们攀升这条曲线，收入可能确实会大大超过我们的固定成本基础。我认为这就是为什么所有实验室都在加速的原因，因为他们都看到，如果我们沿着这条曲线继续发展，可能在三年内，我们的电脑就会严重短缺。
▶ 英文原文 ⏱
Per gigawatt. Per gigawatt. All of that is a very heavy fixed cost base. But all of that is like pure margin flow through now. Right. And you're actually, you know, as we scale like the willingness to pay for all of this, and now all of this stipulated by like, you know, everything we're talking about of like how much is open source versus not and all of these different flows. Right. But really like as we're climbing this curve, you know, the revenue is, might actually outstrip our fixed cost base by a significant amount. And I think that's why all the labs are pushing, you know, the gas of the pedals because they all, they all see like within, if we continue this curve within like three years, you know, we're just going to be so short on all the computers.
好的，我很抱歉。这是一个很好的观点，就像你在做这些决定时所想的那样。是的。在2025年11月，你以为会得到某种回报。而今天，你可能得到了三倍的回报。的确。在Tropic公司，他们根本没想到能接近收支平衡。是的。在这个曲线上是这样。人们称之为“意外盈利”，因为他们本来想在计算上花更多的钱，但实现起来比较困难。
▶ 英文原文 ⏱
Go ahead. I'm sorry. Like, it's a great point. Like you thought you were getting, when you made these decisions. Yes. In November of 2025, you thought you were getting a certain return. Yeah. You may be getting triple that return today. For sure. At Tropic, no way, no way did they think they were going to be anywhere close to break even. Yeah. Right. In this part of the curve. And the reason, like I called it accidental profitability that, you know, people have been talking about that because they want to spend a lot more money on compute. They just had a hard time doing it.
现在，也许借助SpaceX，你知道，他们可以把其中一些资金花在其他地方。对我来说，这是一种根本性的变化。反对前沿实验室的第一个论点是他们永远不会产生收入。好吧，然后这个论点被推翻了。接着就变成，即使他们能产生收入，毛利率也会很低，他们永远无法盈利。但这种说法也被推翻了。现在，我认为人们开始退而求其次，他们说这些公司收费过高，这是极限榨取。我一个好朋友Tamatha说，这些支出根本没有投资回报率，这一切都是极限榨取。
▶ 英文原文 ⏱
Now, maybe with SpaceX, you know, they could take some of those dollars and go spend them other places. But that to me is, you know, a fundamental change. The first argument against the frontier labs was they'll never generate revenue. Okay. And then that got blown up. Then it was like, even if they generate revenue, it'll be really shitty gross margins and they'll never be able to make money. And then kind of that's blown up. And, you know, I think now, you know, people are falling back and they're saying, well, they're overcharging. This is token maxing. My good friend, you know, Tamatha said there's no ROI on any of this spend. It's all this token maxing.
我们所有人当然都知道，当有人投入这么多资金时，就像我们曾经有的高度计一样，我们并没有在每一美元上做到最优消费。但问题是，为什么有数百万个独立的企业，无论是小型、中型还是大型企业，以及数百万的消费者，都在选择同样的做法呢？他们并不傻。这些都是理性的经济行为者，他们同时都在说：“我想这样做，因为这让我的生活更好，这让我的生意更好，等等。”对我来说，这正是为什么我认为这个收入能够持续的最佳证据。
▶ 英文原文 ⏱
My best evidence for why we all know, of course, when somebody puts on this much spend, like we had altimeter, we're not optimally spending every single dollar. But the question is, why are millions of independent businesses, small, medium, and large? Why are millions of consumers all choosing to do the same thing? They're not dumb. These are, you know, rational economic actors that are all simultaneously saying, I want to do this because it makes my life better. It makes my business better, et cetera. To me, that is the best evidence as to why I think this revenue can continue.
好的。我完全同意你所说的，Clark。因为在通胀环境下，你确实应该拥有重资产的企业。同时，代币价格在上涨，供需关系也在趋紧。在我们即将结束这段讨论时，我想说，你和我已经从事这行很长时间了，加文，有几十年了。也许你相比我从事的时间更长，即使我比你年龄稍大一些。我总是喜欢做市场检查，因为我发现很多时候，分析师在这些场合中会谈论一些他们自己偏好的观点。
▶ 英文原文 ⏱
Yeah. And Clark, I think like the point you made is dead on because, I mean, you want to own asset heavy businesses in inflationary environments and token pricing is going up and supply demand is tightening. So, totally agree. You know, as we begin to find our way to the exit ramp and wrap here, one of the things I, you know, you and I have been doing this for a long time, Gavin, a couple of decades. You may even sketch longer than me, even though I'm a little bit older than you. You know, we have, I always like to do a market check because I find a lot of time that analysts come on these things and they talk their, you know, talk their book.
"你知道，有很多人，包括散户投资者，都会关注这些事情。然后就会想，我们到底怎么看待这些问题呢？所以，我总是用小、中、大来形容。比如，我具体在做什么？我的投资敞口是小的、中等的还是大的？看看今年市场的发展，半导体行业表现得非常出色。就像，你做了这么长时间的投资，从未见过这样的情况，对吧？从未见过像今年这样整体翻倍甚至三倍的现象。但市场中也存在着巨大的分化。比如，互联网板块下跌了16%，软件板块下跌了8%。"
▶ 英文原文 ⏱
And, you know, there are a lot of people who listen to these things, retail investors and others. And it's just kind of like, what do we really think? And so, I always characterize as kind of small, medium, and large. Like, what am I doing? Do I have small exposure on? Do I have medium exposure on? Do I have large exposure on? You know, and if you look at what's happened in the markets, semis ripped this year. I mean, like, you've been doing this a long time. I've never seen it before, right? I've never seen, you know, the doubles and the triples across the board like we saw. But there's been huge dispersion, right, in the market. Internet's down 16%. Software's down 8% on the year.
你知道，SPY和纳斯达克指数确实上涨了，但主要是因为其中与人工智能和计算相关的成分股表现优异。而整体市场其实表现得不算太好。同时，如果你投资的是我们所选择的那些东西，我们的收益都相当不错。我想，如果今年Anthropic的收益没有出现，因为这一直是市场的悬而未决的问题，那么整个市场今年可能都会下跌，对吧？但最终收益出现了。我们在四月和五月经历了几个月的巨大增长。对我们来说，由于价格上涨得很多，加上我对地缘政治和经济大环境短期内通货膨胀的担忧，持有一定的谨慎态度。
▶ 英文原文 ⏱
You know, SPY and NASDAQ are up, but really up because of their components that are related to AI and compute. And so, the market itself has kind of struggled. Meanwhile, if you were in the stuff that we were invested in, we've all done pretty well. I think, you know, I've said it a couple of times. I think if the anthropic revenue had not shown up this year, because that was the overhang on the market, I think the whole market could be down this year, right? But that showed up. You know, we just had these huge months in April and May. For us, you know, because prices came up so much, because I have some worry about, you know, geopolitics, the macro backdrop with, you know, with what's going on with inflation in the short run.
就像在这个市场中需要一点整合来回答一些问题，因为现在期望值更高了。我们从我称之为对Altimeter来说较大的规模缩小到中小规模。对我们来说，事情从来不是全有或全无的，而是看在某个价格下的风险回报。我们认为这可能是走向更高水平的整合期。我很好奇你是如何管理账户的，像一个投资组合经理一样是怎么思考的。同样，我总是将股票、市场想象成赛跑者。
▶ 英文原文 ⏱
And just like, you know, needing a little consolidation in this market to answer some of these questions, because now expectations are higher. You know, we dialed back from what I would call large for altimeter to something kind of like medium-small. Again, it's never all or nothing for us. It's like, what is the risk reward at a given price? And so we think this is a, you know, maybe going to be a period of consolidation on way to much higher highs. Curious just how you run the book, how you think about it like a portfolio manager. Very similarly, man. I always think stocks, the markets, I imagine them as runners.
是的，好的。比如在22年的时候，那名跑者已经下降了。它曾经充满活力，兄弟。那是痛苦的，真的很痛苦，一点都不好玩。是的。但从那之后，市场中有很多积蓄的上涨空间。对，特别是在最近的两个月，市场攀上了一个非常陡峭的高峰。很多公司，尤其是半导体公司，像英伟达和博通，出人意料的是，它们一直表现落后。完全是这样。不过，我在X上看到很多关于寻找下一个瓶颈的讨论。我认为，那是上一个阶段的游戏。是的，是的，那场游戏已经结束。很多股票已经不仅仅是在爬山或小丘。
▶ 英文原文 ⏱
Yeah. Okay. And like in 22, that runner had gone downhill. It had a lot of energy, man. It was painful. It was painful. It wasn't fun. Yeah. But coming out of that, there was a lot of kind of pent up upside in the market. Yes. And, you know, the market, particularly the last two months, it has run up a very steep hill. And a lot of companies, semiconductor companies in particular, you know, ironically, you know, Nvidia and Broadcom, they have been laggards. Totally. And so, but a lot of these, like I do see a lot on X about finding the next bottleneck. I think that was the last game. Yes, yes. That game is over. You've had a lot of stocks that forget climbing a mountain or a hill.
是的，他们直接爬上了一座悬崖。是的，没错。他们累了，是的，他们需要休息。是的，我们看看。他们是否就在攀爬到的崖顶休息？是的。他们会在安全带中稍作停留吗？我们看到上周，我们看到了一些调整。或者他们需要先下山一段时间？是的，我们拭目以待。但我和你有相似的想法。不过我认为，市场是有季节性的。是的，确实存在关于通胀和利率的真实担忧。今天早上的消费者价格指数是多少？是4.2。我想核心数据是0.2，而不是0.3，所以稍微好一点。但显然我们又超过了4。是的，而且短期内核心个人消费支出等方面有压力，而且还有一些未知的未知。
▶ 英文原文 ⏱
Yes. They've gone straight up a cliff. Yes. Okay. Yes. They're tired. Yeah. They need to rest. Yeah. And we'll see. Do they just rest at the top of that cliff they climbed? Yeah. Do they hang out in their harness for a while? We've seen the last week. We've seen, you know. We've seen some. Some retracement. Or do they need to go downhill for a bit? Yeah. We'll see. But I'm thinking very similarly to you. But it is, and I think there's, you know, the market is seasonal. Yes. Real concerns around inflation and rates. What was CPI this morning? It was 4.2. I think we added core came in at like 0.2 versus 0.3. So a little bit better. But, you know, clearly we're above 4 again. Yeah. And there's short-term pressure on, you know, core PCE, etc. And we have some unknown unknowns.
但是市场，我的意思是，如果我今年告诉你这些事实：我们将与伊朗发生战争，石油价格将达到100美元，CPI将继续上升，互联网行业将下降15%，软件行业将下降8%，那么你可能会说，你绝对不想与这样的市场有所牵连，对吧？然而事实是，在我们所参与的领域，市场表现相当不错，因为世界低估了人工智能的收入和对计算资源的需求量。有趣的是，尽管有各种担忧和我们即将进入季节性疲软期，但是人工智能在过去三个夏季中实际上都是有季节性的。这很有趣。
▶ 英文原文 ⏱
But the market, I mean, if I had told you the fact pattern for this year. That we're going to be in a war with Iran. That, you know, oil was going to be at $100. That CPI was going to be creeping back up. The internet was going to be down 15%. Software was going to be down 8%. You would have said, I want nothing to do with that market. Right? And here we are. The market's done pretty good in the stuff that we traffic in because the world underestimated AI revenues and underestimated the amount of compute that was going to be needed. It's odd to say, you know, we're heading into a seasonally weak period with all these fears. Right. AI has actually been seasonal for the last three summers. That's interesting.
好的。令牌的消耗量有点停滞，放缓了。这是因为大学生是AI的重要消费者，但他们使用AI的频率并不高。希望他们都在用AI学习，而不是作弊。当然，事情可能会发展成这样，也可能不会因为没有巨大的AI。我的15岁孩子正在建立多代理系统，制作一个SpaceX的模型。他星期五会跟我一起去交易所参加SpaceX的IPO。不过他需要在我们去交易所之前，利用AI代理建立一个DCF模型。他对此非常着迷。
▶ 英文原文 ⏱
Yeah. Token consumption has kind of plateaued, slowed down. And that's because, you know, college kids are big AI consumers and they don't use as much AI. You know, hopefully they're all using it to learn and not cheat. But that may happen. It may not happen because of a gigantic AI. My 15-year-old is building swarms of agents, building a SpaceX model. He's going to the SpaceX IPO with me at the exchange on Friday. But he had to build an AI model. Using AI agents, he had to build a model, a DCF, before we go to the exchange. He is mesmerized.
他绝对是个与众不同的人，他正在创造非凡的东西。因此，他是那种即使在夏天也不减少计算力使用的年轻人，反而在增加。他不断地投入更多的计算资源。不过，如果令牌的使用达到一个平稳状态，如果开源项目占据了一部分市场份额，那就会有一个显示消费和定价趋势的硅数据指数。我认为在过去两周里可能有所转变，人们倾向于选择更便宜的开源令牌。我觉得那些认为这种数据趋势不利的人并没有真正理解这个情况。
▶ 英文原文 ⏱
He is absolutely, and it's extraordinary what he's building. So he's one kid who's not using less compute in the summer. He's burning it. He's burning it. Yeah, but you know, if token consumption plateaus, if open source takes some share, there's a silicon data index that has showed, which is an index of kind of consumption and pricing. I think there may have been a little bit of a shift over the last two weeks to open source tokens that are cheaper. I think people looking at that data as bearish or not understanding it.
尽管如此，我认为还是有理由让人环顾四周，小心行事，多加思考。我总是假设有危险正在向我袭来，所以要时刻保持警觉。通常都是那些你没看到的危险真正击中你。所以我尽量让自己快速反应。市场可能需要一个喘息的机会，但当我想到Noam Brown所说的话和看到Fable的能力时，很难对未来太过悲观。在我看来，Noam Brown和Fable是我们这一代最卓越的两个人才。
▶ 英文原文 ⏱
But nonetheless, like I just think there's reasons, you know, to look around, be careful, be thoughtful. I always assume a bullet is coming for me. Head on a swivel. It's the bullet you don't see that gets you. So I'm trying to spin as fast as I can. But yeah, the market may need to take a breather. But man, when I think about what Noam Brown said, and when I see the capabilities of Fable, it's just hard for me to get too bearish. I mean, like, to me, we got two, I think, of the most extraordinary guys of, you know, the next generation, you know, sitting in the room.
在Altimeter，我们对你们的工作始终充满深深的敬意。我总是很感激你们给我发信息，讨论我们所做的工作和发表的内容。不过，对于那些新加入这个行业的人来说，他们可能会觉得情况一直都是这样的，对吧？就像这种创造性破坏的急剧加速，规模优势的快速增长。我一直相信这会成为现实，但从未想到它会以如此快的速度实现。
▶ 英文原文 ⏱
We have at Altimeter, we have deep admiration for the work that you guys do. I always appreciate when you send me a note about the work that we do and we publish. But for the guys who are newer to the business, they might think this is the way that it kind of always was, right? And like this line, the steepening of the line of creative destruction, the steepening of the line of, you know, scale advantages. I always believed it was going to be true. I never thought it would be true at this rate.
我昨晚回来了。在过去的七年里，我们为Mag-7增加了一万亿美元的收入。要达到第一个万亿美元，花费了超过20年的时间。在最近的七年里，我们又增加了一万亿的收入。而这一个万亿美元增加了17万亿美元的市值。现在的预测是，在未来四到五年里，我们将在仅仅三家公司——SpaceX、Anthropic和OpenAI身上再增加一万亿美元的收入。不是七家公司，而是三家公司，而且只需要一半的时间。
▶ 英文原文 ⏱
I went back last night. In the last seven years, we've added one trillion of revenue to the Mag-7 in the last seven years, okay? To get to a trillion, to get to the first trillion, you know, took over 20 years. In the last seven, we added another trillion. And that added 17 trillion in market cap, that trillion dollars, okay? The forecast now that we're going to add another trillion of revenue in just three companies, SpaceX, Anthropic, and OpenAI over the next four to five years, okay? Like not seven companies, three companies, and in half the time, right?
所以，我想说，我们在未来的道路上会遇到一些坎坷。我知道情况会是这样的，但我们的目标会更高，因为这个机会的影响力巨大，能够转变全球GDP的5%、10%甚至15%。对此我深信不疑，而全球GDP的10%就是10万亿美元。参与这样的未来真的让人激动，和你们一起做这件事很有趣。我认为我们需要努力工作，确保美国在这个过程中获胜，同时要更新社会契约，把每个人都带上，让大家都能享受这个旅程。这确实是一个令人振奋的时刻，与你们一起做这件事真的很有趣。
▶ 英文原文 ⏱
And so I would say that, you know, we are going to have bumps in the road. I know that it's going to be like this, but we're going to higher highs because the size of the prize, this is going to transform 5%, 10%, 15% of global GDP. There is no doubt in my mind, and 10% of global GDP is $10 trillion. It's an exciting future to be a part of. It's fun to do it with you guys. I think we're going to have to do our work to do the things to make sure America wins, and that we evolve the social contract, keep everybody, you know, lift the floor, take everybody with us on this ride. But it's a really exciting time to be doing what we're doing. It's fun to be doing it with you guys.
是的，我只是想说，布拉德，谢谢你邀请我们。也感谢你在特朗普账户上所做的努力。我真的认为，让人们在很年轻的时候就拥有股份，对于美国乃至全世界都是非常重要的。他们会看到这些股份在他们一生中不断累积。这是你为世界做的一件伟大事情，所以谢谢你。
▶ 英文原文 ⏱
Yeah, I just want to say, Brad, thanks for having us. And thank you for what you've done with the Trump accounts. I actually think it's super important for America, for the world, to give people an equity stake at a very young age. They will see it compound over their lifetimes. This is a great thing you've done for the world, so thank you.
我完全赞同你所说的一切，比如对你和你的团队的深切钦佩，以及对我们公司之间友好合作和友谊的感激之情。我认识克拉克和福克斯，他们几乎一直在一起闲逛。
▶ 英文原文 ⏱
I'd echo all your comments, like deep admiration for you, your team, gratitude for the collegiality and friendship between our firms. I know Clark and Foxy, they hang out like all the time.
是这样的。人们认为你知道，在我们的行业里，有些人不愿意分享任何东西。我们的看法是，我们可以开源，但我们实际上只会打电话请教很少一部分人的意见，因为真正投入数千小时工作并有所贡献的人非常少。
▶ 英文原文 ⏱
Yeah, that's it. People think that, you know, and there are people in our business who don't want to share anything. Our view is like we open source it, but there are very few people who we actually call and ask their opinion because there are very few people who do the thousands of hours of work that we do, you know, that are adding to that.
你做到了，我们对此很感激，Gavin，你也是。我们对此感激不已。那么，在这充满爱的氛围中，我们就到此为止吧。感谢你的到来。谢谢。谢谢。
▶ 英文原文 ⏱
And you do it, and we appreciate that, and you do as well, Gavin. We appreciate that. So with that love fest, let's call it a wrap. Thanks for being here. Thank you. Thank you.