Thomas Laffont:4万亿美元的AI IPO浪潮即将到来……而我们从未见过这样的行情
Laffont认为,AI让独角兽经济更健康,但也极度集中。 自2024年9月以来,这一经济体增长了70%;由于融资公司数量减少、单轮融资规模大幅增加,单家独角兽获得的融资额自2021年以来增长了5倍。结果是一个K型市场,“幂律支配着我们的生活”(“the power law rules our lives”),错过赢家的代价持续上升。
一个由私募市场“Magnificent Eight”构成的组合——录音中列出了其中7家公司——如今总价值接近4万亿美元,可能引发前所未有的流动性浪潮。 Laffont点名SpaceX、Stripe、Anthropic、Databricks、Revolut、ByteDance和Anduril;他说,几乎每个成员的表现都超过了Magnificent Seven。若把预期中的SpaceX、OpenAI和Anthropic上市算在内,回流资本规模可能超过此前大约10年的总和。
OpenAI和Anthropic的扩张速度,已经足以挑战为它们提供资金支持的超大规模云服务商。 按照Laffont的假设,AI龙头的收入到年底可能超过AWS,到2028年甚至可能超过整个Microsoft,但他强调这只是预测。他对泡沫论的反驳很直接:“这些不是虚假公司”——它们拥有可观收入、惊人增速,而且据报道,Anthropic甚至已经实现过单月盈利。
SpaceX应被估值为一个不断升级的平台,而不只是发射服务商。 Laffont发现,发射频率与估值的相关性最高,但单次发射对应的估值也在上升,因为每次发射都推动业务从不可预测的合同收入,走向经常性星座收入、多个客户自有星座,最终进入空间数据中心等新应用。仅Starlink就可能对应全球电信商和服务提供商2000亿至4000亿美元的利润池。
本期节目的“10倍悖论”在于,规模最大的公司区间,历史上实现10倍增长的比例反而更高。Laffont的数据表明,独角兽晋升为十角兽的比例接近8%,十角兽晋升为1000亿美元公司的比例为8%-13%,而市值达到1000亿美元以上的公司中,已有31%实现过10倍增长。 他据此外推,万亿美元公司达到10万亿美元的概率可能高于30%。主持人质疑了一个显而易见的交易策略——等公司市值达到1000亿美元、甚至1万亿美元后再买入——因为拥挤需求可能让估值脱离熟悉的指标。
在被动资金冲过供给端之后,下一次公开市场检验可能还需要一段时间才能显现。 主持人提出“6个月加1天”可能是更适合判断的时点。Laffont欢迎做空者、政客和公开市场投资者的审视,但拒绝从极小样本中推断结构性低效:Claude Code之后,Anthropic已经变成另一家公司,而这一单一事件“改变了几乎整个行业的轨迹”(“dented the trajectory”)。从更长期看,循环使用的IPO资本可以为基础设施提供资金,也可能引发OpenAI与Anthropic之间的价格战,不过Laffont表示,双方的基础设施支出让这一结果并不明确。
1. AI通过集中化让独角兽经济更健康
Laffont的基准判断是:自2024年9月以来,独角兽经济增长了70%,大致追平公开市场涨幅;与此同时,AI连续数年在融资总额中占据越来越高的份额。
造就独角兽的“工厂”已经远低于2021年ZIRP时代的峰值,独角兽数量回落至接近疫情前水平。由于融资公司更少、单轮融资更大,单家独角兽获得的融资额自2021年以来增长了5倍:“独角兽更少了,但每一家融到的钱更多。”
集中度还在进一步收窄:前10家公司拿走了相当大比例的融资,其中Anthropic和OpenAI完成了超大规模融资。
他的健康度测试揭示了悬而未决的问题:在73家ZIRP前独角兽中,80%在20个季度内再次融资或退出;而2021年479家公司组成的 cohort 中,不到20%做到这一点。问题在于,2024年的AI公司最终会更像哪一批。
2. 一个4万亿美元的私募指数正接近流动性事件
Laffont暂称其为“Magnificent Eight”,画面中的名单包括SpaceX、Stripe、Anthropic、Databricks、Revolut、ByteDance和Anduril。这个组合横跨航天、金融科技、AI和互联网业务,总价值接近4万亿美元,表现“远远击败”Magnificent Seven。
2026年的现金回报正在恢复,尽管还没有回到2021年的水平。Laffont表示,若加上预期中的SpaceX、OpenAI和Anthropic上市,仅这3家公司就可能超过此前大约10年退出交易的总和;一个消耗现金远多于返还现金的生态,正在显著走向平衡。
主持人向LP提出了一个令人不适的含义:等公司达到1000亿美元后,再涌入最不脆弱的赢家。Laffont承认,这一策略过去5年有效,但关键问题是未来5年是否仍然有效。他也欢迎公开市场成为这些公司的终极测试,以及对它们进行“强力消毒”的机制。
3. SpaceX每完成一个发射规模阶段,价值都会上升
发射频率是与SpaceX估值相关性最高的变量,但Laffont更关注单次发射对应估值的上升。他的解释是:“SpaceX的商业模式质量会随着发射次数增加而提升”,因为后续发射创造的是经常性收入,而不只是证明火箭能够工作。
业务路径从政府主导、一次性且不可预测的发射合同开始,随后进入第一个星座,再发展到为希望“掌握自己命运”的企业、政府和军方建设多个星座。达到一定规模后,SpaceX会成为一个平台,并可能延伸至空间数据中心以及月球和火星应用。
Laffont“完全不知道”1.75万亿美元的IPO估值是否合理。他更确定的锚点是:Starlink的产品明显更好,而全球电信商和服务提供商的利润池估计为2000亿至4000亿美元;他认为,卫星驱动的设备可能在几年内实现随处通话。
更广泛的流动性问题带来一个战略风险:充裕现金可能催生类似网约车行业的OpenAI与Anthropic价格战。主持人认为,理性上双方应该在价格上竞争,但Laffont指出,双方的基础设施支出让这一结果“并不明显”。
4. 10倍悖论反映了对支配地位的反复筛选
Laffont将公开市场和私募市场公司放在一起分组,得到一条反直觉的阶梯:独角兽最终成为十角兽的概率约为8%;十角兽成为1000亿美元公司的概率为8%-13%;而1000亿美元以上公司中,已有31%实现过10倍增长。
Laffont据此外推,万亿美元公司达到10万亿美元的概率可能高于30%。他将这一递进归因于对复合优势和持久盈利能力的反复筛选;一位主持人则补充说,支配性企业可能会发现,市场规模远超预期。
Laffont不愿将其称为结构性低效,因为样本太小。Claude Code之前的Anthropic是“一家完全不同的公司”,之后则可能更像《基地》里的不可预测角色Mule。他确实认为,模型是商品这一说法已经“被相当彻底地证伪”。
5. 收入、记忆和半导体正在拓宽AI交易
Laffont强调了OpenAI和Anthropic的增长速度:从2025年1月开始,两家公司先后超过Workday、ServiceNow、Adobe和Salesforce,随后又超过Google Cloud和Azure。按他的预测,AI业务到年底将超过AWS,到2028年可能超过整个Microsoft。
Cerebras提供了一个关于耐心的反例:多年艰难研发、期间长时间没有新资本注入之后,一份来自OpenAI的大合同让其估值翻了5倍。Laffont将这一结果放在始于2024年峰值以来的一轮世代级半导体行情中。
每位用户对应的内存需求可能增长5倍,因为更有用的AI系统需要掌握关于个人或企业的大量信息。Laffont转述了别人给他的一个比较:芯片设计师可以向TSMC寻求制造帮助,但“如果我想制造内存,那就没有一家TSMC”。
Coatue估计,AI生态目前规模约为1400亿美元,今年达到3000亿美元,2027年再翻一倍。支柱包括消费者订阅、Claude Code和Codex等企业级突破,以及广告业务:据估算,Meta和Google约四分之一的广告已经获得AI支持,最终这一比例可能达到100%,对应1500亿美元规模。
Laffont最后将视野从软件扩展到更广泛的产业变革:Starlink冲击电信业,算力重塑半导体,数据中心改变能源方程式,自动驾驶挑战汽车公司的特许经营权,GLP-1改变食品、酒精和健康消费。“赢家的复合增长速度比以往任何时候都快”——而这还发生在超级智能到来之前。
Why do you think I waited to make my world podcast premiere for all in? All the ankle biters called and I said, "No, I'm just going to wait. [laughter] I'm going to wait till the besties call."
Coatue is one of the most successful hedge [music] funds of the last two decades.
$55 billion under management.
This is their flagship hedge fund.
The reason we decided to kind of get into this business is to find great entrepreneurs and find great companies.
And they're looking to raise a whole billion dollars more [music] to invest in AI.
We're in an idea business and when you have a truly revolutionary idea, it can get really big.
I hope to do something a little bit different. Besties, you've been on for a couple of hours, so you can take a break now for a few minutes. Sit back. We are going to show you some slides, and we're going to walk you through an update on the unicorn economy.
The markets are back. We can see that the unicorn economy, on average, is up 70% since September 2024. I think that's intuitive to a lot of us. But what's even more amazing is that the public market has really made the same move up.
If we look at the share of the unicorn economy relative to the NASDAQ, which had a significant move up since 2015, it's really plateaued over the past few years. I think that speaks to the performance of public companies like Palo Alto and others.
AI is dominating fundraising. What's interesting in this slide is that you can see its share continues to increase. For multiple years in a row now, AI has increased its share of fundraising. But the composition of that funding has changed.
If you look at the unicorn factory, which really peaked in the ZIRP era of 2021, we've now normalized at a much lower level, pre-COVID. So, mathematically, if you put both together, you can see that funding per unicorn has increased 5x since 2021. We have fewer unicorns, and each one is raising more.
Now, I'm going to spend a minute on this slide because it's really about the health of our ecosystem. The way you interpret this is: If you look at the green line, which is the pre-ZIRP-era unicorn cohort, of which there are about 73, you can see that 20 quarters after becoming a unicorn, 80% of them had either raised a new round or exited. I would say that's pretty healthy.
Now, if we look at the 2021 cohort, which is the red line, two things stand out. First, 20 quarters in, you can see that less than 20% had either exited or raised. But look at the number: 479 versus 73 in the prior cohort.
So now here comes this new cohort, what we'll call our 2024 cohort of AI companies, and the key question is: What will happen in the future? Which of these cohorts will they resemble the most?
We talked about how AI is concentrating the funding base of unicorns, but what we also see is that the top 10 are capturing a significant share of funding. So it's not just AI companies; it's a small number of AI companies, which probably makes sense, since we know that Anthropic and OpenAI are raising massive rounds.
What I like to think is that we have a new index. If we really thought about what the index of the future is—what, for now, I'll be able to call the Magnificent Eight, although that number is going to shrink as these companies go public—the first thing that jumps to my mind is, “Wow, what an incredible group of companies.”
Look at the diversity: SpaceX, Stripe, Anthropic, Databricks, Revolut, ByteDance, and Anduril. We have internet, AI, fintech, and space tech. I'd feel pretty comfortable owning this index, if I could, for the next decade-plus.
Obviously, the performance of this index has been incredible. It represents almost $4 trillion of value and has really crushed the traditional Magnificent 7. Almost every single one of these names has outperformed that index.
We'll go to the next slide. Another positive sign is that, if we look at the exits, they're thawing. One of the things we've talked a lot about with the besties over the years is that we know the unicorn economy is great at consuming cash, but how much cash is it really returning?
We need to have a balance between the amount of cash consumed and the amount of cash returned. That's how an ecosystem stays in balance. If we look at the exits, 2026 is actually on a pretty good trend—not quite where 2021 was, but pretty good. We still have half a year to go.
But that doesn't include 3 companies that we know will be coming public pretty shortly. SpaceX, obviously, in the next few weeks. We know Anthropic just today—the headlines hit that they've submitted confidentially for their S-1.
If you add up the totality of just those 3 companies, you can see that it's basically going to be more than the 10 years combined. Ultimately, if you remember—and you were there when I presented at the first All-In Summit in 2024—we knew our ecosystem was out of balance. We were consuming way more cash than we were returning.
That's a fundamental imbalance, and you can see that now, even before the liquidity events that I just mentioned, our ecosystem is significantly more balanced. That will continue to improve.
Part of it is that the growth rates of OpenAI and Anthropic are unlike anything that we've ever seen. If you look at this chart, just remember that it starts in January 2025. That was only a year and a half ago.
Just a few months in, these companies passed Workday, a pretty incredible HR company. Then it was ServiceNow. It was Adobe by the end of the year. Salesforce was on the way in January. Now they're even bigger than Google Cloud and Azure.
So what can that look like in the future? This is based on some assumptions and forecasts, but you can see that we estimate that not only is it bigger than Azure, but by the end of the year it could be bigger than AWS and potentially bigger than all of Microsoft by 2028.
Now, these hyperscalers aren't sitting still. They're seeing the disruption. But they're actually doing more than seeing it; they're funding it. If you look at the ChatGPT moment that we know happened, look at how much these companies—the largest in the world—have invested in enabling and creating this change. It's truly unprecedented.
I know a lot of people are going to talk about SpaceX, so I thought I would share a little bit of how we, as investors, think about it. That way, as you think about whether it's a stock you want to own or you just want to seem smarter at a cocktail party, you can benefit from our knowledge.
The first thing that pops out when we look at and study SpaceX is that the number-one driver correlated to its valuation is the cadence of launches. Intuitively, that makes sense. If your business is the launch business, the more you launch, the higher your value should be. I think we see that in the data.
But there's another fundamentally different ratio that I'm going to point you to. What if we took the valuation and divided it by the number of launches? What would that look like?
You can see that it was in a fairly fixed range for a while, and then it really started to move up. We believe that markets are rational, so we started thinking: Why is the market valuing SpaceX higher on a per-launch basis when it's launching more than when it was just starting out?
My fundamental view—and we'll call this our Coatue framework—is that the reason is that the quality of SpaceX's business model increases the more you launch.
In phase 1, which we call pre-constellation, you're just trying your rockets. We know rockets are hard. Maybe you have a few government customers, and that's a one-time-revenue business that's unpredictable.
Then you get into your initial ramp, and now you might have 1 constellation. Why is a constellation important? It's an end market and a recurring-revenue business. The more satellites you put up, the more subscribers you have, the more revenue you generate, and so on.
Now you can move from ramp into scale. You don't just have 1 constellation; you have multiple constellations. Ultimately, we believe that a wide variety of companies, governments, and militaries will want to own their own constellations so they can control their own destiny.
Now you move into being a scaled business, which ultimately becomes a platform. We know how valuable these platforms are in this technology age. A platform means not only do you have many more customers in your core business, but you also have new businesses.
It could be space data centers. It could be the optionality of the moon and Mars and other space applications.
We know that one defining feature of this era has been how quickly these companies are scaling. If we look at the PC, the internet, or mobile, Anthropic in particular is scaling like no other company that we've ever seen.
This was an interesting analysis, and it's what I'm curious to discuss with the besties. We looked at essentially 3 buckets of companies and asked, “Within each bucket, what is the likelihood that you will have a 10x?”
As an investor—not a seed investor like J. Cal, but as growth investors—a 10x is pretty good. They're hard to find.
The data showed us that if you're a unicorn, the odds of you one day becoming a decacorn are about 8%. If you're a decacorn, meaning you're over $10 billion, the odds of you becoming a $100 billion company aren't much better: 8% to 13%.
But how interesting is it that if you're a centacorn—$100 billion or more—and, by the way, we're including public and private companies, you now have a 31% chance of having had a 10x?
This, in my opinion, flies in the face of what maybe we would have expected. If we look at how quickly these companies are creating value, this is a chart that I added at the last minute because the data is so fresh. You can see that it typically takes multiple years to go from $500 billion to $1 trillion in market cap.
Well, something happened very recently in the public market, which is that not only did we have 3 companies do it in the same year, but we had 2 companies do it in a matter of weeks. So, we can talk about what conclusions to take from that.
Now, even as these companies were scaling incredibly quickly from $500 billion to $1 trillion, we had other companies take a long time to succeed. Now, this is a company called Cerebras that just went public, so I thought it would be a good candidate. I was very proud to be a board member for a long time and led the Series B. But if you look at the company's funding history, you can see why I put the little construction icon: It took a long time, and there were some dark periods—multiple years of no new capital and a hard grind to develop their technology—all of that time leading up to a massive OpenAI contract, which then quintupled the value of the company.
But we know Cerebras has been successful, and frankly, it's not just Cerebras. Semis are on a generational run. I was just talking about this with my friend Brad Gerstner earlier. This is just since 2024 at the All-In Summit. You can see how much the semiconductor industry has outperformed the index.
What will happen in the future? Well, 1 takeaway from having listened to a lot of speakers this morning is that there seems to be wide agreement that the more an AI system knows about your business or you as a user, the more useful it is. You want to know, when you go and book a restaurant, that it already knows your preferences—whether it's what time you like to eat or what food you like to have, et cetera. So, we think ultimately that in this era, the amount of memory per user could quintuple just based on the demand these AI systems are requiring to provide their services.
That helps explain why we've seen some of these moves in these memory companies. And then I want to finish on a point that I think has a lot of controversy: Where's the revenue? If we remember over the past 12 to 24 months, there's been a lot of discussion about whether there is revenue, whether there is ROI, and what it is associated with. So, we tried to look and see what the size ultimately of the AI ecosystem is. We believe that it's about $140 billion today. It'll be about $300 billion this year, and it'll double in 2027.
So, where is that revenue coming from? Well, if we break it down, we can see we estimate 3 key pillars to this industry. 1 we know: consumer. The number of subs times an ARPU gives you your consumer revenue. 1 that I think a lot of people forget is ads. We estimate currently that about a quarter of ads served by Meta and Google are AI-enabled. We think that penetration will eventually go to 100%. That's $150 billion.
And then obviously, we all know about the breakthroughs in enterprise and what Claude Code and Codex are doing inside of those businesses. So, if you add all these together, you get a good sense of the size of this ecosystem.
This will be my second-to-last slide. 1 thing that's different to me about this era versus the prior eras in which I was an investor is that almost every sector of the economy is being transformed at the moment. We know some of the obvious ones, software, but look at telco. I believe that within a few years, Starlink will power a device that will actually enable you to make a phone call anywhere in the world.
We think that's a solved problem, but every time we get a dropped call, we get reminded that there's a better technology out there. So, back to Nikesh's framework on profit pools, I think the Starlink profit pool is the global telco profit pool of broadband and wireless. We know compute is driving massive changes in semis. We had senators earlier telling us how data centers have changed the energy equation in Pennsylvania.
Just think about the auto business. I'm sure a lot of us followed what happened to Ferrari last week, trying to introduce new electric and autonomous technology. That begs the question: What is the future of that franchise in an autonomous and electric world? I think the response to that car fed into this narrative. And then obviously, in consumer, we know GLP-1s are having a profound impact on food and alcohol consumption, diet composition, and wellness.
So, if we put all that together, what are our takeaways? My 1st takeaway is that the new unicorn economy is healthier, and we really have AI to thank for that. The winners are compounding faster than ever, which means the cost of not being in a winner is higher than ever. Disruption is impacting every part of the global economy. And, by the way, we don't even have superintelligence yet.
If I think back, it was about 2 years since my last All-In Summit, and I started thinking, “Gee, what could this look like in 2 years?” We know it's going to be a really interesting time, and thankfully, we have a great group to help us navigate what the next 2 years will look like. We're going to give this a title: “The power law rules our lives.” The power law rules our lives. All the great gains are being consolidated into small numbers of companies, but we're still seeing strength in those.
How do you see the private-market ecosystem—the game on the field—evolving because of companies staying private longer and these extraordinary outcomes? Obviously, I operate in the earliest stages. You have people who are doing Series A's, like Craft Ventures. You have yourselves dipping down into private, but I was talking to Brad Gerstner, who you discussed earlier. He was like, “I have to figure out where to put my time.” We have early-stage, and they do obviously public like yourselves.
And then add to that, you have people like Andreessen Horowitz maybe going for the average in a major way and indexing venture. What is the playing field going to look like for people who are LPs, angel investors, and venture firms? How does this all sort out into a cohesive strategy over the next decade or 2? Because clearly, the private markets are operating much differently than the playbook 20 years ago.
Yeah, so I think the 1st breakdown I would submit is on the positive side of the ledger: The outcomes are big, right? We're seeing outcomes that we never thought possible in private companies, and I think that's good just generally for our ecosystem. So, we have big outcomes. It's really why I wanted to show that SpaceX slide. It was somewhat counterintuitive to me in the launch business: Why is it that the company would be valued more as it launched more?
So, I think at least we have a number of big outcomes. And those outcomes will be public within, it seems like, a 12-month period. If I think about the ZIRP era, where the outcomes were smaller and companies were not going public, I think at least in this era, we have big outcomes and a desire for these companies to go public. I think both Anthropic and OpenAI are publicly saying that they want to be public. So, I would say that's good.
I'd say the biggest issue is that it seems like we're talking about K-shaped dynamics and power law in every aspect of life.
Yeah.
And it seems like that's the case in startups as well. So, we've seen, if you looked at my centacorn slide, we've really been stuck at this number for a little bit now. So, I think, JCal, the point that you're asking is: If we were to see no new centacorns in the next decade—we've basically not seen any new ones in the past couple of years—I think that's going to be a warning sign for us.
What does this mean for where capital allocators should be thinking about putting their money? Because what you're showing here, a rational person who's an LP, would just say, “Wait for whoever gets to $100 billion and YOLO every dollar you can in there,” because it's the most sure thing, it's the least brittle, it's the least amount of effort, and it's the quickest return.
But as we know, supply and demand equal valuation. These valuations are disconnecting from any valuation metric we've ever had. We had it explained to us today by Bill Ackman, I think quite accurately. You're making venture investments in trillion-dollar companies and giving them 50-times-revenue, 100-times-revenue valuations. So, talk a little bit about where people should rationally, as a limited partner, as a private investor, a high-net-worth individual, or an ultra-high-net-worth individual, be putting their money to work. And do you worry about everybody racing to be in 3 names?
Yeah, look, that obviously was the right strategy for the past 5 years. The question is about the next 5 years.
Correct.
Right? So, the 1 pushback I would have just on the valuation argument is that these are not fake companies.
No, absolutely not.
I think we have to remember the bubble of 2000. I also remember 2021, right? These are companies generating substantial revenue at scale that are growing faster than anything we've ever seen. So, these businesses are real and they're performing, and I think it was widely shown that Anthropic even had a profitable month, I believe is what was reported. So, they're also profitable.
But ultimately—and I think Chamath, you agree with this—the public market is the great test.
Equalizer.
Yes.
Yeah.
At scale, it will be the great antiseptic. It will not care about my presentation or anything else. And so, I love that. I love that these companies are going to have to face the scrutiny, both SpaceX, OpenAI, and Anthropic, of the market, right? And ultimately, I'm a big believer in the market. So, I'm very excited to see these companies go public and withstand the scrutiny of short sellers, pontificators, debaters, politicians, et cetera.
Let me ask you 2 questions on that.
The first is very tactical. Normally, we would say that the antiseptic or disinfectant happens on T+1 day, right?
Yeah.
Now the rules are changing. There’s going to be a lot of passive buying, so it’s going to move out that date because you’re going to have to wash through a lot of supply and demand. So that could maybe—
6 months plus 1.
6 months plus 1 is when you’d say we can really start to get a sense of what these companies are. Okay, so that’s a tactical question.
The more strategic question, Thomas, is: Do you think that there’s something structurally inefficient or wrong that’s allowing these compounders to accelerate at scale? Is that a market-efficiency problem, or do you think that’s just survivor bias and we shouldn’t look too much into that? How do you look at that?
I don’t want to read too much into it because the number of those companies is so small. Look at Anthropic, right? Anthropic pre-Claude Code was a completely different company from post-Claude Code. One event completely dented the trajectory of almost that entire industry.
So it’s hard for me to know whether these companies were like the Mule in the Foundation series—something that could never be predicted, just came out of nowhere, and was a one-time thing. We’ll see. I do think that the narrative of, “Oh, these models are commodities and these companies are going to get commoditized,” I think that’s been pretty thoroughly disproven now. Right?
As your asset base has swelled and you’ve expanded your strategy—you’re now doing data centers and many other things—how do you keep it all organized when maybe a slide like that would say, “Hold on a second. Maybe we should have just plowed $10 billion into Micron”? How do you balance that?
The reason I make a deck like this—and in some ways, I should thank you guys—is that when I do something like this for you guys, it is a tremendous amount of time from myself and our team, and we really want to present you with accurate information. So the past 2 weeks have pretty much been a full-time job doing this.
But for me, it re-anchors my conviction around what to do. I can’t go and listen to 1,000 people, and then I get distracted and I don’t know what I’m thinking anymore. So going back to these ground truths of numbers and valuation brings me back to a point of, okay, conviction.
For me, whenever I try and understand the world, I go back to, okay, what do I understand? I understand models. I understand numbers. Let me go back and peel this out.
What I think, hopefully, the deck will show is, “Look, there are substantial reasons why, right?” If you look at the trillion-dollar companies that became trillion-dollar companies in a matter of weeks, these are not fake companies. These companies have been around for decades, right? And they trade at the lowest multiple of earnings of the S&P 500 of almost any other company. So there is something kind of real happening.
There’s energy there that just got released.
Correct. And now it’s like, well, someone made a point to me on memory, right? They said, “Well, if I want to design a chip like OpenAI, I can go to TSMC. And I know it’s hard, but at least I have TSMC to help me. If I want to make memory, well, there is no TSMC.”
Right.
So what should the memory multiples be versus ASIC chips, as an example?
The wrath of Lina Khan can be seen clearly in this. And Zach, I want to get your input into how policy and elections matter when it comes to outcomes.
I don’t know if it was this chart, but the chart where you show the odds of each category reaching the next level—
Would you have predicted that, out of curiosity?
Very counterintuitive. Where my mind went was extrapolating one more: What are the odds that trillion-dollar market-cap companies get to $10 trillion?
The last one was 31%. I mean, it seems to me it would be like 50%, 100%. I don’t know. I’m thinking: Is it going to be greater than or less than 30%? And it seems to me it’s greater than 30% that are going to hit that.
Yeah.
It’s probably the filtering mechanism of what’s the compounding advantage or the durability of earnings of that company. For every step, you have a filter that says, “Do you have a compounding advantage? Do you have stronger durability of earnings?” And if so, you’re going to accelerate to the next phase.
It’s almost fundamental business-valuation analysis, like Ben Graham-style analysis.
To get to that level—that’s called the trillion-dollar club—you have to have a dominant business. And then the question is just: At what point do you hit saturation? It seems like all of these markets have ended up being so much bigger than anyone would have predicted.
Yeah.
And monopoly or government intervention, because fundamentally, if you think about the breakup of the Bell System, who knows where that would have gone over time? They could have had a monopoly on the internet. They could have had a monopoly on commerce. They could have had a monopoly on e-commerce, and on and on and on.
But as a trading strategy, what you’d like to do is have a bot that just starts buying up shares of a company once it hits $1 trillion. And actually, if you had done that, a lot of the—
I remember who was the first company to hit $1 trillion. Was it Apple?
I believe so, yeah.
Yeah, and then everyone was like, “Oh my God. Well, now there are, what, like 5 or something?”
A study showed that if you bought the Nasdaq over a 10-year period, you got like a 3× multiple, or something quite significant. You just rebalanced every year on the top 10 companies in the Nasdaq. So just buy the top 10 companies by market cap, and you outperform over a decade by like 3×.
Yeah, Thomas, why didn’t you do that? Maybe just the last question, so we make sure we wrap up about something that I think you are uniquely positioned to tell us: What happens when all this money gets distributed back? What do you think happens to your competitive dynamics? What do you think happens to entrepreneurial dynamics? What happens in Silicon Valley when $3 trillion or $4 trillion gets put back to GPs, then to LPs, and then the recycling happens?
Well, the first thing that comes to mind is I remember when David was so bearish on California real estate.
We’ll see whether this influx of capital—
Time to sell.
San Francisco homes are still—
Yeah, maybe buy the mausoleum.
Anybody interested in a 40,000-square-foot mausoleum?
Protesters not included.
The one thing I’ll say on SpaceX—and look, I don’t know whether $1.75 trillion is the right price for the IPO. Frankly, I have no clue. What I do know is that the global profit pool of telcos and service providers across the world is anywhere between $200 billion and $400 billion, depending on who you ask.
So you do have to think about a company that, just in its core business—which, by the way, wasn’t even around a couple of years ago—is addressing a profit pool of multiple hundreds of billions of dollars with a substantially better product. I think all of us, when we think about Starlink, know that it works all the time: no radio towers, et cetera.
So I go back to it, and I think it’s hard to know, Chamath, because we’ve never had anything like this before. The ultimate question would be: If you look a bit at the ride-sharing wars and the food-delivery wars, at some point that excess capital was used to have a price war.
Could we see a price war between OpenAI and Anthropic? That’s the question, right? If these companies have so much capital, is one of them ever going to pull a price lever to try and compete with the other?
Rationally, they should.
They should. So we might see things that we can’t predict today, where companies might say, “Well, I have my $200 billion of cash.”
Now, the issue is they’re spending so much on infrastructure, right? So it’s not obvious, but I do think we’re going to see some counterintuitive changes. You guys will discuss them on the show every week, and hopefully I’ll come back in 2 years and analyze what went right and what went wrong.
Honestly, I think what should happen is you should come back here every year, and we should get the benefit of—
Yeah, let’s lock it in.
We’ll lock it in.
We’ll pay—we’ll pay—we’ll pay—we’ll pay for the 2 years.
Pay for the 2 weeks of work that’s done.
Which we really appreciate, by the way. We really do appreciate the work and the effort. I know it’s a lot.
And it’s really great to have you bring this to the audience.
It also shows the power of sometimes slowing down—
Yeah.
—and meditating on the actual state of reality. It was incredibly grounding.
Incredibly rich coming from you. Incredibly grounding.
I think it’s a compliment or an insult. I’m not smart enough to know.
Compliment to Thomas.
Thank you. I’ll just say thank you.
To you, Chamath, for that incredible compliment, and for you, Thomas, for coming. Thank you.