Is AI a Bubble? | Gavin Baker on Data Centers, GPUs, and the AI Economy

0:00Are we in an AI bubble? I do not believe we're in an AI bubble today. I was, depending on how you look at it, the privilege and the misfortune of being a tech investor during the year 2000 bubble, which was really a telecom bubble. And I think it's really helpful to compare and contrast today to the year 2000. The year 2000 internet bubble or telecom bubble was defined by something called dark fiber. At the peak, 97 % of the fiber that had been laid was dark. Contrast that with today. There are no dark GPUs. The headlines change. The underlying questions don't. As AI investment continues to reshape the technology landscape, founders and investors are still grappling with the same core issues.

0:41Are we building too much infrastructure? How durable are today's economics? And where will the long-term value accrue? David George sits down with Atreides Management's Gavin Baker to unpack the AI boom, from GPUs and data centers to frontier models, software, and robotics. Whether you're an investor, founder, or simply trying to understand where AI is headed, this conversation offers a thoughtful framework for thinking about one of the greatest technology shifts in decades. And that brings us to our opening fireside chat. We're going to start with a taboo question right out of the gate. Are you ready for it?

1:21If AI is the biggest trend in the world right now, where is the evidence for it? Why is it only just beginning to show up in the economy? And as Andre Carpathi asked, are agents really just ghosts? To kick this off and to help us answer this question, please join us in welcoming Gavin Baker, managing partner and CIO of Atreides. Now, some of you may know Gavin as that really thoughtful guy on Twitter. Anytime some big piece of AI news comes out, I know more than a few people who count on Gavin to explain what the F is really going on. So a huge thank you to Gavin for being with us today. Joining him is our very own David George, General Partner at A16Z.

2:18Who knows what that music was from? Glad they got our pump-up music right. Yes. Battlestar Galactica, the original 1977 one. in case we have to all fight Cylons in a few years. Yeah, good segue into the topic, I guess. So thank you for being here. I always love talking to you. Same, really grateful to you for inviting me, grateful to your colleagues for having me here. I really look forward to the next two days. I think I'm going to learn a lot, so thank you. Yeah, okay, all right. So the big topic is AI bubble, kind of macro view of things. So maybe just to start with a couple stats to set the stage, and then I want to get your take on where we're at.

2:57So we have about a trillion dollars of data centers in the U.S. The plan is to add three to four trillion dollars in the next five years. Over the past three years, we have already built out in data center capacity a larger amount of dollars than the entire U.S. interstate highway system, which took 40 years just in terms of dollars. And that's inflation adjusted. OpenAI alone, I think, has more than a trillion dollars of deals set up that they've committed to. and we can talk about that. But at the same time, so those are all like big numbers on infrastructure and they're scary and they say, oh, bubble.

3:33And Google released a stat recently that they have seen a 150X increase in the amount of tokens processed in the last 17 months. So on the one hand, you've got this crazy, scary sounding build out. On the other hand, you actually have a bunch of usage that's happening. So are we in an AI bubble? I do not believe we're in an AI bubble today. I had, depending on how you look at it, the privilege and the misfortune of being a tech investor during the year 2000 bubble, which was really a telecom bubble. And I think it's really helpful to compare and contrast today to the year 2000. First, I think Cisco peaked at 150 or 180 times trailing earnings.

4:13NVIDIA's at more like 40 times. So valuations are very different. Most important, however, is that the year 2000 internet bubble or telecom bubble was defined by something called dark fiber. And if you're a veteran of the year 2000, you'll know what that was. But dark fiber was literally fiber that was laid down on the ground and not lit up. Fiber is useless unless you have the optics and switches and routers that you need on either side. So I vividly remember companies like Level 3 or Global Crossing or WorldCom would come in and they say, we laid 200 ,000 miles of dark fiber this quarter. This is so amazing.

4:50The internet's going to be so big. We can't wait to light these up. at the peak of the bubble, 97 % of the fiber that had been laid in America was dark. Contrast that with today. There are no dark GPUs. All you have to do is read any technical paper and one of the biggest problems in a trading run is that GPUs are melting. And there's a very simple way to kind of cut to the heart of all of this. It is a return on invested capital of the biggest spenders on GPUs who are all public. And those companies, since they ramped up CapEx, have seen, call it a 10-point increase in their ROICs. So thus far, the ROI on all the spending has been really positive.

5:35It's an interesting and open debate about whether or not it will continue to be positive. With the quantum of spend we're going to have on Blackwell, I personally think it will. But there's no debate that thus far, the ROI on AI has been really positive. And valuation-wise, we're just not... in a bubble. I couldn't agree more. The other thing that I would say is you can contrast the actual adoption and usage of the technology from then, right? The internet was actually really hard because you had to build a two-sided network. Like you had to build websites and then you had to get users and it's much more difficult.

6:11In the case of the AI tools, all you have to do is kind of light them up via API or turn on your website, chat GPT, and everybody has access to them, right? Built on top of cloud computing, on top of the internet, and you can get to instant distribution, a billion people right away. Absolutely. So the other thing is the counterparty. So you mentioned this, they happen to be the best companies in the history of the world, right? I think collectively, the people who are coming out of pocket, the writing checks for this CapEx, I think they collectively generate like$300 billion of free cash flow a year.

6:43Is that right? Some directionally? Round numbers. Yeah, and they have$500 billion of cash on the balance sheet. So whenever people are like, oh my God, it's a bubble. or is it going to pop? I'm like, I think it's kind of fine. I mean, it costs like$40 or$50 billion to light up one gigawatt. Yeah, if you're on NVIDIA chips. On NVIDIA chips. Yeah. Yeah. So, you know, there's kind of like an$800 billion buffer growing$300 billion every year. Yeah, I mean, free cash flow at some of them has begun to maybe, you know. Well, this goes to your point on return on invested cash flows. We should see that next year.

7:18A little bit of a mismatch in the build-out. But, you know, Larry Page apparently internally said, I'm happy to go bankrupt rather than lose this race. And I think that is the mentality for sure at Google and perhaps Meta. It's just seen as existential and you have to win. Okay, so lots has been written about these round tripping deals. So, because round tripping is a very scary concept from the internet build out. That was a big problem. What do you make of it here? It is objectively happening. Money is fungible. So NVIDIA, if they sign a deal with OpenAI, they can say, hey, you can't use our money to buy our chips, but money is fungible.

7:56But it's happening at a very small scale. I know this is like a crypto or blockchain. Exactly. And I think what is driving this isn't the need to finance GPU or data center purchases, but it's actually competitive dynamics. So NVIDIA's biggest competitor, it's not AMD, It's not Broadcom. It's certainly not Marvell. It's not Intel. It's Google. And more specifically, it is Google because Google owns the TPU chip. And this is by far, maybe perhaps today, the only alternative to NVIDIA for training and maybe the best inference alternative. And Google's a problematic competitor because they also own a company called DeepMind and they have a product called Gemini.

8:47And I think you could argue that they're the leading AI company today. I think they've taken 15 or 20 points of traffic share in the last two or three months, and that's just traffic to Gemini. It does not include search overviews. I suspect on an actual traffic basis, Google is bigger than OpenAI, Anthropic, anyone today. And that business is going to run on TPUs. And then we have three other labs that are relevant today. There's Anthropic, and that's an Amazon and Google captive. You know, Anthropic is really going to run on TPUs and Traniums. And so you're left with XAI and OpenAI at the forefront.

9:23And if Google is going to a lab like Anthropic and saying, I'm going to help you fundraise and give you chips for competitive reasons, it's very hard for NVIDIA not to respond. And as Jensen said, he thinks it's going to be a good investment. So I think the round tripping concerns are pretty overblown. Yeah. I mean, what NVIDIA really needs is they need Meta to get their act together or another American open source player to emerge or maybe some sort of detente with China in AI. Yeah. When people ask me about NVIDIA and all the moves and the round tripping, my reaction is everything they've done is completely rational.

10:02100 % rational. Yeah, long-term. Yeah, long-term. Some of the things they do may not have, yes, I have a return on capital as other things, but strategically, I think they're all kind of the right moves. Jensen's one of the two best CEOs, along with Elon, I have ever known. And I think he's playing a strong hand really well. Yeah. All right, so you started getting into the model companies. Let's just talk about the model. So we can come back to chips and memory and networking, because I want to get your take on that. But since we're on the model side, what do you think happens with market structure?

10:33Who wins where? Who are you most optimistic about? Where do you have concerns? So I think humility is an important virtue for an investor. And I'm just, if we're going to make an analogy and say that ChatGPT is to AI, has Netscape Navigator was to the internet. At this point in the internet boom, Google had not been founded. Mark Zuckerberg was in middle school. Travis Kalanick was in kindergarten. So it's just very early. So I think it's important to be humble about making high-confidence predictions at the application layer. It's one reason I think the infrastructure layer is often maybe a safe place to be at the beginning of one of these new technology waves.

11:18Well, actually talk about the role they play at the infrastructure layer, because there's a piece of them that obviously they serve as an infrastructure layer powering other application providers, and then they also have their own application. So I think I would draw a distinction. Yeah, I mean, that's most true of Google. But I think it's hard to have high conviction other than to observe. The internet was a very disruptive innovation. I think there's reasonable arguments that AI could be a sustaining innovation because the raw ingredients of kind of data, the capital to buy compute and distribution, which is what you need, all of today's biggest tech companies have all of those in spades.

11:56So as long as they execute well, hire good people and have a sound strategy, I think you could see it be a sustaining innovation for a lot of members of the Mag-7. On the other hand, I do think it's existential. And if you don't execute, IBM might be a good fate. Yeah, that's tough. Yeah, data distribution, compute, dollars, talent. Yeah, they have every right to win. Yeah, they have every right to win. And it seems now more than before they're taking it quite seriously. Yeah. Maybe Google in particular, but obviously Meta's making the dramatic moves they're making too. No, to me, ChatGPT was Pearl Harbor for Google, and we're going to see how they responded.

12:41And they're slowly starting to respond. Yeah. And then what do you think, what's your forecast for that sort of, the platform piece of their business, the infrastructure piece? What do you think, how do you think it shakes out in terms of like business model, market structure? So do you think they end up as high margin businesses like the clouds or like aircraft manufacturers? Or do you think they end up very competitive and low margin businesses like airlines? I don't think they'll be airlines, but you can, anybody can just look at the P &L, you know, of a SaaS company circa 2021 and 2022. And you see, you know, 80, 90 % gross margins.

13:23and the nature of AI because of scaling laws, Richard Sutton's the better listen, they're just more compute intensive. So their gross margins are structurally going to be lower, but that doesn't mean they can't be great businesses. I think it's going to be a long time before we see a truly kind of, an AI lab, a frontier lab with gross margins anywhere near SaaS or internet era margins. Now, their OPEX can be a lot lower and maybe that's how you square it, but just the gross margins are fundamentally different. And until scaling laws change and the importance of test time compute, things like that should change, which I don't see happening, they are going to be lower margin.

14:10Yeah. Okay, so let's talk about application layer. So you just kind of got into it a little bit with the SaaS businesses and I don't know if you've waded into this fight on Twitter, but it's sort of, you know, the like, you know, every few months it comes up and it's like, SaaS is terrible and it's dead and, you know, it's all going to go away. And then, you know, with Andre's Dworkesh interview he just did, it's, you know, like the market's reacting positively to it and it's like a whipsaw reaction. So what do you think happens with SaaS and software? You know, I think I, you know, first said probably in early 24 that I thought all of application SaaS might be a zero, different than infrastructure SaaS.

14:53I would say I have a more nuanced view now. And I think there could be some really big application SaaS winners, especially if you serve a more fragmented SMB customer base. Google is making it really easy, if you're a customer of theirs, to use your data and essentially make any SaaS app you want, and then your data isn't shared with anyone else. But the critical mistake that I think a lot of retailers made in dealing with Amazon is they looked at Amazon's margins and they said, we don't want to be in that business. And that was obviously a terrible mistake. And here we are 25 years later and, you know, Amazon has really healthy retail margins.

15:37And I worry that application SaaS companies are trying to preserve their existing gross margin structures. Because they believe that if their gross margins go down, their stocks will go down. It is definitionally impossible, given what we just discussed, to succeed in AI without gross margin pressure. and I do not know why they have concerns because we have an existence proof that a software company can deal well with declining margins. And Microsoft and Adobe to the whole AI thing came along. It used to be that companies were scared to go from on-premise to the cloud because margins were lower.

16:17Cloud margins are lower, they're still good. And Microsoft, they transitioned from on-premise perpetual licenses with maintenance to a cloud model. and it was a pretty good stock for 10 years. So I don't, if you're an application SaaS company, like what I would just say is don't be scared and look at declining gross margins kind of has a mark of success rather than a badge of shame or something to be feared. It's actually so funny you say that because whenever we have these discussions about companies, basically every company that comes to present to us is like, we're an AI company. And we always look at the gross margins and it's become like a badge of honor for them to actually have low gross margins?

16:58Because you're like, oh my God, people are actually using your AI stuff. But if you show up and you're like, I'm an AI company and it's like, I got 82 % gross margins. You're like, I don't think anybody's really using it. You're not. It's interesting. Yeah, if you're one of these public companies, would you rather have like 10 bucks of revenue with 90 % gross margins or 50 bucks of revenue with 60 % gross margins? Not hard. Like it's not that complicated. It's hard to do in the public market. It's hard to do in publics, but if you communicate it, you draw parallels to the cloud transition. I mean, I'm an investor and I would be excited about it.

17:27And I don't think I'm alone in the world. And then the big advantage these legacy applications SaaS companies have is they do have these really profitable existing businesses. And so you can run your new AI products at breakeven and catch up to the leaders, et cetera, et cetera. And I'm just surprised more people have not done that. Why are none of the public coding companies even trying to compete with Cursor? And the reality is, Christian, now they have a trillion tokens. And, you know, there will be a point where they have enough coding tokens that it's tough to catch them. But I think today, if you're a public coding company, and you said, I'm going to lean in, I'm going to run it break even, I have an existing business, I'm going to attach it to everything.

18:13Hey, you have a chance. And, you know, the prize is clearly really big. I see Martin is skeptical. Martin, you have a chance. I said a chance. I said a chance. It's like a dumb and dumber, you're telling me there's a chance, not like a real chance. You're telling me there's a chance. Yes, exactly. Yeah, exactly. I totally agree. We see it, we may, if we, Figma, for example, when they went out, they are extremely high gross margin and they're like, hey, we're going to pretty aggressively distribute our AI tools and our gross margins are going to go down. Investors asked a few clarifying questions and then they were like, oh, that actually would be a good thing.

18:51And so it's probably more people in the public markets aren't doing it. It worked out okay for them. It's working out well. Long game to play. What about on the consumer side, the application layer? So obviously Google was the portal to the internet, kind of still is the portal to the internet. And the whole business model was predicated upon taking some intent and directing you to someone else's website where they would do stuff with you. It's kind of not going to be that way. It already is not that way with AI. Although I tried the browser today and I tried to do some pretty basic shopping stuff and it's still some work to do.

19:27But I think it will get there. So what do you actually think happens with the sort of market structure of the consumer internet companies? Do they get subsumed into a component of a chatbot interface or do you think it's something else? So one, humility, hard to say. to, I would just say, I think the AI companies that have launched these AI browsers may come to regret it because there's something called Chrome that has whatever it is, 5 billion users. And if you're Google, you can just go look at what happened with Google Buzz. They are very cautious. They're currently in litigation with the government.

20:11And they could easily do this and probably do it even better but they didn't want to be first. So now you have two AI native companies with their own browsers, let them run for three to six months, get a little headstart. And then, wow, here we are. We had to do this. And I don't know how that's going to work. Maybe for the companies other than Google who don't own Chrome.

20:40I guess data and distribution is pretty powerful. Yeah, hindsight's 20-20. And the one thing I would say is I do think it's tough to bet against the companies with large existing user bases today. And I also think reasoning has fundamentally changed the economics of these frontier models. You know, pre-reasoning, I often said, if you are a frontier model without access to unique valuable data and internet scale distribution, you're the fastest depreciating asset in history. I think reasoning really changed that because the way RL works during post-training, having a big user base now kind of unlocks that flywheel that was at the center of every great consumer internet company where you have a good product, you get a lot of users, the users make the algorithm better, the algorithm makes the product better, and it just spins.

21:37And it's not quite spinning yet in AI, but you can squint and see it. And so I think that fundamentally changes the economics for Anthropic, for XAI, for OpenAI. But I mean, Mark Zuckerberg's trying hard. We'll see. Yeah, yeah, yeah. A lot of smart people in there now. Yeah, for sure. I think the worry is, and I think this is another interesting thing, is if you don't, like in a strange way, the Chinese open source model ecosystem is a godsend to any American company that's trying to catch those four leading labs. Because the problem is, if you don't have Gemini 2.5 Pro, or a later checkpoint of it, or a later checkpoint of Grok that we don't see, or a later GPT checkpoint, training the next model, you're at a big disadvantage.

22:31Oh, by the way, one thing I just want to say that drives me crazy is all these people who say that GPT-5 is the end of scaling loss. GPT-5 is a smaller model. It was not designed to be better. It was designed to be more economical for OpenAI and Microsoft to run. Any reference to GPT-5 and scaling laws is crazy. Yeah, sorry. Rant, rant over. We get the pedestal up here if you want. Yeah, exactly. Shaking your hand. Yeah, that'd be good. That'd be good. Do you want to talk about chips? Sure. So, okay, I know you love NVIDIA. Talk about, you know, your view of NVIDIA, AMD, TPUs, ASICs, and how do you think sort of market structure shakes out their, you know, competitive advantage that the various players have?

23:21Yeah, I think it goes, I think it is really, it's a fight between NVIDIA and the Google TPU. And then something that I don't think is broadly appreciated is the extent which Broadcom and AMD are effectively going to market together. NVIDIA is no longer just a semiconductor company, as I'm sure you'll hear from Jensen tomorrow. You know, it was a semiconductor company, then a software company with CUDA, now a systems company with these rack-level solutions, and now arguably, you know, a data setter level company with the, you know, level of architecting they're doing with scale up, scale across, and scale out, scale across networking.

24:02so the networking the fabric, the software, it's all important and what Broadcom is saying to companies like Meta is hey we will build you a fabric that can theoretically compete with NVIDIA's fabric which is a mixture of NVLink and either InfiniBand or Ethernet we'll build it on Ethernet, it's going to be an open standard and hey we'll make you your version of TPU which by the way took Google three generations to get working and you know what if your ASIC isn't good, you can just plug AMD right in. But I personally believe most of those ASICs are going to fail, particularly if it's in the fullness of time, like over a period of time or in the fullness of time?

24:45In the next three years, I think you'll see a bunch of high profile ASIC programs canceled, especially if Google starts selling TPUs externally, which has been all over X. And then, you know, Who knows exactly how that would work? Because if you're an Anthropic, it was just rumored Anthropic wants to buy tens of billions of TPUs. If you're Anthropic, maybe you don't want Google seeing your secret sauce, but there's ways around that. So I think this is really a battle between Google and its TPU, enabled by Broadcom for now. And Google can take the TPU away from Broadcom whenever they want. Now, they can't do the Ethernet networking that Broadcom is doing, but they control the TPU.

25:26So it's really Google and the TPU versus NVIDIA. You know, with, you know, Amazon, like that's a very talented team, arguably the most talented silicon team at any hyperscaler, the Annapurna team. Like I think the Tranium 3 will probably be a much better chip than the Tranium 2. It took Google three generations to get the TPU right. And then AMD will, you know, will always be kind of the second source and you need a second source. All right, exciting. What do you think happens? Okay, so I want to go back to business models. So one of the big things that is widely discussed is like, you know, source of disruption.

26:04And most of the CEOs in this room are CEOs of startups who are trying to go beat some incumbent or find, you know, some new market opportunity. And the most ripe opportunities tend to come when you have a big platform shift that is also accompanied with a business model shift. And so there are a couple of areas where I can see it, I feel like in an obvious way. So, you know, we're investors in Decagon, customer support. Like you can pretty easily see a business model that is priced on the resolution of a task because it's so measurable. You can see, you know, like encoding, like a lot of the business model has now shifted to consumption.

26:43And, you know, obviously, especially for developer facing things, like that's comfortable and pretty well known. What about the rest of the industry? Because I feel like there's sort of this hand wave thing that is going on, which is like, we're going to go get all of services. But it's like, okay, so how do you actually go do that? It's going to be pretty hard. So do you have any prediction on how that plays out? Well, I think what you're seeing in customer service, which is kind of like an easy first example, we have a lot of textual data, the LLMs are good at text. you can kind of probably really easily run some RL to make sure that they get a good verified reward being a happy customer or first call resolution or whatever it is but I do think you will see that played out like humans were fundamentally paid based on outcomes and a lot of AI will be augmenting humans but probably also replacing some humans and that will involve being paid paid for outcomes.