Are 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.
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? If 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 Andrej Karpathy 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.
Who 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. It's a 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'm really looking 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. So we have about a trillion dollars of data centers in the US. The plan is to add 3 to 4 trillion in the next 5 years. Over the past three years, we have already built out in data center capacity a larger amount of dollars than the entire US 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 and 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 buildout. 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. Nvidia is 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 in the ground and not lit up. Fiber is useless unless you have the optics and switches and routers that you need on either side. I so vividly remember, you know, 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. The 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 that one of the biggest problems in a training 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 the 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. It'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. In the case of the AI tools, you know, all you have to do is kind of light them up via API or you know turn on your website ChatGPT and everybody has access to them right? Built on top of cloud computing, on top of the internet, and you know, you can get to instant distribution, a billion people right away.
Absolutely. So the other thing is the counterparties. 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, they're writing checks for this capex, I think they collectively generate like $300 billion of free cash flow a year. Is 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. Is it going to pop?' I'm like, I think it's kind of fine. I mean, you know, it costs like 4 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, well, this goes to your point on return on invested capital. It might we should see that tick down a little bit. A little bit of a mismatch at the buildout, 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, give me the because you know round-tripping is a very scary concept from you know the internet buildout that was a big problem. What do you make of it here?
It is objectively happening. You know 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. But it's happening at a very small scale.
Yes. Yeah. And I think I didn't know this was like a crypto or blockchain.
Exactly. Good. Yeah. And I think what is driving this isn't the need to, you know, 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, you know, 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 what Google, and Google's a problematic competitor because they also own a company called DeepMind and they have a product called Gemini. And I think you could argue that they are 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 does not, 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. Tranium is, you know, Anthropic is really going to run on TPUs and Traniums. And so you're left with xAI and OpenAI at the forefront. And if Google is going to a lab like Anthropic and saying, 'I'm going to help you fund raise and give you chips,' I think 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. And what I mean what Nvidia really needs is they need you know Meta to get their act together or another American open source player to emerge or you know maybe some sort of detente with China and AI.
Yeah. 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. 100% rational. Long term. Sure. Things they do may not have as high of 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 you know, since we're on the model side, what do you think happens with market structure? Who wins where, you know, who are you most optimistic about? You know, 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 as 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.
Well, actually talk about the role they play at the infrastructure layer because they are, there's a piece of them that like 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 the distinction. Yeah, I mean that's most true of Google. But I just think it's hard to have high conviction other than to observe you know 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, you know, the capital to buy compute and distribution, which is what you need. All of the big, you know, today's biggest tech companies have all of those in spades. So, as long as they execute well, hire good people, and have a sound strategy, like 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, you know, IBM might be a good fate.
Yeah. Yeah. Yeah. That's tough. Yeah. Data, distribution, compute, dollars, talent. Yeah. And like 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 is 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, and they're slowly starting to respond.
Yeah. And then what do you think what's your forecast for that sort of in 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 will 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 and the nature of AI because of scaling laws, Richard Sutton's The Bitter Lesson, 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 just think it's going to be a long time before we see a truly kind of you know 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 you know 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 and things like that change which I don't see happening they are going to be lower margin.
Yeah. 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 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 Andrej's Dario 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. I 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 like a more fragmented SMB customer base. You know, Google has make 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. And 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 in Microsoft and Adobe before the whole AI thing came along. You know, it used to be that companies were scared to go from on premise to the cloud because margins were lower. Cloud margins are lower. They're still good. And Microsoft, they transitioned, you know, 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 as a mark of success rather than a badge of shame or something to be feared.
