Is There an AI Bubble? Baker & George on the AI Capex Cycle

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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 misfortune of being a tech investor during the year 2000 bubble which is 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.

Every major technology cycle raises the same question.

Is it real or are we in a bubble?

Today you'll hear a conversation from runtime between Gavin Baker, managing director and CIO of Atreides Management, and David George, general partner at A16Z, about how AI is reshaping the global economy.

From capital allocation and infrastructure spending to business models and margins.

It's a detailed data-driven look at where we actually are in the AI cycle and what's likely to happen next.

Let's get into it.

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 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.

[MUSIC] Who knows what that music was from?

Glad to get our pump up music right.

Yes.

Battlestar Galactica, the original 1977 one.

In case we have to all fight psilons 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.

So we have about a trillion dollars of data centers in the US.

The plan is to add three to $4 trillion 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 US interstate highway system, which took 40 years, just in terms of dollars.

And that's inflation adjusted.

So 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 150 X 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 is 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, and videos 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 will 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.

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.

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 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 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 a 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.

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, 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.

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, it costs like $40 or $50 billion to light up one gigawatt.

Yeah, if you're on Nvidia chips.

Yeah.

Yeah.

So 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 cash flows.

We should see that next town a little bit.

Yeah, a 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."

But it's happening at a very small scale.

Yes.

And I think...

I know this is like a crypto or blockchain.

Exactly.

Yeah.

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.

And 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 a actual traffic basis, Google is bigger than OpenAI and Thropic, anyone today.

And that business is going to run on TPUs.

And then we have three other labs that are relevant today.

There's Entropic, and that's an Amazon and Google captive.

You know, Entropic is really going to run on TPUs and traineeums.

And so you're left with XAI and OpenAI at the forefront.

And if Google is going to a lab like Entropic 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 and 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.

A hundred percent rational.

Yeah.

Long-term.

Yeah.

Long-term.

Sure.

Some 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?

Who 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 chat GPT 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.

Well, 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.

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 Mag7.

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 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 met is making the dramatic moves they're making too.

No, to me, chat GPT 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 the platform piece of their business 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 better 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 just I 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 things like that should 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 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 Andres 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.

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 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.

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 definitely 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 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.

Cloud 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, you know, a batch 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 their gross margins and it's become like a badge of honor for them to actually have low gross margins.

Oh my God, people are actually using your AI stuff.

Yeah.

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.

Yeah, 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.

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 drop parallels to the cloud transition.

I mean, I'm an investor and I would be excited about it.

And I don't think I'm alone in the world.

And then the big advantage these legacy application SaaS companies have is they do have these really profitable existing businesses.

And so you can run your new AI products at break even and catch up to the leaders, et cetera, et cetera.

And I'm just surprised more people have not done that.

Like why are none of the public coding companies even trying to compete with cursor?

And the reality is cursor now, they have a trillion tokens and 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 at break even, I have an existing business, I'm going to attach it to everything.

Hey, you have a chance.

And you know, the prize is clearly really big.

I see Martin is skeptical.

Martin is taking his edge.

You have a chance.

I said a chance.

That'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.

Exactly.

Yeah, exactly.

I totally agree.

Yeah, we actually saw, I mean, you know, we see it, you know, we may if we if we, you know, Figma, for example, like when they went out, they are extremely high gross margin and they're like, hey, we're going to, you know, pretty aggressively distribute our tools and our gross margins are going to go down.

And, you know, investors asked a few clarifying questions and then they were like, oh, that actually would be a good thing.

And so I'm surprised more people in the public markets aren't doing it.

And 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 is 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 with AI, although I tried the browser today and I tried to do some pretty basic shopping stuff and it's, you know, still still some work to do.

But 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.

Two, 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, five billion users.

And if you're Google, you know, you can just go look at what happened with Google Buzz.

They are very cautious.

You know, there's you know, they're currently in litigation with the government.

And 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 head start.

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.

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 appreciating 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.

And that 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 X, AI for open AI.

But I mean, Mark Zuckerberg trying hard.

Yeah, 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, a checkpoint, training the next model, you're at a big disadvantage.

Oh, 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 open AI and Microsoft to run.

Any reference to GPT-5 and scaling loss is crazy.

Yeah, sorry.

Rant, rant over.

We got the pedestal up here if you want.

Yeah, exactly.

Shaking your hand.

Yes, it'd be good.

It'd be good.

Do you want to talk about chips?

Sure.

So, okay, I know you love Nvidia.

Talk about your view of Nvidia, AMD, TPUs, ASICs, and how do you think sort of market structure shakes out there, competitive advantage that the various players have?

Yeah, I think it goes.

I think it is really, it's a fight between Nvidia and the Google TPU.

And 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 center level company with the level of architecting they're doing with scale up, scale across, and scale out, scale across networking.

So 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.

It will 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.

In the next three years, I think you'll see a bunch of high profile ASIC programs cancelled, especially if Google starts selling TPUs externally, which has been all over X.

You know, who knows exactly how that would work, because if you're an anthropic, you know, it's just rumored anthropic wants to buy tens of billions of TPUs.

If you're an 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.

Yeah.

Now, they can't do the Ethernet networking that Broadcom is doing, but they control the TPU.

So it's really Google and the TPU verse Nvidia, you know, with Amazon, like that's a very talented team, arguing the most talented silicon team at any hyperscale or 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.

And 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.

And, you know, obviously, especially for developers 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 that LLMs are going to text.

You can kind of, you know, probably really easily run some RL to make sure that they get a good verified reward, you know, verified reward being happy customer or first call resolution or whatever it is.

And but I do think you will see that played out like humans were fundamentally paid for 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 for outcomes, you know, going back to the consumer business model.

You know, everybody's talking about affiliate fees.

And for sure, I'm going to have, you know, my own AI will be a version of Grok, because we're both ex AI shareholders, it will be a version of Grok that knows me and it likes me.

And, you know, when I when I want to, you know, the next time I want to go on vacation, it will know the hotels that I like to go to and it'll say hey, three hotels, I have Gavin, you know, I have Gavin coming, who's got the best price and the best room.

It's gonna massively upgrade the gifts that you give to Becky.

Becky Becky's in the audience she really appreciated your dumb and dumber reference I'll have you know.

But, um, yeah, and then there will probably be some sort of affiliate fee and again that's just being paid for an outcome and kind of closing that loop, which will be probably a little bit of a business model degradation, because the great why did Google never start a marketplace, because people over value, systematically, their ability, once they've acquired a customer through Google to keep it has an organic customer.

So they systematically overpay, and they continue doing that that's why Google never went to outcomes, or marketplace, because advertising leads to the advertisers systematically overpaying.

So that inefficiency will be squeezed out.

But yeah, we'll go to outcomes and you know I think Elon tweeted today that you know work would become optional you know like, instead of buying your vegetables at a supermarket you can grow your own garden if you want.

Now who knows how long it takes us to get there.

But I, that doesn't sound wildly implausible to me for how powerful this technology is.

As you struck our pathy you know whatever two days ago, you know is being painted has like a skeptic for saying AGI is 10 years away.

Are you kidding, in 10 years.

Yeah, that's filed.

Yeah, sign me up.

Most of shorter timelines, please.

Yeah, what's okay.

No, that's awesome.

While we're on the topic of very exciting futuristic things.

Robotics.

Do you have you on Yeah, very real, and it's gonna be Tesla versus the Chinese in the same way it's Tesla versus the Chinese in in cars electric cars.

Yeah.

Yeah, I would just say cars not electric cars.

Yeah, cars.

Yeah, do you have a sense of timeline.

I mean you can you can all watch the optimist videos.

Every roboticist I know is extremely impressed.

You know there's there's a giant debate is it going to be humanoids are not humanoids.

I think that debate is over because humanoids can kind of learn, you know from watching YouTube videos and then it's easier for human being, you know to put on a suit and show the robot how to do it.

I mean it's kind of crazy to watch the video of all the you know the 50 optimist robots doing 50 different tasks.

And then it's very simple you know did you did you put the glass in the dishwasher correctly or not.

This is so fun Gavin I always love chatting with you.

Let's give a hand to Gavin.

Thank you David.

Thank you.

All right.

Next up, we have a very exciting panel on building out real world infrastructure, but first give us a few minutes we got to do a quick stage change here.

So thank you.

Thanks everybody.

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