Aswath Damodaran: Big Tech Has No Idea How AI Pays Off

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That's fetchpet.com/save. Today's number 48. That's the percentage of US adults who now support the idea of banning funds for the full school day. Ed, why did the smart funding glasses?

Why? 'Cause a lost all its contacts. How are you, Ed? Well, I've got to tell you, I'm excited for vacation, which is happening for me in about two weeks.

Where are you headed?

“Oh, wait, we talked about where you've gone somewhere fabulous.”

I'm going to Austria. I'm going to a wedding in Germany and then I'm going to drive to Kitspule in Austria. Oh, Kitspule. I've been at Kitspule. It's a great, quite a friend that's great for kids.

I'm very excited. It'll be very nice. We'll go hiking, we'll play sports, we'll do sorners and swim. It'll be a very health-oriented vacation, which is exactly what I want right now. I'm going to wedding, you said?

Yeah, I have a wedding first, and then I've attached, sort of, bolted on a vacation next

to it. So I'm pretty proud of how I've kind of maneuvered this, because we have the wedding in Bavaria, which will be awesome. And then rent the car, drive about two hours into Austria, and then spend the weekend at a hotel.

So I'm very excited about this one. That is exciting. You know, it asks you as greatest achievement is. It's commencing everyone Hitler with German. He's back.

That's what he needs it. He needs it back. I knew that. That's not going to do it. That's actually a good point.

Yeah, that's true. They did commencing. He's in Austria. Yeah, that's true. That's true.

Everyone needs the German. Nope. Austria. Nope. Do you have vacation plans?

The better questions do I have work plans? Because most of the time, as your team now, yeah, I'm here in Colorado, and I had to. But you're on vacation. I'm up at 7.30 doing these Joey Baguette on a podcast with you.

But I'm technically, I mean, my kids are all causing trouble and bored and doing hikes and shit like that. And it's all bare less than I'd actually in town, which was kind of fun. Brown, bad? Yeah, a little brown bear.

My son said, should we run on like, no, you stay here. I'm going to run. That's a very, very dangerous animals. I saw this one of those TikToks about what kills when animal kills the most people.

And everyone's so freaked out about sharks. Moose kill more people than sharks. Yeah, I've had that. Moose could be quite aggressive. Yeah, and hit the bottom eye and crocodiles snakes kill a shit ton of people.

“I think mostly in India, but this is what you've been doing on your vacation.”

Well, of course, you know, the animal that kills the most people, right? No, I don't. What is that? The amateur answer is a mosquito, but the animal that kills the most humans is other humans. Um, so it's true, we're the problem.

We're the problem. The amateur answer is the mosquito. How many times have you had this conversation? I think it's fascinating. Have you been through this?

Should we turn this into an animal's podcast?

Maybe that's what this should be. Oh, I would love to bring on. I like that guy, the dog with the Oscar guy who goes into homes. And then establishes his dominance over the Chihuahua that thinks it's a season of lawn. Is that he talking about?

Yeah, yeah. He was really good. Yeah. I remember he's growing up. Despite the fact you hate dogs, that's the underrated side about me.

I do prefer cats. That's not going to help her download. Did you? You had a dog when I had a cat going up, right? I did have a dog.

And as everyone knows, he was, he was okay. He was an average dog at best. It's more of the honor that was the problem here. It's fair enough. I think that's probably true.

All right, well, we've got a very exciting interview to get into here. We recorded this conversation live on Substack earlier this week. And if you'd like to catch the next live stream, we'll be doing plenty more.

“And you should head over to proffgmedia.com and subscribe to proffgplus without further”

ado. Let's get into it. We've joined by the one and only dean of evaluation professor Aswaf Demodarin for our quarterly review. We will break down the latest earnings from Big Tech.

We'll get his take on SpaceX, off for its blockbuster IPO, and we'll discuss whether we should be worried about the growing debt behind the AI, fill that among plenty of other topics. So let's get into it. Professor Demodarin, thank you so much for joining us.

I'm going to launch us right into it. I want to start with Big Tech earnings. It seemed pretty good across the board. Microsoft revenue up nearly 20% Amazon revenue up 20% meta revenue up nearly 30% the response was kind of mixed.

I have some underlying questions about these earnings, but I'd love to just start with your reactions to what we saw in Q2 from Big Tech.

“In revenue growth, they're absolutely right, I think the company is delivered more than”

expected in terms of revenue growth, and that's good news, at least in the near term. On the earnings level, what you notice is it's happening under the surface, these companies are so big that you don't see them. The marginal returns that these companies make it, basically the incremental earnings, relatively incremental invested capital, continue to show a shift in business models, which I think investors

need to keep their own. It's not a good news, no bad news. These are very different companies than the companies investors were investing in five years ago. I think we need to talk about what's happening at least outside of Apple, what's happening

to Mag 7, that's changing these companies and changes what investors need to look at going forward.

The thing that jumped out to me, if we just go straight down to the bottom line, if we go

to the free cash flow, meta's free cash flow came down 91% Amazon's free cash flow went negative, Googles went negative, which is something that I don't know if anyone thought would ever happen, certainly wouldn't have predicted it several years ago, just due to how much money these companies make, and somehow they found a way to spend it. Does that concern you?

It's something that needs to be thought about more seriously. These are long-term shifts. It's a one-year change. You might say, okay, that a big investment this year, they're going to go back to being cash cause next year.

I don't think that's going to happen at these companies. The one company in the mix that's had experience with this negative to positive cash flow and back again is Amazon. So in many ways, if you're going to pick a company that's equipped to deal with negative cash flows of the Amazon, because they've seen this movie before.

They've lived through it for their 25 years, you look at them, they're in and out of cash

flows, and they've found a way to always get back.

So meta for alphabet, and for Microsoft, this is new territory, something they've never had to deal with. And the question is whether they're equipped to deal with a very different kind of company going forward. And this isn't the top down.

These are more capital intensive businesses.

“Is there anybody who's running capital intensive business will tell you?”

It's a very different business model, a much more difficult business model to generate value from than the models that they used to use pre-AI. When you said investors need to be cognizant of the fact that they're investing in much different companies than they were five years ago, can you give us a broad overview or get a specific, as you want, is what type of companies were these five years ago and

what type of companies are they now? These companies, five years ago, they asked me what their invested capital was. I wouldn't even have cared because you knew that they could generate revenues in operating income with very little additional invested capital outside of acquisitions. And with R&D, consider these companies generate returns of 70, 80, 90 person invest capital.

The only survivor from that group is Apple, would still continue to deliver that kind of return. An analyst are not happy with it because it's not investing.

They're building huge capacity for whatever AI products and services. And like all manufacturing companies historically, they're now going to be judged on whether they can deliver the earnings on this investment.

Something they've never had to do historically.

So measures like return and invested capital, it used to be not that useful with tech companies, now come into play. Questions are, are you earning more than your cost of capital, a laughable question, five years ago with these companies, now becomes a relevant question.

“And I think that is the question on which these companies will live or die.”

If they can manage to deliver returns that exceed their cost of capital, I think they can come out of the other side as more capital intensive, but still valuable companies. But if they fail, markets are punitive on companies and invest lot of capital and can't deliver the earnings to justify that capital. My sense is that when the market gets these earnings, it's not about the earnings.

It's about the capax and the market's ability to discern and return somewhere down the road on that capax. And if you were on the board of one or more of these companies and you were headed to the finance committee, the audit committee, obviously every company struggles with the tension between investing for the future and trying to build modes around your business while

recognizing, you know, while not getting too far out in front of your skis, where do you think that that full-crummer that tension is right now? As you look at these companies, do you agree with the markets right now or recently that the

“capax is quite frankly gotten a little bit out of control?”

Or do you think that these guys are in a unique position to do it, so why not do it? I think the lesson that Facebook should have learned from the Metaverse investment fiasco is investing is easy, spending money is easy, but spending a narrative that markets get of why you're spending the money and what your business model is going to be is just

critical. As an investor, these companies, my concern is not the spending money, I think

they can afford to spend the money, I can see that they are going for growth, but none of these companies is enunciated, what exactly the business model it is that they hope to deliver? I mean, at the very minimum, are you going for scale with low margins? Is this the kind of business has to be looking at?

Are you going for premium products with high margins or niche markets? What is it exactly a planning to do? And for the moment, at least, that's not there and maybe they don't know, but then they need to be open about the fact that they're trying stuff out just as much as the rest of it.

It's caring for markets, but if you don't say something, markets fill in the vacuum. The fact that you're not being open about your business model, markets look at that and say, "Hey, maybe you don't have a business model, which is one reason, markets have turned increasingly skeptical about the capex," because you remember early on two years ago, when they started the capex with all good news, look how much money they're spending,

the assumption was, "Hey, that's smart companies, they'll figure a way out to make money." But markets are recognizing that you can be a smart company, but you've got the situational awareness, I hate to bring that in, component of your smart and perhaps you're too immersed in this space to step back and ask the objective question of, "Is there really a business

here that can justify not a billion, five billion in capex, but tens of billions of

capex?"

“And I think those questions only get going to get loud, is why are the board of these companies”

or the top management? I'd be thinking seriously about the business narrative end and not just throwing out the capex numbers and leaving them at that because markets are going to continue to respond negatively to big capex numbers without a story back in the capex. There's an outlier here.

We have a tendency to talk about big tech as if they're all one in more fist-plop, and the real outlier, I see as the following, everyone that's spending between, that we're talking about today, 150 to 200 billion in capex, but Apple is at 11 billion. Apple has made a distinct decision to pursue a dramatically different strategy. As far as I can tell, they've said, "We're not going to engage in the capex wars of

AI." It strikes me as a very big bet, like one of them is wrong. It's thoughts on that. I agree with you. This is going to be a classic case study 10 years from now, as to whether it's better to

wait out the uncertainty and then decide what kind of factory to build rather than build a factory first and worry about what can be produced from the factory. The analogy I keep coming back to is this factory-building exercise, which is Apple is saying, "We don't know enough about this space. We don't know yet whether the kinds of products and services that AI with the level will

this premium product, high margin, lower-scale business."

“I think even within the LLMs you see this fight, you know, with the open AI versus anthropic,”

when tropicalism is going for the premium pricing strategy. Open AI, surprisingly, is saying, "Maybe the big market here is to sell stuff for at a lower-cost and sell at scale." The Chinese, of course, are waiting on the sidelines to throw the story into complete turmoil, because they can come in.

This briefly we saw this with deep seek a couple of years ago, coming in and shaking up the story to all-travel everybody. The only prompt for Apple is they're facing the side costs of the huge AI capex in the sense that chip costs have gone up and they're facing, I mean, part of the reason they got punished so much was because it raised the prices of almost every single device because

everything has become more expensive to make.

And much as Apple would like to be completely on the sidelines, at least for the moment, they cannot be because they get dragged into the space because of what everybody else is doing.

“But I think you're right, and I think it reflects Tim Cook's personality and it'll be”

interesting to see if continues under the new CEO of saying, "Look, you know, jumping in with both feet into things you don't know is not the greatest way to make money." He's a cautious person, and an atmosphere of taking an issue with Apple for being cautious. And I think it kind of shows up in the ways, shows and around the business, but I think it indicates why CEO is mad at it because it's a much more ambitious CEO at the top

of Apple, or probably charted a different path. And you'd have seen Apple with tens of billions of AI investment as well. >> So if you mentioned this idea that they haven't, none of these, the high-piscales have really articulated what the ROI on these AI investments are actually going to be. And when they do report their ROI, it's generally in kind of these as vague a metric as

possible.

Amazon says, "Oh, we generated $25 billion in AI ARR."

And it's like, "Okay, well, why are we doing ARR? Why don't we just like hear the actual revenues?" But the worst of all is Meta, who is they're not saying anything. And Zuckerberg was literally asked the question, like, "How are you going to generate the return?" and he just fill a busted.

He didn't answer the question. He didn't talk about the cloud plans. You said something really interesting. You said, "Maybe they don't know." Is that possible if this is a trillion dollar bet?

Could they really not know? >> I think they truly don't know.

“And I think that they're afraid to say that.”

But I think in this business, they're better off being transparent about what they don't know. What I'd like them to do is just as I've done with the cloud business, which is clearly a money-making business to that, is to have an AI division, a separation of AI, where they tell you how much they're spending, how much money they're losing, think of it as a startup that they've created with a huge amount of venture capital investment.

And say, "Look, we're making a bet on what we think is going to be in the growth space, like a venture capitalist. We can afford to do that because we have the capital to do it." But like most venture capitalists were venturing into the unknown. And they think markets will punish them for being honest.

But I really think markets would welcome that honesty, because I think markets increasingly as they listen to vague answers to questions and said, "These guys have no idea what's happening." You know, they don't know what's going to happen. And they're trying to act like they know more than they do when in fact they don't.

It's better to be seen as trying to find an answer than acting like you have the answer, but you're not willing to get the answer to markets. So I think more transparency would be good for these companies, but I'm not sure they will take my advice on that. It seems that the lack of transparency and the unwillingness to answer the question to your

point, it makes me more anxious. It makes me think that they're not telling us something because if they tell us the truth, then the business models don't work anymore. And there's one piece of data that I'd love to get your reactions to. Something we I'd love to know the answer to is what share of their AI revenues are coming

from open AI and anthropic, two very, very big companies whose financials we know to be shaky at best because they're highly unprofitable companies. We don't know the answer to that question fully because they haven't told us, but there have been some estimates from some Wall Street research, Barclays estimates that open AI and anthropic make up 73% of Amazon's AI revenue.

Wells Fargo thinks that open AI and anthropic make up 74% of Microsoft's AI revenue.

How big of a problem is that if all of that is true?

It is a big problem because almost all of the revenue talking about is intra-company revenue building the factory, building the architecture. It's not revenue from end users.

“And that's really the part that we're uncertain about, right?”

I mean, you can keep spending more money on the factories, Nvidia sells chips and I have you pay for the, I mean, the intra-company revenue just reflects the fact it collectively of building the biggest architecture businesses ever know. But to do what? If people are not buying their end product and services, what difference does it make that

degenerated revenue from each other? So I think that it would be useful to actually get a sense of that end revenue. That's the part where all seeking out is.

And anthropic might be the one company that you can talk about end revenues because the

LLM's and what they generate. But it's a fraction of what you think of as total revenue from AI. And it's a small fraction and for this to be a healthy business, that's got to be the driver. The architecture can be 80% of your revenues.

In a healthy business, the architecture's got to be 10, 15, 20% of your revenues. The rest has to come from end customers. End customers can be businesses. They can be individuals. But that's not what we're seeing right now in the AI space.

And we're not getting a sense of whether that's building or not other than through anecdote levidence, which is the worst kind of evidence.

We can get of somebody saying, I use Claude and I say $300 million.

Hey, that's great. But what does it tell me about collective revenues in $300 million is a drop in the bucket when you're spending hundreds of millions in building this architecture.

“So I think more transparency or all the way around would be helpful here.”

Because an SP, as somebody who's an optimist on AI product, I think that there is a market out there. It's going to be a big market. But I'm not getting any sense of clarity on that market from all of these companies reporting on that space.

And I wish I had more clarity. And I think the palenter earnings are in a sense. One of the few companies that can actually say, look, we're making money on selling stuff to people with AI built into it, rather than selling to other companies, building more of the AI architecture.

So I think that that's the place where I'm looking for more clarity that end use or revenue. And I'm not getting that from any of these companies yet. We'll be right back after the break. And if you're enjoying the show so fast, send it to a friend and please follow us on YouTube, Spotify or wherever you get your podcasts.

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So why not you? Try Odo for free at Odo.com. That's OdoO.com. We're back with Proftory Markets. It seems as though these big tech companies were looking for a growth engine.

They saw AI happen.

They invested huge amounts of money into basically two companies, open AI, and anthropic.

Then open AI and anthropic turned around and sent the money back to them, buying all of the compute from the data centers that they're building. And that is now how they grow. And that's what we're seeing when the numbers explode. That to me signals something very unhealthy that we are, and I thought about you a lot

when I was looking at these earnings, the idea of the mature company versus the young company. And it seems as though these companies are trying to sort of artificially inject these Botox into themselves to pretend that they're young again.

“Is that not what's kind of happening here with Big Tech?”

They are middle age companies, and I mean saying that for a while for the Mag7, Middle

age is not bad. They're in great shape, they make a lot of money, they're good middle age companies. But right, nobody wants to be a middle age company, especially these companies, the history of growth. And there are two things that drove them into AI.

One, of course, is great. The fact that there's a big market and they can find growth there. But I think you can't underestimate the fear of fact that the fear of being left behind of history books saying alphabet got into AI, but meta was slow to join in. You can almost see that playing in the way they talk and the way they invest is they don't

want to be pointed to as the company that's not keeping up with everybody else. There's an element of the Empress' new clothes here, which is, we talk about AI, it's going to be a big market, we all buy into it, and they hang out with a crowd, where this is accepted with it. Conviction that AI is going to be a huge market is deeply embedded.

And I think when that's deeply embedded, you don't want to be the company or the CEO of the company. Right to the top here, the CEO of the company that falls behind, and I think that's a big part of what you're seeing in this race to spending is not that there is a belief that they're going to make money, but the worry that they will be left behind in this race

and be the company that didn't catch that race. I mean, we often learn the wrong lessons from looking at history, a lot of chip companies looking in video, and they say it would have been like in video, I think how much money we could have made in the AI chip business or, and I think that the in video lesson for a lot of companies is if you bet on a growth business, and it works out, you're going

to be this insanely valuable company, but that's betting, that's not investing. You can't run a company betting on the odds that you have right now.

“And collectively, that's why I think they're going to collectively, I think they're”

over-investing. I don't think the thing, I think there's a question. The question is whether there'll be one big win and lots of big losers or how big the losers will be or how this business will shake out. With the worry that somebody outside the space who didn't invest like they did could

be a late entrance into space, but because, you know, it's like, you know, every time I take the train from San Diego to LA, I curse the fact that US railroads were built a hundred years before everybody else, because they were built for trains that could go only 25 miles an hour, and by the time you got around to putting fast speed, you couldn't take. My worry is you're building a architecture, and you might find out three years from now

that you've been building for the wrong kind of product and service. And that's the charitable view you can take of Apple is they have the money to spend,

to find that end game before they jump in with tens of billions.

“But I think, I mean, uneasy is the word I was used.”

Worried might be, you know, it might be the follow-up to that, but I'm uneasy about the way they're spending money. And as somebody owns five of the Microsoft, I don't own in very anymore or Tesla anymore. I see the end truck company, both investing and financing. That's the other side of this, right?

In addition to the end truck company operations, there's end truck company financing with in video, often financing customers who buy from them.

And end truck company investing something that, when I first started value companies, I used

to be happy to be able to value US companies because cross-holdings were not common year. I hated value family group companies in Asia because to value one company had to value four companies. I worry about the fact that a value, any of these companies in the near future, I'll have to value three companies that to value Microsoft, I'll have to value open AI because it's a big position it has.

So the intro company investing financing and operations creates noise in the process and noise is just a fancy word for. We don't know what's going on under the surface because of the intro company stuff. On this point, when we look at the net income for Amazon and Google, both of which exploded almost tripled an Amazon's case, 85% of its net income, Amazon's was attributable to its

paper gains.

It's unrealized gains in their stake in anthropic and open AI and for Google, looking at their

stake in SpaceX and anthropic, that number was 87%. So their earnings have been massively inflated by these gains in these AI startups, which they haven't even actually realized. So we don't even know if this valuations are fair or even makes sense. We don't know how they were valued either and this is something I pointed out on Twitter

recently. As a result, their PE multiples have been massively skewed. We've come way, way down somewhere below 20 times earnings because their earnings have exploded. And I worry that that means that the metric has been compromised by AI because it looks

cheap. But you're not getting the full story. We made our own little adjustment where we kind of stripped out the AI startup gains and you pointed out that actually we need to be including their value in the numerator. Could you talk a little bit about how we can actually value these companies now that they're

so in bed with the AI frontier labs? When I talk about pricing metrics in class, PE, EBITDA, EBITDA sales, I mean, the whole dozens of multiples.

One of the first rules I start with is a consistent zero, which is what's in your numerator

should be what's in your denominator. So let me give you an example, you know, enterprise value to EBITDA, widely used in capital intensive businesses. What's in the numerator is the market value equity in that net of cash. And people say, why do we net cash out?

Because the income from cash is not part of EBITDA. And then I point to a danger with EBITDA when you across HODICs when you across HODICs here's the problem. If you have minority holdings in other companies, your market value reflects those HODICs.

Because the market knows you own 30% of this very valuable company. So what happens is your market cap inflates, you enterprise values higher, but your EBITDA does not include the earnings from that cross-holding. Because it's viewed as a non-operating, it shows up below the EBITDA line.

“So I say, with even with enterprise value EBITDA, you should be netting out the value”

of the cross-holdings because otherwise you inflate these companies are more expensive than they are because the EV is inflated by including them, but the EBITDA doesn't include it. And people say that's a pain in the neck, and they say, "Welcome to reality." A lot of the reason people like to use multiples is the shortcut, right? You're not asking the in-depth questions you need to ask to value companies.

I need a shortcut, and that shortcut historically has been the PE ratio. But for 20 years, I've argued the PE ratio is the most dangerous of all multiples to use because it's this mess, right? It's a numerator that's just the market value of equity, and it denominated includes everything. It includes interest income from cash.

What if you're making a huge interest income from cash, and you're including it? And that's part of it denominated. You're mixing up a business with a cash holding, and in this case a cross-holding, and you're trying to come up with a consolidated multiple.

“So the lesson I think that you get by looking at the Google and the alphabet is, "Don't”

trust net income." Net income is a deadly number of these companies because the mess that goes into it.

and because in a sense you worry about things like financial expenses and other income,

but separate the tip. The operating income is going to tell you what the operating business of these companies are doing, that arrest of the stuff is telling you what the other investments are. Now, I'm surprised to see the marking up, because on the Amazon income statement, it says, gain from sale of asset as opposed to the marking up component.

“The reason I'm surprised is, when you hold an investment for trading, you have to show the”

marking up a market on soft bank as a classic example. When you hold an investment as a strategic investment as an investment, it's going to be part of your business in the long term. The generally don't do that.

You hold that original value and any income, you show will be the actual income and loss

from that holding. That's what happened with Microsoft. So I am confused about what the accounting is, and if the accounting is that holding it, these companies as trading investments, that's a very revealing statement, because you told me this investment in an open AI was because you wanted to build the AI business

in the long term, not because you wanted to make money like a venture capitalist by buying open AI at a low price and selling it at a high price. So again, it goes back to this once you create crossholdings, you create these follow-up questions. What's the motive?

Why are you doing it?

“And I think that's what I mean about transparency, tell me what the end game here is.”

What is it that you're hoping to get from an anthropic investment, or an open AI investment, can frame it in terms of the end business, that this will give you an advantage on that AI product and service business. I'm willing to listen, but don't tell me you're doing it because you want to make money, because you're not a trader, you shouldn't be doing this if you're objective is to just

make money on another player in the AI space. But if all of Wall Street were as rigorous as you, then maybe we'd be okay, but I think the trouble is that people like short cuts, people don't want to do all of the homework but you're describing, so they just look at the numbers, they go, "Oh, it's okay, the revenue exploded.

The net income is up." I don't think it's it's it's rigor, particularly that that keeps it apart. It's the fact that you're required as an analyst to react in real time. I'm glad that I'm not there at 430 after learning school, where somebody says, "What do you think about that earnings call?"

I mean, I need a little time to digest what's in that statement. I need to look at the footnotes, I need to see the breakdown, but I think we live in a world where instantaneous reaction is required as it's part of your job. So I cut them some slack on what they're doing, but I've faith that eventually markets kind of figured it out, and I think that that's going to be the end game is, no, I did

strip out the Google and the Amazon earnings from the effect of earnings and they're pretty good quarters, even without it and I think it made more sense for them to say, "This

“is what we did without, and that's what I meant about separating what's happening with”

AI from everything else is I don't think markets would punish them if they did that. I think markets would actually reward them for transparency." I mean, it's one of the reasons I think Jeff Bezos was cut so much slack by the market for so long that Amazon was in his open about what he was doing. He said, "Look, I'm building, I mean, I called the field of dream story, which is with

me build it, they will come, it was open about the fact that Amazon, in its early years, was building revenues, and margins would look terrible, that they'd give away shipping for free because they had an end game. He brought people into the end game. And it's that belief that allowed Amazon to do what it did.

So that's why I said if there's one company in this mix that should have experience having gone through this before it's Amazon. So I'm going to get my cues on whether Amazon starts to become transparent earlier than the rest because I would expect them to.

So there has never been this level of catbacks in emerging technology that didn't ultimately

result in a fairly serious correction, if not a crash. Whether it's the railroads, the electric grid, you know, the highways, whatever, the steel underground infrastructure in '99, there's always a correction. And also to be fair, the technology and many of the companies survive that correction and go on to be big winners.

But the thing that gave me the sense that we might be closer to that correction moment than further is when meta or when Zuckerberg announced they're trying to sell their compute. And the same when Musk and my sense is that, I mean, if you look at it at the beginning

And now both Musk and Zuckerberg are trying to spin it as look at the premium we're getting

for the infrastructure we built. And what I see in that is that the AI demand curve has been vastly overestimated. And now you have essentially hundreds of billions of not choice of dollars in catbacks all going to only two sources of demand creation, open AI and anthropic. It feels like we have all of a sudden pivoted from a supply crisis to potentially a demand

crisis, your thoughts. When I was looking at the SpaceX prospectus, and I noticed that they were making more money by leasing out their data centers to others, in this case, in anthropic. And then they were making, I thought it was actually at seriously at odds with the AI

story they were telling in the prospectus of this huge market, 28 trillion.

“And I think in the aggregate, what you're pointing to is the fact that you're making more”

money by selling into the AI architecture space, and I include LLMs in this, then from talking about AI product and services is very revealing. It tells me that you're not as confident as you claim to be, that there's going to be a huge market. If you were really confident that there was going to be a huge market, you wouldn't want

to lease the space out to who could be potential competitors in that market. So fact that you're doing it, I think, is a sign that at least for the near term, you don't have as much faith as you claim to have that AI is going to be as big as it is going to be. I take that as one data point, and then I take the fact that the amount of tokens being

consumed from Chinese LLMs or AI infrastructure companies has, the data I've said it's gone from 8% share in January of 25 to somewhere above 50% now. It feels as if the cracks are really beginning to emerge in the whole narrative here. And then China is potentially engaging in AI dumping, trying to do to our market, what they try to do to our still market, 30 or 40 years ago, and doing in kind of 20 weeks to

Silicon Valley, which appended to Detroit over 20 years.

“Am I overstating the threat of these inexpensive LLMs out of China?”

No, I think China's just ahead of the game and seeing that the AI product and service market, this mythical market we keep talking about, is going to buy for game. There's going to be a premium component of the market, primarily business products and service, which is high margin. And there's going to be a big component of the market, which is going to be a low margin,

big scale market, and China is clearly putting its stakes and saying, that market, we're going to go after because we're equipped to go after it. So I think China in many ways is taking a look at that endgame playing out. And I think the real question is in that endgame. So let's play it out.

Let's suppose the endgame, the AI product and service market turns out to be looked, let's play along with the AI optimist.

Let's say it's 6 billion, 8 billion, 9 billion, even 10 billion.

That by itself doesn't create valuable companies because you haven't told me much about the business models that will be used to generate money in that market. If 90% of that market is low margin, large scale, you could be a 10 billion dollar market. But the companies in that market are not going to make much money on those trillions of dollars, because your margins are going to be single digit margins.

Now, one of the most revealing components of the entropic success story was how much it costs entropic to deliver the product and services that they charge 6,000 an hour or four. Right? It's now, this isn't software, where the unity economics are amazing. The unity economics are struggling in a business that's still evolving.

“I think the question though is what's the catalyst that's going to create a major correction?”

This might be one of those things where you get multiple catalysts and corrections along the way. Rather than a big dime, like the dot com bus, I like the dot com bus, something that happens, staggered pain, I'm not sure which is worse to get the pain and one go and clean up and move on, or a staggered pain where individual companies get into trouble and markets go through these cycles of correction and whole, where you come back a little bit, then you have a correction again.

But I don't see an individual catalyst that's big enough for a moment, because oh my god, the air market is not going to be as lucrative as we thought it was. Because it seems like every time you get something that has the potential to do it, there are still, there's still money on the sidelines that jumps in and says, we need to be an AI because everybody else needs to be an AI.

the next day you wake up and there's a 10% jump in all of the stocks, clearly money coming in and

say, we've never been an AI, we need to be there because everybody else is there.

“I think I know whether this is being accentuated by social media and the awareness of other people”

make money, I don't know. But that factor still seems to be strong enough to overcome the catalyst effect, but at some point it down the catalyst effects are going to overwhelm that moment in effect. We'll be right back and for even more markets content, sign up for our newsletter at proffgmarkets.com. I'm thinking a lot about this one question I've been asked over and over.

A question about the choices I've made, the colors of my hair, the things in the world I've spoken about and the things that I have it. I've heard this question ask so many different ways,

but it always came down to why are you like this? And as you know, there's no simple answer

because people are not simple. We're messy and complicated and contradictory and layered. So on my new show, I'm sitting down with the ultimate disruptors, the athletes, the artists, the activists, and the architects of our culture who looked at the way things were and asked,

“why do we do it like this? And can we do it differently?”

My hope is to give us a little more space to that question. And to the person on the other side of the mic, not to tell us their answer or read from their script, but to take us on their journey. Check out my new show, why are you like this? On YouTube or listen in your favorite podcast app, new episode's drop every Thursday.

Presidential races are always messy, but 2020 is shaping up to be our messiest presidential campaign yet.

There are a ton of names that are rumored to be thinking about throwing their hat in the ring. Alrighty, here we got Trump. We got Kamala Harris. We have Marjorie Taylor Green. So this week on America actually, I wanted to hold a little fantasy trap. Of course, we got to have ALC on the list and stud George Clooney. And to do that, I went to invite two of the messiest people I know. Box journalist and podcast host, Cara Swisher. Let me tell you. Uh-huh.

Here's the charm of a cyber truck. And independent journalist and political commentator Don Lemon. This could go really fast because I got boom, boom, boom, boom, boom, boom, boom, boom. I'm sure Cara's the same way. I'm a stead-horrenton. And this is America actually. Catch us every Saturday on YouTube or wherever you get your podcast. We're back with Prof. Markets. Do you think that Open Out you mentioned the unit economics

anthropic charging all of this money, but then they spend way more money delivering that product? Do you think that Open Out and Anthropic ever figure out the unit economics? Like, I'm just going along with, I guess they will. But I don't know why I should believe that. The way AI is set up right now. I don't think there's going to be that much give on the unity economics in the new term, right? You still have to build. I mean, the physical infrastructure has seemed so expensive.

“Honestly, you can figure out a way. To build data centers at one tenth the cost, right?”

This is not the kind of investment where scaling up is going to help you. That much you have to figure out how, you know, so none of the elements are easily going to bend to a economy of scale argument. Maybe I don't know enough about AI. Maybe they have some secret sauce. It's going to allow them to do this. But I don't see it. I think every, you know, every time I open Google and AI helps me out there, it seems like a marginal cost is being created somewhere

along the way that I'm not seeing. And that marginal cost is not decreasing because tens of millions of people are using Google at the same time because each surge seems to provide an additional cost. So as I said, I am not enough of an expert in AI to see whether these economies of scale will come from, but I don't see them yet. I don't see anything in the architecture that bends

I don't see it either. And I feel as though we're just being told to trust that it's going to

work out and trust that the economics will make sense eventually. But if they don't, the whole thing collapses. On the premium side, it starts to shrink. Maybe not collapse, but shrink. McKinsey might be willing to pay $9,000 or $90,000 and $500,000 for an AI agent. There would be premium products where you can charge a premium price even over the high cost. But it'll mean that that end market is going to be more premium product. The economy is

in scale argument. It might work better in that lower margin market where you don't need Nvidia chips. You don't need expensive data centers. And the reason I say that is I see a lot of stuff that I saw 10 years ago that was labeled as machine learning or you know, look at this macro we built for itself. I see the same stuff today marketed as AI. And my question is, what do you think any of this AI? You don't need data centers. You don't need Nvidia chips. You could do this with

the traditional computing power and without the access to data. That's the part of AI that I think is going to be the scalable part. We have low margins, but the scale takes care of it. So it's not that the app product and service market will not exist, but it'll become almost primarily

“a mass market, low margin business. And that's why the architect actually a building might not”

be right for that. It might be too much for the premium part of the business where you need these high-end chips and data centers to feed those products. We're describing a lot of AI anxiety. As you can tell, I'm pretty anxious about this myself. How much of this anxiety in your view is priced in right now? I get the sense that it's somewhat priced in. Certainly priced in the case of meta in my view. Perhaps not the others. What do you make of these valuations? Do

you think that the markets are telling us that they see what we're saying? They seem to see it and then they seem to forget it. You take the meta example. Over the last week, it's made up of about 70% of what it lost in the previous six months. So it's not like the lessons are sticking because you know, all you seem to need is some other distraction along the way. And that's why for the moment at least, the calculus are not working because they have a temporary effect. One

company gets heard, but you're not seeing it ripple into the other companies. It seems to be

“company specific and time specific. So I think that collectively, I think anxiety kind of”

abs and flows, but it doesn't seem to be at a level where it permeates in deployment and pricing changes yet. And I think maybe that reflects the fact that those of us who are anxious are in the

wrong. So I'm always open to the possibility that maybe we're missing a really big story. Maybe Leo

was right about this being the ultimate winner. It's going to happen in 2027. And I'm always going to lean that door open because I've learned that you can't ignore somebody just because you disagree with them. I have to be willing to listen. So I try my best to read as much as I can from the AI opens. I'm looking for a story that explains economies of scale. But so far, the story still seems be focused on fuzzy end games and how great AI agent has worked in an individual business.

I'm not seeing the aggregate numbers from any of these stories that lead me to say, okay, there's something here that I should be taking of closer look at. So it's going to be a race between whether those stories come into play or whether the skepticism builds up to a point where people stop believing. So are you comfortable with current valuations of big tech, Microsoft Amazon, Google Meta, will leave Apple aside because they're not getting into AI.

“Are you comfortable with them? These valuations are they too volatile to even have an opinion?”

I can live with them. And it's because of my framing. I frame them based on what I've paid for them. I paid for them a long time. I know the sounds are rational. But if we keep comparing the price to something, you know, that I could have got for six months ago, a year ago. So I'm willing to accept 20% right down in those investments and accept it as part of the long term costs and benefits. Now the reason I do it is, if I think there's a shake out in the AI space, these companies will be

impacting. But the lesser companies in this space are, I mean, none of these companies have net debt ratios that are beyond the single digits. Their debt is completely manageable. And I did net

to net to net to net for all of these companies one and a half times every time. So basically

businesses would pay off the debt. So debt is not my concern of these companies. But they're a whole host of lesser companies where debt is a much bit of component there. And AI meltdown in the story will be catastrophic. Now just this Amazon got hurt after the dot dot com bus, but it's

“the best thing that happened to them because it wiped out all of their dot com competition.”

In many ways, the mag seven might be, you know, this is a very sinister view of this whole thing, maybe they're wishing for an AI correction. They'll be punished, but the rest of their competition will be decimated. Now, and remember, open AI and anthropic can't survive on their cash flows either. So maybe there's a, you know, if you were, you know, if you were looking for a story with villains that knew more than they did, you could admit, and maybe this is the end game for them.

Is they're hoping for an AI shake out with they come in and pick up the pieces that bargain basement prices, because they want to survive. I mean, I don't have worries about failure rates, these companies. I just worry about their problems and what they're doing in terms of AI investing.

“There's been a lot of concern around, they have 1.4 billion in disclosed debt,”

but the debt you don't see is now bigger than the debt you can see. So for example, Meta is

carrying 420 billion of off-book versus 140 billion on-book, but I don't entirely know if that's

a feature, not a bug. Are these companies taking advantage of their credibility in the marketplace to offload from their shareholder sum risk, or is it just an accounting trick to create opacity around the actual amount of debt they have? Now, I'd be interested to see what the recourse on the debt is. If you're lending money on a data center that Meta is a player in and the debt has recourse only against that data centers or revenues and assets, then you're not going, I mean, in a sense,

as a Meta shareholder, it's clearly not something I want to see happen, but it's not something that's going to impact me. Now, I'll be, again, I want to go back and look at the accounting rooms as to what happens when you take that that's off-valent sheet debt, where there is recourse against the parent company and whether you can get away not revealing that as part of your debt. And maybe there's this iceberg of debt that you're not seeing underneath that could be. No,

“but I think that even, I mean, let's bring the recourse debt in then and let's say,”

I mean, I'd like to see full disclosure of that debt that's not in the balance sheet, because even then I would wage it's three, three times that we're not talking about heavily levered companies in the sense that companies that are, you know, that are going to be dragged down by the failure of these of AI. But I might be wrong on that. Maybe I need to do more of my homework digging through that debt. But that would require some bending, perhaps even breaking of accounting

rooms to be able to get away with that. So, you know, I'll do another read of the footnotes to see if there's something in that, but at least for me, the worry with the mag seven is not so much the debt, but the investment paying off, whether this enough for return. The worry with lesser AI is whether they can make it to the other side. And the worst case scenario is that AI turns out to be an incredibly big market, but they don't make it there. They fail because the debt comes

due and they have to sell themselves to one of these other companies at a fraction of what they should be charging. And that's a very real possibility in this space. And if it does happen,

there's going to be serious side costs for the rest of us, because debt going down is always going

to create side costs. Have you looked at OpenAI and Anthropics? What very little we know of their financials? And would you ever value those companies? Well, because I've added space sex with the novel. Let's face it. 80% of the space X value, at least the numbers. The story was about an X AI. So, it's an X AI story embedded in a space launch company. So, with the prospectus comes out, I plan to value them ahead of the iPad. And it'll be interesting to see as you move from space

sex, but with the sum of the the shine has come off the story, because of what's happened at space X, where people have them, you know, maybe the Anthropics IPOs not going to be a

trillion, maybe it'll be 800 billion, maybe OpenAI is not going to get the price it's wanted.

It really didn't stick. And they need to get there, you know, and I think there you're going to

look for more specifics, because, no, just telling me you're a great LLM, you have amazing agents.

“AI agents doesn't do it for me. You need to show evidence that this is actually”

sticking at a business level that you're making money. You're there. I need to see the unity economics and evidence that there are economies of scale, you can point to this is what it costs to the studios to go the year ago this year. Because that's how you back up in the economies of scale story, just don't give me the words, show me the numbers. Would you ever value OpenAI without the full story? Would you ever undertake that? Because it seems as though

and you pointed this out in our exchange on Twitter, like we need to put the value in the numerator, but that kind of means valuing OpenAI in order to value big tech, correctly. I need to value OpenAI, but how can I value OpenAI? Because I know nothing about it. Would you ever try to do it anyway? Absolutely. I mean, in a sense, you all have no choice, but to tell the full story. The question is, is this a story you're entirely making up based on clues you're

getting as well, which is a very date, which is what I did with X AI. There was no story in the prospectus, there was just numbers thrown out of thin air. There was no story from the

managed middle of what they planned to do. So I had to write the whole story. That's always

going to create more uncertainty. So it's not a question of whether you can tell a full story, but what's the basis for the story you're telling? And the case of OpenAI, unless they fill in the blanks, I am coming up with the story based on my limited understanding of AI. So I'll give you an economy of scale story. That's not very strong. And I might say your costs are not,

“you might disagree with it. But part of the reason I think it's critical that investors,”

flesh out their full story is then companies are forced to respond. Right? So if OpenAI feels that they have true economies of scale and the story being pushed into the valuation is, there are no economies of scale. The costs are not going to go down. Then show me the data that you have. That tells me that I'm wrong. Because as long as we let these companies get away with these diffused, totally dressable markets trust me and you don't even tell a story. Use a pricing metric

and say it's okay because there's a big market out there. There's no incentive on the part of companies to tell the fuller story. So I think I will try to tell a full story. But I'll be open about the fact that much of the story is my story based on little strands that I pulled out of different places. Some from the companies, some from people who know AI a lot better than me.

But I'll always tell a full story and people will take issue with me saying your story is

wrong. And as I absolutely I know it's wrong. But what's the counter? Where is the counter narrative?

“You can tell me a narrative is wrong, but you have to be with the counter narrative. And that's”

good because it extracts the counter narratives from not just the company, but from other investors who disagree with me. But it seems as though there is almost no price discovery in the frontier lab world at all except for, and this is how we'll end SpaceX, where as soon as it went public, it went up and then it came crashing way down, cutting off within a couple of months, maybe less than a couple of months. Let's just get your reactions to SpaceX. What happened there? And I think in many ways

it shows you the power of hype, the power of momentum and how social media is added to that momentum factor, which is, I mean, this is the ultimate social media experiment because you think of growth and X. And basically, you've got the, and social media is like writing the title. It's, you know, it's great when you're on the back of the tiger, but sooner or later you're going to slip up and end up being its mean. So I think it shows you both the upside and the downside

of social media driving prices, but I think as more numbers come out of the company as the earnings, much as we take issue with the earnings missing from the max 7. Now, weak extract information from it that is useful and kind of financing a story. So once you go public, that is something that these companies will face is now in addition to telling the story, got numbers that come out. And either your stories consist with your own numbers, or people are going to look at the inconsistencies.

So now I think that they're more test coming and I think for SpaceX and these are the companies

I'm fascinated with 1999 because I think it was a year at was born, but also, but also, we remember

“that as well. And I understand things are different this time in quotes, but it just feels”

eerily reminiscent. First, the B2C guys took a hit. It feels like OpenAI is under real fire around

a business model right now. And then I'm going to say, "Okay, no problem. We'll go to B2B. Everyone piled into an anthropic, which had greater share on the enterprise market. And when that didn't live up to its expectations, it started going after the infrastructure guys." It feels like we are midway through the exact same cycle with the dominoes beginning to fall. This feels, this feels more similar than not to me to the to the 1999 and then ultimately the

2000 implosion. Where do you see the parallels are not from 1999? No two corrections ever work out

the same way. So I mean, now part of me doesn't want to see a correction because of what it will do to any put every portfolio in the US. But part of me just, you know, from a market observer standpoint, I am interested and I'm much more aware now than I was in 2001 of the catalyst that created.

“Because in 2001, if you remember, it wasn't a single catalyst. It was just a collection of small things”

happening. You know, as you said, you know, not even dominoes falling, but trees falling in the

forest. And eventually, you wake up, oh my god, half the forest has gone. So, you know, I'm keeping

tabs as I can, you know, whether it's on the investor side, we see a meltdown of a hedge fund shutting down because it made too much of a bet in AI. Or on the company side, we see companies stepping back from the brain, can saying, we screwed up. We're going to write off that, you know, we still haven't seen a major AI capX right off from a company yet. Because that would be the ultimate admission. Hey, guys, we screwed up. We've admitted we screwed up and we're not going to do this anymore,

right? Whether that'll happen after the correction or before the correction or whether triggered the correction. So, I keep my eyes on accounting revisions and, you know, restructuring charges and look at what's being written off because that might start to give us as an indication of, you

“know, of how this correction will play out. That's what the motor is to encourage the family”

chair and finance education and Professor of Finance at NYU's Stern School of Business, where he teaches corporate finance and valuation. You can read his research on his blog, Musings on markets. That's what, thank you so much for joining us today. And to our live audience, thank you for tuning in. We will see you next time. Thanks, how's it going? Thank you. This episode was produced by Claire Miller and Alison Weiss and engineered by Benjamin Spencer.

Our video editor is Jorge Coltty. Our research team is Dan Choulon, Kristen O'Donnell, Hugh and Mia Solverio. Jake McPherson is our social producer, Drew Burrows, is our technical director, and Katherine Dylan is our executive producer. Thank you for listening to Profile Markets from Profile Media. If you liked what you heard, give us a follow and join us for a fresh take on markets on Monday.

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