AI Has A Hidden Debt Problem

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I'm Ed Elson. It is July 23rd. Let's check in on yesterday's market vitals. The S&P 500 and the Nasdaq declined. The Dow was flat.

Print crude climbed above $95 per barrel for the first time in nearly six weeks,

as both the U.S. and Iran escalated their attacks. The yield on tenure treasuries increased. And finally, Google and Tesla shares fell. After both companies reported earnings, we will get into those reports later.

Okay. What else is happening? The big AI spenders are increasingly turning to debt. And a lot of it turns out to be hidden. A NICA Asia investigation found that five tech giants,

alphabet Microsoft Amazon meta and Oracle, are carrying roughly $1.65 trillion in debt that doesn't show up on their balance sheets. That's more than the $1.35 trillion they actually report. Meaning the debt we can't see is now bigger than the debt we can.

Met is off balance sheet debt is roughly three times its report to debt, and Oracle's has ballooned about 30 fold in four years. It's all legal, but it raises one big question. What happens if AI demand isn't as strong as investors are betting? Joining us to discuss this question,

we're speaking with Ed Zitren, author of the Where's Your Ed at Newsletter and host of the better offline podcast. Ed, thank you for joining us. I just want to give you some context. Yesterday, I was talking about Oracle on this show,

and I was talking about how they're increasingly relying on debt to finance their data centers and how it's becoming kind of borderline

“and manageable, and that's why the credit rating is getting downgraded”

in their boron costs are exploding. They're kind of being sent into this downward spiral. Up until this point, though, it has been my understanding that the debt in the AI ecosystem has been relatively contained to a handful of companies like Oracle,

but that it hadn't infected the bigger names, which is why I was so alarmed to see this reporting from Nikke, which says there's $1.7 trillion of hidden debt that we haven't been seeing, that we haven't been looking at. You've just written a huge piece on this.

You investigated these numbers. You did a sweeping analysis of all of this. What do we know about debt in AI? And how is it that so much of it appears to be hidden? So, there are several factors here.

With the hyperscale, there's the reason they're able to do that is because they've found this interesting accounting treatment. The Ernst and Young Claimers are red flag in matters case, where when you build a data center, it's not like you as the company say, "I'm going to buy all the stuff, I'm going to get the debt for this and here we go."

They make a special purpose vehicle or a variable interest entity,

which is basically an SPV where you dump it on as much.

So, for example, with Hyperion.

and Meterolion is 20% of it.

Despite Meter being the only client, the person that's going to fill it full of GPUs as well. I think they're moving somewhere across their assets, despite them being the obvious, despite Meter announcing it. And saying, "This is our data center,

because they don't have full ownership of it. It's not counted as something they put on their balance sheet. I think with an operating leases when it starts paying." But the thing is, this is the entire AI data center industry. Every one of them are these SPVs that people pull money into.

The SPV owns the debt. The SPV often owns a lot of the risk, though, through non-recourse loans,

“which means that technically you have to go after the assets of the SPV”

before you go after the company. But nevertheless, these things, on the risk, they own the GPUs. They pay investors not out of anything other than the revenues from the data centers,

which leads to the important point of what happens if the revenue for the data center isn't there. How do investors get made whole?

And the answer is, they do not.

And the only reason this is not considered a problem here is it hasn't actually happened like it. The data centers have not been built at the scale that would have to happen for the revenue not to flow in. What actually is an SPV?

And this is important because you say that these data center SPVs are the AI bubbles equivalent of CDOs, which, of course, were the financial instruments that basically sparked the great financial crisis. You say that that is our equivalent today.

So what actually is an SPV? And why are they so popular? So typically a CDO is slightly different. It's holding mortgage bonds and stuff.

“But they are the same kind of financial instrument”

that will cause genuine harm to the markets in the world. So an SPV is basically a company. It's a company. It has people that technically are on the board of directors. You can do that.

But really it's just a holding entity for money and stuff. And so when they build a data center, that SPV raises the debt. That SPV holds the debt. That SPV buys the GPUs.

It builds the data center. And when the money flows into it, the SPV is the one that pays out to contractors, that pays the opx costs. And there's a cash war for even where it goes.

Paying opx, paying investors, and then paying the people that own it in theory if there's more money than there should be. That is not going to happen. But nevertheless, these things are so dangerous

because they are being sold as stable infrastructure. Like commercial real estate or residential in just saying, oh, it's physical land. It's good. It's great.

But the problem is in the critical difference.

Is that data centers are nothing like a regular mortgage. And then nothing like commercial real estate. These are complex financial operations. They're both in the construction and the ongoing cost.

“And then there's the important thing of,”

you need revenue to actually get paid out of them. And because the real project financing, which just means they exist to finance a project, there is no other money for them to pay people out unless. Like the company on the other end,

a call we even Oracle what have you, isn't on the hook for those payments. Basically, the client is. And if the client is, say, I don't know, open AI and can't afford to pay it,

then invest us with invested in these SPVs. Well, they kind of shit out of luck. And the problem is, when I say investors, I mean anyone who's involved in private credit right now. And private credit is well funded,

as we can sure get into by pensions, retirement funds, insurance funds, teachers, pensions, cops, pensions, all this different stuff. We all rule involved in private credit, whether we want to or not.

I just want to read you a quote from Amanda, you're kind of, of Bloomberg and you quoted this in your piece. She made this comparison to Enron, she said quote, "Enron exploited US accounting rules to hide from investors and lenders hundreds of millions in debt.

It had bundled into off balance sheet entities, obligations that contributed to one of the biggest corporate collapses in US history." And what you are describing right now is that there is a trend among the big tech companies,

Meta, Microsoft, Amazon, Google, Oracle. They are creating these shell entities, these SPVs, seemingly to hide literally hundreds of billions of dollars of debt that they are issuing in order to finance their data centers. In other words, they're showing us in their reporting,

in their earnings like here's everything we've built, but then they're hiding all of the borrowing that they took on to build all those things that they're kind of bragging about in their reporting. That does seem to be a very, very similar link.

I guess, could you expand on that, on how this has come to be and potentially how this might unravel? So I want to be clear that other than Oracle, I don't think these companies died.

it wasn't clear if they were saying there was 300 billion

or $1.6 trillion of hidden debt. It was a very weirdly written piece, but let's say it's a trillion or so of off-balance sheet debt. That means that there's a trillion dollars in loans that we just don't, we actually cannot really quantify

outside of media reporting. But I must be clear, it's not just hyperscalers doing it. It's coreweave, it's iron, it's nebious. It's Nvidia in some cases. It's whoever is building a data center

is using these shell corporations, as a mean of, of the case thing ownership. And also, off a skating risk, as in basically handing off the risk to investors, and even though there are some that are recourse loans,

even if there's up the chain, you could eventually see the company. At that point, you would have sold off all the GPUs, so you'd be screwed either way.

But the larger point is, yeah, this is a corporate scandal.

This is a huge scandal. This should be, from page news everywhere, this should be a shareholder riot. But because we live as you put it, well, in my show, in this culture of worshiping the wealthy,

we just kind of put it to the side. This is a significant risk to these companies, though. This is a real, let Google, we're talking just as Google's earnings came out. They narrowly missed on search revenue.

Their other businesses are slowing down. It's happening across the board. So their businesses are going to slow down. Just as these massive debts creep up. And let's say they have ways of getting out of these things.

The investors will still be screwed. The investors involved will still be screwed. And if they cancel these projects, I imagine they'll pay off investors to a point, but anyone involved is going to take a loss.

And then this spreads out, like these are, this is the good news. The fact that the hyperscalers have these, these are the good SPVs.

“These are the ones that I think might survive.”

The problem is, every single data center is through an SPV. And every single investor is invested in a data center, has invested not in the data center itself, but in the potential revenue it brings in.

And the problem there is that is dependent on there being 15 or more times the AI compute demand that currently exists. It's actually, it's genuinely terrifying when you start quantifying it. And people are way too flippin' about this stuff and say, "Oh, it's not as bad.

Oh, it's not as bad as the great financial crisis." It's still a great financial crisis with this happens. It's still horrifying, and it's everywhere. You write, quote, "Much like a subprime mortgage, AI data center debt is being poorly underwritten,

virtually uncollateralized, and the issue to projects that have extremely low likelihoods of repayment, or based on flimsy information and hype-driven mania." And quote, "Sounds like a provocative statement,

but I actually think it's pretty much factual and correct.

“I think one thing that isn't in that statement.”

When we make the comparison to the great financial crisis, is the fact that a lot of that poorly underwritten debt that virtually uncollateralized debt was obfuscated and hidden away to the point where ratings, agencies, and investors and traders didn't even know what was happening,

because it had been so well hidden in the markets. It had been so well kind of complexified. I guess my question to you, do you think that this is the same situation where investors ratings agencies?

I mean, we know that S&P just downrated Oracle's debt. So clearly, they have some semblance of an understanding of what might be going wrong here, but is it your view that this is not being priced in that investors literally don't know what is happening

in terms of the debt that is being issued among many of these companies? Let me tell you the tale of private credit. So private credit in the last few years has gone on a tear merging with a requiring insurance companies

and retirement funds. Apollo bought a theme while they merged with them. Blue Alport Coveau. There I forget who the others are. Nevertheless, Blackstone's infrastructure fund

is funded by retirement funds.

The problem is, is a lot of the SPVs are funded by private credit.

That private part is the lethal part. S&P doesn't rate private debt. No one does other than the private credit fund. So there was a story in the information a few months ago that said that Blue Al decided to invest

“I think up to $10 billion in Stargate Abelene”

after 10 minutes. Alex, you diligence, do you think we can get done in 10 minutes? Probably not very much. This is standard for the SPVs. So while people will say, "Oh, well, the ratings agency is failed here,

actually know the SEC failed here." The Ili, like the insanity of private credit, which is basically a multi trillion dollar shadow banking system is what's propping this up. For the most part, the debt raised for these SPVs

is coming from private credit. You look at corewaves coming from private credit. When it comes from the banks, the banks themselves SMBC

There's like they're just funneling the debt straight in. So much of this is coming through institutional investors that are funneling money through private credit. That the ratings agencies aren't even involved. And the ratings agency is done.

The only reason they do it with Oracle is Oracle's predominantly raised this money via bonds, except for the fact that a lot of their private projects are SPVs and the SPV raises the debt. And it's this situation where in theory,

“like I think the Michigan data center they're building is a recourse loan,”

so you can go directly after Oracle. But that's the thing. Even in that situation, there are these legal barriers that if every data center is exploding, we'll make it hard to litigate at scale

or at least hard to pull down who's actually responsible. And if you are anything touching and a theme or a coup d'air or any other insurance company, it is worth checking where the money's going. I think the Lions actually invested in the Cyrus one bond.

And the thing is these bonds get rated somehow. They get rated as junk because insurance companies are now effectively run by private credit funds. I don't give a crap. That's like, oh, that's sure.

Because of this giant lie. And this giant lie is that data centers are the equivalent of investing in power plants and factories that they're AI factories. When in fact what you're investing in

is a very large town-sized building or Siri Acampus that is full of depreciating GPUs for an industry that has not proven it has to demand. And I mean my estimate for actual AI compute

is about 120 billion a year.

The, I did the math and it's something like if they build all 130 gigawatts of IT loads for the actual operational GPUs that they say is implanting. Based on site land climate,

we will need 1.68 trillion dollars of annual compute revenue. Just to pay for them all. And they'll have to pay consistently because if you stop paying consistently,

the loan covenants for the SPVs break. And the crazy part about this is the global software industry is less than $800 billion. So we're just going to magic up another software industry and to be clear what I am saying sounds radical.

“I think you can't have said this already.”

It sounds like a scary thing. Or it's alarmist. This is just very basic math. This is site land climate. It said 190 gigawatts of capacity was being

was implanting around a construction PUE1.35 which is just the energy efficiency 130 gigawatts.

12 million dollars in megawatt.

It really, if this is simple math, that anyone could do. And the thing is even if it's just half of that, we still don't have enough demand. And so we're in this weird situation where

this risk is now spread everywhere. To the point that because it's private, we actually do not know how far. And it's within the insurance companies. It's different to how AIG collapsed.

It's just smaller. It's smaller little bits. But the other problem is, is that AI data centers are so expensive. They're cost 500 million minimum,

properly several billion.

“So instead of having millions of or hundreds of thousands”

of supply mortgages that collapse, in a kind of slow boil over time, it's going to be a 500 million,

a six billion, a two billion,

a one billion collapses. And each time one of these happens, that's a massive mark down with a private credit fund. But also a bunch of investors who have lost money and have no recourse beyond,

I don't know, selling all the GPUs in a market that will become saturated with them. It's the recourse point that is getting us into such dangerous territory here. I mean, it's one thing to make it to sell equity on a speculative bed about the future,

in which case, you know, the people know what they're buying into. We know what the risks are. It's another thing to finance an extremely speculative business through debt.

And then to hide that debt. Because I mean, if this doesn't work out, we're not just talking about equity going down here. We're talking about bankruptcies, we're talking about faults.

There's also one, one other problem, which is the reason that insurance for insurance and the retirement funds invest in private credit is because they need yield. They need ongoing yields.

So if these data centers do not pay out, we have retirement funds and insurance premiums that cannot get paid. And I'm sure they have some buffer. I'm sure they have other assets.

But it doesn't have to be an AIG commercial paper level collapse for this to be systemically damaging. And after this, there is no more yield to be found, I guess other than treasury bonds, which are going up now, yay.

But when they go down, I don't know. But so it really is, and what sucks is, most people have no idea about this. Most people don't realize that like,

the California pension fund is invested in blue out. Like, these are, it's everywhere, and it's not just in America. It's across the board. You've got, I think the Dutch pension funds

they invested, I think, in a core we've data center. Like, this is everywhere.

“And I'm furious at the fact that it's so yielding.”

It's so rarely discussed, but also people are so quick to be like, "Oh, it's not as bad. Oh, it's not as bad. Not as bad is still bad."

(laughs) All right. Well, we're going to have to continue this conversation another time, I'm going to have to let you go, but it is fascinating stuff.

And I do encourage listeners to go read your article. It's extremely rigorous, and gets a lot of the issues that we're talking about. Ed Zichran is the author of the Weiser, Ed At, newsletter, and host of the better offline podcast.

Ed, always appreciate your time.

Thank you. Thanks for having me. (upbeat music) After the break, a breakdown of Tesla and Google's earnings.

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Tesla just reported earnings and Wall Street was disappointed. A head of earnings, Tesla had reported impressive delivery numbers for the quarter. Up 25% year over year.

That gave investors the impression that Tesla's worst quarters were behind it. This time last year, the company was reporting a 13% decrease in deliveries. But the company's second quarter earnings told a different story.

While revenue beat analyst expectations up about 26% year over year, profits fell 5% over the same period. And the quarters free cash flow came in about $1.1 billion in the red.

The stock fell more than 3% after hours. And is out down roughly 25% from its peak. So here to break down Tesla's quarter. We are speaking with Karim Booster. Kel founder and managing partner at DVX ventures

and former vice president at both Tesla and Lyft. Karim, thank you for joining us. The interesting story here, you got decent delivery numbers, especially compared to last year.

Revenue was up, but profits down.

What went wrong here on the bottom line?

I think what we're seeing with this published result should not come as a surprise for anyone who's been understanding and following what's been going on. We tested for the past and say 18 to 24 months. Essentially what's been happening

we've seen declining sales for several quarters in a row. But more importantly, we've seen declining market shares. And even in this quarter where for the first time in a few quarters, Tesla has been able to report increasing sales number.

“You have to look at this in the context of a growing EV market”

where the market overall has been growing faster than the sales number that Tesla has been reporting. So that's one factor, which confirms what we've been seeing

on the automotive side, which is essentially the vehicle line-up.

The product line-up is becoming old. It has not been able to renew it.

“There's been a refresh of the model-wide last year,”

but it's still based on the same platform that launched almost 10 years ago now, with the Model 3 and the Model Y. So there hasn't been real innovation, both from a product side and technology side,

that would have allowed for the company to catch up on the market share losses that they've been seeing. And at the same time, continuing improving the margins. It's actually been the opposite.

The margins have been eroding.

We've seen it in the results that have been reported this quarter. So all this comes down to the lack of innovation, and new product and fundamental platform launches that we haven't seen for the past few years. And that's in the context of a competition that has been increasing,

with all competitors catching up to where Tesla was even six or seven years ago and creating great products with better margins, better production systems, and then where Tesla has been able to accomplish. So all this to say, I'm not surprised by this results. It's so coming down to what we've been seeing in the past few quarters,

and everything is coming into place. When you look at the lack of innovation,

and new breakthrough product on the product line at site.

The Tesla balls will say, "What about the robot taxi?" They will say, "What about Optimus?" Which is the humanoid robot. What would you say to those people,

"Are you convinced by those products?" And do you think that that is going to work for the company? If the existing product being the current self is deteriorating as a business? That's in the bet that Elon and Tesla balls are making, that there is going to be an evolution,

a transformation of the company that is going to evolve from an EV cloud manufacturer. To a robot taxi, robotics company, AI, driven company. And that's a great strategy and great vision.

“Now you have to look at the fundamentals of,”

"Okay, what are these products going to look like?" If you take Optimus, the humanoid robot, for example, there's a number of questions that people should ask. What is really this product? What problem is it addressing? What market does it really have?

Where is the demand going to come from? And even assuming that you solve these questions and these problems, then there's the other question that is, "Are you going to be able to make this product?" It's a brand new product, brand new supply chain, brand new design.

There's no history at Tesla. There's no experience building such a product. There's no track record of being able to ramp the supply chain and the production system at that level of complexity that is required and the quality and the cost, et cetera.

So when you look at these new lines of business, that Tesla is betting that Elon is betting the future of Tesla on, you look like as a dozen fundamental questions that need to be answered positively in the ability of the company to address and solve all of them.

So a lot of question marks on, in my opinion, with regards to these new lines of business, that are supposed to be the next wave of growth for the company. The stock is down 15% yesterday. It's down almost 25% from its peak.

But still, it's a $1.4 trillion company. It's trading at nearly 350 times earnings. It is all of that optimism still based in expectations around the humanoid robot and the robot taxi. And if so, is it too optimistic of people putting too much faith

“in this idea that all of those questions are going to be answered well by the company?”

So I will add one more challenge that Tesla has to overcome. That is often under estimated, or that we rarely talk about. If you look at what has made Tesla successful in the past, and the same applies to SpaceX by the way. So there's fundamentally this Elon's vision,

Elon's aspirational vision, the way he puts the vision into a strategy, but then to make the strategy actionable and to execute the strategy,

thousands of highly talented people. And these people used to come to Tesla and help Elon work. And I was one of them a few years ago attracted by the magnitude of the challenge, by the boldness of the ambition. And also by the fact that some of these problems were extremely how to solve,

“and that's what typically attracted talented people and ambitious people.”

They want to work on the hardest problems. That's what being able to attract and attract this kind of people has been fundamental in Tesla's successes in the past. Exactly the same thing at SpaceX. Now the difference compared to five years ago, eight years ago,

where Tesla had to solve incredible problems and challenges,

is that by now most of these people are gone. They're working on other things. They're still innovating and solving how problems, but they're doing it somewhere else, not at Tesla anymore. I know that really well because with my team,

we're all excesses of people. We launched a company creation platform. We launched 17 companies in the past few years. And they are literally hundreds of these people that are now using applying their talents in other places.

“So the question one of the questions that I'm still asking about Tesla now”

is now that all these people that made the success of Tesla, possibly in the past, that they no longer, they're helping Elon solve these problems. How is the company going to do that? So, if you look at the robot taxi business for example,

the company has to solve the autonomous driving, which is the first priority. But even if they are able to do that, and catch up to the levels of service that and safety that way more, for example, has achieved,

then they have to create a business out of this. And creating a business robot taxi, right-hailing business is something that took lift and Uber a decade to figure out how to position the cars,

so there's always availability.

How to maximize the revenue utilization, and put $1 invested, all these things, that Tesla is going to have to figure out. So, large number of questions and challenges to overcome, and there's this saying about the talent tool

that has made Tesla successful in the past, that has not been replaced, we all know, but the exodus and all these brilliant people that have less in the past few years. That's what gets me a bit concerned,

and at the same time, we've seen over and over again, that Elon has been able to figure out a way to overcome these issues and come up with new solutions.

“So, that's why it's hard for me to answer one way or the other,”

but I'm just looking at the number of challenges that they have to solve, and in the end, at some point running out of time, just because the competition is very active, and progressing, and moving very fast, and growing much faster than Tesla is at this point,

so Tesla is going to have to massive catch-up to do. And even on robotics, there's tens, and if not hundreds of companies that are actually working on it, making the competition and the space, really hard to win it.

Alright, Karen Booster, co-founder of Managing Partner at DVX, Ventures and former Vice President at Tesla, and left the career. We really appreciate your time. Thank you. Thanks for having me.

Google just delivered another blockbuster earnings report. Revenue jumped 24% year over year to nearly $120 billion. That was fueled by explosive growth in cloud revenue, which surged 82% from a year ago, net income quadruples to $12 billion,

and Gemini saw monthly active users grow to $950 million up 27% from February. But Google's AI push is coming at a cost. The company is spending so aggressively that free cash flow swung into negative territory

for the first time ever, ending the quarter at negative $5.9 billion.

And CapX guidance for 2026 was raised to $25 billion up from $19 billion reported in April, the stock dropped more than 4% during the earnings call. So joining us to discuss Google's earnings, we're speaking with Scott Devitt,

seeing a research analyst at Rosenblatt's securities. Scott, good to see you. Thank you for joining us. This was pretty good on the revenue side. Not just cloud, I would add. I mean, search revenue also growing pretty substantially up 17%

It seems like that was all overshadowed by the amount that they're spending on AI and the negative free cash flow. That seems like a big deal. What do you make of it? You have the stock reactions,

“and then you have like what's happening in the business,”

without a bit, it's been such a substantial move in the stock over the past 12 to 18 months. You know, some of this is just the digestion of this reality that good the business is doing right now. And if you look at, in a search business,

you mentioned up 17%. That business was thought to be left for dead 12, 18 months ago because of AI. And on that base that the company has to be growing that 17%,

also be growing YouTube 13%, building out way most capabilities. This company is like re-architecturing their entire business as they have the exploding cloud business. That's attached to the company.

Now it's well, and that was up. The cloud business was about 82%. So the major knit, you know, I think, is the fact that, as you mentioned, free cash flow of the negative,

“they're going to need more capital to grow the business.”

But when you get to the other side of this investment cycle, Alphabet's going to have rebuilt the entire company

and they have a multi-hundred billion dollar cloud business on top of it.

And so when they go into harvest mood, they think the spot starts to show much stronger returns. After I digest this kind of window of time of this kind of recovery period, the last 18 months. And now the reality, you know, setting in,

that's going to be expensive to build what they're doing. Just looking at, you know, YouTube, such, I mean, that traditional businesses that bread and butter, there is no question that they continue to excel. But just from my personal perspective,

it does seem concerning how aggressive they are getting with the AI spending, with the data-sender building. And there was some news that we were just digesting earlier, which I wanted to get your reaction to. This was some reporting from Nikkeh Asia,

where they found that there is a lot of debt that isn't being reported by some of the tech companies, like Google, Meta, Microsoft, Amazon, Oracle, that they are taking a lot of their debt and issuing it through SPVs,

which is basically off-balance sheet debt.

And to be clear, like there's not a lot of clarity into any of this, but I'm wondering if you consider that to be a concern for these big tech companies, the amount of debt that they're seeming to be more interested in issuing at this point, and then also the possibility that there's a lot of this happening off-the-balance sheet, and the questions that raises of the sustainability of how much they're spending.

So less concerned about the efforts of Alphabet and Amazon and Microsoft in that area, but some of the newer entrants that are being more aggressive with financing,

“I think that the smart companies for a period of time can only operate”

as well as their less smart competitors, in terms of the way that they structure the growth of this. And so I think the risk is just the proliferation of competitors and some less discipline than others that has the risk to drag down even those players that are discipline, which I put Alphabet in that basket as well as Amazon and Microsoft and Meta, but there's a lot more companies providing these services now,

and some like Meta that never provided cloud-based services before that are now getting into the business.

So from that standpoint, it's definitely worth monitoring. You know, there's a possibility that you get to the point where this build out goes too fast, and that lack of discipline ends up getting paid for by the great companies as well, and that's something we pay a lot of attention to. I will say with Alphabet, you know, here I think they're doing everything that they need to do as a company

to be well-positioned in this AI world, where when you re-architect the entire company through this process, you're limiting the number of competitors that exist in the world in the next 3, 5, 10 years. So when we get to the inevitable other side of this, there's just going to be less competition. If you're a small company competing and advertising and content and otherwise, there's almost zero chance you can compete with these companies with the amount of money that's being spent.

Just to on the cloud revenue that grew 82% and 25 billion dollars, huge numbers. Do we know much about who those customers are? And I ask that because one thing that I've been trying to monitor is how much of the revenue is coming from an open AI and an anthropic?

Do we know much about the diversification of that revenue?

“It's concentrated and those are two key components of it.”

I would say in addition with Alphabet now, you have the selling of the TPUs to third parties that's beginning to show up in revenue as well.

So I don't want to say it's polluted because that's not a bad thing, but that's a driver of incremental growth. Some would have a contributor to the acceleration, but the company did say that the cloud business accelerated even without that. And that's also going to be a big driver of the business, you know, in coming years. I mean, this is now on kind of a run rate path.

If you look at the current quarter plus the rate of growth, you know, about a hundred billion dollar business this year.

And then if you look at their backlog that they have as a company like the baseline for the next two years is north of 150 billion. You know, so there's so much growth here. If one player of faulters, then that can have an effect. But if one player of faulters and the demand for AI stays constant, then it will be manageable.

And that, you know, we may be seeing one if if someone that's in leadership position.

Now that that changes, you know, and two if demand for AI holds up otherwise.

“I think those are topics that have been flow in the day-to-day media as well.”

All right, Scott Devitt, seeing a research analyst at Rosenblatt Security Scott. We really appreciate you joining us. Thank you. Thank you. Okay.

That is it for today.

“Tune in tomorrow for a conversation with Noah Smith.”

We discussed the AI bubble, the rise of inequality in America, the fertility crisis, the national debt. And lots, lots more don't miss it. [Music] This episode was produced by Claire Miller and Alson Weiss and engine in by Benjamin Spencer. Our video editor is Brad Williams.

Our research team is down to long. Chris Nodon, Hugh, and Mia Savario, and our social producer is Jake McPherson. Thank you for listening to Prof. Markets from Prof. Media. If you liked what you heard, give us a follow. I'm Ed Alson. I'll see you tomorrow.

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