The $500 Billion AI Debt Machine & The Great CapEx Test

0:01This episode is brought to you by Google Chrome. You think you know a browser, but Gemini and Chrome, that's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a 50-page restoration block, or finally break down that long article you've had open for weeks. Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses set up required, compatibility and availability varies 18+. hello and welcome back to the market maker podcast and piers i was going through some of the analytics and looking at the performance of some of the recent episodes and and just as you might expect anything with ai in it seems to be outperforming and i don't want to be one who's like chasing clicks but if that's what the people want then who am i to deny them of that so give Give the masses what they crave.

0:54So in this episode, we would normally do a bit of review of the week. So what I've tried to do here from the research perspective for this episode is blend together some of the news that's been happening this week with the dominant kind of narrative stat of AI and on macro, on inflation, US CPI, which came out yesterday from when we were recording this. So it's kind of framed around this shift we've spoken about a few times in recent episodes between who builds the best AI model to now who has the trillions of dollars needed to build the data centers to run them. And that's distinctly tied to a headline of which we'll cover shortly.

1:34Piers Curran: yep absolutely um and like just to look at the numbers hitting the tape this week so there's a pure play ai cloud provider uh who you'll know the name of when we get to it um but basically they've been showing a staggering 104.2 billion dollar revenue backlog blog. I know that's a bit of a mouthful, but the order book, well, I don't think in the history of mankind there's ever been an order book that looks like this. Anyway, we'll get onto that. The next up is then, well, NVIDIA teaming up with six of Wall Street's heaviest hitters to basically mobilize a new$500 billion financing machine. And then we've got global AI capital expenditures pacing towards one trillion dollars annually that is um in terms of the if you like the hyperscaler uh spending splurge that seems to be continuing to accelerate yeah so we'll try and go through this in the next kind of 30 40 minutes been loving the comments by the way recent videos has really taken off.

2:50People sharing their ideas, agreeing, criticizing. Actually, if you do like the conversations in the show, do that, please, because it really helps the show perform on the different platforms. So we'd love to hear from you. So really dissecting then the financial plumbing, we can call it, behind this AI super cycle. When it comes to that company you mentioned, that company is CoreWeave. And CoreWeave had an earnings blowout. I think their shares went up like almost 20 % when I was watching Bloomberg yesterday. Brings up the question then, what are NeoClouds and why their revenue is doubling and how they manage their massive debt loads?

3:32I mean, the numbers are quite staggering, actually, which I'm sure you're going to unpack in a moment. With NVIDIA, their 500 billion Wall Street consortium. So the names involved in this, the ones that everyone likes to hear about, the Blackstones, the Apollos, and I guess trying to explain how they're transforming GPUs into a brand new financial asset class, which we were just talking offline about, which is really interesting. And I think a good point to know, particularly if you're a student, going into some of these conversations application season coming up. And then the CapEx, of course, ongoing tug of war.

4:08This massive hardware spending is triggering volatility in tech stocks and driving a bit of a rotation, some of the broader market sectors. So let's dive into this first theme, CoreWeave's Q2 earnings report. I went on the about section of CoreWeave and I was like, okay, what's the easiest way to try and explain this business? So here's the best way of doing it. And the reason why a lot of people look at it has become like this ultimate bellwether for AI hardware demand. And we'll talk about circular financing in a moment but it's really important within that ecosystem so what is it specialized cloud computing provider that builds data centers packed with these nvidia graphics processing units to rent high performance compute power to ai developers and major tech companies so that's what it is top line revenue so just 112 percent year over year to 2.58 billion they also raised their full-year guidance range to around 12.5 to 13.2 billion.

5:15So 112 % year-over-year revenue. You can't top that, surely. You haven't got any numbers that can get better than that.

5:24Piers Curran: Well, I can, because that wasn't the most impressive thing in the report. Even though that in of itself is just outrageous. The most crazy, crazy number was, as I mentioned, this$104.2 billion revenue backlog. So, I mean, what is that? So firstly, right, so they made$2.58 billion. That was our revenue. That's for the quarter that's behind us, okay? They'd given guidance for the full year that we're in to say that on this full year that we're currently in, we might get to 13 billion, okay? So think about those for some numbers. Even if you take the 13 billion and they hit that this year, 13 across a whole 12 months, their revenue backlog, that is basically their order book, that is orders committed, is 104 billion.

6:24which what's the legal um what's the legal tie-in for that are they well surely that could change though that number could could flex or i guess they'd probably have to pay a penalty right if you pull the order yeah absolutely look some the bears out there will talk of this circular

6:43Piers Curran: financing or put in a easier way to understand the house of cards and whether all that that's going to come collapsing down. We're going to talk about that in a minute. All right. But let's just bask in the glow of this unbelievable number. So look, that order book backlog, 104 billion, right? That's up just the backlog now has increased by 246 % year over year. Okay. So this is all cut. it's like in the last 12 months and well it's been in the last 24 months but the exponentiality of the way this is ramping is just staggering right and by the way then that being that right right after the quarter ended so not in these figures they just landed another 25 billion dollar in net new customer commitments 20 another 20 another 25 so that their backlogs now basically 130 billion, which is 10 times their forward-looking revenue for the year that we're in now.

7:52Piers Curran: I mean, words just failed me at this point. But look, so here we're talking about the long-term contracts from the big guns, all right? So it's your Metas, your Open AIs, your Microsofts, okay? And obviously, you can split and you might say, well, okay, that sounds all amazing. But when might this revenue, you know, when are they committing to this revenue? And actually, so 40 % of that$104 billion is committed in the next 24 months. You then got another 39 % that's committed 25 to 48 months, and then 21 % the remainder is committed for 48 months plus. So we're obviously talking about a very long, you know, runway of commitments here, which is awesome for this business.

8:42Piers Curran: I mean, look, you know, we're talking about valuations and so on, like your order, but your forward looking order book is everything, right? Because if you're buying shares in this company now, well, of course, you're buying future growth. And I mean, they've got committed growth that's just insane. Right. Maybe we could take a step back for a second. And this essentially is cloud. But when people think of that, a lot of people think traditional cloud providers. So Azure for Microsoft or Amazon AWS, Google Cloud. So maybe we could just explain for a moment, what is this? What is a NeoCloud rather than traditional cloud providers?

9:25Piers Curran: Okay, so your traditional hyperscalers, so the big three, as you've mentioned, right? So Amazon's AWS cloud, you've got Microsoft's Azure, and you've got Google cloud. So they've been building those platforms for decades, and they are general purpose computing. All right, we're talking web servers, whatever, enterprise databases, app backends. I mean, we are a big user of AWS, like Amplify ourselves. That's our cloud provider that we use, right? But it's general purpose. The NeoCloud, we're talking specialization here. These are specialized providers built ground up exclusively for artificial intelligence.

10:13Piers Curran: They are optimized for AI, right? So CoreWeave uses things like liquid cooled racks, custom high speed interconnect networks. They use bare metal GPU deployment. So outside of computing, you can kind of think of it as in Volkswagen and Tesla both make cars. But Volkswagen will try and use the traditional manufacturing plant and tweak it a little bit to make the electric vehicles. whereas Tesla's built ground up. Does that be a similar kind of comparable top level? You might say, yeah, Volkswagen's mass market, trying to build cars for everyone in the entire system, and maybe Ferrari, who are trying to build a car that can race around a track the fastest.

11:04Piers Curran: And so it's that specialization that has attracted all the big guns because their very specific spend from these hyperscalers, their very, very, very specific spend is for this AI. Is that why people buy Ferraris? Apparently. I don't think many people buy a Ferrari to race it around tracks. No, but from an engineering point of view. Of course. I know you're such an engineering purist. And that's what attracts people to buy them because they're buying into that specialization and the thought of it. Yeah, at any rate. Okay, so let's talk about the flip side of the hyper growth and the cost structure of this.

11:49Because giving you a couple more numbers from their earnings release that we had this week. So they reported an adjusted net loss of$567 million for the quarter. Their gap net loss was$1.14 per share. Check this figure out though, because everyone goes a bit CapEx crazy when they're talking about the fragility of the sort of stock market rally we've had based on the spend. So the capital expenditures hit 9.4 billion in Q2 alone. So the company's spending 9.4 billion in the quarter, their adjusted net loss of half a billion on the CapEx spend. What I thought I'd do is look for a comparable. And I know there's a bit of a defensive nature of Apple and they're not the biggest spenders on CapEx.

12:41But I just thought from a magnitude of company, given that not many people even know CoreWeave exists in the kind of public domain. So that 9.4 billion, Apple's CapEx in Q2, 2.5 billion. I mean, that's just insane.

12:59Piers Curran: Yeah. So look, whilst those revenue figures, the revenue growth's awesome the revenue backlog i the order book looking forwards is disgustingly unbelievable in a positive way they are racing to try and keep up with demand to the point where they're having to spend and spend and spend to try and keep up but the spending rate is right now obviously much greater like that 9.4 billion spending q2 their revenue was only 2.5. So they're spending three and a half, whatever that multiple is, three and a half, nearly four times their revenues, right? So obviously they're making a loss, but the point is that they can't capture that 104 billion order book.

13:51Piers Curran: They can't capture the money that's been committed without investing in their growth now, right? So it's about rapid expansion. so they're taking tens of billions in debt to buy nvidia chips and build out mega facilities and in fact you know quarterly interest expense alone surged to 640 million dollars so just to service the interest on the debt they're having to take on to try and build out capacity to try and capture this revenue commitment in the future right so a couple of more stats then power capacity um so core weave's active power footprint at the moment is 1.5 gigawatts right well that's what they're monetizing um they've got contracted power so what they've committed to to build out is to reach 4.2 gigawatts at the moment.

14:51Piers Curran: So they're at 1.5 gig and they've got a pathway to 4.2, right? Just to put that in perspective, one gigawatt powers about 750 ,000 homes, right? So if you think about CoreWeed's contracted power pipeline, it basically matches the electricity consumption of a city of 3 million households. So that's the kind of power roadmap that they're trying to fund and right now the revenues haven't quite caught up so they're still losing money. So if you want to know why you're sat in England right now and it's 38 degrees outside you could probably pin some of the blame on these guys contributing to that. But so the demand pipeline definitely is legit.

15:38I mean looking at those percentage splits and it seems very weighted to the near term which is a good thing. So 104 billion backlog. Is this like You often talk about this when you and I talk about more traditional markets, this priced for perfection idea. So is this an execution risk scenario?

16:01Piers Curran: For sure, it's an execution risk. But I would say more than anything, it's a funding risk. And we'll come on to it. It's the house of cards risk. Or maybe it's a solid foundation. It's kind of all interwoven, and people use this word circular financing. But I would say it's a funding risk above everything else. Okay, well on that point then, that ties into that other big story we had of the week. And that was NVIDIA announced strategic partnerships with six of the world's premier private capital institutions. Those being Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, KKR. They've got all of their hands in on this.

16:56Piers Curran: It's the big guns. But basically, what's the mandate? Basically, they're mobilizing over$500 billion of third-party capital over time to underwrite this whole AI infrastructure build-out. Yeah. And thinking about the sheer scale of this, historically chip makers sold hardware to companies that funded purchases out of corporate cash flow or standard corporate bonds. But to quote the main man in the center of all of this action, Jensen Huang of NVIDIA, the CEO, he said, in AI, compute is revenue. in his words. We're helping create a new class of productive investable infrastructure, i.e. these AI factories.

17:45So I thought that's quite a good then segue from what he said as to trying to then unpack this idea of the business model and this advent of a new asset class in terms of how these big institutional pockets of money, Blackstones and apollos and kkr's how are they engineering this these are clever people there's definite risk here so how have they done it in a way to mitigate that risk to maximize the opportunity

18:17Piers Curran: well i mean let's try and break it down you know how is this financial engineering actually working So like historically, I mean, think back pre-AI, tech hardware used to depreciate very quickly. That's just because, you know, the new version is going to be out next year, right? So in terms of what value can you extract from an asset? What's its lifetime worth to you as a business? And if you buy it this year, and if you're going to buy something else and replace it next year, well, obviously you've got a super short one year timeframe. And so you can't really, you know, you have to write off all that cost in this year, number one.

19:11Piers Curran: And you can't use that as a tangible asset to borrow against because next year it won't have any value, right? That's how it used to work. But the game in town now is basically NVIDIA's CUDA, right? That's their compute unified device architecture. Their kind of software ecosystem gives these GPUs a much longer, flexible software life across different models and operators. Okay, so there's this thing called the value cascade concept that they've come up with to try and give this a kind of basically a new category but basically the core argument is that the gpu stays cutting edge for six years so even though you think about nvidia and we talked about it on previous episodes their engine engineering kind of cycle is 12 months so each 12 months they're trying to bring out the latest chip and the latest chip is always you know several x factor better than the previous one so isn't it the same if you bought a chip last year well it's worth nothing this year?

20:20Piers Curran: Well, the answer is no. So they're basically in this CUDA system, these older chips stay valuable. So chips basically move down a hierarchy of workloads as it ages. And at each stage, it still generates revenue. So years three to four, we call this supporting the secondary life, real-time inference, right? And then you've got years five to six, there you support tertiary life it's more like batch inference and analytics workloads i mean what does that mean you know when you're on claude at the moment or chat gpt or whatever you can choose which of its systems to use right depending on the job you want it to have and basically think about it like that i don't want to use the Ferrari every single day, you know, just to drive to Sainsbury's.

21:14Piers Curran: Okay. So I want to use my, my Volkswagen Golf to go to Sainsbury's. So even though the Ferrari is much, much better, I'm still going to use the Golf and it's going to give me value. Basically these companies can continue to generate revenue for five, six, I don't know, people are talking 10 years, right? and obviously we don't know yet about the 10, but do we know about the five or six? What I will say is Michael Burry, the famous dude from The Big Short who nailed the financial crisis and made an absolute fortune, he's closed his hedge fund, closed it. I think it was at the end of last year. Closed it.

21:56Piers Curran: Why? Performance is shocking. Why? Because he was taking the other side of this argument. This precise argument. He was saying, these chips only have a 12-month lifetime. These companies are buying them, and then they're spreading and capitalizing that cost and spreading the cost over six, seven years. And this artificially inflates their profit. And so you're trading these stocks at valuations on the idea they're making these profits. He was saying they're false. However, Michael Burry's wrong. and he's now out of business because we're already seeing this this because we were talking when was it last week open ai launched its kind of consumer facing product in 2022 we're almost four years in now and these chips are still producing revenue so it looks like the companies are right and michael burry is wrong i'm reading a book at the moment called super forecasting which is this research theory about trying to determine really who has an ability to forecast things in the future and why this is particularly relevant in a financial context is like trying to identify you know who can predict what's going to happen in a certain event and so therefore you have to think about multiple different layers in order to arrive at that decision one of the qualifying factors early in the chapters is about when you have these people particularly in finance talking heads people who go on Bloomberg, sell-side institutions, Michael Burry, never ever will explicitly put a timeline on the forecast.

23:37And that null and voids the forecast in which they're making. Because if you're going to say this is an AI bubble, that's a house of cards, but you don't define the timeline, well, then basically it's an open-ended statement that has zero commitment and zero predictability power behind it. So if it does fail, you can expect Michael Burry to be like, right, Netflix, where's my, you know, the big short part two, because I want to get paid out now because I was right about everything like I'm right about before.

24:08Piers Curran: Well, of course, that's what happened in the financial crisis. He was so early on that trade, the trade being that the housing market's going to collapse. He was so early, he was almost too early. he was like starting to put these trades on 2005 2006 we got into 2007 and it was still going against him and against him and he was getting margin calls from the banks who he'd done over the counter options and kind of derivatives deals with to kind of position himself for this strategy and he almost killed him before then just just in time he was right and fine made a fortune So maybe there's an argument there that he's right, but not for five years.

24:55Yeah. Maybe he's just not right. The other one was Ray Dalio. There's a book called The Fund, if you read that one. And he was back in the 80s talking about all this negative stuff and very doom and gloom. But yeah, I mean, he ends up being right, but a decade or two off the needle. But okay, so summarizing then what you've said. So because these GPU clusters generate predictable long duration cache flows via these, you know, when you're dealing with these hyperscalers, these are long-term contracts off of very established deep capital pocketed companies who are spending big time. So even when you think about the others like Anthropic, but then the traditional ones like Meta.

25:44so wall street is treating them right to say like real estate or aircraft fleets or or probably the more correct definition infrastructure assets is that how you'd see it yeah absolutely yeah it's that classic you know if you want to lend someone money well then as the lender you know you obviously

26:08Piers Curran: got to assess the credit risk and you've got to assess well what's the opportunity for the person and I'm lending to here, and is there any tangible asset that I can under, or they can underwrite the loan with? So if it goes wrong and the wheels come off, what am I left with as the lender of value that I can extract at least some of my money and get it back? And yeah, so a very old school way of financing like a manufacturing business was you would lease your you'd basically sell your machinery you know on your production line and basically lease it back or you would borrow money with the machinery being the collateral to underwrite the loan you know it's these physical tangible things from which you are able to generate value and generate the revenue that you do right and so that's it these chips or these data centers if you want to kind of just zoom out a bit these are the infrastructure plays of our time it's interesting you said that because i know your your brother's in a bit of this space for the manufacturing plants yeah i didn't think of it like that so actually this isn't a new model it's a different type of machinery i the technology ships but the model is a traditional one this episode is brought to you by google chrome you think you know a browser but gemini and chrome that's new it can help you with practically anything on the web, like restoring a vintage motorcycle from a 50-page restoration block, or finally break down that long article you've had open for weeks.

27:45Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses set up required, compatibility and availability varies 18+.

27:55Piers Curran: This model is, oh my God, decades, decades, decades, decades old. Yeah. Okay, well, look, that leads us on then to the somewhat elephant in the room, which is that word, the circular financing that when you go on youtube it's like that's that's the buzzword because everyone wants the house of cards because we're human we love to see the world burn it seems to be the way that people like to look at these things so yeah let's dive into a little bit about when what happened to nvidia when some of this news was breaking with this funding because you would think hang about they're all they're forming a consortium they're gonna they're gonna give you a half a trillion dollars in cash to fuel the dream and then your shares fall like yeah how does that work well so on the news that broke earlier this week about this 500 billion dollar debt deal that nvidia have spun up their stock their share price dropped 2.9 and like for them that's a lot when you kind of spin it into market cap terms that's 60 billion market cap just vanishes, right?

29:05Piers Curran: Just in that 2.9 % drop. And this is because, you know, critics point to the circular nature of these deals, right? So NVIDIA invests in or helps structure debt for its clients, the NeoClouds, CoreWeave, for example, right? Those clients, they then use that borrowed cash to buy NVIDIA GPUs nvidia records that as revenue that's your circular bit right let's kind of let's like go on hold on given what you also previously said are they not also like a seed investor in open ai and therefore telling open ai you should have multiple series of models that users can deploy so that we can extend the lifetime value of the chip clusters so this is it right this is the house of cards.

30:02Piers Curran: So basically NVIDIA, they're using their balance sheet strength. Obviously, monster balance sheet. They've got cashflow that's just unbelievable. Massively strong balance sheet. And they're using that and their reputation to back its key customers. So how are they doing this? Like CoreWeave, they'll go and buy an equity stake. right and then in return they're going to get purchase commitments from core weave and basically from the lender's point of view you know if you're apollo why would i lend into this this circular machine it's because basically nvidia's the backstop guarantor for the loan right it's not a straightforward loan this you've got the payer of last resort is nvidia the biggest company on the planet who's got hundreds of billions of cash on their balance sheet right so these arrangements they typically come with strings though so as we've alluded to core weave commits to buying and deploying nvidia's latest chips so when you think about core weave's 104 billion you know revenue backlog.

31:18Piers Curran: Well, some of that is from obviously NVIDIA and this loan, but anyway, we'll come back to that. So the actual debt financing, these build outs comes mainly from the private credit and the kind of banks and the insurers, right? So NVIDIA's backing is part of what makes that debt investment grade. So investment grade is important here because CoreWeave have issued their own debt. They issued an 8.5 bits. This is separate to the NVIDIA 500 bill thing, right? They issued a corporate bond for 8.5 billion. And it was rated A3 by Moody's. This is March of this year. And that is the first GPU-backed loan to reach investment-grade status.

32:03Piers Curran: And the only reason it's investment-grade... So investment-grade status just means it's cheaper for CoreWeave to borrow because the credit risk is lower. If you like, the risk to the lender is lower and it's all lower and a lower interest rate as a result because NVIDIA and their role in that deck stack is basically, so it's less lender and it's more the entity whose backstop makes the debt investment grade in the first place. So because NVIDIA are propping this all up, it makes it cheaper for their customers to borrow to then buy nvidia chips that's your that's your kind of circular nature right but to kind of finish this off as long as core weave can build that compute which is dependent on hyperscalers keeping their commitments to buy that commute then fine revenues flow and the debt gets serviced okay the moment that basically the moment the hyperscalers stop spending or they're not they're not going to stop currently is an exponential acceleration in spending thus the moment we get evidence of a deceleration in spending it only needs to be a deceleration worse would be flattening so we're going to carry on spending but only at the same rate even worse would be we're going to start to reduce our spending right you've got different grades of problem here even worse i mean the absolute armageddon is we're going to stop spending right which isn't really going to happen but but just to finish if they stop spending, then obviously there's multiple NVIDIA exposures here.

34:02Piers Curran: There's revenue, like NVIDIA's revenue drops, their equity stakes in all of the pies they've got their fingers in, well, that devalues and basically then the backstop obligations become mount up and become maybe unserviceable and you get hit simultaneously, which is then that systemic concentration risk that analysts are flagging. yeah and just on that point of the concentration risk i read a research paper from columbia university and i know it's just a neat way of just summarizing that in three categories so one that you've just been talking about is nvidia's near um monopolistic position in ai chips compounds the concentration risk.

34:51I mean, it blows my mind that the authorities can let this happen. I mean, it's just kind of cops and robbers, I guess. When there's money to be made, you can move as fast as you can. The regulators are too busy trying to work out who's got power rather than sort out this sort of stuff. But the entire ecosystem stability, depending on one company's financial health, strategic decisions. So the monopoly that NVIDIA have, they're like the center of the universe they're the sun if you like in this instance then you've got the geographic and infrastructure concentration so you remember several months ago this is the additional layered risk if you remember the word Stargate that was the one if you remember when all of the all of the AI bros were with Trump in the Oval Office and they were like right yeah and then there was the SoftBank were there as well Oracle and they were talking about oh yeah they're all there and they were talking about a multiple hundred billions in cumulative spending across five u.s sites so that in itself creates a concentrated exposure to specific data center locations and power infrastructure i mean such as everything diversification is key and this is not that and then you've got the customer concentration which you've kind of alluded to yeah amplifying compounding the systemic nature of the risk so your microsoft alphabets your amazon and your metas so yeah and maybe maybe

36:24Piers Curran: like nvidia's the sun your hyperscalers that's the fuel that's powering that sun right as long as microsoft and alphabet and amazon and meta carry on spending shoveling in the fuel then we're fine okay there is another risk which is more of a regulatory risk for the u.s i would say because you've got those massive commitments oh we're going to build data centers here and there and whatever and all these states there's a real regulatory lots of regulatory hurdles slowing everything down so actually in the end so you've got a you've got a compute capacity problem you just can't build the stuff quick enough partially because the regulators get in the way and block it then you've got a power problem which is are there enough electrons in the world to actually power all of this kind of planned build out and that that's also back to regulatory stuff in the US you know trying to build more nuclear reactors I mean it basically takes 10 to 15 years to from start to finish to get a to spin up a nuclear reactor right I think China do it in 12 months so I think from a from a geopolitical race perspective yeah the US they want to be careful they don't score an own goal here by regulation regulating their way you know out of the front position that they're currently in well look let's step back a bit and let's look tie this into some of the macro context firstly of how does this fit then within the investment thesis or strategy so to speak So the fuel that they're shoveling into the sun.

38:13Piers Curran: So AI hyperscalers, their capex, this is an estimate for 2026, so a 12-month period, they'll spend$730 to$800 billion. That's just the four or so biggest companies, right? If you take everything, it's thought that we're going to break a trillion dollars this year, right? so like if you think about goldman's and jp so they're projected global ai so if you're trying to forecast this out as you said it's very difficult but morgan stanley estimates that the total cumulative hyperscaler spending will cross 3.5 trillion over the next three years 3.5 trillion so if morgan stanley are right if these hyperscalers carry on stepping up their spend which they will only do if they can prove a return on investment for this spend then this this engine this circular financing engine will carry on firing like super hot But if at any point there's not an ROI sort of evidence, then this is where your kind of wheels come off this circular financing machine.

39:41In order to sort of hedge yourself then in this scenario, is this where Stephen and I were talking about this a few episodes ago. So this is where you diversify by moving into the other parts of the supply chain, namely, as you were just talking about, energy is the ingredient, energy and utilities, so data centers requiring power, driving demand for nuclear, nat gas, grid infrastructure. Then you've got the industrial material orientated category, so electrical transformers, cooling systems, construction, so forth. Interestingly, I was with my friend from uni at the weekend and he's a surveyor and he was saying it's crazy where Google has these like secret entities that goes around just buying up swabs of like real estate so they don't get basically charged a ton of money.

40:38And they're just trying to find any location in proximity to natural water where it pulled out some of these centers and it's going crazy. And then there's the value and defensive, so high dividend sectors providing that stability while the mega tech digests its capex investments. So maybe we could kind of finish this section off then. One other thing that we did see was Anthropic. And the FT just broke a few hours before we were recording this. The valuation of$2 trillion. i thought we were at one what have i missed i've blinked i've missed it

41:22Piers Curran: revenue growth that's what you've missed we're a little bit in the dark right if you go back to the start of the year we know that at the end of last year they were on a 10 um a 10 billion dollar revenue run rate so in that month of december if you just took what they did in that month multiplied it by 12, then that's 10 billion. They were at 1 billion at the end of 2024. So that's a 10x growth, right? Now at the start of this year, everyone was going, they can 10x again. So 1 billion to 10 billion to 100 billion, they can 10x again here, right? And everyone's going, no way, not possible, not possible.

42:09Piers Curran: In May, which is the last official revenue kind of news we got there they're already at 80 billion now we're in a blackout phase because they've filed for their ipo they go dark so we actually haven't heard anything much from them but you're now people who were in the know they're talking about they're talking about by the end of this year forget 100 they're look they're 110 120 billion which would be a 12x so that the growth rate is accelerating. And then you're talking about people saying, well, it's going to 10x again the year after. So people are saying they'll do a trillion dollars of revenue, or the run rate at least will be a trillion dollars by the end of 2027.

42:55Bear in mind the biggest companies on the planet do, what, 400 billion,

43:01Piers Curran: like the hyperscalers. They do 400, 500 billion revenue a year. we're talking a company that didn't exist five years ago didn't exist doing a double that trillion dollars by the end of 2027 look that's that's the that's the bull case right um so the point about valuation then well because it's hard right how do you compare it uh to you know what's what's the kind of market comp here and you could look to people like palantir for example or nebius right these are they're obviously much smaller but they're trading at 55 times revenue in the open market now right so if anthropics growing basically was like a thousand percent a year um then you would think you know even at the low end they'd be getting 30 times revenue like low end 30 times revenue would be three trillion not two some are saying two trillions an absolute steal so it's like caveat though when i was reading this report on the ft the person quoted in saying these numbers you're right there's let's say a blackout period not allowed to speak just so happens to be an investor in the company but you know just talking their book up i mean i don't think they're wrong like don't get me wrong but i think it's uh yeah it's so funny this is like the marketing uh the marketing person just juicing just you know we haven't heard from anthropic in a while it feels like it's been a couple of weeks hang about back front and center please all this core weave core weave go away come on this is anthropic story this is october three trillion here we go so yeah interesting um so one thing then to wrap up this bit then we'll talk to close on us cpi and tie this to the macro because as i said the two major narratives for markets definitely are this ai infrastructure and where it might go and the spend around it, given the magnitude of the companies involved in it, lifting the stock market to these record highs, but also the macro climate in regards to inflation and interest rates.

45:21Before we taught US CPI, is Wall Street's$500 billion private credit pool a masterstroke then in scaling this global compute infrastructure? Or is it too much leverage before the RRI has even begun to be proven? I don't want your answer, Piers. I want anyone listening because this is quite divisive. What do you think? I've got a feeling everyone's going to be slightly bearish here, but I'd love to see the thesis behind the bullish or bearishness that people have. All right. Let's hear. Let's talk about the US CPI report then because, lo and behold, stocks did rise on the back of this and it was a bit of a surprise.

46:09The one that Bloomberg and the rest of the financial media were latching onto, rightly or wrongly, was the core CPI. That came in at 0.2 % month-to-month, 2.5 % year-on-year, the slowest annual pace since March of 2021. So how does that fit in then to where the market is at with its thinking with the new Fed chair, Walsh and interest rate expectations going out for 2026 yeah

46:41Piers Curran: so it's a good report 2.5 % you're right it's the lowest since March 2020 however it matches January and February 2026 numbers so we have been here this is like a new low we don't say that it doesn't sound a sexy thing you don't why did you have to go and mention that so look we had I think obviously it's tied all to Straits of Hormuz and what goes on and energy prices and how that filters down through the system. But look, we're back to pre-Straits of Hormuz, right? That's the point here. January and February, before things kicked off in the Gulf, we were at 2.5. And we were expecting the downward trend of the previous couple of years to continue.

47:29Piers Curran: And back then, remember, we were expecting a couple of rate cuts this year. If that trend were to continue, it obviously didn't. We bucked higher. So we went 2.6 March, we went 2.8 April, we went 2.9 May, but now it's toppled back down. June 2.6, July 2.5. So it's like, all right, that inflation concern maybe is over. So it just means Walsh doesn't have to hike. I think you forget, we've got one more so this was inflation for july right we will actually have the august inflation data announced before the next fed meeting but based on this yeah the fed watch tool which allows us to look at short-term interest rate futures so it basically gives us an implied probability of how the markets are expecting what for when and so that now sees a september rate hike odds down to 38%.

48:25I think that's too high. I'd be selling that myself.

48:31Piers Curran: I'm a seller. There is the one thing in the mix in the basket that's causing concern. Computer, software, and accessories. That part of the basket is up 21 % year on year. Why? Because of everything we've just spoken about, right? The demand or the lack, the demand supply imbalance for everything AI has meant the cost of these semiconductors, chips, for example, has just gone through the roof. So obviously that's feeding through into inflation, but it's not enough. That component's currently not big enough. Or, I mean, you could argue the basket isn't set up appropriately for the modern day's expenditure.

49:17Piers Curran: So I don't know, there's two sides to that argument, right? But for now, the way the inflation basket is measured at the moment, that computer software and accessories classification isn't enough to kind of take the whole inflation number back higher, right? So there is one thing in the basket, just as a quick aside, biggest faller in the basket, lettuce the price of lettuce dropped 16.4 percent there you go i can i can stack my burger now with tomato and lettuce there's a disease there's a parasite or disease in the midwest in the u.s in lettuce people aren't buying it because they don't want to get so you've got now oversupply because the demand has dropped so you've got let it stand 16.4 % so there's a supply and demand case study if you want to go and grab hold of that and then one thing on the timeline also to be aware of next month is Jackson Hole the Jackson Hole symposium is one of those platforms where the Fed chair gets to give a keynote speech that's happening at the end of august i think 27th through to 29th he's normally like the main headline act like the glastonbury headline and it's definitely outside of the fixed set schedule of fed events that happen eight times a year that's the other one where if there is a little signal to the issue to the market about what's going to happen in september the likelihood he might give some things or not given what he's like I don't know come up and go hi nice mountain scenery thanks very much he's going to say nothing I know historically that holds not a thing anymore I don't think well I think it's definitely going to become less and less a thing whether it's he's only just got into the seat so maybe it's still a thing but I doubt he would use that platform to signal forward guidance given that everything he's about is not giving forward guidance right so it's good nightlife though out in wyoming he might have a few beers the night before and then the genuine kevin comes out to play and then we can have some trading activity then keep trading

51:48Okay, so that concludes the episode. As I said, love to hear your thoughts and what you think about a lot of the, particularly the AI investing side of things. Let us know, but thanks very much, Piers, and thanks everyone for listening. Thanks a lot. Brussels clean up nicely at Sweetgreen. Maple glazed, roasted, and edges perfectly caramelized. Sweetgreen's fall harvest is back on the menu and the season's most overlooked little green vegetable is dressed to be devoured. You know what to do. Order on the Sweetgreen app.