1 Earnings Report That Could Move the Market

0:01Matt Frankel:There's one earnings report that could move the market. Motley Fool Hidden Gems Investing starts now. Welcome to Motley Fool Hidden Gems Investing. My name is Jon Quast. I'm your host today and I'm joined by our guests, Matt Frankel and Rachel Warren. Today we're going to dive into our mailbag a couple of times to talk about data centers, also talk about mergers and acquisitions. but first we wanted to get to our kind of news of the week this week nvidia is going to report quarterly earnings results and just to share an anecdote from over the weekend it's amazing that there are some people who still don't know what nvidia is and i had to explain it to somebody so i want to do that here in the podcast not take for granted that everybody knows what nvidia is this is a five trillion dollar company so mass very very very important uh really kind of got its start in gaming, but those GPUs that it makes are what is powering the AI revolution.

0:59Matt Frankel:And these are what are being bought up like crazy to fill the data centers that you might have heard about that are going in around the country. So very, very important company. And it is reporting its earnings later this week, Wednesday to be precise. And so just as we get started here, Matt, tell us about NVIDIA and what we should look forward to in this report.

1:23Jon Quast:Yeah, well, I mean, just to put what you said in a little more perspective, NVIDIA actually invented the GPU, and they have roughly a 95 % market share in the data center GPU space. So they're a dominant player. That's why all these data centers that everyone's pushing back, being built in their towns, it's their chips that are filling them. So they're expected to report about$92 billion in revenue this quarter. Billion, would it be? Their management guided for$91 billion, but honestly, investors kind of just simply assume that they're going to beat expectations at this point. It's a pretty fair assumption given the past few quarters.

1:59Jon Quast:So that would be roughly 100 % year-over-year growth, as well as a sequential acceleration, meaning that the growth rate from quarter to quarter is expected to pick up. And that's off of an already pretty enormous revenue base. So, I mean, of course, Data Center is the big piece to watch. They do other things, but quite frankly, everything else NVIDIA does, their gaming chips that you mentioned, Pro Visualization, which is like graphic design chips and things like that. The auto division, they make chips for automotive use. They're essentially rounding errors at this point compared to the data center business.

2:30Matt Frankel:Yeah, and they would be enormous standalone companies if they were standalone. But I just want to circle back to what you just said here. We're talking about the world's most valuable company growing revenue at 100 % year over year, doubling year over year. I mean, this is just absolutely astonishing. But one of the other astonishing things, if that wasn't astonishing enough, is NVIDIA's margin over the last decade. You know, 10 years ago, a 58 % gross margin, more or less, and that's good. But right now, sitting at 74 % gross margin, basically for every$100 of product that they sell, it only costs them$36 to make it in direct costs.

3:08Matt Frankel:Obviously, there's operational costs as well, but$74 gross profit per 100 that they sell. is this something that investors should watch in the upcoming report?

3:17Jon Quast:Yeah, for sure. And it's something I'll definitely be keeping an eye on. The margins, it's not just because NVIDIA got a lot bigger over the past 10 years. That's definitely part of it. Like, you know, companies get more efficient as they scale. A lot of it is because of the new big data center build out. NVIDIA has a lot of pricing power. They can charge whatever they want. They're essentially sold out of chips for data centers for the next couple of years. So right now they can charge whatever they want. So I'm going to be really watching that because It's a great indicator of pricing power.

3:45Jon Quast:And I'm especially interested because AMD just rolled out its first full scale rack system for data centers. So competition is heating up that 95 % market share. AMD is trying to take some of it. So, you know, the margins are going to be a good indicator of whether or not they're successful.

4:02Matt Frankel:So, Rachel, let's bring you in here because obviously higher gross margin good and that could start to come down feasibly. let's say that there's just not as much demand or if competition starts coming in, what would be a level of gross margin that it comes down to that you would start to be concerned about the competitive nature of the market? Yeah, well, first I want to talk a little bit more about what's driving these gross margins. I mean, Matt hit on it briefly, but to understand, you know, how is NVIDIA commanding these roughly 75 % gross margins? You really have to look more at that supply, demand, and balance in high-end computing that we're seeing right now.

4:39So right now, the hyperscalers, right, Microsoft, Amazon, Alphabet, they are ordering these next generation ships faster than NVIDIA's manufacturing partner, DSMC, can actually produce them. And, you know, it's a classic scenario of when demand heavily outstripped supply, you have essentially total pricing power. NVIDIA can pass these rising input costs, like the surging prices of high bandwidth memory from suppliers like SK Hynix. They can pass these costs right out of their customers without hurting order volumes. But it's also important to note, you know, they have millions of developers locked into their proprietary Kuda software ecosystem.

5:15And, you know, building or optimizing an AI model for anything else takes months of engineering work. There's a real lack of viable alternatives that work out of the box. And so a lot of the tech giants choose to pay NVIDIA's premium prices rather than to risk falling behind in the AI race. and they're buying in so doing from NVIDIA, really what's an entire ecosystem, not just the silicon. Now, for me, where I would maybe start getting a little bit nervous or at least questioning what's happening behind the scenes is if gross margins were starting to fall down towards that 70 % floor. It kind of might tell us a bit of a story about what's happening on the ground.

5:49It could indicate that supply would have caught up with or exceeded market demand. It could also mean that some of those cheaper competitive architectures like AMD's MI300 series or Hyperscaler's internal custom chips, which is another piece as well to consider, might have achieved some software compatibility that bypasses that moat. Now, I do not think that we are anywhere close to that reality. I also don't think, to be clear, this is a winner-takes-all scenario. But those are some things to watch as we get deeper into the AI race and the AI revolution.

6:24Matt Frankel:Obviously, on this podcast, we don't do an earnings preview for all the companies. And the reason that we're doing it for NVIDIA today is not for so much completely NVIDIA's sake. Obviously, we're talking about NVIDIA stock, but there is, in my opinion, a 0 % chance that something good would happen for NVIDIA that wouldn't have economic ripples throughout the stock market. Or conversely, something bad would happen with NVIDIA and we wouldn't see the ripple effects from that as well. And so I guess here my question to you guys is going into this earnings report, one, do you own NVIDIA stock personally?

6:58Matt Frankel:And what are the kind of the connected places in the market that you'll be watching for that ripple? Well, to answer your first question, John, I don't currently own NVIDIA stock heading into earnings. Part of it's the valuation. I'm right now just happy to watch this one from the sidelines. I think, you know, any statement from management that would trigger sort of an effect across the entire sector, I don't think it would be about things like a manufacturing delay or even a slight marginness, actually, to be clear, to go back to our prior conversation. I think it would be maybe any commentary from Jensen Huang that would indicate some type of deceleration or plateauing in hyperscalar CapEx.

7:38Now, we're not looking at a scenario anytime soon where this is likely to happen. I think what we are seeing is the hyperscalar balance sheets are very strong. We're looking for another double increase in AI CapEx spending heading into next year. And honestly, the competitive pressure among the tech giants to build out infrastructure is so intense, they can't really afford to blink or to slow down the build out. We've seen all the big tech management teams saying that the risk of underinvesting in AI infrastructure vastly outweighs the risk of overbuilding. And I think it's also important to note, you know, the Microsoft, Alphabet, Meta, these are companies that are generating tremendous cash flow from their core advertising and cloud businesses.

8:21They're putting that back into data centers to secure market share. So the cloud providers are seeing huge backlogs of enterprise customers also waiting for compute capacity. So that near-term demand pipeline remains filled. So any commentary from Jensen Hong about a slowdown in the build-out would be key, but I don't think we're gonna be seeing that anytime soon.

8:38Jon Quast:Yeah, I don't own NVIDIA. I mean, at least not directly. By ETF ownership, I've calculated it. NVIDIA is something like 3 % of my total portfolio just indirectly. But I'll be watching the results really closely because NVIDIA's performance can have ripple effects on so many other companies and not just the hyperscalers, which that's definitely part of it. I mean, NVIDIA's numbers, their future guidance, the commentary they give, it gives a sense of the pace of the AI build out. That could have a big implications for, you know, networking companies like Cisco and Arista Networks, for example, that, you know, are direct winners when these NVIDIA chips are installed and have to be linked together.

9:16Jon Quast:Nvidia's tone on future demand, it affects how companies like, say, Applied Materials, which builds the equipment that semiconductors are made with. So they can kind of forecast future demand and investors can forecast future demand based on what Nvidia is doing. So those are just a couple examples. I mean, we could spend a whole episode on all the companies that are affected by Nvidia in one way or another, and I don't even know if that would be enough. But there are a lot of ripple effects that we're going to see in the wake of NVIDIA's announcement. NVIDIA might not even be the biggest stock to move, or the stock movement on its announcement.

9:52Matt Frankel:Yeah, when we are talking about a$5 trillion company, you better believe that there will be some movement around the market. And so thank you all for sharing your thoughts on that. But we are not done because after the break, we're going to take a mailbag question regarding data centers. You're listening to Motley Fool Hidden Gems Investing.

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11:41Matt Frankel:Welcome back to Motley Fool Hidden Gems Investing. We love to take questions from our mailbag, and I'm going to go ahead and read this one. This comes from a listener in Bogota, Colombia. So thank you for listening to our show. And basically, the premise of the question is pointing out that back in the 70s, a computer used to fill a room, and now we can carry it around in our pocket. So computing has a history of doing more with less. And so here's the question. What happens to all this spending if data centers follow the same path? If chips and cooling get efficient enough that the same workloads need far less physical infrastructure, does today's build out end up looking overbuilt?

12:24Matt Frankel:Or does demand grow fast enough to absorb whatever efficiency gains show up? Would love to hear your thoughts. Thanks. And that's from Nico. Matt, I want to I want you to answer this question first. So essentially, the question is, in the past, computers became more efficient. We could do more with less. Therefore, it's reasonable to assume with in the future with AI, we can do more with less. And so the question is, are we building way too much physical infrastructure if that's the case? So you have an interesting observation here about two kinds of overbuilding. On one, you kind of have supply and demand temporarily out of balance.

13:04Matt Frankel:And the other, you have an evaporation of demand completely. Just walk us through what you're thinking. Yeah.

13:10Jon Quast:So I know the commercial real estate industry very well. And that's really what this is not a technical question. This is a real estate question. There are two kinds of overbuilding you see in real estate. So for just the first one, a few years ago, self-storage had a surge of demand during the pandemic. Everyone wanted to declutter their space because they were stuck in their homes. and by 2023 markets had too many too much supplies you know these were very easy to build they're little more than prefab buildings in most cases and but after a couple years of little to no development the market started to reach equilibrium we're also seeing that happen in the warehouse space right now as e-commerce demand was really pulled forward the other type is what happened with office space office space has oversupply issues because of a permanent structural change People are working from home.

13:58Jon Quast:The three of us are working remotely as we record this. I mean, there's a lot less need for office space than there used to be. And that's not going to reach equilibrium until offices are demolished, turned into other things. And so it's a great question of what basket we're going to be in. So when it comes to data centers, we are going to see some overbuilding at some point. You know, even if it's very temporary, like there's a surge in development and there's a chip shortage or a power shortage or whatever, there's going to be some supply demand imbalance at some point. But it's a really great question of whether these are going to be temporary supply demand issues or a more structural like office type problem if chips and cooling do become more efficient and less space is needed.

14:43Matt Frankel:Well, and that's really the question, right? Which basket do we fall in? Because there are profound differences in the implications of those answers. And, you know, I would say that on the one hand, I can make the argument that there is no imbalance right now because I just saw some research this morning saying that data center vacancy is only at 1%, whereas more historically, it's closer to 5%. So and already sold out with what is coming online. So it seems like demand is still pretty high, but assuming we can do more with less with AI in the future, I guess my question is, are we building the physical infrastructure based on AI today or are we building the infrastructure for the AI of the future?

15:23Jon Quast:I think we're going to see a self-storage situation unfold here. So, I mean, let me unpack that a bit. So historically, the more technologically efficient something gets, more consumption happens. So the question is predicting that chips will become far more efficient and take up less data center space over time, a prediction that's likely to be accurate. But the overbuilt thesis assumes that companies that need data center space, like the Anthropics, the OpenAIs, the Googles, just want to do the same amount of work with less space because they're more efficient. But more efficient compute will unlock workloads that aren't economical before.

16:01Jon Quast:I mean, do you think Apple's factory space has gotten bigger or smaller since PCs took up a whole room and now can fit in your pocket? Do you think they need more or less factory space now? And the way I'm asking that, I'm sure you know the answer. I'm sure the same thing is going to apply here over the next decade or two, although we're going to see supply demand balances along the way. But I'm also assuming, and it's a pretty big assumption, that chips and equipment will not only become far more efficient, but will become cheaper based on the amount of compute, kind of like how PCs did over time.

16:36Jon Quast:Now, the data center build-out right now is very capital intensive. And honestly, that's the biggest bear case to everything I just said.

16:43Matt Frankel:But Rachel, there is an official term for what Matt has just walked us through and just introduced to us. What is that official term and how does it work? Yeah, I mean, this is very much kind of bringing us back to this foundational concept in economics known as the Jevons paradox. So in the 19th century, there was an economist named William Stanley Jevons, and he observed that when steam engines became more fuel efficient, coal consumption didn't actually decrease, it skyrocketed. And because steam power became cheaper and more practical, there were entirely new industries that adopted it and even formed from it.

17:20And we are seeing that play out with AI data centers right now. Obviously, it's a different time, but this is very much a concept that, in my view, rings true. When we are seeing these companies find ways to make AI chips or cooling systems more efficient, it drastically lowers the cost of a single AI computation or token. And lower costs make AI economically viable for a new wave of applications that maybe used to be too expensive to run. So, you know, for instance, if inference costs drop significantly, a company can pivot from using AI occasionally to running really complex, continuous AI agents across their entire supply chain.

17:59That's just a basic example. So what you see when you look at this concept and you bring it forward into the AI and data center era is that rather than shrinking the physical footprint, efficiency can act as an accelerator for demand. And tech giants aren't really looking at efficiency gains as a way to downsize their data centers. They see it as a way to extract vastly more capability out of the infrastructure they're currently building. And we are seeing a huge appetite for compute that doesn't appear anywhere close to slowing down. In my view, I think that the current buildout is unlikely to result in overcapacity because demand is scaling at a pace that is much faster than hardware is shrinking.

18:41Matt Frankel:Of course, the counter argument to Jevon's paradox is, especially when we look at the historical example, you had coal, but you also had a ton of businesses lined up with real demand on the other side of that coal price coming down. And I think that kind of the counter argument here with AI is that a lot of the demand is perhaps being subsidized, and that does have a finite lifespan. At some point, it will need to be financed with cash flows. And so is the demand really there? I think that's a question that is really pertinent to this discussion. However, if I'm going to stake my claim on one side of this or the other, I would say we're probably not overbuilding by a whole lot right now because demand is so high, but that's just my take.

19:22Matt Frankel:Coming up after the break, we are going to dip back into the mailbag a second time, and we're going to talk about some acquisitions. You're listening to Motley Fool Hidden Gems Investing.

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