CoreWeave's CSO on the Business of Building AI Datacenters

26:51So you talked about the advantages of NVIDIA hardware, like the chips themselves. But one of the things you sometimes hear is that those same chips might perform differently in different clouds. So what is it that you can do to sort of boost the performance of the same chip in your structure or ecosystem versus, say, an AWS or someone like that? Sure. Great question. We do a lot of work around this internally. And it's a big part of our technical differentiation. And what we call it internally is mission control. And mission control is effectively a portfolio of different services that we run on our infrastructure to make sure that these incredibly complex supercomputers are healthy and performant and are optimized, where we take a lot of that responsibility off of our customer engineering teams.

27:41And it sounds like that might be an easy lift, but when you're running supercomputer scale, you know, you need a team of 50 to do that, right? So we provide a ton of software automation around that, providing that health checking and observability to our customers. But it's also the engineering engagement, right? Is, you know, working with our customers to understand, okay, what are you doing? What's the best way to optimize this? How do we, you know, how did we design the data center to be more performant, to make sure your storage solution was correct, your networking solution was correct. So it's not just a, hey, CoreWeave provides like this one little thing that makes it better.

28:14It's the comprehensive solution starting from the data center design through the software automation and health checking and monitoring via mission control, via the engineering relationships that really add that value. Let's talk about electricity because this has become this huge talking point that this is the major constraint. And now that you're becoming more vertically integrated and having to stand up more of your operations, we talked to one guy formerly at Microsoft who said, you know, One of the issues is that there may be a backlash in some communities who don't want, you know, their scarce electricity to go to data centers when they could go to household air conditioning.

28:48What are you running into right now or what are you seeing? So we've been very, very selective on where we put data centers. We don't have anything in Ashburn, Virginia, right? And the northern Virginia market, I think, is incredibly saturated. There's a lot of growing backlash in that market around power usage. And, you know, just thinking about how do you get enough diesel trucks in there to refill generators that they have a prolonged outage, right? So I think that there's some markets where it's just like, okay, like stay away from that. And when the grids have issues and that market hasn't really had an issue yet, it becomes an acute problem immediately.

29:21Like just think about the Texas power market crisis back in, I think it was 2021, 2020, where the grid wasn't really set up to be able to handle the frigid temperatures. and they had natural gas valves that were freezing off at the natural gas generation plants that didn't allow them to actually come online and produce electricity, no matter how high the price was, right? So there's going to be these acute issues that, you know, people are going to learn from and the regulators are going to learn from to make sure they don't happen again. And we're kind of citing our plants and markets where our data centers and markets where we think the grid infrastructure is capable of handling it, right?

29:56And it's not just, is there enough power? It's also on things, you know, AI workloads are pretty volatile in how much power they use. And they're volatile because, you know, every 15 minutes or every 30 minutes, you effectively stop the job to save the progress you've made, right? And it's so expensive to run these clusters that you don't want to lose hundreds of thousands of dollars of progress. So they take a minute, they do what's called checkpointing, where they write the current state of the job back to storage. And that checkpointing time, your power usage basically goes from 100 % to like 10%.

30:27And then it goes right back up again when it's done saving it. So that load volatility on a local market will create either voltage spikes or voltage sags. And a voltage sag is what you see is what causes a brownout that we used to see a lot of times when people turn their air conditioners on. And it's thinking through, OK, how do I ensure that, you know, my AI installation doesn't cause a brownout when people are turning their, you know, during checkpointing, when people are turning their air conditioners on? Like, that's the type of stuff that we're thoughtful around. Like, how do we make sure we don't do this?

30:57Right. And, you know, talking to engineers and NVIDIA's engineering expertise, like they're working on this problem as well. And they're they've solved this for the next generation. So it's everything from is there enough power there? What's the source of that power? You know, how clean is it? How do we make sure that we're investing in solar and stuff in the area to make sure that we're we're not just taking power from the grid to also when we're using that power? How is it going to impact the consumers around us? I want to ask you more about what NVIDIA is doing. But just on that note, what's the most important metric for evaluating a data center's quality or performance?

31:32Is it like days without brownouts or uninterrupted power supply? Or is it measures of efficiency, like power usage effectiveness or something like that? If I'm surveying a bunch of data centers, I want to pick a good one. What should I be looking for? So right now the market's pretty thin. So right now - I won't have a lot of options. Okay. Imagine I'm like the biggest customer on earth and I can get in anywhere. What should I be looking for? So the first thing goes back to the electricity piece, right? Is the grid stable? Is there enough power supply? Is there excess renewable generation in the area that doesn't have the ability to make it to downstream consumers, right?

32:12A lot of the renewables that we have in the U.S. are built in places that don't necessarily have the consumers. So you're citing these data centers in places where you have this excess supply. So that's the first piece, right, is how good is the electricity supply and how angry are the people around me going to be if I take it? Now, you go from there into everything else is kind of solvable, right, in the way that you design it. And if you're building a greenfield, it's, okay, you know, what type of UPS systems am I putting in? Are they capable of handling that load volatility? You know, how am I thinking about my cooling solutions?

32:46There's been a big shift to liquid cooling, right? And liquid cooling from a PUE perspective isn't a 30 % to 40 % decrease in electricity utilization like people think. It's more like 60 % to 70%, right? And the reason for that is it's not just the efficiency of the data center plant. it's also that now if you're not cooling things with air you don't have to run the fans inside the servers as well and for these ai installations because they're so dense the fans consume a lot of energy right so everything that we're building now is a combination of liquid and air cooling right and the liquid cooling piece has solved the pue issue right and we're everything we're doing is trying to say okay how much power can we use only for running our critical like it operations versus cooling the environment, making sure the environment's running correctly from a resiliency perspective.

33:39And there's been big strides made there over the last 12 months.

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35:05Need AI to turn 100 pages of market research into five insights with a click? Do that with Acrobat. Need templates for a sales proposal that'll close that deal? Do that with Acrobat. Need an AI specialist to tailor the tone of your market report to sound real smart in real time? Do that with the all-new Adobe Acrobat Studio. Learn more at adobe.com slash do that with Acrobat. Does co-location trump grid reliability? Like if I'm Elon Musk building some sort of new AI thing, as I think he's doing, in Texas, say, like, am I just going to have to find a data center in Texas? Or how much flexibility do I have to use one further away?

35:49So great question. It's a different answer for different use cases at different times. And right now, we're in the middle of this rush to train, whether they're open source or proprietary foundation models, the largest, most valuable companies in the world. And they're mostly worried about access to contiguous compute capacity. How much compute can I get in one location all connected together so I can go faster than the next guy? But when the models are trained, they want that compute to then be local to their customer base, right? How do they take it from the middle of nowhere and then go serve it in the metropolitan markets?

36:25And as the use cases are more distilled and they get more real time, think like the type ahead suggestions that you get in your Gmail account, right? As you're typing something and it's getting better and better, it's, you know, that's an AI model somewhere predicting what you would want to say next. and they want to make sure that's delivered at human speed. So that human speed is a latency consideration, right? As you're citing those GPUs and you're citing that compute to be local to the people that are using it. So that move started probably four months ago where we saw customers finally becoming concerned around latency for their serving use cases.

37:03So initially training, people don't really care where it is, cheap power, reliable grid. They just need it all contiguous and they need it fast. And then down the road, as their applications find success, they're more worried about where the compute is for their customers. What are some of the areas that are going to be the next northern Virginia when it comes to data center clusters? So I think we're seeing it in Atlanta already, where Georgia has paused or has attempted to pause some of their tax incentives around it because they want to make sure they do grid studies. I think that we're probably going to see it in some of the other hotspots.

37:39You see AWS up in Oregon who is trying to find creative alternative ways to power their data centers from non-grid generation to alleviate some concerns there. But I think that the market has to solve this problem. And you're starting to see some of the startups around nuclear generation and the small reactors at the data center level as people are being thoughtful for five to 10 years from now. Do you have any influence on the type of power being built in certain areas? Could you say to a utility company of some sort, we're here, we need access to energy, but we want it to come in a particular form?

38:20So you can, but you have to understand that the investment cycles and the physical build cycles for those are so much longer than how quickly our customers need infrastructure. So you may go to a market and say, hey, we're going to be here over the next 10 years. we'd like you to install XYZ, you know, renewable. And they're happy to do it. It's just that you have to find a medium term solution while that's being built. I'm going to ask a question. So there was a news story, and maybe you won't comment on the news story specifically about CoreWeave having made a$1 billion offer for a Bitcoin miner called Core Scientific.

38:55Apparently it was rejected according to things I've read in the news. Setting aside this deal, there used to be a lot of crypto mining and then Ethereum went from proof of work to proof of stake and that all basically disappeared overnight. There are still Bitcoin miners. I never get the impression it's that great a business, but whatever. Are there Bitcoin miners that have latent value in the fact that they... I mean, I know the Bitcoin mining chips, the actual ASICs don't work for AI because all they are is Bitcoin mining chips. But are there, by dint of their access to electricity, space, et cetera, is there a fair amount of latent value in the general physical structures that they've built for the mining?

39:39So I'm just not going to answer your question at all. I'm going to go on a tangent. Okay, that's fine. So I think that when I think about CoreWeave and what our mission is, it's to find creative solutions to problems in various markets. And those various markets can be blocking for us and our customers to achieve our goals. so if power is a concern for us and power availability and substations and substation transformers bitcoin miners definitely have access to power uh that that is true i'm just stating facts here you can keep doing it uh so you know as we go and we try to solve these problems you know we're going to go to places that others may not have thought of and we're gonna go do due diligence and i'm gonna personally go and walk the sites and i'm gonna to look through and see, okay, can we pull this off?

40:31And we're going to get our engineering partners in to help us design retrofits. And we're going to do deals with the companies that we believe have the ability to provide us value. Since we're doing stuff in the news, this has been in the news for a while, so it doesn't really count, but the new NVIDIA chips, the GB200s, what will those do for CoreWeave? And when would you expect to get them? what will they do for us? It's more about what they're going to do for our customers. Right. And I think that they are, this is a great question. Um, they are going to open up a lot of both training and inference use cases in the AI side that I think our customers have been blocked by, uh, with the existing generation in that, um, you're now able to link 72 of these GPUs together to work almost as one unit.

41:27And previously that was limited to eight. They have a much larger, what's called a frame buffer, which is how much memory that's usable for their matrix operations. So, you know, I think that we're going to see a lot of new use cases show up for this stuff, but I think it extends well beyond AI as well. And it's going to be a lot more useful for things like scientific computing. One of the things that has me really excited is the computational fluid dynamics. And I'm specifically thinking about the uses for that in F1 under the new regulation in 2026. I'm excited for the new platform. I think in a year and a half, people are going to be using it for things that are different than anybody expects today.

42:08And that's to me the pace at which this is changing is the piece that's really cool. Wait, I'm sorry. I hate sports. What's the F1 2026 thing? Yeah, I was going to ask you, and explain how the NVIDIA is. Yeah, so the F1 platform, they have very tight restrictions around what type of compute and how much compute you can use to do aerodynamic testing in your cars. And you can either do real-life testing in a wind tunnel, or you can do it through CFD analysis. And one of the great uses for the Grace Blackwell and the Grace Hopper architectures in pairing that Grace super chip with the GPU is they're great for CFD workloads, right?

42:45And the - CFD stands for, oh, computational fluid dynamics. Yep. Yep. And the regulations around the existing program in F1 are they're only able to use CPUs. They have very specific limitations around it. But there's been a lot of talk of that changing for the 2026 car models. And for me, that's pretty cool. And I'm gung ho excited about possibly supporting that. That does sound very fun. I want to get back to actually the financing a little bit because I guess two questions. So the logic of why you would borrow money both, I guess, for the acquisition of chips and the chips are sort of collateral, but I understand they're not really chip backed loans per se.

43:30A, do you see your clients getting more into debt financing rather than equity financing? I mean, there's a whole generation of software companies from the Zerp era that was just, you know, all equity and never had any debt at all. And they never really had to think about like their compute costs. They did, but not as much. Do you think that will rise their own use of debt instead of equity in terms of their own financing? And another topic we talk about a lot on the show, private credit, like, is there an emergence of an ecosystem of lenders for whom this is going to become a specialty of some sort.

44:09To the first piece of the question, I don't believe that the venture-backed kind of AI lab startups will ever take on debt in this type of environment, largely because they don't have the collateral to back it if they're buying cloud services to run their infrastructure. And you may see some that start to buy their own infrastructure and to do that themselves, but it is a Herculean task to do this at scale, right? There's a reason why clouds exist is that there's a lot of complexity that they abstract away. On the second question around, is there a private credit sector that's going to be built to do this?

44:40I think that it's more, you're seeing public lenders that are extending into the private credit space because the opportunities are there. And I'm going to give you the party line answer that my CEO gives all the time is that, you know, as we're thinking about financing our business, the biggest thing for us is our cost of capital. and we're always going to do the things that provide us the lowest cost of capital. And the lenders that we work with, including Blackstone, that have been so wonderful for us, them extending on the private credit side as we go to the public markets, because we're dragged there by cost of capital concerns, I would expect them to be involved as well.

45:17So I think it's a continuation of the business they've been doing in the public markets, just kind of extending into this capital intensive business. Wait, what was, I guess you can't get into specific details, But my impression was for these types of loans that the interest rate is usually higher than like a basic bank loan or say issuing a corporate bond. I would definitely say our cost of capital is lower than some of the corporate issuances out there. OK. But, you know, it's definitely higher than if our cost of capital today is definitely higher than if we were a public entity. But specifically on the GPU-backed loans, and I know you keep saying it's not really a GPU-backed loan, but that's sort of an uphill battle to call it trade receivables financing instead.

46:01It sounds so much better that way. I know, I know. But on that in particular, okay, there's collateral, so maybe that brings the overall borrowing rate down. But on the other hand, it's kind of a new thing, new structure. How does that compare with more traditional types of financing? Yeah. So, you know, every credit facility that we do, the cost of capital declines and it's declining because it's the execution risk and the ongoing concern risk are reduced. Right. And, you know, when we first did this, people like you guys are crazy. You have no history of execution. And as we've gone through and we've done it, like now there's a path that everybody that's underwriting these loans now understands, OK, this is what happens.

46:39This is how it performs. This is what we should expect from the customers. This is what we should expect from receivables. They get more comfortable. They're willing to do it at more aggressive rates. So the risk premium associated with it has just decreased over time. Got it. I just have one last question. I sort of touched on it earlier, but okay, we know that power is scarce. We know that there's not an infinite number of NVIDIA chips, et cetera. Those are quite scarce. For the other stuff, we've done episodes in the past talking about just generic electrical gear components. And we've certainly done a lot on labor shortages.

47:13What are you seeing on that front, sort of like simple gear and the sort of basic building blocks of a new construction and how difficult that is to acquire versus, say, if you were doing this? You know, you started in 2017. I imagine a lot of things were more plentiful back then. Yeah. So it's not even that they're less plentiful today than they were. You know, the lead times were always the lead times for this electrical gear. It's that there was capacity to go buy off the shelf. Okay. There was inventory in the data center market and the inventory is basically gone. And I see deals today that get brought to me and there's seven people bidding on the same deal and they're all trying to sell it to similar customers.

47:52So the market has gotten pretty thin. So now you're looking at it going, okay, my only option here is for new build. And you're looking at lead times that haven't really shifted that much on things inside of the data center. The substation transformers are multiple years out. and part of that reason is that it takes a year for them to cure after they're manufactured like there's no getting around that there's no speeding that piece up what does that mean it takes them a year when the transformer is built that's taking on so much power that whatever the process is it has to sit for a year and harden before it's able to take on that electrical load so even if you went and said hey i'm going to build 10 more of these this year it's still a year away before you can use them huh right and those are the types of things from a manufacturing perspective you just can't get around and it takes time for the supply chain to catch up.

48:40But you know, the problems that I'm solving on a day-to-day basis in these builds isn't even around the substation transformers. It's around like small components that somebody missed when they ordered the gear 16 weeks ago. And now you have to go scramble and call in favors across the country of, Hey, who has this part? I need it by tomorrow because I have 50 ,000 GPUs that are blocked by this one little thing, right? So it's a lot of it is logistical and human coordination and solving dumb problems in real time. Brian Ventura, thank you so much for coming on AdLoss. That was fantastic. Thanks for having me.

49:23Tracy, I'm really glad we did that conversation because there are a number of these sort of like big picture ideas in there that we've sort of hit on, of course, about data centers and AI and electricity consumption. And it was really interesting to hear some of them. So like, for example, just this idea of like Northern Virginia is out and like needing this sort of hunt to find these spots in the country where there is ample electricity and basically nobody local is going to get upset at you for using it. Yeah. No one will come out with pitchforks. The thing that stood out to me from a bunch of these conversations at this point is the arms race aspect of it and how urgent building out AI is for a lot of these companies.

50:07And then there seems to be this mismatch between the immediate need for scale and compute and energy now versus these really long timelines of actually building the stuff out. And Brian mentioning the substation transformers taking a year to cure. I had no idea about that. I didn't know that either, but that's a really good example. That's super interesting. And of course, now we have to do a, how do you build a substation transformer? How do you cure a substation transformer? Totally. I mean, maybe this is probably something that electrical engineer is not interesting to them at all. But for me, I did not realize that there was this one year long, one year long curing process.

50:50You know, I think there are like a couple other things that now I like want to talk more about. So I'm interested. I mean, like CoreWeave is an NVIDIA company. It's not owned by NVIDIA, but, you know, it's joined at the hip in many respects. So how difficult is it going to be either for some other maker of chips, whether it's an Intel or some other maker of software environment, whether it's Meta and PyTorch going against CUDA or whatever? Like, that's a really interesting question to me. We have to do more essentially on how much of a lock NVIDIA really has on this industry. Yeah, this seems to be the really big question.

51:32And then the other thing I was thinking about, and I know Brian emphasized this and other CoreWeave executives have emphasized this before, but this idea that hyperscalers maybe are starting from a point of being disadvantaged because they have to retrofit all this old infrastructure for this new AI technology. Totally. And like, I can see that. But on the other hand, these are insanely impressive companies who are explicitly trying to compete against CoreWeave in this business. And they're not going to stand still. And so I guess there's an open question over how much progress they're making or how fast that progress is actually happening.

52:12Right. Right. Large incumbent companies always are going to have some challenges when there's like a new model or something. But these companies have all the money in the entire world. Right. And they also have all the, you know, one of the things that Brian said is like they if they were if one of them are going to do it, they would have to go out and buy a big chunk of the market, which, again, they have all the money in the entire world. So theoretically, whether it's the big companies and retrofitting the clouds or building new clouds or, you know, a lot of them like a Google, even if they're for now using their TPUs internally, primarily like it does seem like in theory the opportunities out there, particularly with the the sky high amount, you know, valuation that a company like NVIDIA is getting.

52:57Oh, yeah. You mentioned the sky high valuation. That was something that also stood out to me just on the financing side. So this idea of, you know, the debt financing deal that they did. And I'm not going to call it trade receivables because no one. GPU backed loan. Yeah, no one will be interested when we start talking about trade receivables. But the GPU-backed loan, this idea that, okay, it's a new structure, but the more you do it, the more the cost of that particular capital starts to fall, the more the market gets comfortable with it. I mean, we can talk about whether or not it's priced correctly for a new type of unfamiliar risk, but it does seem like that might be a new avenue for the vast amounts of capital that are needed for this business.

53:40So one, it's interesting to think about the idea that like, you know, I don't think it's like totally true, you know, that if you need compute at scale for AI, that you don't just get to call up CoreWeave and get it. And you actually have to prove that you're going to be a good customer. And so like have something that is probably going to be sustainable, have the balance sheet capacity. So this, even if the sort of software, the end users aren't themselves raising debt, it does sound like they have to have a lot of equity up front just so that they're perceived as a sustainable, viable customer for a company like CoreWeave.

54:19I also thought on the electricity front, like obviously we talk all the time about just sort of the raw demand for electricity. But this idea, what he said, and I hadn't heard anyone say it, that the runs, the modeling runs stop every, what do you say, 30 minutes and have to be saved. Oh, yeah. And so you have this big variability at times and that creates its own specific issue because it's not just steady state flow of electricity and solving for that. That's probably another area in which the legacy data centers or cloud companies, perhaps my guess would be that they're just sort of the demand is more constant and therefore something that would be a novelty for them.

54:59Just thinking about the financing more, I do kind of wonder how much of this is like AI built on top of AI on top of AI, like to the point where if the bubble were to burst or if funding was suddenly pulled from a bunch of these startups, like what would that mean for CoreWeave's financing? And what would that mean for BlackRock, which lent money based on the GPUs that the clients are taking on who might not be there anymore? I don't know. By the way, have you ever looked at a chart of Riot blockchain? Oh! No, it's interesting. Not for a while. Yeah, well, I mean, they're still there as a miner.

55:37But, like, here we are in the midst of this pretty big crypto bull run. I mean, I guess it's cooled a little bit. But, and that stock has done terribly. Yeah. So it's interesting to wonder, and apparently it doesn't seem like anyone's made a bid for them. But it is interesting to wonder, like, OK, those chips are useless for for AI because they don't work for that. But, you know, they do have capacity and they do have electricity agreements already in place. So it does make you wonder whether like some of the Bitcoin mining companies, which aren't really getting a very the market is not excited about them, clearly, even in the midst of this crypto bull run.

56:16Maybe they should go back to being a diagnostics company. That's what they were before, right? Is it? I think so. I think they're one of the ones that changed their name and then like something including blockchain. And then their shares went up enormously and now they're back down. Well, they have been. Riot Platforms has been around. OK, now I'm curious. Yeah, so it's a Bitcoin mining company, but it's been the stock has been around since 2003. So pretty clearly they were in some other business. I don't know what I mean. Yeah, I'm looking on the terminal. It says Riot Blockchain, formerly Bioptics, has ditched the drug diagnostic machinery business for the digital currency trade.

56:57Well, there you go. So if you have some sort of computing power or something, I don't know what they were doing before, but maybe it is interesting to think about maybe some of the option value for some of these miners. is in all the infrastructure other than the Bitcoin mining operation. Maybe we should put in a bid. Let's do it. We can crowdfund and start our own business. OK, maybe we should leave it there. Let's leave it there. This has been another episode of the All Thoughts podcast. I'm Tracy Allaway. You can follow me at Tracy Allaway. And I'm Joe Weisenthal. You can follow me at The Stalwart.

57:30Follow our guest, Brian Venturo. He's at Brian Venturo. Follow our producers, Carmen Rodriguez at Carmen Armin. Dashiell Bennett at Dashbot and Kale Brooks at Kale Brooks. Thank you to our producer, Moses Andam. For more OddLots content, go to Bloomberg.com slash OddLots, where you have transcripts, a blog, and a newsletter. And you can chat about all of these topics, including AI, including semiconductors, including energy in our Discord, discord.gg slash OddLots. And if you enjoy OddBots, if you like it when we talk about AI and chips and energy and all that stuff, then please leave us a positive review on your favorite podcast platform.

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