Welcome everyone to the information ti. My name is Akash Pasicha. It is Monday, October 19th. Today on the show, we're going to speak with Palo Alto Networks CIO about how it is helping customers deal with the risk of rogue agents. We'll then talk with the CEO of Modal, the AI infrastructure company that recently tripled its valuation to more than $15 billion in less than 6 months. We'll also get a status update on the Neocloud route and how CoreWeave is holding up. And to close out the show, we have an extended conversation with the Pentagon's chief technology officer about their work with Anthropic. We're also going to hear from him about the new super intelligence task force and dealing with foreign AI risks. It's going to be a great show. So, let's get right on into it. Palo Alto Networks is expanding its cybersecurity platform to protect businesses from AI agents going rogue and accessing sensitive data. Joining us now is Palo Alto Networks' CIO, Leena Rajal. Leena, welcome to the show. It's great to have you here.
Thank you, Akash. Thank you for having us on the show.
So tell us about this product that you're releasing this morning.
So Akash, we are releasing a product called XDR1. XDR is endpoint security, and if you think about traditional endpoint security, they focus on network, cloud, and the local infrastructure of what is getting executed. But today the biggest thing is AI and the AI agents and what they are doing. So you go to any company, it's actually a great productivity. It's a great powerful tool when you give it to the employees for the reason of software engineering or for the reason of individual productivity, like having something that's their personal twin. However, all these AI agents pose a serious new risk. And when you give an agent autonomy or agency for what I'm doing with my permission, then it has actually access to things that I have access to, not just on my laptop, but also beyond our endpoint, beyond the systems. I'm having simple things from the code bases to financial ledgers. When we're dealing with it, there are multiple different things that agents can get into: vulnerability issues like data poisoning, supply chain attacks, and prompt injection. You just feed these agents a malicious skill that can put you in a place that's deadly for the company. The second thing is, as a CIO, I care about the full visibility, but most of us, the AI agents are today a blind spot because the traditional endpoint security gives you visibility of what's coming in, it doesn't say what exactly is happening. The analogy I've used: XDR is like you have an X-ray scanner, it scans through, but if you wanted to know every single thing in that box, how it is getting used, that visibility, that's where the agent endpoint security comes into picture.
We spotted this risk because we are a company of 14,000 engineers, and as a CIO, my job is to really enable innovation, not hold them back. When we started seeing the power of AI in software engineering, we spotted this as a significant risk, and this is also a supply chain risk for our customers we didn't want to take. So we were scanning the market to see what's going on, and when Koi Security was even in stealth mode, we spotted them. In fact, we literally brought them in, and we became the first customer of implementing them to say, 'Okay, we really need to get this enabled before we let our engineers touch the tool to go and do the software engineering.'
Let me jump in here because I think you have an interesting perspective here on this, being the CIO of a company that effectively is advising other CIOs on their own stack here. You know, the issue around agents and security is interesting because on one hand, we have these coding agents that help us write code. And you know, I saw that Bank of America came out and said that they're hiring a thousand contractors now to help them deal with the vulnerabilities that Mythos found in their own code. And you know, this is additional headcount that they have to bring on. And the question I have for you is: is the problem here that the coding agents and the code that Claude Code and Codex create is a problem that they are creating vulnerabilities in companies' own stacks and in their architecture because maybe it's just a little bit quick and dirty and it's not the most secure code? Or is the problem more that the code can be attacked from agents that can be used by malicious actors and stuff like that? Which of these two risks is more prevalent right now from your view?
I think, Akash, both are a risk, right? Because when you talk about what Mythos found, take a company like Bank of America or any company that is in existence for a while, right? I mean, they have a lot of software today, especially with the digitization. Every company, no matter which industry you're talking about, even highly, highly legacy or the brick-and-mortar companies are digital, so they have software code. And when we talk about vulnerabilities, Mythos and Fable, or you know, for that matter, GPT-5.6, everything is finding vulnerability in the code that they are using to run their business today, and it is actually a must that they have to address those vulnerabilities because that's an existential crisis, right? Because you don't want that to be exposed to the attackers who are leveraging AI to compromise into their environment. That's one side. Then you talk about AI producing code. Remember, AI is also producing code by learning from what's out there. And if you remember what Mythos found 25 years ago, the Berkeley Unix kernel, it found the open-source vulnerability that we are all using for so long. So now when you think about the software code it's generating, there is a possibility that it may be introducing vulnerability as well. I'm not going to say every time, but it will. So it's really important you start looking at software supply chain, right? So there are two things, right? I mean, like two weeks back we launched something called Frontier AI Security, which is actually a service we launched because we saw our customers saying, 'Hey, Mythos was a moment, but it's not anymore Mythos because we are finding it.' Forget about frontier labs, even open-source, open-weight models are as good as the frontier labs, and it's only like earlier it used to be four to five months before they catch it, now it's four to six weeks. So we launched a service which is a multi-model harness that can actually continuously scan whether they are producing new software or they're introducing a new one on their brownfield. We want to make sure the posture of our customers are continuously managed and monitored. Again, also we introduced something called virtual patching, which is like it's impossible for a company like Bank of America, which has been in existence for so long, to really patch everything within a matter of time. You need actually something to stop in the fringes, and then you need to really work through this. Both are required, and also this goes back to basic zero trust security hygiene. And I keep talking to, I mean, when I keep talking to CIOs and CSOs, one of the things I emphasize is more than ever, security hygiene is becoming super important today.
Yeah, we have to focus on hygiene. Let me ask you a couple more questions about how you are approaching your own stack internally. So of all the models that you're using, is Palo Alto Networks, are you using open-weight models from China at all?
We actually use multi-model, but we are not using open-weight Chinese models at this point in time.
I mean, it is a decision we made at this point in time where things are. We just wanted to be in control of the models that we are using, and that was more a strategic decision.
And how are you controlling your own spend on these models internally? Are you giving employees specific caps on their usage? How are you dealing with that?
Yeah, I think I agree. I mean, one thing is this is nothing different than when cloud came, but it's just that it is so accelerated and much more expensive than cloud, right? I mean, shadow AI is absolutely a concern today. So we have actually full visibility of the use of AI in the company today. This is one of our critical things that we introduced. So we have full visibility of what AI uses in the company, and we also have a way to continuously monitor our spend. We haven't gone down the path of quota; rather, we have gone down because we wanted to make sure we are rewarding outcomes and efficiency rather than just putting an artificial quota. And we also want to make sure people who are doing really good, efficient outcomes, that has to be replicated. So at this point in time, we watch and we stop, you know, behaviors that are not the right behaviors, and we are actually taking the ones where the outcomes are higher or efficiency of use of AI is higher, and we are taking that and replicating as part of our harnesses. So absolutely, cost is something we focus on, but not with the artificial, you know, boundaries saying that we are going to give you a quota. At some point in time, we may consider that, but at this point in time, that's not the way we are approaching.
Well, yeah, because you know, I'm sort of curious on how you prevent internally this idea of what Tobi Lutke at Shopify has called the slop grenade, and people just, employees sort of launching slop at each other, and it actually not helping productivity. This is something we've talked about, productivity being one of the most difficult things to measure. How do you prevent that? Do employees have to say that, you know, 'I used this, this is AI generated, this is not AI generated'? Like, what's your method?
Absolutely, great question, right? I mean, this has been a ramp. I mean, the last, I would say, three, six months, we have actually put a lot of focus on our SDLC harness, and the harness is the way people can come into it, and that's the way we are watching where the spend is. When somebody is outside, we can see, like, for example, in IT, I have a harness that actually connects to both our first-party applications as well as third-party applications. Anybody using AI has to use through the harness. I also know if they're outside the harness where the spend is, and we nudge them back into the harness because when I put them in the harness, I'm not just talking about coding. I'm tracing from PRD all the way to what they are releasing in production. Right. Today, I would say in some technologies it's a little harder to trace it, but I'm able to get the visibility for over 85, 90% of the work that's happening. So I look at it as three things: one is the quality of code they are producing, how secure it is; two, what is the velocity of outcomes that we are generating or release outcomes; three, how efficiently we produce that work. So to give you a simple example, I mean, the market is heating up, security is heating up, we are actually, you know, doing a lot of M&A, and the new product introduction for Palo Alto has gone skyrocketed. I mean, for me as a CIO and my organization is responsible for NPI, every single innovation that comes to the business, and we have gone 3x NPI over the last six months, and I have not increased even a single headcount on my software engineers.
But are they, are they good product? Like, this is, this is the question.
Are they good product in, in a sense what...
Help me understand the sense of like, what is AI producing good code?
Yeah, yeah, no, I mean, I guess what I'm saying, so product launches are one thing, but have the products met the goals that you have set?
Yes, yes, yes, yes. Because it is human in the loop, right? I mean, I don't believe in autonomous agents yet. We are not at the place where, you know, having autonomy fully, especially when you're looking for outcomes and the bigger things. I always have the code is generated. There is always a human review before the release, and also there is actually a user testing before the release. This also brings us to what we are launching today with XDR1, because the XDR1 will give me the endpoint security guardrail. So I can be a lot more taking higher risk on because I'll have a full visibility of how the AI... I mean, we have already rolled it inside, by the way, but we'll have a full visibility of how the agent is behaving and how I can have the appropriate guardrails and kill switches to protect it if it's going rogue. And it's also connected to our, you know, SOAR/XM solution, which has a way to respond in an autonomous fashion. To go back to your question, I think it really comes down to having the high-risk or higher-value things putting human in the loop, and the second thing is really looking at it from the point of do you have the right security guardrails, and if you need to go down the path of saying no, we have a quick way to respond to it.
Great, Leena. I want to thank you for coming on. That is Leena Rajal, the CIO at Palo Alto Networks here on TIV. Thank you.
AI infrastructure startup Modal announced it raised $750 million at a $15.75 billion valuation. That is more than triple its valuation from just five months ago. I want to welcome back to the show Eric Bernhardson, co-founder and CEO of the company. Eric, welcome back to the show. It's great to have you here.
Thank you. It's great to be here.
Okay, so big numbers on the board here. Hundred billion dollars... sorry, one billion, I'm sorry. That would be great.
One billion in annualized revenue as of now, up from 300 million in May. Where is that growth coming from, Eric?
Yeah, I think we just see so much demand coming from all these insanely cool AI applications getting built out there. Whether it's, you know, Ramp or Cognition doing agentic coding, could be generative media like Runway, and could be, you know, TypeSafe with Java, many other things. There's just so many cool applications getting built, and I think it's really representing kind of a new wave of software. Like, these things are things that couldn't have been built just a few years ago. I mean, I've been coding for so long since the early '90s, and this is the biggest change in how software works and what you can do and how you build software. And, you know, it's just kind of amazing seeing all these changes and the incredible demand that that's unlocked, and a lot of that runs on Modal.
So, one billion in annualized revenue. I just want to make sure I understand this. So is this the, like, is this one billion in revenue that the customers are paying you, and then you have to pay out some proportion of that to the model providers? Like, how are you measuring that? What's the gross versus net on this?
So, this is our run rate revenue, right? So if you annualize the last 30 days times 12, and we don't pay it to model providers, like, we pay it to... we rent a lot of compute capacity from various different clouds. In fact, we work with 25 different cloud vendors. A big part of the value prop of Modal is like, don't think about capacity. We kind of manage all that entire... we aggregate a lot of the capacity and present it to the customers in a way where they don't have to think about it and they can move fast and build a lot of cool things, whether it's, you know, inference or training or sandboxes, a lot of other stuff. And so, yeah, I mean, you know, we have meaningful COGS, like we have to spend, you know, a fair amount of money on the underlying layer, but we have very healthy margins actually. In fact, like, it turns out like building that very differentiated software layer on top of it means you can have, you know, very healthy gross margins. They're actually growing over time.
How, what do your margins look like right now?
I don't know if I can comment on, you know, latest numbers, but...
I mean, you're the CEO, actually. You could say whatever you want.
I can say whatever I want, but some things I don't want to say. [laughter]
But okay, so you're right. The main cost is compute. And look, you guys sit in an interesting spot here because, you know, I'm looking at the Neocloud route of last week, and, you know, I'm thinking about how they are looking to move up the stack a bit with their own inference-like services. I think helping people, you know, optimize the models that are being used, stuff like that. So what's your view of, you know, that story coming crumbling a little bit here? What do you think? Because by the way, I mean, it doesn't seem like you're too far from it in some ways, right? You're renting compute as well.
I think the Neoclouds have had a good run over the last few years. I mean, at the end of the day, they're relatively undifferentiated software, undifferentiated businesses. I think software is really where you can make a massive differentiation. We have a very rich software layer. We provide a number of building blocks. Like, we really think about Modal as, like, sure, you can get the capacity, you can go out and rent capacity from Neoclouds, but there's a number of problems. Like, most developers, like, the way you think about it is like you want these higher-level building blocks, you know, inference, sandboxes, training, reinforcement learning, agentic applications, but in the future it's going to be way more, and that's at the level where you want to operate. And so enabling developers to move fast and ship these incredible applications in a way where they don't have to think about infrastructure, there's so much alpha to capture in that layer. And that's an asset-light layer where you can move very fast and have very good margins, not quite software-like margins because we have significant COGS, but certainly way better than the sort of the Neoclouds where getting squeezed between Nvidia and the rising borrowing costs. So I think it's a very different part of the stack, and, you know, it's a stack where software actually makes a very massive difference, and that software is quite unique and it's quite hard to copy.
Tell me, in a billion dollars of this annualized revenue for you, is customer concentration a concern for you at all?
No. Diversification keeps getting better every month. We see, you know, some very large customer, but also a long tail of smaller customers across like a very wide range of different verticals and use cases. I mentioned inference and training and sandboxes and many other things, but it's also different spaces. So you see a fair amount of stuff in biotech actually growing very fast, and life sciences, materials, physics. See stuff in robotics growing very fast. Big companies, small companies, enterprise, startups, it's all over the place.
So, what do you think inevitably happens to the Neoclouds here? I mean, do you see there being consolidation? Do you see yourself maybe moving, not becoming a Neocloud, but you're renting the chips right now. Could you buy chips? Have you bought chips? Like, how do you think the story goes?
It's possible. I mean, I think the Neocloud businesses are fine. I think there's been a correction because, you know, it's a tough business. I mean, at the end of the day, it's a financing business. You know, you're borrowing a lot of money up front and then collecting the payment from your customers. You know, you're in the financing space. As it pertains to us, like, we may go down in the space, like, we might go and look at ownership. We're quite interested in looking at, you know, colo or doing joint ventures with Neoclouds or other things. We think we can go down in the stack relatively easy. It's harder for the Neoclouds to go up in the stack into software, into the software space. What's going to happen with the Neoclouds? I'm not sure. I think they're actually going to be quite fine. I think, you know, there's been a little bit just a correction. People have been like very excited. Now, you know, turns out these businesses are still fine and pretty good.
Do you think they... I mean, I was going to ask if you saw them, you know, buying their way more into the inference space, buying, you know, some of these inference providers, although I don't know that they have a lot of money to do that with right now given their bills.
They have, like, if you look at Nebius and CoreWeave, they made...
Well, yeah. I just mean, I just mean they're using it all to build the facilities. I don't know how much cash they have to...
Exactly. And I think it's a question of, like, you know, retained earnings and how do you reinvest the profit. And I think that's exactly right, but I think they will try, and I think that we will see a lot of attempts to move up in the stack. And, you know, in some cases, like, you know, it might succeed. Like, I mean, we take it very seriously, like, all competition. And, you know, like, in certain ways, like, we like to work with Neoclouds because we get a lot of capacity with them, from them, but I also think there's going to be some interesting, you know, attempts by Neoclouds to move up in the stack. So we'll see what happens for next year.
You guys had your flagship conference, if I'm not mistaken, a couple runs.
Yeah, yeah, Runtime. So, our reporter Cory Weinberg was there, and he wrote a piece about his experience there. So, there were two things that stood out to me, two comments from speakers on stage at the event that I wanted to ask you about. One was from Dario, who co-founded TypeSafe, which is the company behind Java. And then there was another comment from an executive from Anthropic. Both of these comments were around agents and around the extent to which we can automate things. I think the Anthropic executive said something to the effect of, 'We're still dealing with the 20%, you know, human in the loop right now.' And the Java executive, you know, he said, 'Where is all the automation?' I think I'm paraphrasing his comment. So my question for you is, Eric, are the models just not good enough for agents to fully automate everything? Is full automation even the goal? What needs to happen here from your perspective?
I think the models are incredible. I mean, you know, I use them for writing code every day, and they're phenomenal, and they're getting better every day. I think full automation, I don't know if it, like, matters. Like, my view is always like people are obsessed with sort of, you know, automating away humans. I think in every era, like, the value that gets created is rarely a sort of, you know, getting rid of humans. The value is like creating new use cases and new amazing things and building new products, right? Like, that to me is like the exciting thing. Like, I'm incredibly excited about AI, you know, using AI to discover new drugs or to enable new applications like Suno or Runway that previously didn't exist. Like, that to me is like typically where the value is created.
So, but let me push back on that here because, I mean, you're saying it doesn't matter, and the reason I'm asking the question, though, is because if you think about enterprises and companies spending on AI seeing any kind of return, I mean, the reality is they are not seeing the return right now. And you could argue maybe it's because they still have to have a person in the loop. The person is doing different work. They're not doing, you know, as much manual work, but they're still spending the same amount of time. So, I mean, I'm going to push back here. I think it does matter.
Yeah, I mean, I think so. Like, it does matter. I'm not trying to, like... I think if you go back 30 years and you look at word processors or internet and email and things like that, like, every time there's like a new technology, you get rid of like 80% of old junk, and then you make humans more efficient at the remaining things, and humans are able to move higher up in the value chain and have even more leverage. And that is, I think, what's going on, is like, I think these agents are incredible at letting humans get more stuff done, just as like, you know, I feel it when I'm writing code, I'm able to write way more code. And so I don't know if it, like, really matters. Like, do we really need to automate away, like, the last, you know, the 10% to get rid of me? Like, I'm not sure. I think at the end of the day, you're going to have a human controlling a lot of these things, and the human is going to have way more leverage, and I think that's incredible.
But isn't automation the only way you can then quantify the cost savings, or at least attach a dollar value to what productivity it's actually having?
No, I don't think so. I think you can look at the output. I think you can look at the number of lines of code being written or the number of PRs being merged, or, you know, I mean, these metrics are hard. I heard a previous conversation, it's always hard to measure productivity, right? How do you measure output? But I think that's ultimately what matters, right? Is like the output coming out of the factory, right?
Great. Well, Eric, I want to thank you for coming on. That is Eric Bernhardson, the co-founder and CEO of Modal, here on TIV.
Microsoft pulled out of a data center deal with Nscale in the UK in the latest data point to a challenging narrative facing Neocloud companies right now. To break down where this story is headed, I want to bring on Nick Delo, managing director at MoffettNathanson. Nick, welcome to the show. It's great to have you back.
Yeah, thanks for having me, Akash.
So, Nick, you know, we saw the Microsoft Nscale news over the weekend. We'll get to the power side of this story in a second here. I think CoreWeave is the name that everyone is watching as a proxy for all this. It was a tough week. I saw Goldman upgraded the company, which gave it a little bit of a pop this morning, although it looks like that was short-lived. So, where do you think we are with the CoreWeave story? Where are you on it? Help us walk through the scenarios.
Yeah. So, I would argue that from a pure fundamentals-based valuation, it's probably undervalued right now, but I think we also have to be cognizant of the fact that the financing environment is not necessarily that great for them at the moment. There's sort of this collision taking place where CoreWeave and a lot of the other Neoclouds have these immense capital needs over the coming years, but their balance sheets and their internally generated cash flow don't support those ambitions. So they need to rely on external capital to really achieve what they're trying to deploy. You know, at the same time, however, you see this increasing scrutiny on AI-linked debt deals, you know, particularly for higher-yield issues. The market is anticipating a lot of AI-linked high-yield issuance over the coming years. So between those two things, you know, you've got a setup where, you know, again, maybe from a pure fundamental perspective, the stock looks interesting. But on the other hand, if the capital markets don't cooperate, the company could be in a very difficult situation where they are unable to raise the capital they need or fulfill the commitments that they've made to deploy compute for customers.
Why are the fundamentals attractive to you?
Look, I would argue, and to be clear, we've had a neutral rating on CoreWeave since they came public. So we've been, I think, a more conservative stance than most of our peers. But when you drill down into the project-level economics, how much money do they actually make from a deal? It's reasonably attractive today. And it has gotten somewhat more attractive with the increase in pricing that we've seen for GPU rental. That's partially offset by higher costs and a higher cost of capital. But for every dollar that they put to work deploying compute, we estimate that they generate 15 or 20 cents in net present value. So under those circumstances, the more money that they put to work, the more value it creates for their shareholders. Obviously, again, I have concerns longer term that, you know, eventually the market is going to normalize from a supply and demand perspective. We'll see competitors improve the quality of their offering relative to CoreWeave. Again, there will be just less of the imbalance that we see in the markets that's benefiting providers of compute today, but at least for the foreseeable future, it seems like they're in a decent spot with respect to the pure value creation potential, the deals that they've been consummating.
I want to talk about the financing component to this, the second half of this story. So, I mean, we saw inflation was hot last week. You know, the rate hike risk is real for the financing story. Is all of their debt right now, is it fixed? Is it floating? What exactly is the concern here?
Well, it's a mix. So, we should probably step back a little bit because CoreWeave has a reasonably complicated multi-layered debt capital structure.
And you're going to tell us how creative they've gotten.
All right. So, the foundation of their borrowings are really what they call delay-draw term loans. And this is essentially secured borrowing against contracted revenue that they have with the GPUs posted as collateral. So let's say that they sign a deal with Microsoft for five years. What they will do is take that contract, put it in a box, take the GPUs, put it in the box, can then go to a lender, and the lender will underwrite that revenue stream from Microsoft and loan money against it. It's essentially receivables factoring. And that's the bulk of their debt, basically secured lending. They also use some vendor financing, say from Dell. That tends to be the safer portion of their debt capital structure. It's closer to the assets, and the interest rates are naturally lower as a result. You move up, and then to the extent that lenders, depending on the credit quality of the customer, may loan 70 to 90% of the value of the GPUs in these secure deals, CoreWeave needs to plug the remainder with essentially parent company debt. So it has a residual claim on those assets, and that's where you've seen the rates spike recently. For straight parent company debt, it's probably gone from 9 or 10% several months ago to closer to 15% today. They also have some convertible debt outstanding, you know, so in that case, you know, the interest rates are lower today, but if the stock does well over time, that can get converted into equity and dilute shareholders. You know, what's really interesting about this dynamic is that if you look at CoreWeave's enterprise value today, it's probably 60% equity, and again, you know, without getting into the weeds, you typically don't find distressed companies with 60% equity as part of their enterprise value; tends to be a lot lower. So there's a bit of a mismatch in terms of what the equity market is saying about CoreWeave's prospects and what the debt markets may be saying. But again, the 15% interest rate number that's gotten a lot of attention recently is for a portion of their debt capital structure closer to the equity. And that's where a lot of the pushback or a lot of the tension in the markets has been, that high-yield component. I think the secured debt component is probably not an area where they're going to have a lot of issues raising capital prospectively.
Have you talked to the company at all in the last week as they've sort of navigated this recent reaction from investors?
No, haven't spoke to the company, but they've made, you know, comments that were either public or, you know, made privately but intended to be public, effectively.
I'm just wondering if you've gotten a sense, if they have changed anything about their strategy, not just in the last week, but maybe the last couple months to get ahead of some of these risks, or if you've gotten the sense that they're going to change anything, you know.
You know, they have historically been very focused on the use of debt to scale the business. The argument being that to deploy the amount of capital that they want to deploy using anything but debt would result in essentially an obscene amount of equity issuance and dilute their shareholders into oblivion. After the second quarter, you know, they issued a reasonably large convertible bond. I think it was 4 billion or thereabouts. So they have some cash on the balance sheet from that. They have a number of delayed-draw term loans that they have not fully drawn down yet. They've got about 5 billion in cash on the balance sheet. So I think in total between those things they have about 22 billion or so in liquidity available, which is probably sufficient to carry them through the end of the year or thereabouts.
So I would think by year end they probably need to come to market again to raise additional capital.
We'll see what happens. They did put an ad...
Well, we'll see what happens. Meaning whether...
How the capital markets respond to that.
And if they don't, I mean, if they don't, then that's going to be pretty dicey, right?
Absolutely. And that's the risk they face because the sheer quantum of capital they require means that the capital markets need to be open for them to draw what they need. They did put an at-the-money offering in place that means sell equity into the market. My anticipation, or my expectation rather, is that they probably lean a little bit more heavily on equity respectively, try to lop off some of this tail risk that comes from being so levered to the debt markets remaining open at reasonable terms. But we'll see. That's kind of my read on the situation as opposed to anything the company has said outright.
So the other risk, I guess, that I've been hearing about is sort of this refinancing risk. If they need to refinance any of this debt, to what extent they will be able to do that, what rates they'll be able to do that, whether or not they'll be able to meet their interest payments. That's why I was asking about the fixed versus floating and the extent to which, you know, any of these interest payments will change. I don't have a great idea of the extent to which interest payments will get more expensive. My sense is it could, right?
Yeah. So, the parent company debt is, I don't think they have a maturity until 2030 or thereabouts. So, the parent company debt, they're not going to have to refi that for some time, right? The delay-draw term loans do have an amortization schedule. So, they pay those down as they collect from the underlying customer contracts. Those are typically floating rate instruments, so SOFR plus a spread, but in many cases the lenders actually require that they hedge that exposure. So I think, you know, there is some potential for rates to increase in the near to medium term with the broader rise in interest rates. But in terms of a big refinancing wave, probably not on the horizon for some time.
Okay. So then let's talk about sort of the, I guess, the other risk that people are scared of, which is just default, which is why these credit default swaps have gotten so much attention. How much of a risk do you think there is at all?
Yeah. So yeah, I think the secured term loans that they have outstanding, very close to the assets, I think those are fine. The parent company debt, it's really based on the residual value of these GPUs at the end of the day. You could say that CoreWeave's business model in a sense is basically buying GPUs and paying for them with a combination of borrowed money and prepayments from customers where you put in effectively no equity. So the value to the company comes from the residual value of the GPUs and what they can generate from a cash flow perspective after the term loans are paid off. It seems like the economic lives of GPUs are likely to extend beyond the four or five years that a lot of people thought they would be previously. We've seen a lot of evidence in the market to support that. You know, in terms of their ability to repay based on that, you know, it would suggest that they're not in a terrible spot. I think the bigger risk to CoreWeave is the idea that the capital markets seize up and they are unable to procure additional funds to deploy compute that they've contracted to deploy for customers, or again, if we look out a few years and they have some of this parent company debt come due that they need to refinance, that they're unable to tap the market for that.
So I think if that, you know, this is not just a CoreWeave risk, by the way, we're talking about the whole sector here. Just looking ahead here, if that happens to CoreWeave, if that happens to any other of these Neocloud companies, who, I mean, do you think Nvidia steps in and buys one of these companies? What do you think?
Yeah. So, clearly, you know, one of the options that Core has, or they have several options, you know, if stuff really hits the fan, they're not going to stand still. You know, yeah, I think that equity is a likely option. There's the Nvidia put, you know, where Nvidia might come in and either guarantee, provide to allow CoreWeave to get financing on more reasonable terms, maybe a direct investment in the company, maybe eased payment terms, things like that. You know, we could see additional vendor financing from key suppliers like Dell. We could see them embrace more of a bring-your-own-compute type models, maybe offload some of the capex to other parties. Yeah, I don't think any of those are very appealing options. You know, to the extent that Nvidia stepped in and helped them, I think that would sort of shatter the image of, you know, these businesses as ones that could stand on their own two feet and, you know, do some...
They're already investing. They're already investing in these companies, though.
Yes. Yeah. But I think there's, you know, at least in my mind, there's a difference in, you know, investing to help get them going versus being CoreWeave where you've got, you know, a very large enterprise value and you need help from your key supplier to keep it going. But I view an outright acquisition as less likely simply because if Nvidia were to do that, it starts to introduce some conflicts, you know, between, say, the chips, the pricing, the terms that they would give like their own cloud versus third parties that they're working with. That's one of the challenges that Google is trying to work through as it tries to build out its TPU ecosystem. And so I think Nvidia would try to avoid that if they could.
And let me ask you another question here about falling token prices. This is another discussion that's been going on. How do you think falling token prices affect the economics of these Neocloud businesses? Because there's the whole Jevons paradox argument that, well, people will keep using it. I don't know if you have any counterarguments against that or if you think that is actually a threat.
Yeah, I think, you know, to a point it's arguably helpful. You know, lower prices stimulates more use cases, more demand for the underlying infrastructure. We've seen, you know, despite the rise of open-weight models, we've seen prices for GPUs rise this year. So again, there are plenty of factors that go into that, but it's not obvious to me that falling token prices, you know, completely trash this business model.
Because they'll be able to sell more capacity, basically.
Yeah. Ultimately, you know, the customer base may be less profitable. I think it's, you know, you think about the different layers of the value chain, that's probably where it has the most impact. So long as it isn't so detrimental as to impair the customer's ability to pay for the compute, it probably helps infrastructure providers.
Right. And if we let's go full circle to the Microsoft Nscale story now, that is a story about power. Microsoft reportedly was not able to, well, I guess the Nscale facility wouldn't have been able to get connected to the power supply as quickly as they wanted to. So of the companies that you cover, you cover a lot of these Neoclouds, how many of them are having issues or facing delays in their facilities because they cannot get connected to a power grid or supply of some kind?
Look, it's a challenge across the data center space. Different players have been more successful than others. You tend to find that folks that are more experienced, so think of the brand names like Digital Realty, Equinix, QTS and so on, who have long-standing relationships with the utilities, with key suppliers, with municipalities and so on, tend to plan further out and can leverage that relationship and experience to get projects online on time. I think disproportionately the challenges tend to arise with newer, less experienced players. So certainly Nscale would fall into that category. They have tremendous ambitions but, you know, a relatively short track record. But certainly, you know, again, the biggest challenge across the data center space today is access to power and whether that's access to the generation, the transmission, transformers, UPS, whatever it might be, that whole ecosystem is the biggest single challenge to bringing capacity online.
