Inside the AI power wars

For those steeped in the world of AI development, the major differences between tech giants’ chip strategies are easy enough to see: the speed of Google’s TPUs, the affordability of Amazon’s Trainium, and Nvidia’s market dominance. But those same companies’ respective energy strategies often fly under the radar. As data center buildouts surge across the U. S., the tech industry is hitting a massive wall: a power grid that can’t move fast enough to support them. In this episode, Shayle sits down with Jeremie Eliahou Ontiveros, who leads coverage of infrastructure and power at SemiAnalysis, to lift the curtain on the hyper-competitive world of AI energy procurement. They cover topics including: The hyperscaler leaderboard: Why Google remains the most energy-sophisticated tech giant, as others continue to innovate Why power has effectively become revenue for frontier labs How Google uses its massive balance sheet to provide financial backstops for Anthropic’s data center buildouts Why the interconnection queue is forcing AI labs like OpenAI and Anthropic to bring their own generation The sudden market frenzy over modular speed-to-power options—ranging from aeroderivative gas turbines and massive reciprocating engines to billions of dollars of fuel cells Catalyst: How data centers are complicating transmission expansion Catalyst: Live from Transition-AI 2026: Inside Google’s massive AI capex Catalyst: The rise of flexible data centers Catalyst: AI scaling pathways: On grid, on edge, off grid, off planet Open Circuit: The new reality for data centers: No easy answers Open Circuit: Can data centers regain their social license? Open Circuit: Grid utilization vs expansion: The 100GW debate Latitude Media: FERC to grid operators: Connect large loads to transmission faster Latitude Media: The rise of the data center power exchange Credits: Hosted by Shayle Kann. Produced and edited by Max Savage Levenson. Original music and engineering by Sean Marquand. Stephen Lacey is our executive editor. This episode of Catalyst is brought to you by ENGIE, the smarter energy supplier. ENGIE doesn't just provide the power to run your business — they supply the energy to move it forward, with reliable, flexible solutions built for what's next. Learn more at engieresources.com. Catalyst is brought to you by EnergyHub. Peak season puts every grid to the test — and the utilities that pass are the ones that built flexible capacity before they needed it. EnergyHub works with more than 170 utilities to coordinate 2.5 million devices and 3.4 gigawatts of dispatchable flexibility through a single platform designed to perform when it counts most. See what that looks like at EnergyHub.com. Catalyst is brought to you by Bloom Energy. Bloom Energy fuel cells deliver affordable, ultra-reliable onsite power for hospitals, utilities, and data centers – at speed and at scale. Learn more by visiting BloomEnergy.com.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:02Speaker 00

  Latitude Media, covering the new frontiers of the energy transition.

• 0:07Shayle Kann?

  I'm Shayle Khan. I invest in early-stage companies at Energy Impact Partners. Welcome to Catalyst. So let me make two observations. First, if you're paying close attention to AI world, I'm guessing that you can articulate pretty clearly the major differences amongst the hyperscalers, maybe even also the frontier labs, in terms of their chip strategy. You know about Google's TPUs, you know about Tranium coming from Amazon, you know what Microsoft and Meta are doing, you probably know about the partnerships Nvidia has set up across the value chain, you know who's vertically integrated, who's not. But do you have the same level of knowledge down to the individual company level about their power strategy? I would guess no. Here's the second point.

• 0:49Shayle Kann?

  You've heard, I'm sure, about the war for AI research talent going on amongst all these companies. TBPN and its ilk reports every single time a top researcher switches teams. But do you know the same thing is happening on the energy teams? I think there might even be more teams switching there lately. Which is all to say, I think that the topic of exactly what strategy all the companies building out the AI infrastructure are employing with regard to power is poorly covered and not well-understood. So let's fix that. For this one, I brought on Jeremie Eliahou Antiveros, who leads coverage of infrastructure and power at Semi Analysis. He's coming up next.

• 1:35Speaker 00

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• 2:19Speaker 00

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• 2:33Shayle Kann?

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• 3:07Shayle Kann?

  Jeremy, welcome.

• 3:08Speaker 02

  Yeah, thanks for having me.

• 3:09Shayle Kann?

  You have a GPU sitting right behind you. What is it? Which version is it?

• 3:14Speaker 02

  That's a Hopper H100. You know, I run a lot of agents on my local computer now. Just joking, I don't have the GPU actually. I just did a visit of sort of the factory of a NeoCloud that does a lot of pretty cool engineering stuff. And so, you know, they gave me this token of appreciation.

• 3:33Shayle Kann?

  Good swag. I haven't been given a GPU yet. Just hint, hint to everybody in the audience. All right. So I want to talk about the the power strategies of the companies who are building, owning and operating data centers. Here's a first question for you. We're going to talk about the different categories. Let's focus on the hyperscalers for a second first. When you think of the hyperscalers and how they approach power, provisioning power, getting enough power to build the infrastructure that they want for AI, do you think of them as being fairly monolithic? And they are all approaching, basically, do they all have the same strategy in your mind? And they're just in a land grab? Or do you see meaningful differences within that group?

• 4:15Speaker 02

  I think there's pretty meaningful differences, company by company. You see really varying degrees of, first of all, USA versus international appetite to sort of be behind the meter versus grid connection, sort of location of data center, how close to the end user versus sort of middle of nowhere B campuses. So I would say pretty different overall, also with regards to the way they negotiate with utilities. Generally speaking, I think it's fair to say that Google is the most sophisticated company. And on the energy side, they have sort of the biggest, you know, trading desks. They've choked some pretty big deals with utilities, as you probably know, for load flexibility kind of stuff. So they're definitely sort of at the frontier of innovating on the on the energy side.

• 4:56Speaker 02

  Another way you'd see this is when you look at the minutes of the conversations with officials in PGM or COT, you always see Google's name. You generally see them more than others. So I would say probably the most sophisticated company is Google. But other companies have different strategies. For example, I would say Meta was probably the first among the four big guys to adopt behind the meter at bigger scale.

• 5:21Shayle Kann?

  Yeah, but it's that Louisiana project or which is, there's like a five gigawatt behind the meter project that they're doing.

• 5:27Speaker 02

  So it's actually, it's actually in Ohio, in Columbus, Ohio. So as of today, they've announced sort of two major training clusters. There's a bunch of others that are on their way. But the two major they've announced and the closest to delivery, there's one in Columbus, Ohio, and the other one in Louisiana. The one in Ohio is really interesting because they actually rolled out a new type of data center design that is significantly faster to deploy. We call it the tent, right? Because when you look at it, it literally looks like a tent. The reason, speed. And they've done, they've done a whole lot of crazy stuff in Columbus, Ohio. I think probably one of the, one of the craziest examples is you could see a picture where basically there's a piece of land that they own.

• 6:11Speaker 02

  There's a piece of land nearby that is from another company from, from, if at least the data center. And so they have these two substation, substations, and then they own another piece of land in between. This is where they build the tents, the one in between. They didn't have the Time to build a new substation. So essentially, what they did is they took the medium voltage current from sort of the two already established, you know, utility connected substations. Instead of they they've built a new medium voltage line to feed their new data center. Which means that, you know, you get the idea, they're not adding new generation, they're using the same transmission line. So you could imagine in peak summer days, they're going to have to curtail actually that data center. So that was sort of a temporary solution and now they're building, you know, onsite power plants with, if I remember correctly,

• 6:56Speaker 02

  solar titan turbines from CATS to deploy, yeah, to get power on that side.

• 7:02Shayle Kann?

  Yeah, from my observation, I'd say both things that you said so far ring true. One being, Google is the most sophisticated. I think actually, Google was best positioned because they have long been the most sophisticated on energy. No offense to my friends at Microsoft, who I think have been kind of second behind them historically. But Google was always pretty, pretty deep in the energy world. They were early to PPA, offsite PPAs, VPPOs. They were the first to make the 24/7 clean commitment and that required a lot of sophistication. They were doing, you know, carbon aware flexibility long before they were doing this version of flexibility. And so they were like shifting workloads, this is pre-AI, right? But they were doing shifting workloads geographically in order to minimize carbon impact.

• 7:47Shayle Kann?

  So I think they had the benefit of all that. And the other thing I would say is that this is speculative, but I anecdotally, I'm, I'm like pretty sure it's true. I think Google's energy team is probably a multiple of the size of the next hyperscaler. Just the sheer number of people they have dedicated to it. So that seems true to me. I would have said for a long time, Microsoft was a clear second there, but they've actually lost. This is another thing I've noticed, which is that the, the small group of people who have spent a long time focused on provisioning energy for data centers are very, are hot commodities in the same way that AI researchers seem to be. And so there's a lot of. You know, people changing roles and I think Microsoft has lost a bunch of people in

• 8:31Shayle Kann?

  that in recent days. And so now it's not clear to me who's kind of second in terms of sophistication.

• 8:36Speaker 02

  Yeah, 100% agree. I don't think I wouldn't call Microsoft now the second. I probably would rank them fourth now. I think you've seen Amazon step up pretty dramatically and you've seen them at a frontier of a bunch of, you know, unique type of deals. For example, obviously, talent energy was a pretty flagship one more recently, you know, Vestra, Comanche Peak. So they've done also pretty large scale PPAs with gas power plants, with nuclear power plants, in addition to, of course, you know, renewables. So I would view Amazon as fairly sophisticated as well. And I think Meta is probably doing the most unusual stuff of all the hyperskitters. And in some sense, that's sort of where you see Meta being different

• 9:18Speaker 02

  because they don't have this cloud business. They sort of have less use cases. They're actually much more of a first party, a first party company. And that's a pretty big difference when you compare this to Amazon and Google, which, you know, build their infrastructure for actually customers, right? Customers are going to rent their infrastructure and they need to have a whole bunch of different services. So they build for maximum fungibility, right? And Google is kind of increasingly in between because they have more and more services. They used to be, I think, much more first party, where they basically just had Google Search, but now they also have Google Cloud. They have a whole bunch of other workloads. So they kind of sit in between. And that's a meta because they're sort of fully their own workloads, you know, their own cloud, their own infrastructure to support

• 9:59Speaker 02

  their first party workloads. It's kind of easier for them to to try new things. As I said before, they've done, they've been the first to go to move in a bold direction in behind the meter. Another interesting thing they've done, for example, is more at the data center level than at the energy level, but no backup. You look at any one of the modern meta data, so they don't have any gen sets. Or they have, you know, like 10 megawatts for 100 night data center.

• 10:22Shayle Kann?

  Yeah, I wanted to talk about that. And that's actually a really interesting point. So this gets to the behind the meter stuff, right? Which is, I think people, I don't know, I mean, people who are paying a little bit of attention to it here, hear these huge numbers for we're building mostly gas behind the meter. Occasionally, it'll be something else. But why, right? Is it intended? None of these are actually off-grid, or none of these are intended to be off-grid long-term. Let's say that, at least not yet. You could tell me if you you know of an exception to that that has been publicly announced. I know of some that haven't been announced yet. Mostly what they're doing is they are using behind-the-meter generation to bridge to a grid connection that is that is going to come at some point in the next few years.

• 11:04Shayle Kann?

  But in the meantime, if they are acting as a bridge and you are running off of those those gas gen sets or gas turbines, then you're not getting the four nines of reliability that you normally would provision for a data center. Now, I think you make an interesting point. Like, maybe Meta doesn't need the four nines in the same way that the others do. They don't have customers who are relying upon their uptime. So maybe that gives them the flexibility to do, as you said, behind-the-meter gas with no backup power, which is wild.

• 11:34Speaker 02

  Yeah, and and look, that's where I would actually think that the most important question is not the one you asked first. I would slightly change it. I think right now, if you want to understand the world of power, you don't have to ask about hyperskaters. You need to ask about AI Labs. These guys are the ones that are driving sort of the demand in the market, right? And so increasingly, you you basically look at Amazon or or Microsoft, how many gigawatts they're building every quarter. Half of that is going to either, or both of them combined, right, OpenAI and Anthropic. These guys are basically proxies increasingly for OpenAI and Anthropic. So maybe right now, these guys don't have sort of the the the financial strength to do everything themselves, but they have a clear view on how to get there. And and look, I'll also answer your first question, because, you know, why do you go behind the meter?

• 12:19Speaker 02

  And and I think like this is where there's maybe kind of a misconception. I think just folks don't understand the order of magnitude we're talking about here. Just look at how much generation is being added on the grid. This is just not enough. You know, we're actually publishing a report right now. As we speak, I'm not sure if it's live, it is going to be live probably next couple hours. We're looking, so when you look at the data center build-out, you're looking at tens of gigawatts per year. The trend is increasing every year by high double digits, you know, let's say 50% per year. Currently, no signs whatsoever of a slowdown, so you know, things just keep going up. Now compare that against how much generation is being added on the system. You know, how much gas is gonna be brought online next year? Five gigawatts, six gigawatts? How much solar and battery?

• 13:04Speaker 02

  Like, you know, twenty, twenty-five nameplates? But as you adjust for like ELCC values and whatnot, you just sort of add it all up. There's just not enough being added on the grid to support the build out. Now, how does that actually show up? You know, you're talking about generation constraint, essentially. How does that show up? Basically, you talk to any, any data center developer, sort of, you know, in the US, they're all gonna tell you the same story. They're all gonna tell you about this, this time where, you know, they talked to a utility, they were promised a gigawatt or half a, half a gigawatt by twenty twenty-seven. And then two months later, the utility tells them, actually, sorry, it's gonna be twenty twenty-nine, it's gonna be a hundred megawatts, and I'm gonna give you the gigawatt by twenty forty-two. There's a broader conversation with regards to incentives.

• 13:46Speaker 02

  Obviously, have no penalties whatsoever if they fail on their commitments, so that's probably one issue. But the, the bigger issue is that if you're an AI lab, power is the lifeline of your business. Power is revenue for Anthropic, power is future revenue in the form of training for Anthropic. So they need power, you know, more than anything else. If they don't have power, their business doesn't exist. So they basically cannot make a multi-billion dollar investment decision. You're talking about a gigawatt, you know, as you probably know, capex is like fifty billion dollars. Or if it's a contract because someone else pays the capex sixty, seventy billion, whatever. You cannot make that kind of investment decision if there's uncertainty on the timeline. So at some point, you gotta think first principles. How am I sure that I'm gonna meet with my roadmap?

• 14:29Speaker 02

  And let's talk about roadmap, Anthropic, you know, one and a half gigs of capacity out of twenty twenty-five. By twenty-seven, they went over ten gigs. Alright, so they're gonna build basically more than eight gigawatts in two years. That's the size of Google today. So, you know, you're building a Google in two years. You need to have certainty if you wanna do that to ensure that your revenue is gonna grow as expected and so on and so forth. That's not gonna happen with the grid. There, there's just no way, no one is building generation fast enough. And no one can give you the guarantees that they're gonna give you that power on time, except in some very specific cases. So essentially, if you wanna be in control of your destiny, the best option from a buyer's perspective, some of the folks That actually deploy power is to simply bring your own generation. You have your equipment, you know, you you you handle your own permitting and then you know when your thing is going to be online.

• 15:13Speaker 02

  At least there's always uncertainty, but it's sort of lower than if you talk to utility. That has obvious generation constraints and cannot sort of promise promise you anything. And doesn't have any binding sort of reason to, you know, comply with those.

• 15:27Shayle Kann?

  I would offer one.

• 15:30Shayle Kann?

  I'll make a bet with you, which is I think we'll add way more generation than you are saying that we will. Set aside behind the meter, like exclude that. I think we will. I think we're going to add a lot more generation. Now, that doesn't entirely make your point wrong, because the constraint in my mind is less generation and more transmission distribution. Right. And like you can add generation, but you still need to upgrade a substation and you need a high voltage transformer. And that takes three years to order, whatever. Like, there are many things that gum up the ability to provision power in the hundreds of megawatts or gigawatt scale. But I actually think from a generation perspective, there is a wave coming that is not behind the meter as well. There's clearly a wave coming behind the meter too.

• 16:13Shayle Kann?

  But I just think it's important to distinguish between a generation or a capacity constraint, which exists. But I think will won't be as big as a lot of people think there will. And a T and D constraint, which I think is as big as people think it is, or maybe is bigger.

• 16:29Speaker 02

  Well, I I I I think it's both. Or I don't know. Let me ask you this. How much, you know, how much generation obviously adjusted for like ELCC, UCAP and whatnot? How much do you think is coming online in, say, 27 or 28?

• 16:41Shayle Kann?

  Oh, let's say, uh, let's say 10 to 15 gigawatt. I'm just giving you numbers off the top of my head. I think we'll do 10 to 15 gigawatts of gas. And I think we'll do, uh, let's say, ELCC adjusted.

• 16:56Shayle Kann?

  20 gigawatts of solar and batteries? So say 35 total, something like that?

• 17:03Speaker 02

  Yeah, on our numbers, the ELCC adjusted is lower for battery and gas and solar. I agree with you. In both cases, you know, rookie numbers for when you compare that to data centers.

• 17:15Shayle Kann?

  Right, fair enough. If we're trying to build 50 gigawatts of data centers every year, plus all the other load growth that we're going to see, that's tough, right? Yeah, I get that point. You talked about the Frontier Labs. I'm interested in how you think about their energy strategy, such as it is, because there's one extent to which, okay, mainly they're just, they're just buying capacity from those who are actually building the infrastructure, which is the hyperscalers. But that's not entirely true, right? They are building their own capacity as well. And back to the point of the like, energy teams, you know, both OpenAI and Anthropic have started to hire up energy teams. They're small and small but mighty at this point compared to the hyperscalers. But what is your perspective on what OpenAI and Anthropic are doing from an energy perspective themselves?

• 17:59Speaker 02

  Yeah, so you've seen them work at different layers. I think in a lot of time, they're looking at sites themselves. And you could argue, for example, Stargate was kind of a two-way street between OpenAI and Oracle, where sort of they were both involved in the decision-making process to get this done, right? I think both of them evaluate a lot of sort of powered land sites, they look at their different options, they hire a bunch of people internationally as well to look at how, what do these markets look like? And then, you know, once they sort of find sites that they like, they can bring in partners, whether it be Microsoft or Oracle or Kori and so on and so forth, right? I think overall, like, their biggest problem is that they just need a lot. They just need a lot.

• 18:44Speaker 02

  And they have a financing constraint in the sense that they're obviously not investment grade. And a lot of this is very capital intensive and it's upfront CapEx that they just can't afford. So that sort of slows them down in their ambition and desire to be more vertically integrated, which creates, you know, very large market opportunity for hyperscalers. And again, as I was saying- Before hyperscalers are essentially, you know, half of their business, Amazon, Microsoft, in terms of like megawatts built goes to Anthropic and OpenAI. So these companies are the number one sort of,

• 19:18Speaker 02

  you know, folks that deliver capacity. Now, the second thing is that there's the silicon wars that are at play. And the silicon wars are fascinating and Google stroked first. Surprising, you know, doesn't happen very often, but Google stroked first and very large scale. The way they did it is that they sort of understood very well this issue with regards to financing. And so they were very innovative in the sense that they sort of invented, you could argue, at scale, the concept of backstops. And so they also saw the tremendous value in selling their hardware externally. I, I, I think they understood very well that when, when their biggest customer is Anthropic and that customer is basically becoming bigger than Google from a gigawatt perspective,

• 19:59Speaker 02

  there's just no way they're going to be always reliant on, on Google Cloud, right? Renting, renting from Google. They want to go vertical. It's just absolutely normal. It's table stake. And so I think Google sort of saw the opportunity as a way to sell their hardware externally and compete straight against Nvidia. And from an energy point of view, that is interesting because again, like that led sort of Google to tell Anthropic, you can build your own capacity. I'm going to support you financially if you buy TPUs essentially. And Anthropic loves TPUs, so it's a two-way street, right? Anthropic also wants to deploy TPUs because it's just a great piece of.

• 20:35Shayle Kann?

  You're saying Google has enabled Anthropic to be more vertically integrated and actually build their own infrastructure, which means dealing with energy directly rather than indirectly?

• 20:44Speaker 02

  Yeah, absolutely. And they do that. They have financial support in the form of backstops. The first way was through for party developers. So, you know, you saw Terror Wolf, HeartAid, Cypher Mining. These guys built, signed deals with FluidStuck and Anthropic in the end for about a gigawatt of capacity, all backstopped by Google. So Google enables these sites to bring to fruition through sort of, again, their credit signature stepping in in case FluidStuck or Anthropic fails. And now they're doing this at very large scale. Um. So if you look at how much capital they have sort of indirectly deployed, it's already fifty billion dollars of sort of obligations that they have on their balance sheets that are solely uh in sort of the the goal of supporting uh Anthropic's data center build out.

• 21:28Speaker 02

  Uh. And, you know, that it's actually brilliant because, you know, these fifty billion dollars, which are, let's call it four to five gigawatts, uh, that's gonna be then the capacity that's gonna yield tremendous revenue for Google because Anthropic is gonna be buying the TPUs at twenty billion dollars a gigawatt. So, you know, that's actually fifty billion that generate a hundred billion dollars in revenue.

• 21:49Shayle Kann?

  It's kind of the equivalent at a at a single customer larger scale of what Nvidia has been doing with all the Neo clouds. Like, it seems like Nvidia has been just like one by one trying to stand up more Neo clouds because they're gonna buy GPUs essentially. It's kind of what Google is doing with TPUs and Anthropic.

• 22:06Speaker 02

  It is, but it's uh what Google did is actually more aggressive. What Nvidia did initially was just investing in these companies. Uh. So they invested in CoreWeave, they invested in Navi, they invested in Lambda and a bunch of others. Uh. So they supported them financially just through equity investments, uh, but not really much more than that. And obviously code design and so on and so forth, but the burden of sort of securing data center capacity, uh, securing financing for the GPUs was still uh on on the sort of books of the of the Neo clouds themselves, right? Um. So actually, Google is much more aggressive because they're directly supporting the build out, right? Um. And I think, you know, what what what you'll observe is that for a company like CoreWeave, uh, if they wanted to build a gigawatt of data center capacity

• 22:50Speaker 02

  or most likely to lease it, that would be more more likely for them, uh, they're just not gonna be able to do that. They don't have the credit profile to do that, right? Because if you've seen a gigawatt of capacity, uh, then, you know, the data center operator uh needs to get that financed, uh, typically very high loan to cost. It's typical real estate, uh, you need a construction loan. That's not gonna go through if you don't have any investment.

• 23:11Shayle Kann?

  Yeah, related to that, actually, I've I've been curious. I mean, speaking of the Neo clouds, um, they they don't have, they're not investment grade. But in addition to all the other challenges that presents from a from an energy perspective, um, you know, if you want. To go buy turbines right now, you need to put down pretty big deposits. If you want to do a large load interconnection, the deposits are getting larger and larger. Like, you know, the the dynamic in the market is that because there is so much of a supply constraint in providing power or generation or whatever, um, you know, the the supplier can demand more out of the customer. So yeah, is that becoming a challenge for the NeoClouds? Is it putting them at a competitive disadvantage in being able to build capacity relative to like the hyperscalers who obviously have big balance sheets?

• 23:56Speaker 02

  Yeah, and a pretty massive one. Um, you can just look at the numbers, you know, CoreWeave, they have, you know, three and a half gigawatts of contracted power. Contracted for that means signed leases for the most parts. Some self-piloted signed leases with third parties. And what you saw was that this number was about, if I remember correctly, 1.3 gigawatts in Q4 2024. So they've scaled that up pretty fast, uh, but since Q3 25, they haven't really been able to secure more. And that sort of coincided with the overall tightening of financial conditions, where you saw a pretty massive bond sell-off, uh, which impacted the likes of CoreWeave, of Oracle, uh, and many of these guys. And suddenly, sort of the high-yield market, uh, froze to some extent, right?

• 24:38Speaker 02

  And that's also, you know, obviously related to the fact that this market is not that big. And basically, you know, they massively increased the supply in that market. Uh, anyways, we get, uh, we sort of get to where we are today, which is that, um, it's getting pretty tough for these companies to get the financing, um, for all of these parts. And they're all, as you said, more and more capital intensive. Utilities now are asking multi-billion dollar commitments for gigawatts, uh, gigawatts of power, turbines and so on and so forth, the same thing. So yes, pretty massive disadvantage. And and again, like I go back to what I said earlier, that's essentially what Google sold for by providing their balance sheet as support. Um, and it's actually becoming a pretty existential risk for Nvidia, because if they don't support the NeoClouds, they're at risk of basically seeing Google, Amazon and others

• 25:21Speaker 02

  take tremendous market share on the silicon side, right? So you would see Traneum take more share, TPU take more share, Nvidia's share go down just as a function of deploying more capital, uh, to get that power secured and, you know, power is revenue, right? So it's becoming a pretty strategic Angle and you know, I I expect Nvidia is already reacting pretty strongly and expect to see pretty big announcements pretty soon, you know, or institutional clients know all about this already. We talked about the talk about this all the time. Nvidia's big moves on the data center market and on the power market. It's a pretty big topic for them, but I think they've been a bit late to the game. But I expect, you know, second half of 26, you'll see NeoCloud's sort of growth be unlocked much more through the actions of Nvidia as they provide their balance sheet support.

• 26:10Speaker 00

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• 26:52Speaker 00

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• 27:35Speaker 03

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• 28:20Shayle Kann?

  All right, I want to talk through some individual energy generation technologies, and I want to hear from you, how you think about them, and particularly like who amongst all these players really leaning in, because it does seem to differ. Starting with, okay, so everybody, as far as I could tell, is trying to get their hands on gas turbines, and you know, everybody's buying from GE, Mitsubishi, Siemens if they can. Let's set that aside, because that's kind of the incumbent thing. Just focused on gas, though, you know, this has been a time of the rise of reciprocating engines, aerodermivative turbines, all these other things. Who in your mind is doing the most sort of interesting innovative stuff around gas that's not just buying from the big three?

• 29:03Speaker 02

  Yeah, Blue and Blue Energy.

• 29:04Shayle Kann?

  Well, yeah, fuel cells was my next one. I was going to talk about that. Let's set fuel cells aside for a second.

• 29:10Speaker 02

  Yeah, so look, I mean, the way I kind of see it is, like, there is like, basically tiers, and obviously the most premium is this turbines, and then you sort of start going down, and maybe then the second best thing that you like, and maybe even like it better than H-class turbines would be aerodermatives. Anyway, then you start going down and down into reciprocating engines, high-speed, medium-speed, and so forth, and then fuel cells. So basically, it depends on sort of the appetite of players with their gas to behind the meter.

• 29:41Speaker 02

  And look, the name of the game here is generally speed as well. So you have to like, think of like, what enables fast deployment? XAI, as usual, sort of showed the way and everyone followed. So what did XAI do? They deployed these aero derivatives, or actually IGTs. IGTs in the order of 20, 40 megawatts per unit. And then you started seeing other players follow. So that was 24. In 25, you saw OpenAI being sort of the next one through Crusoe and Oracle in Abilene, Texas, using again aero derivatives. Then you saw Meta essentially doing the same thing in Columbus, Ohio. Again, aero derivatives, IGTs, a lot of this.

• 30:25Speaker 02

  And I guess like, you started really getting into very large scale reciprocating engine in 2020, actually 25 as well, second half of 25 with OpenAI again. You know, they signed this gigantic deal with Oracle in Shackleton County, Texas, where they're going to deploy 2.3 gigawatts of four-megawatt reciprocating engines. So you're going to see a whole lot of reciprocating engines. The way to handle the transient is also pretty interesting because of the kind of deploy flywheels. So you know, there's going to be things running all day, sort of spinning. That's a pretty interesting one. And essentially, it's kind of like companies, one by one, are sort of folding and realizing that their best way to keep scaling is sort of going in that direction.

• 31:08Speaker 02

  Now, I would say the two companies that have avoided this to some extent so far are Amazon and Google, because they're the most aggressive in putting deposits to every single utility in the US. When you see these gigantic numbers of like contracted loads by all of these utilities, AEP or you know, the mini and

• 31:27Shayle Kann?

  Excel for Google.

• 31:28Speaker 02

  Bulk of that. Excel, the bulk of these contracted loads, I think at the end of 25, we had like 150 gigawatts. The PPL, you know, in Pennsylvania, that's mostly Google and Amazon. They're the ones sort of scouting all of the utility markets and, you know, putting deposits and so on and so forth. So they've been more aggressive on that side. And folks like Meta have been, you know, more aggressive on the BTM side. And also, I would say, what you've generally seen is hyperskaters being Generally speaking, a bit slow to react to that trend and being a bit late to the game and realizing that, hey, I'm going to face generation constraints and I might not be able to scale as fast as possible. And that has led to tremendous rise of third-party data centers.

• 32:11Speaker 02

  And the general share of data center build-out, you had a period in time in like 2024 and part of 25 were self-built, was the bulk of it. And now you're seeing the leasing markets really go up tremendously through the likes initially of Oracle, who really don't self-build, but now even the Metas of the world, the Microsoft of the world, they're essentially scaling through leasing. And when they lease, they lease through operators that oftentimes for gigawatt-scale sites, abuse behind the meter. And that can be reciprocating engines, either high-speed through like Janne Bakker or medium-speed through Virzila, Bergen. All of this is sort of being adopted at scale now. Essentially, the end of the game is, do you have it soon enough?

• 32:48Shayle Kann?

  Well, so speaking of speed, then, let's talk about fuel cells, because it's been a wild ride for Bloom. Bloom's, as of this recording, I don't know, I haven't looked today, but it's like a $90 billion market cap company somehow. And the fuel cells, they were not designed for this scale, right? They're similarly like few megawatt individual units. They're also higher CapEx, generally speaking, though CapEx on the gas turbines is going up too, so you can tell me where you think the comparison lies today. But historically, higher CapEx, somewhat higher efficiency. The main thing seems to be availability, which is like Bloom was not sold out till 2031, and so they were able to take advantage, and particularly with Oracle, it seems. But how do you think about fuel cells in that cascading chain that you described before?

• 33:33Speaker 02

  Yeah, I think the biggest disadvantage that fuel cells have, not really cost, it matters, but not so much these days. I can explain why, but generally not. I would say it's, as a bridge power solution, it's really bad. Because Bloom Energy fuel cells, they have to run extremely hot, and so if you want to use them as backup, this basically takes two days to go from like zero to 100. Whereas aerodynamics, as you know, can scale up fairly fast, reciprocating engines can scale up fairly fast. And a lot of folks, the initial hope of behind the meter was that it's all going to be bridge power, is I'm going to deploy these power plants for a year, two years, maybe three years, and then the grid is going to come, and hey, maybe I'm going to use this as backup.

• 34:17Speaker 02

  In many cases, you see folks starting with sort of lower redundancy, no diesel gen sites like that. And so in some sense, Bloom is like the ultimate play on power constraints, because it's the play on I-LAN data centers. And if you do Bloom, you're basically I-LAN it for life. Either that, or maybe you get grid at some point and then you move your fuel cells to some other location, but you can't use them as backup. It's not a very efficient solution for backup purposes.

• 34:42Shayle Kann?

  One thing I think has been interesting to see some projects, I don't know if any fuel cell projects are doing this or not, but certainly some of the some of the RESA projects and so on are, they're bridge power, which then upon the grid connection coming, transfers to the utility. So the utility then gets to operate, own and operate them. So it's not like they have to get moved to a different location. They don't sit there as backup. They do provide value to the grid on an ongoing basis. They no longer, you just kind of like shift them so they're no longer behind the meter, which I think is kind of clever. Yeah, so fuel cells, interesting story, like I think, perfect, perfect sequence of events for Bloom. We'll have to see, you know, how, how it evolves over time.

• 35:21Speaker 02

  Oh, yeah, I, I was just gonna say, like, I, I think one of the lead times that is generally maybe a little, a little sort of underestimated is not just the equipment, it's the actual deployment. And as you know very well, CCGTs take forever to, to install, you know, a couple of years or something.

• 35:40Speaker 02

  Bloom Energy fuels are really fast to deploy. So that's a massive advantage for them is, you know, as you're, as you're desperate and for some reason, you know, you can't get your power. The two high profile examples we've seen so far are permitting challenges, which I think are going to be happening more and more as well. And Bloom is sort of the natural option because you can just, you know, just plug them in, right? It's, it's pretty fast. And so that makes them an amazing play. And again, like as the data center market sort of grows, tens of gigawatts, 50% year growth per year essentially. Basically, you know, if you keep that direction by 2030, you're talking about 100 gigawatts per year being added. Then, you know, at some point, you've got to think about like what, what can be deployed, you know, fast enough.

• 36:24Speaker 02

  And I guess the other option, the other thing is, who can expand capacity fast enough? And who, who has sort of the incentive to do so? And Bloom scores really well. Because obviously their high capex also means that the payback period on a new factory is pretty low. As opposed to turbine manufacturers, you could argue now prices go up so much that payback is shortening. But you know, still, it's like much more modular. You can sort of build Bloom's sort of capacity faster. So if you assume, you know, the super AGI scenario of, you know, half a terawatt by, you know, 2030 or whatever per year. You could assume that Bloom could become this gigantic company because they're sort of one of the best at scaling and meeting sort of the demand to scale.

• 37:09Shayle Kann?

  Let's talk about solar and I guess wind. All of the hyperscalers for a long time have been signing VPAPAs for renewables. Let's just set that aside, you know, soon they continue to do that. As far as behind the meter goes, clearly you have Google, Google acquired Intersect. Intersect was already in the process of developing a bunch of these kind of hybrid sites that have, you know, a lot of capacity for data centers and a bunch of behind the meter stuff, including solar and batteries and some gas as well. So clearly, Google has at least a play in behind the meter renewables. Do you see anybody else active there?

• 37:47Speaker 02

  Yeah, I think the action is going to concentrate in Texas. I think the way big data centers, big data center campuses are going to look like a few years from now. Again, like obviously the scenario is we keep adding tens of gigawatts per year that keeps growing. So, you know, we're in this AI scenario. I'm not a religious, I'm not saying it's going to be a terawatt per year. We'll see, but just if you sort of keep on that trajectory. I think at some point, the only path is going to be to essentially build these massive campuses in West Texas. It's already sort of going up pretty tremendously, West Texas, and I think it's going to keep going up. And for solar, that is actually a strong positive.

• 38:28Speaker 02

  Obviously, because there's a ton of land in West Texas, having solar on site can reduce your energy costs. Sort of, you know, reduce, shield you from, I guess, variations in store power prices and whatnot. And then you can put a bunch of batteries. It's actually quite profitable to do arbitrage and so on and so forth. Anyways, so it makes sense and the answer is yes. There's other companies that are doing this. If we want to talk about like the ones that have said it publicly, I think Lancome has been pretty open about this. If you don't know them, they're the ones sort of building the owning the land and developing the power infra. Enabling taxes for Oracle and OpenAI. They have a bunch of other sites that are pretty massive in West Texas. And there's other companies that are thinking about this as well.

• 39:13Speaker 02

  Crusoe is another one. They have a really interesting site in Armstrong County. What they reported to be with Google. So that's another interesting one where they're connected with a wind farm, you know, across the meter, as they say. I think we're going to see more of that towards the end of the decade. More of those campuses with potentially tens of thousands of acres. Gigantic campuses that are going to have gas, solar, batteries, maybe wind. But I think, yeah, that's going to be a pretty big recipe as you get into that gigascale. And one last thing I would say is I think the market for like five gigawatt campuses is really changing now, actually.

• 39:56Speaker 02

  In the sense that over the last two years, you've seen a bunch of announcements of most of the time. Companies that no one really knows. You know, you look at their website, you see, contact us.

• 40:09Speaker 02

  I know of very reliable developers now that are planning five gigawatt data centers in West Texas. So I think it's really changing. We're at an inflection point and I think you're going to see some pretty gigantic announcements. And as you said correctly, Google sort of paved the way for others and I think folks are really all looking at this now.

• 40:26Shayle Kann?

  All right, just rounding out the technologies to talk about, let's bucket together the clean firm stuff. So in nuclear and geothermal, so in nuclear. Meta, Google, Amazon have all made pretty big announcements, reasonably sized investments into different nuclear reactor technology companies into projects. They've bought power from, you know, up rates or restarts of existing reactors.

• 40:52Shayle Kann?

  Like fair amount happening in nuclear amongst hyperscalers. And then in geothermal, I think a shorter list, at least off the top of my head. Google obviously is a big partner of Furvo, which just went public. Meta signed a PPA with XGS, which is kind of a next generation geothermal developer. So rather than running through these all one by one, I guess, how do you think about this world of like the clean, firm category from the hyperscalers perspective?

• 41:18Speaker 02

  I mean, I think the big difference with other types of technologies is just the type of contracts that have been signed so far are for the most part non-binding, subject to milestones, you know, nuclear being the best example, you know, if you don't get your approvals and so on and so forth, the contracts are obviously not executed. So I think right now it's more of an option for hyperscalers. If it works and is economical and so on and so forth, I think it's going to be massive. So it's more on the execution side for all of these companies to actually be able to deliver. Right now it's we're still in the in that more speculative phase where I think many of these, especially these next gen technologies, you know, SMRs, for the most part on next gen geothermal, I think it's still like overall fairly early stage and at the non-binding.

• 42:02Shayle Kann?

  I mean, maybe the way to put it is that all the other technologies we've talked about are there for the purpose of speed to power. That's why they're getting directly involved, right? It's like, let's, we're gonna do a bridge power, whatever, we're gonna do fuel cells, we're gonna do something. Nuclear and geothermal are not speed to power today. Long term, they could be massively scalable capacity, which the hyperscalers believe that they will need. But they're serving a different purpose. It's long term capacity, not speed to power.

• 42:32Speaker 02

  Yeah, 100% agree. And you know what, I double down on that. So we have these thesis currently that we've shared to some of our to our clients. We think gas turbine orders are going to pick this year, you know, which I think is a pretty bold sort of idea because, you know, everyone is sort of like, you know, GEV, Infinity and whatnot. But the reality is that I think the bulk of the orders have been driven by utilities indirectly data centers. But a lot of that is utilities, you know, the Dukes, the AEPs of the world. And I think those guys are not going to be ordering so much because now the sort of window is really concentrated on like 27, late 27, mostly 28. You can't really get turbines for 28. They're all sold out.

• 43:13Speaker 02

  So really, the rush right now is to secure whatever is available and works. And that's really a favorable environment for fuel cells, to some extent for reciprocating engines for the most part, and to some extent, new types of turbines, like you've seen Pro Energy and some of these new guys that have good solutions. And so, yes, 100% agree in the sense that I think, you know, things that are not speed to power are deprioritized today over speak to power. And still think we could see like more nuclear deals and geothermal deals, but those are going to remain more sort of options rather than binding contracts.

• 43:50Shayle Kann?

  Jeremy, this was a lot of fun. Thank you for doing this.

• 43:55Shayle Kann?

  Jeremy Eliahu Antiveros leads data center and energy infrastructure research at Semi Analysis. This show is a production of Latitude Media. You can head over to latitudemedia.com for links to today's topics. This episode is produced by Max Savage Levenson. Mixing and theme song by Sean Marquand. Anne Bailey edits the video version of the show. Stephen Lacy is our executive editor. All of our episodes are now on YouTube. You can subscribe to Latitude Media for episodes of this podcast and also Open Circuit, their other podcasts. You can also find the audio version of the show anywhere you get your audio podcasts. I'm Shayle Khan, and this is Catalyst.