Catalyst with Shayle Kann - Inside the AI power wars

Episode Date: July 9, 2026

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.

Latitude Media covering the new frontiers of the energy transition. I'm Shail 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 hypers, maybe even also the frontier labs, in terms of their chip strategy.

You know about Google's CPUs, you know about Traneum coming from Amazon, You know what Microsoft and Meta are doing. You probably know about the partnerships. InVIDIA 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.

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 switch teams. But do you know the same thing is happening on the energy teams? I think there might even be more team 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 Jeremy Eliahuantiveros, who leads coverage of infrastructure and power at Semi Analysis. He's coming up next. Catalyst is brought to you by NG. Your business has enough challenges. Energy shouldn't be one of them. That's why NG builds tailored energy solutions around real business needs to support growth, strengthen predictability, and move businesses forward.

Because real power comes from shared expertise and relationships that outlast the paperwork. Learn more at NG Resources.com. That's E N-G-I-E-N-G-Resources.com. In May and June alone, millions of thermostats, batteries, and eBs across North America shifted energy during peak periods, quietly becoming one of the most powerful resources on the grid. Energy Hub builds and operates virtual power plants or VPPs that turn 2.5 million customer devices into 3.4 gigawatts of dispatchable capacity. That's the equivalent of more than three nuclear reactors worth of flexible, clean grid capacity, coordinated from customers' homes. Learn more at Energyhub.com. For data center developers, power availability is the defining challenge, but it's not the only one.

Today, growth also hinges on earning a community's trust. Bloom Energy solves for both. Bloom's fuel cell platform delivers on-site power for the digital age, sustainable, reliable, and scalable from tens to hundreds of megawatts. Bloom generates electricity without combustion, meaning lower emissions, minimal water use, and quieter operation than conventional solutions. That's why developers and utilities turn to Bloom to power their operations, and you can learn more at Bloomenergy.com.

Jeremy, welcome. Yeah, thanks for having me. You have a GPU sitting right behind you. What is it? Which version is it? That's a Hopper, H-100. 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 Neo-Cloud that does a lot of pretty cool engineering stuff. And so, you know, they gave me this. Nice. So kind of appreciation. It's good, 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 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? 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 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 trading desks. They've choked some pretty big deals with utilities, as you probably know, for low flexibility kind of stuff. So they're definitely sort of at the frontier of innovating on the energy side.

Another way, you'd see this as when you look at the minutes of the conversations with officials in V-JM, ERCOT, 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. And it's that Louisiana project? There's like a 5 gigawatt behind the meter project that they're doing somewhere. It's actually in Ohio, in Columbus, Ohio.

So as of today, they've announced two major training clusters. There's a bunch of others that are underway. But the two major, they've announced in 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 set of design. and there's 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 a whole lot of crazy stuff in Columbus, Ohio. I think probably one of the craziest examples is you could see a picture where basically there's a piece of land that they own. There's a piece of land nearby that is from another company, from whom they've leased the data center. And so they have these two 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. And sort of 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 their 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, on-site power plants with, if I remember correctly, solar Titan turbines from Katz to deploy, yeah, to get power on that side. 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 deep in the energy world. They were early to PPA, off-site PPAs, VPPAs. 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. So I think they had the benefit of all that.

And the other thing I would say is that this is speculative, but anecdotally, I'm 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 small group of people who have spent a long time focused on provisioning energy for data centers are hot commodities in the same way that AI researchers seem to be. And so there's a lot of people changing roles. And I think Microsoft has lost a bunch of people in that in recent days. And so now it's not clear to me who's kind of second in terms of sophistication. Yeah, 100% agree. I don't think, I wouldn't call Microsoft now the second. and I probably rank them fourth now. I think you've seen Amazon step up pretty dramatically,

and you've seen them at the frontier of a bunch of unique type of deals. For example, obviously, Thailand Energy was a pretty flagship one, more recently, Vestra Comanchee Peak. So they've done also pretty large-scale PPAs with gas power plants, with nuclear power plants, in addition to, of course, 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 hyperskaters. And in some sense, that's sort of where you see meta being different

because they don't have this cloud business. They sort of have less use cases. They're actually much more of 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 see in between. That's in meta because they're sort of fully their own workloads, their own cloud, their own infrastructure to support their first party workloads. It's kind of easier for them to try new things. As I said before, they've been the first to move in a bold direction. behind the meter. Another interesting thing they've done, for example, is more of the data center level than at the energy level, but no backup.

You look at any one of the modern metadata, so they don't have any gen sets, or they have, you know, like 10 megawatts for a hundred-knock data center. 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, people who are paying a little bit of attention to it. Here are 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 can tell me if 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 going to come at some point in the next few years. But in the meantime, if they are acting as a bridge, and you are running off of 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. Maybe meta doesn't need the four-nines in the same way. If 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.

Yeah, and look, that's where I would actually thank you. 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 hyperskators. You need to ask about AI labs. These guys are the ones that are driving, sort of the demand in the market. And so increasingly, you basically look at Amazon or Microsoft, how many gigawatts are building every quarter. Half of that is going to either, both of them combined, right, Open AI and Anthropic. These guys are basically proxies increasingly for upon AI and anthropic.

So maybe right now these guys don't have sort of the financial strength to do everything themselves, but they have a clear view on how to get there. And look, I'll also answer your first question because, you know, why do you go behind the meter? And I think like this is where there's maybe kind of a misconception.

I think just folks don't understand the odor 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 repulse right now as we speak, I'm sure if it's live, it's going to be live, probably next couple hours. 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, let's say 50% per year.

Currently, no signs whatsoever of our slowdown, so things just keep going up. Now, compare that against how much generation is being added on the system. How much gas is going to be brought online next year? 5 gigawatts, 6 gigawatts? How much solar and battery? like 20, 25 nameplates, but as you address 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're talking about generation constraint, essentially. How does that show up? Basically, you talk to any data center developer or sort of, you know, in the US, they're all going to tell you the same story.

They're all going to tell you about this time where they talked to utility, they were promised a gigawatt or half a gigawatt by 2027, And then two months later, the utility tells them, actually, sorry, it's going to be 2029, it's going to be 100 megawatts, and I'm going to give you the gigawatt by 2042. There's a broader conversation with regards to incentives. Obviously, you have no penalties whatsoever if they fail on their commitment. So that's probably one issue.

But the bigger issue is that if you're an AI lab, powers the lifelor 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. If you're talking about a gigawatt, you know, as you probably know, CAPEX is like $50 billion, or if it's a contract because someone else pays the CAPEX,

60, 70 billion, whatever. You cannot make that kind of investment decision if there's uncertainty on the timeline. So at some point, you've got to think first principles. How am I sure that I'm going to meet with my roadmap? And let's talk about roadmap, Anthropic. you know, one and a half gigs of capacity and of 2025. By 27, they won over 10 gigs. Right? So they're going to build basically more than 8 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 want to do that to ensure that your revenue is going to grow as expected and so on and so forth. That's not going to happen with the grid. There's just no way. No one is building generation fast enough. And no one can give you the guarantees that they're going to give you that power on time, except in some very specific cases.

So essentially, if you want to 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 handle your own permitting, and then you know when your thing is going to be online. 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 you anything and doesn't have any binding sort of reason to, you know, comply with those. I would offer one, I'll make a bet with you. I'll make a bet 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 or whatever. Like, there are many things that gum up the ability to provision power in the hundreds of megawatts or gigawatts 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. But I just think it's important to distinguish between a generation or a capacity constraint, which exists, but I think won't be as big as a lot of people think there will, and a T&D constraint, which I think is as big as people think it is, or maybe it's bigger. Well, I think it's both. I don't know. Let me ask you this. How much generation obviously adjusted for like ELCC, UKAP and whatnot, how much do you think is coming online in, say, 27 or 28?

Oh, let's say 10 to 15 gigawatts. 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, let's say, ELCC, a just. adjusted 20 gigawatts of solar and batteries? So say 35 total? Something like that? Yeah.

On our numbers, the ELCC adjusted is lower for battery and gas and solar gas. I agree with you. In both cases, you know, rookie numbers for when you compare that to data centers. Right, fair enough. If we're trying to build 50 gigawatts of data centers every year, plus all the other load group that we're going to see, and that's tough. That's 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 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 Open AI and Anthropic have started to hire up energy teams. They're small but mighty at this point compared to the hyperscalers. but what is your perspective on what Open AIA and Anthropic are doing from an energy perspective themselves? 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 Open AI and Oracle where 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 what do these market look like. And then once they sort of find sites that they like,

they can bring in partners, whether it be Microsoft or Oracle or Cori and so on and so forth. I think overall, their biggest problem is that they just need a lot. They just need a lot. 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 is upfront KappaX 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 very large market opportunity for hyperskators. And again, as I was saying before, hyperskators are essentially, you know, half of their business, Amazon and Microsoft, in terms of like megawatts built,

goes to Anthropic and OpenEye. So these companies are the number one sort of, you know, folks that deliver capacity. Now, the second thing is that there's the Silicon Wars that are at play. And the Silicon Walls are fascinating. And Google's stroke first, surprising, doesn't happen very often, but Google stroke 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 think they understood very well that when their biggest customer is anthropic, and that customer is basically becoming bigger than Google from a gigawatt perspective, there's just no way they're going to be always reliant on Google cloud, right, renting from Google. They want to go vertical. It's just absolutely normal, it's stable. 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 TPS because it's just a great piece of all. 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. Yeah, absolutely. And they do that.

support in their form of backstops. The first way was through third-party developers. So, you know, you saw Terowulf, HotAid, Cipher Mining. These guys signed deals with fluid stock and Anthropic in the end for about a gigawatt of capacity, all backstowed by Google. So Google enables these sites to bring to Thrition through sort of, again, their credit signature stepping in in case fluid stock or Anthropic fails. And now they're doing this at very large scale.

So if you look at how much capital they have sort of indirectly deployed, it's already $50 billion of sort of obligations that they have on their balance sheets that are solely in sort of the goal of supporting Anthropics Data Center buildouts. And, you know, it's actually brilliant because, you know, these $50 billion, which are, let's call it, four to five gigawatts, that's going to be the capacity that's going to yield tremendous revenue for Google because Anthropics is going to be buying the TPUs at $20 billion a gigawatt. So, you know, that's actually 50 billion that generated $100 billion in revenue.

It's kind of the equivalent at a single customer larger scale of what Nvidia has been doing with all the neoclouds. Like, it seems like Nvidia has been just like one by one trying to stand up more neoclouds because they're going to buy GPUs, essentially. It's kind of what Google is doing with TPUs and Anthropic. It is, but what Google did is actually more aggressive. What Nvidia did initially was just investing in these companies. So they invested in CoreWeave. they invested in Nabias, in Lambda, and a bunch of others. So they supported them financially just through equity investments.

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, securing financing for the GPUs was still on the sort of books of the NeoClaus themselves. Right. So actually, Google is much more aggressive because they're directly supporting the build-out. And I think, you know, what you'll observe is that for a company like Corrieve,

if they wanted to build a gigawatt of data center capacity or most likely to lease it, that would be more likely for them. They're just not going to be able to do that. They don't have the credit profile to do that, right? Because if you're seeing a gigawatt of capacity, then the data center operator needs to get that financed typically very high loan to cost.

It's typical real estate. You need a construction loan. That's not going to go through if you don't have any investment rates. Yeah, related to that, actually, I've been curious. I mean, speaking of the neoclouds, they don't have, they're not investment grade. But in addition to all the other challenges that presents, from an energy perspective, 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 dynamic in the market is that because there is so much of a supply constraint in providing power or generation or whatever, you know, the supplier can demand more out of the customer. So yeah, is that becoming a challenge for the NeoClauses? 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? Yeah, and a pretty massive one.

You can just look at the numbers. You know, Coal weave, they have, you know, three and a half gigawatts of contracted power. Contracted for that means signed leases for the most part. Some self-billed mostly signed leases with fruit parties. And what you saw was that this number was about. if I don't correctly, 1.3 gigawatts in Q4, 2024. So they've scaled that up pretty fast, but since Q325, 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, which impacted the likes of Corrieve of Oracle, and many of these guys. And suddenly sort of the high-yield market froze to some extent, right? And that's also, you know, obviously related to the fact that this market is not that big, and basically, you know, they massively increase the supply on that market. Anyways, we sort of get to where we are today, which is that it's getting pretty tough for these companies to get the financing for all of these spots.

And they're all, as you said, more and more capital-intensive. Utilities now are asking multi-billion dollar commitments for gigawatts, gigawatts and so on and so forth is the same thing. So, yes, pretty massive disadvantage. And again, like I go back to what I said earlier, that's essentially what Google sold for by providing their balance unit as support. 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 see Google, Amazon, and others, take tremendous market share on the silicon side. So you would see traneum take more share, TPU, take more share, invader share go down, just as a function of deploying more capital to get that power secured and, you know, power is revenue, right? So it's becoming a pretty strategic angle.

And, you know, I expect, our MVA is already reacting pretty strongly and expect to see pretty big announcements pretty soon or institutional clients know all about this already. We talked about this all the time. InVIA'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 budget support. When it comes to energy, the best solutions don't start with a product.

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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 everybody's buying from G.E. 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, air derivative 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? Yeah, and blue energy. Well, yeah, fuel cells was my next one. I was going to talk about that. Let's set fuel cells aside for a second. Yeah. Oh, 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 aerodervatives and then you start going down and down into reciprocating engines, high speed, medium speed and so forth and then fuel cells so basically depends on sort of the appetite of players with regards to behind the meter and look Look, the name of the game here is generally speed as well.

So you have to think of what enables fast deployment. XAI, as usual, sort of showed the way and everyone followed. So what did XAI do? They deployed this arrow derivatives, or actually IGTs. IGT is 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, arrow derivatives. Then you saw meta essentially doing the same thing in Columbus, Ohio. Again, arrow derivatives, IGTs, a lot of this. And I guess, like, you started really getting into very large-scale reciprocating engine in 2020, actually 25 as well, so I can have a 25, with Open AI again. You know, they signed this gigantic deal with Oracle in Shackle-Four County, Texas, where they're going to deploy 2.3 gigawatts of 4. four megawatt reciprocating engines.

So you've got to see a whole lot of reciprocating engines. The way to handle the transients 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. Now, I would say the two companies that have avoided this to some extent, far are Amazon and Google, because they're the most aggressive in putting deposits to every single utility in the U.S. When you see these gigantic numbers of like contracted loads by all of these utilities, AEP or, you know, the mini and Excel for Google. The bulk of that Excel, the bulk of these contracted loads, I think as of 20, 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 market. 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 in 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 a tremendous rise of third-party data centers. and the general share of sort of data center build out, you know, you had a period in time in like 2024 and part of 25 where self-built was the bulk of it. And now you're seeing the leasing markets that really go up tremendously through the likes initially of Oracle who really don't self-pill,

but now even the medas of the world, the Microsoft of the world, they're essentially scaling through leasing. And when they lease, they lead through operators that oftentimes for gigawatt scale sites use behind the meter. And that can be reciprocating engines, you know, either high speed

through like Jambacker or medium speed for Vortzilla, Bergen. All of this is sort of being adopted at scale now. Essentially, the name of the game is, do you have it soon enough? 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, you know, the fuel cells are, 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 until 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?

Yeah, I think the biggest disadvantage that fuel cells have not really costs. 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 is really bad. Because Blue Energy fuel cells, you know, they have to run extremely hot. And so if you want to use them as backup, basically takes two days, you know, to go from like zero to 100.

Whereas error derivatives, as you know, can scale up fairly fast. Respirating 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 sort of these power plants for a year, two years, maybe three years, and then the good is going to come. And, hey, maybe I'm going to use this as backup. In many cases, you see folks starting with sort of lower redundancy, no diesel gen sets like that. And so in some sense, Bloom is like the ultimate play on power constraints because it's to play on island at data centers. And if you do Bloom, you're basically islanded for life.

either that or maybe you get good at some point and then you move your fuel sales to some other location but you can't use them as backup. It's not a very efficient solution for backup purposes. 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 RISA projects and so on are their bridge power,

which then upon the grid connection coming, transfers to the utility. So the utility then gets to operate their 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 Cell's interesting story, like, I think perfect sequence of events

for Bloom, we'll have to see, you know, how it evolves over time. Yeah, I was just going to say, like, I think one of the lead times that is generally maybe a little sort of

underestimate is not just the equipment, is the actual deployment. And as you, As you know very well, CCGTs take forever to install a couple years or something. Bloom Energy fuels are really fast to deploy. So that's a massive advantage for them. 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 plug them in. Right? It's pretty fast. And so that makes them an amazing play. And again, like, as a data startup market sort of grows tens of gigawatts, 50% your 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 can be deployed, you know, fast enough. And I guess the other option, the other thing is who can expand capacity fast enough and who has sort of the incentive to do so? And,

Bloom scores really well because obviously their high capax also meets 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 still, it's like much more modular. You can sort of build Bloom sort of capacity faster. So if you assume the super AGI Pell scenario of half a terawatt by 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. Let's talk about solar and I guess wind. All of the hyperscalers for a long time have been signing VPPs for renewables. Let's just set that aside, soon they continue to do that. As far as behind the meter goes, clearly you have Google acquired Intersect.

Intersect was already in the process of developing a bunch of these kind of hyper-escue 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 and behind-the-meter renewables. Do you see anybody else active there? Yeah, I think the action is going to concentrate in Texas. I think the way big data centers, big data centers 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 his 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. 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

and sort of power prices and whatnot. And then you can put a bunch of batteries and 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 Lancium has been pretty open about this.

If you don't know them, they're the ones that are the ones that are building the, owning the land and developing the power infrastructure, enabling Texas for Oracle and Open AI. They have a bunch of other sides that are pretty massive in West Texas. And there's other companies that are thinking about this as well.

O'Cruso 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 across the meter, as they say. I think we're going to see more of that towards the end of the decade.

More of these 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 giga-scale. And one last thing I would say is

I think the market for like five-gawatt campuses is really changing. now, actually, 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 look at their website,

you see, contact us, what? I know of very reliable developers now that are planning 5Ka-W 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 of this now. 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, uprates or restarts of existing reactors. So there's like a fair amount happening in nuclear amongst the 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 Fervo, 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 hypers perspective? 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 people. non-binding subject to milestones, nuclear being the best example.

If you don't get your approval and so on and so forth, the contracts are obviously not executed. So I think right now it's more of an option for hyperskitters. 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, we're still in that more speculative phase

where I think many of these, especially these next-gen technologies, you know, SMRs for the most part on exchange geothermal. I think it's still like overall fairly early station at the non-binding stage. 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, we're going to do a bridge power, whatever. We're going to do fuel cells. We're going to do something. Nuclear and geothermal are not speed to power today. Long term, they could be massively scalable capacity, which the hypers believe that they will need, but they're serving a different

purpose. It's long-term capacity, not speed to power. Yeah, 100% agree. And you know what? I have double down on that. So we have these thesis currently that we've shared to some of our clients. We think gas turbine orders are going to pick this year, which I think is a pretty bold sort of idea because, you know, everyone is sort of like, you know, GV, 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. 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 speed to power. And, you know, 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. Jeremy, this was a lot of fun. Thank you for doing this. Jeremy Eliahu Ontiveros leads data center and energy infrastructure research at semi-analysis. This show is a production of latitude media. You can head over to latitude media.com for links to today's topics. This episode is produced by Max Savage-Levinson, mixing in theme song by Sean Marquand. Anne Bailey edits the video version of the show.

Stephen Lacey 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 Shale Khan, and this is Catalyst.