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- [00:03]
Latitude Media Host
Latitude Media covering the new frontiers of the energy transition.
- [00:07]
Shail Khan
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 hyperscalers, maybe even also the frontier labs in terms of their chip strategy. You know about Google's CPUs, you know about Trainium 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 you've heard, I'm sure, about the war for AI research talent going on amongst all these companies. TPPN and its ilk reports every single time a top research switches 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 Eliahu, Antiveros, who leads coverage of infrastructure and power at Semianalysis. He's coming up next.
- [01:35]
Sponsor/Advertisement Voice
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- [02:04]
Latitude Media Host
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- [02:36]
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- [03:12]
Shail Khan
Jeremy, welcome.
- [03:13]
Jeremy Eliahu Antiveros
Yeah, thanks for having me.
- [03:14]
Shail Khan
You have a GPU sitting right behind you. What is it?
- [03:18]
Jeremy Eliahu Antiveros
Which version is. 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 NEO cloud that does a lot of pretty cool engineering stuff. And so they gave me this as a token of appreciation.
- [03:39]
Shail Khan
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, but 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?
- [04:21]
Jeremy Eliahu Antiveros
I think there's pretty meaningful differences company by company. You see really varying degrees of first of all, USA versus international appetite, 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 the biggest trading desks. They've stroked some pretty big deals with utilities, as you probably know, for low flexibility kind of stuff. So they're definitely at the frontier of innovating. On the energy side, another way you'd see this is when you look at the minutes of the conversations with officials in PJM 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, 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.
- [05:27]
Shail Khan
And it's that Louisiana project. There's like a 5 gigawatt behind the meter project that they're doing somewhere.
- [05:34]
Jeremy Eliahu Antiveros
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 of Dave and Allison, the sort of 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 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 the two already established utility connected substations instead they've built a new medium voltage line to feed their new data center. Which means that you get the idea they're not adding new data generation, they're using the same transmission line. So you could imagine in peak summer days they aren't going to have to curtail actually that data center. So that was sort of a temporary solution. And now they're building on site power plants with, if I remember correctly, solar titan turbines from cats to get power on that side.
- [07:08]
Shail Khan
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 is always pretty deep in the energy world. They were early to PPA, off site PPAs, VPPAs. They were the first to make the 247 clean commitment and that required a lot of sophistication. They were doing carbon aware flexibility long before they were doing this version of flexibility. And so they were 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.
- [08:42]
Jeremy Eliahu Antiveros
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 unique type of deals. For example, obviously Thailand Energy was a pretty flagship one. More recently 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 renewables. So I would view Amazon as a fairly sophisticated as well. And I think Meta is probably doing the most unusual stuff of all the hyperscalers. 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 build their infrastructure for actually customers. Customers are going to rent their infrastructure and they need to have a whole bunch of different services. So they build for maximum fungibility. 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. That's a 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 at the data center level than at the energy level, but no backup. You look at any one of the modern metadata, they don't have any gensets or they have 10 megawatts for a 100 meg data center.
- [10:27]
Shail Khan
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 could 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 gensets 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 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.
- [11:40]
Jeremy Eliahu Antiveros
Yeah, 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 hyperscalers. 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 basically look at Amazon or Microsoft, how many gigawatts they're building every quarter. Half of that is going to either 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 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, which is why do you go behind the meter? And I think 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. We're actually publishing a report right now as we speak. I'm not sure if it's live, but 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 a 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 2025 nameplates. But as you adjust for 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 constraints essentially. How does that show up? Basically you talk to any data center developer 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 talk 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 2032. There's a broader conversation with regards to incentives. Obviously 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, power is the lifeblood of your business. Power is revenue for anthropic, power is future revenue in the form of training for anthropic. So they need power more than anything else. If they don't have power, their business doesn't exist. So they basically cannot make a multibillion dollar investment decision. If you're talking about a gigawatt, 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 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. One and a half gigs of capacity end of 20, 25. By 27, they want over 10 gigs. So they're going to build basically more than 8 gigawatts in two years. That's the size of Google today. So 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 gr. There is 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, from the folks that actually deploy power, is to simply bring your own generation. You have your equipment, 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 comply with those.
- [15:32]
Shail Khan
I would offer one. 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'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 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. 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. 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 and D constraint which I think is as big as people think it is or maybe is bigger.
- [16:35]
Jeremy Eliahu Antiveros
Well, I think it's both. I don't know. Let me ask you this. How much generation obviously adjusted for elcc, UCAP and whatnot. How much do you think is coming online in say 27 or 28?
- [16:47]
Shail Khan
Oh, let's say 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 adjusted 20 gigawatts of solar and batteries. So say 35 total, something like that.
- [17:09]
Jeremy Eliahu Antiveros
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.
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Shail Khan
Right, Fair enough. Trying to build 50 gigawatts of data centers every year plus all the other load growth that we're going to see. And 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 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 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?
- [18:05]
Jeremy Eliahu Antiveros
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 what do these markets 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 Corey and so on and so forth. Right. 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 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 a very large market opportunity for hyperscalers. And again, as I was saying before, hyperscalers are essentially half of their business. Amazon, Microsoft in terms of megawatts built goes to Anthropic and OpenAI. So these companies are the number one sort of 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 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 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 that led 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 CPUs, so it's a two way street. Right. Anthropic also wants to deploy TPUs because it's just a great piece of.
- [20:41]
Shail Khan
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.
- [20:49]
Jeremy Eliahu Antiveros
Yeah, absolutely. And they do that via financial support in the form of backstops. The first way was through third party developers. So you saw Terrorwolf, Hot8, Cipher Mining. These guys signed deals with Fluidstack 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 Fluidstack or Anthropic fail. And now they're doing this at very large scale. So if you look at how much capital they have indirectly deployed, it's already $50 billion of applications that they have on their balance sheets that are solely in the goal of supporting Anthropic's data center build out. And it's actually brilliant because these $50 billion which are, let's call it 4 to 5 gigawatts. That's going to be then capacity that's going to yield tremendous revenue for Google because Anthropic is going to be buying the TPUs at 20 billion doll. So you know that's actually 50 billion that generated $100 billion in revenue.
- [21:55]
Shail Khan
It's kind of the equivalent at a single customer larger scale of what Nvidia has been doing with all the Neo clouds. It seems like Nvidia has been just like one by one trying to stand up more Neo clouds because they're going to buy GPUs. Essentially it's kind of like Google's doing with TPUs and anthropic.
- [22:11]
Jeremy Eliahu Antiveros
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 Navias, in Lamda and a bunch of others. So they supported them financially just through equity investment but not really much more than that and obviously co 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 Neo clouds themselves. Right. So actually Google is much more aggressive because they're directly supporting the build out. Right. And I think what, what you'll observe is that for a company like CoreWeave, 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've seen 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 grid. Yeah.
- [23:17]
Shail Khan
Related to that actually I've been curious speaking of the neoclouds, they're not investment grade but in addition to all the other challenges that presents from an energy perspective, 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. The dynamic in the market is that because there is so much of a supply constraint in providing power or generation or whatever, the supplier can and demand more out of the customer. So yeah. Is that becoming a challenge for the Neo clouds, is it putting them at a competitive disadvantage in being Able to build capacity relative to the hyperscalers who obviously have big balance sheets.
- [24:02]
Jeremy Eliahu Antiveros
Yeah, and a pretty massive one. You can just look at the numbers. Core weave, they have three and a half gigawatts of contracted power contracted for, that means signed leases for the most part, some self built, mostly signed leases with third party. And what you saw was that this number was about, if I remember correctly, 1.3 gigawatts in Q4, 20, 24. So they've scaled that up pretty fast. 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 which impacted the likes of Core Weave of Oracle and many of these guys and suddenly sort of the high yield market froze to some extent. Right. And that's also obviously related to the fact that this market is not that big and basically they massively increased the supply in 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 parts and they're all, as you said, more and more capital intensive. Utilities now are asking multibillion dollar commitments for gigawatts of power, turbines and so on and so forth. The same thing. So yes, pretty massive disadvantage. And again I go back to what I said earlier, that's essentially what Google sold for by providing their balance sheet as support. And it's actually becoming a pret existential risk for Nvidia because if they don't support the NEO clouds they're at risk of basically seeing Google, Amazon and others take tremendous market share on the silicon side. So you would see Trainium take more share, TPUs take more share, Nvidia share go down just as a function of deploying more capital to get that power secured. And power is revenue. So it's becoming a pretty strategic angle and I expect Nvidia is already reacting pretty strongly and expect to see pretty big announcements pretty soon. Or institutional science know all about this already. We 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 Neo cloud sort of growth be unlocked much more through the actions of Nvidia as they provide their balance sheet of support.
- [26:15]
Sponsor/Advertisement Voice
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- [26:47]
Latitude Media Host
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- [27:33]
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- [28:18]
Shail Khan
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 ge, Mitsubishi, Siemens if they can. Let's set that aside because that's kind of the incumbent thing. Just focused on gas though this has been a time of the rise of reciprocating engines, aero derivative turbines, all these other things. Who in your mind is doing the most sort of interesting innovative stuff around on gas that's not just buying from the big three?
- [29:01]
Jeremy Eliahu Antiveros
Yeah. And Bloom Energy?
- [29:02]
Shail Khan
Well, yeah, fuel cells was my next one. I was going to talk about that. Let's set fuel cells aside for a second.
- [29:08]
Jeremy Eliahu Antiveros
Yeah, okay. So look, I mean the way I kind of see it is there's 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 aero derivative. Then you start going down and down into reciprocating engines. High speed, medium speed, and so on and so forth and then fuel cells. So basically it depends on sort of the appetite of players with regards to behind the meter. And 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 these hour derivatives or actually IGTs, IGTs in the order of 2030 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, gts a lot of this. And I guess you started really getting into very large scale reciprocating engine in 2020, actually 25 as well. Second half of 25 with OpenAI again, they signed this gigantic deal with Oracle in Shackelford County, Texas, where they're going to deploy 2.3 gigawatts of 4 megawatt reciprocating engines. So you're going to see a whole lot of reciprocating engines. The way to handle the transients is also pretty interesting because if they're going to deploy flywheel, so 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 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 contracted loads by all of these utilities, AEP or Dominion and Excel for Google, the bulk of Excel, the bulk of these contracted loads, I think as of end of 25 we had like 150 gigawatts. The ppl in Pennsylvania, that's mostly Google and Amazon, they're the ones Sort of scouting all of the utility markets and putting deposits and so on and so forth. So they've been more aggressive on that side and folks like Meta have been more aggressive on the BTM side. And also I would say what you've generally seen is hyperscalers 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 data center build out. You had a period in time in 2024 and part of 25 were self built. What's 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 4 gigawatt scale sites Pews behind the meter and that can be reciprocating engines either high speed through GenBanker or medium speed through Forzilla Bergen. All of this is sort of being adopted at scale know essentially the name of the game is do you have it soon enough.
- [32:46]
Shail Khan
Well so speaking of speed then let's talk about fuel cells because it's been a wild ride for Bloom. Bloom's a 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, few megawatt individual units. They're also higher capex. Generally speaking though capex on the gas turbines has been going up too. So you can tell me like where you think the comparison lies today. But historically higher capex expects 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?
- [33:32]
Jeremy Eliahu Antiveros
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 clearly not I would say 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 basically takes two days to go from 0 to 100. Whereas Aero derivatives 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 good is going to come and hey, maybe I' going to use this as backup. In many cases you see folks starting with lower redundancy, no diesel gensets like that. And so in some sense Bloom is like the ultimate play on power constraints because it's to play on islanded data centers. And if you do Bloom, you're basically islanded 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.
- [34:41]
Shail Khan
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 recent 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, 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. I think perfect sequence of events for Bloom. We'll have to see how it evolves over time.
- [35:19]
Jeremy Eliahu Antiveros
Yeah, I was just going to say I think one of the lead times that is generally maybe 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 install, a couple years or something. Bloom Energy fuel cells are really fast to deploy so that's a massive advantage for them as you're desperate and for some reason 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. It's pretty fast and so that makes them an amazing play. And again, as the data center market sort of grows tens of gigawatts 50% year per year essentially, basically if you keep that direction by 2030, you're talking about 100 gigawatts per year being added. Then at some point you got to think about what can be deployed fast enough. And I guess the other thing is who can expand capacity fast enough and who has 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 still it's much more modular. You can build Bloom capacity faster. So if you assume the super AGI pill 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 that demand to scale.
- [37:07]
Shail Khan
Let's talk about solar and I guess wind. All of the hyperscalers for a long time have been signing VPPAs for renewables. Let's just set that aside. Assume 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 hybrid sites that have 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?
- [37:45]
Jeremy Eliahu Antiveros
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. Now again, obviously the scenario is we keep adding tens of gigawatts per year. That keeps growing. So 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, obviously because there's a ton of land in West Texas. Having solar on site can reduce your energy costs, sort of shield you from, I guess, variations in 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 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 sort of owning the land and developing the power. Enabling Texas 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. Crusoe is another one. They have a really interesting site in Armstrong county where they reported to me 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. 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 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 5 gigawatt 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 5 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 so of paved the way for others and I think folks are really all looking at this now.
- [40:24]
Shail Khan
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, upgrades or restarts of existing reactors. So like fair, 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 hyperscaler's perspective?
- [41:17]
Jeremy Eliahu Antiveros
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. Nuclear Being the best example. 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 we're still in that more speculative phase where I think many of these, especially these next gen technologies, SMRs for the most part or next gen geothermal, I think it's still overall fairly early stage and at the non binding stage.
- [42:01]
Shail Khan
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 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 hyperscalers believe that they will need. But they're serving a different purpose. It's long term capacity, not speed to power.
- [42:31]
Jeremy Eliahu Antiveros
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 cl. We think gas turbine orders are going to pick this year which I think is a pretty bold idea because everyone is 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, 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 late 27 mostly 2028. 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 Probe Energy and some of these new guys that have good solutions. And so yes, 100% agree in the sense that I think know things that are not speed to power are deprioritized today over speed 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.
- [43:49]
Shail Khan
Jeremy, this was a lot of fun. Thank you for doing this. Jeremy Eliahu Untiveros leads Data center and Energy Infrastructure Research at Semianalysis. 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 Levinson Mixing in theme song by Sean Marquand. Ann 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 you get your audio podcasts. I'm Shayl Khan and this is Catalyst.