The Exchanges

Q compare and contrast, right? I'm going to talk about the, the constraints on each of them, but why don't we start with the incumbent thing, the thing we are doing right now, where all the data centers are, which is like large hyperscale data centers connected to the grid. What do you think of as being like the core constraint to just delivering 10 x the compute in that way?

A Yeah, no, great, great question. I think it's going to make for a great, great conversation as we look across the different options here. I think the constraints on the grid side, right, are fairly well known at this point. Um, it's a speed issue in particular on the transmission side. How, how long can we, how much time will it take to build out the transmission capacity necessary to interconnect these mega sites, gigawatt scale sites to new power supply, ideally, you know, carbon free power supply. And in many markets, right, that's running five to seven years now, which is, is a pretty massive Timeline for data centers given the speed of, uh, power and speed of deployment on the AI build out that we're, we're trying to drive. Um, maybe the other couple issues that we should at least be mindful of here are power quality, right? These large data centers, especially as they cluster in certain locations, can have bigger impacts on the grid writ large, and the extent to which society, regulators, and utilities are willing to serve those customers if they have bigger grid impacts, I think is still a bit to be determined, and A space I'm watching pretty closely. And then, of course, maybe the third vector from my side would be, let's call it, you know, social license to operate. And we're seeing in many states, right, just blanket bans on new data center developments. We're seeing …

AI assessment note: “it's a speed issue in particular on the transmission side.”

Q but they're smaller and you put them at the edge. So I've talked a little bit about edge compute on the podcast before. You and I have spent a lot of time thinking about it separately. First of all, define what you think of as edge compute, um, because it is sort of malleable, and then, like, what is your latest thinking on what role that plays in the market?

A Yeah, so, so this is a really tricky question, right? Edge computing has been around for a while. Um, historically, it evolved to serve certain use cases like telecommunications, and more recently, video streaming, for example, is something that happens much closer to the edge than other hyperscale data center. Um, but moving forward, I think there's a school of thought that says that AI inference in particular might move to the edge, and I think the, you know, first principles argument that folks tend to make is that latency is going to matter more, um, and so siting compute infrastructure closer to demand just has a performance benefit that can't be met via, you know, large central sites in West Texas, for example. Um, as we've dug in a little more, I think that's a little bit of a red herring, and so let's come back to that in a second and talk about why you would actually pursue edge data centers and edge computing. Um, but latency has certainly been one of the reasons historically. Um, that said, edge computing can mean a few different things, to your point, right? Um, so in the extreme scenario, I think, you know, as you move out, you know, 10, 10 plus years, more and more is going to happen on device. We already know that, um, you know, like Waymo cars, for example, have a lot of their day-to-day, or all of their day-to-day navigational tools and driving decisions get ma…

AI assessment note: “edge computing can mean a few different things, to your point, right?”

Q We have plenty of land available, right? That is not the constraint here, and, and you can go where there's the cheapest labor, you can go where there's the easiest permitting and siting, like, it does change the game in that manner, but it does have its own set of challenges and constraints, which is why it hasn't happened a lot historically. So what's your perspective on just straight off-grid?

A Yeah, I mean, you make a pretty good case. It should be pretty attractive, right? Um, there was this foundational study that came out about two years ago, um, that was co-authored by Stripe and Paces and Scale Microgrids, and they found over a terawatt of opportunity in the American Southwest alone, with high levels of renewable, um, development being able to support those assets, like, 50% solar, um, plus batteries at cost parity to using all gas and the ability to get up to, I think, 80 or 90% solar without a meaningful, um, Cost increase. So like, from a land perspective and a resource perspective, it makes a lot of sense. Um, and to your point, it can also move really quickly. You can avoid the places where the public really doesn't want data centers, right? You've got such geographic flexibility. Um, it should be the opportunity if you, if you just take a first principles approach. Um, and we certainly don't need to be thinking about going to space until we think about going to remote parts of, of the earth, right? Um, but to your point, it's not happening. At scale yet, and I think there's a couple reasons for it. There are some projects that are happening that we can learn from, right? Um, and, and we've got some, some manic data, um, to support that. I think at the end of the day, um, the grid's a marvel of humanity, and it does a lot of really good things, in particula…

AI assessment note: “if you go off grid and you have to operate on an island”

Q actually data centers on land require a lot of maintenance, and you can't really do a lot of complicated maintenance, uh, to a satellite, right? And so, either we solve that with some robotics, that's going to be very clever, that seems difficult for me to imagine, or it's an economic thing. You lose a bunch of, you just have some loss rate, and you have to account for that.

A Yeah, I mean, you know, in a hyperscale data center today, right, like there's a meta engineer or a Google engineer that is going to replace every CPU or GPU as it breaks more or less in real time and in space, if it breaks, at least today, you're, you're kind of stuck with it broken. And to your point, maybe in 20 or 30 years, if we're really in some super intelligent future, there's, you know, robotic replacement and ways to update chips in real time and whatnot. But, but until then, it just adds economic drag on the, the overall project. And, You know, we kind of skipped over cost, but it, it's not clear that there's a real economic advantage here. I mean, the economic reason to do this, right, is free, free power. Um, you can effectively get 95% capacity factor on the solar panels at a space-based data center because you put it in kind of permanent, um, sun, right, from an orbital perspective, um, and then there's much better solar irradiance, so you get somewhere between five or 10 X the energy output per panel over the life of the panel than you would on earthbound panel, and so, you know, power is really cheap, but As you mentioned earlier, you know, total cost-wise, energy's only, you know, five to 15% of a AI-focused data center, and chips and maintenance are the rest, and you're stuck with the same chip cost, whether you put the thing in, in space or, or on Earth, and…

AI assessment note: “in space, if it breaks, at least today, you're, you're kind of stuck with it broken.”

Q data center on a fully loaded levelized cost of flop, uh, is just gonna be cheaper. So it's probably not a Costing either. Which means it's a speed thing. Right? And speed is the, the name of the game right now. But I think what remains to be proven in Edgeworld is that it can actually be faster at the same scale. This is what we need to find out.

A Yeah, I, I think that's right, and, and I do think at some point the speed game is gonna slow down and cost is gonna matter, especially in the inference world. I don't know exactly when that happens, and, you know, in our future scenario where we're in some kind of relatively quick takeoff around AI capabilities, maybe speed matters for longer because models continue to improve kind of indefinitely, but at some point when we have agentic, you know, employees in most Fortune 500 companies and in this kind of future, right, like, The cost of those workers matters, and so I do think at some point, if there's an edge build-out, and you're looking at two or three different edge deployment models, while speed matters, the cheapest of those models might be the one that ends up winning at scale.

AI assessment note: “Yeah, I, I think that's right, and, and I do think at some point”

Q I do not believe that. Do you believe that?

A I do not believe that. Um, I think, like, we need to start this conversation with a bit of the, the acknowledgement, right, that moving off planet, for lots of reasons, is a crazy proposition, right? Um, and if you listen to Elon talk through it, it starts to sound like a logical endgame in a world where we're building hundreds of gigawatts of compute infrastructure a year. And Elon asserts that that's going to start happening in three or four years, right? Um, I don't think it is likely, I don't think it is going to be the cheapest source of new compute capacity in three or four years, nor do I think that we're going to be building hundreds of gigawatts of compute infrastructure per year in the US alone in three or four years. Um, but in a world where we're assuming that we're somewhere between, you know, AGI and some, you know, more super intelligent, you know, computing infrastructure, It's kind of the end game, right? It's kind of the only place you could go to build, you know, infinite amounts of compute capacity. Um, whether that's in five years or 500 years, you know, I, I'm not quite sure, but I agree it's not, not before 2030.

AI assessment note: “I do not believe that.”