All right. Can everyone hear us? Great. You're a podcaster long enough, you learn to do mic checks. So, I hear you're building a really, really big AI data center in Abilene, Texas.
This is accurate. You know, we have a project in Abilene, Texas that we're doing with Oracle. You know, this has been a very special project to work on because it's really been reinventing a lot of the infrastructure layers of computing that are really the base substrate that enables all of this innovation and enables innovators to do their life's work. And you know, we've really had to rethink the data. We don't even really call them data centers. We call them AI factories, right? These are the factories of intelligence. Because we think about it as one coherent cluster of computing. When you look at it from an aerial view, it almost looks a bit like a motherboard when you're sort of looking down on it because there are these giant clusters that are all interconnected and designed in a way so that it can think as one coherent giant brain. But the scale of the infrastructure is just really dramatic and it's a huge shift from legacy web applications to, you know, the energy needs and the infrastructure needs to support intelligence at scale. Maybe to give you a couple quick tidbits about this site. So, there's about 1.2 gigawatts of power that powers the site.
Can you help us understand that like compared to historical norms?
Sure. So I'm from Denver. So Denver runs on maybe a little bit less than 1.2 gigawatts. So it's about the power of Denver to power this data center. If you look at Northern Virginia where I think many people would consider like the center of the world for data centers, right? This is like where the bulk of the internet runs. You know, end of '24, JL published a report. There's about four and a half gigawatts of total capacity in Northern Virginia. So there's one site, you know, a quarter of that.
That's like all the hyperscaler clouds have very large presences in Northern Virginia.
Exactly. Yeah. So, and I think that's like sort of the evolution that we're seeing. I mean, you know, Sam recently just announced that, you know, his big KPI that he's targeting his team for is basically one gigawatt per week. So, it's basically one of these projects per week that would be delivered. It's like a total insanity. But and 250 gigawatts by 2033. So, and just you know, maybe speaking about a bit of like what it takes to make this happen, right? We have, you know, I think there's a lot of talk about all the jobs that AI is going to take. We're creating just an insane amount of jobs. It's wild. Like we have 7,000 people on site working on this every single day. And this is in a city of, you know, Abilene, Texas is a city of 120,000 people. So, you know, having 7,000 people working on this one project is, you know, a tremendous amount of labor and it's, you know, it's a lot of blue collar trade work, right? It's electricians, it's plumbers, it's, you know, construction workers, that are making all of this infrastructure happen.
So, what we saw here is two buildings. And John, could you loop this video again? What we saw here is two buildings across the street. There are six more of these. Is that right?
Yeah, you can kind of see them in the background there. So basically the first two buildings, you know, we started in June of 2024. And we sort of it was a...
Like that was dirt in June of '24.
Yeah, it was like dirt and mesquite trees and then actually behind it you see the six buildings going up behind it. Those started in February. So it's, you know, the whole project has moved very, very quickly. You know, I think one of the reasons we sort of had the opportunity to do this is that we kind of came up with a bunch of creative ways to really accelerate this. So there was actually, you know, an RFP that went out for the initial first 100 megawatts and it was just going to be like one of these buildings and, you know, the next fastest bid to basically make this happen was two and a half years and we were like, you know, they called me, they were like, you know, I was like the 35th person, I was like the last person that anybody called to do this.
Crusoe was a seven-year-old company. I mean you were in a startup when...
Totally. And they were like, do you think you could do this in a year? I was like, 'Yeah, for sure. I absolutely, like totally.' But, you know, we had to do a lot of creative things. And I think part of it was the fact that, you know, I had a lot of great, you know, data center insiders on my team, but I was very much an outsider, right? Like I'd never, you know, built anything of this sort of scale. And it sort of and I was really coming at it from building out large GPU clusters that we've been doing for our Crusoe cloud business and really having this framework of thinking through, okay, what does it take to build out a large scale coherent cluster and what is it the actual building design, the cooling design, the power design that you would want to have to support that at a much bigger scale. And that led us to all these different modular optimizations in terms of how we brought this infrastructure to life. You know, we actually, you know, at Crusoe we stood up a whole, you know, it's kind of like the journey of an entrepreneur is so funny because like you end up doing all these things that you wouldn't have expected yourself to do when you started. So we actually we have a whole manufacturing arm at Crusoe called Crusoe Industries where we have like, you know, a factory that makes like electrical equipment for data centers. And the reason we did it was so that we could control our own supply chain and we could control time to market for a lot of these things. So like to give you an example, there was a critical component called a power distribution center that distributes the medium voltage electricity, the medium voltage power to get to the data center, distributes to all these low voltage transformers. Okay. When we went out and we were requesting bids from all the different suppliers in the industry, the fastest offer we had was 100 weeks. And we were like, I committed to 12 months, so 100 weeks isn't going to work.
And 100 weeks, that's like three or four big foundational model releases.
Oracle's customers. So we're...
That's not gonna work. So, you know, we figured out how to make it ourselves and we can make it in 20 weeks. And, you know, so it was a lot of different, you know, modular components that we were basically manufacturing offsite but what you see is you see these big buildings but a lot of the guts of the data center, the electrical components, the switchgear, the low voltage UPS, the RPPs, the hot aisle containment systems, these are all modularized into these like data center Lego blocks, right? And then what we do is we actually do that offsite in a controlled manufacturing environment and then we bring it to site inside this big, you know, building and then we assemble it and it's kind of like a lot faster to do that on site than having to, you know, build everything on site essentially.
So just to make everyone in the room aware, a lot of the AI applications you are using when you go, you know, kick off some interaction with image generation or a chatbot is happening right here in this building and it's pretty recent that this has been full of GPUs and actually operating. Can you take us through what it actually takes to the inputs to a site like this and how they're different than the old world of building sort of classic data centers versus the new world of AI factories?
Yeah. So, you know, I kind of touched on this but, you know, I think just from a very first principled basis, the number one thing is like we think about this as one giant coherent cluster, right? And then you sort of end up building and designing around that.
The data center is the computer.
Exactly. The data center is the computer. And, you know, because of that you kind of, you know, you see that like central core that like T in the center of the four wings, that's where all of the network and storage lives. And then it distributes out to, you know, each of those four wings where you have these giant clusters of liquid cooled Blackwell GB200 NVL72 racks. And, you know, on the perimeter you see, you know, this stream, it kind of looks like, you know, we were sort of talking about it as...
