01:12:58 · Ty Morse, Scott Nolan
[01:12:58] S1: Is that mostly, like, a regulatory issue? [01:13:01] S0: I think it's a bunch of issues. A lot of people like to blame the regulator and say the regulator makes it too hard to do things. In our experience, that's not true at all. I think the first industry I worked in, space launch, people would have said, why is space launch so expensive? And you'd say, well, it's really hard, and you need to get this reliability. And maybe the regulations are hard. And then it just turns out that a lot of the organizations were just doing things the way that they'd always done them, that they were cost plus organizations, that they didn't have a lot of incentive to to actually push the limits, to actually innovate and question why they were doing things, question the requirements. And I think what we've seen now in in space launch, for example, is it's even safer, even more reliable, even lower cost, and that's just through getting iterations and by scaling up. So, yeah, our goal is not just bring back US capability. It's not just you know, make it lower cost. It's also make it more scalable so we can power all the things The US wants to do. [01:14:08] S1: What have been the biggest conventional wisdoms in turning on this sort of operation that were actually wrong when you, like, looked at the facts?
01:14:17 · Scott Nolan
[01:14:17] S0: Maybe the most... Like, the least obvious thing on questioning requirements around a company like us or even even some of the nuclear companies in general, reactor companies, people would think that the entire team must be comprised of people with nuclear PhDs. And I think that's the natural intuition. You would say, hey. This is a nuclear energy company. Therefore, it's a nuclear science company. Therefore, you need nuclear engineers. And you do, and you need people who understand the licensing, the safety, in the case of reactors, nuclear reactions. And so it's a part of the team, but it's not the whole team. And so now you look at some nuclear reactor companies, and, yes, they have a handful of nuclear engineers, but it's mostly mechanical, aerospace, electrical, software, building the other systems that go into it with only a core group that's really looking at the nuclear reactions and making sure that you're gonna get the power production you think out of a reactor. In our case, it's even it's even one step further where, yes, there's nuclear engineers on our team, and they're they're a really important part for making sure that our system's safe and that there are not nuclear reactions. But you look at an enrichment facility, and there's actually no nuclear reactions occurring. There's no chemical reactions occurring. It's simply phase change and separation. And so the team that you need to do that again, yes, we'll have some nuclear engineers. We'll have some chemical engineers, not for the sake of chemical reactions but process development, making sure you're getting the performance of the system that you need, making sure that your pumps, power systems, everything are what you think they should be, what you think they're gonna do. But it's mostly software, electrical, mechanical, aerospace engineers, and which is why we're... You know, we chose to locate the company in Los Angeles, really the the hub for that. So your number one assumption would be, oh, we need a lot of nuclear engineers. We need to be located in or at a national lab or right next door to one in a historically nuclear community. And after thinking about that at the very beginning of the company and, okay, should we locate the company in Oak Ridge? There's an incredible amount of talent there in the nuclear industry. Should we locate it somewhere else? We real...
01:16:39 · Scott Nolan, Ty Morse
You know, Los Alamos. We realized, no. We need to locate the company where most of the employees are gonna be coming from and where we think we can recruit great nuclear engineers to, which is LA. [01:16:51] S1: Yeah. This is similar to what Elon has kind of done where Dwarkesh was asking about, like, do you try to, like, optimize for PhDs or something? And he was like, no. I just want great engineers. Yep. And great engineers don't always have PhDs. [01:17:03] S0: Yeah. I mean, great engineers even might not even have a master's degree or even an undergrad degree. There's people who are incredible technicians who are basically very hands on engineers who might not have gone to college, but maybe they have worked on all sorts of mechanical systems for decades, even from when they were a kid, because they were tuning up their shifter cart or doing car engine rebuilds or they were working on hot rods. And so I've worked with people before who are some of the best engineers who don't have a formal degree at all but have really built a lot of systems and have really smart ways of doing things that someone who maybe spent four years in university wouldn't realize.
01:17:03 · Scott Nolan, Ty Morse
[01:17:03] S0: Yeah. I mean, great engineers even might not even have a master's degree or even an undergrad degree. There's people who are incredible technicians who are basically very hands on engineers who might not have gone to college, but maybe they have worked on all sorts of mechanical systems for decades, even from when they were a kid, because they were tuning up their shifter cart or doing car engine rebuilds or they were working on hot rods. And so I've worked with people before who are some of the best engineers who don't have a formal degree at all but have really built a lot of systems and have really smart ways of doing things that someone who maybe spent four years in university wouldn't realize. [01:17:46] S1: They don't have traditional proof of work, but they have, like, real real world stuff. Yep. I think one thing that's very important to cover is basically the idea that we've got this massive tsunami, which is AI, and you have to turn on all these data centers. And I think a lot of data centers, you need nuclear power. But if you can't actually produce power because you don't have enriched uranium, it doesn't work.
01:18:04 · Scott Nolan, Ty Morse
[01:18:04] S0: Yeah. When we started the company, the whole AI data center wave was not not really top of mind for people or even for us. We we were just very focused on bringing back capability as quickly as possible. So there wasn't the AI data center boom. There wasn't the Russia ban. It was, we need to do this, and we need to do it for the advanced reactors as quickly as we can so that they can succeed. Now it's become obvious that not only do we need to do that, but we need to massively increase the amount of nuclear fuel produced to power all the reactors that people are working on that the hyperscalers are planning to put at their sites behind the meter. And so it's one of the most urgent things we think about is how do we build for capacity? So right now, as we build enrichment capacity in Kentucky, we're sizing that to completely satisfy the domestic industry all the way through 2040. We want to get way ahead of it and make sure there's more than enough capacity to power this first in decades net meaningful expansion of The US grid. The way we think about it is not just cost. It's not just schedule. It's how do we do these things at scale and allow ourselves to scale up capacity both responsibly as we see the demand coming, so on short timelines, and then in a way that really moves the needle. And so, yeah, that's something we think about constantly. [01:19:25] S1: How did that change the way that you think about building the company and your need to go produce way more uranium?
01:19:25 · Ty Morse, Scott Nolan
[01:19:25] S1: How did that change the way that you think about building the company and your need to go produce way more uranium? [01:19:32] S0: The the AI boom makes it even more obvious how quickly we need to expand grid capacity. So if we go back to something I said earlier, it's 2010. The US and China were exactly at the same place on the grid. Today, they've doubled it. So in about fifteen years, it is the case that if you really want to, you can double your grid from where we're sitting today. And then if you look at the AI demand, it's dramatic. It's like by 2030, I believe the AI... The latest projections are that the AI data center demand for electricity is gonna completely consume or equal today's A [01:20:09] S1: eclipse, yeah.