Stanford CS153 Frontier Systems | Scott Nolan from General Matter on Energy Bottlenecks

1. 0:09 – 3:55

   Why energy (not just compute) constrains the AI “factory” pipeline

   1. SPSpeaker0:09

      We are super lucky to have with us today to talk about energy bottlenecks, Scott Nolan. Welcome, Scott.

   2. SNScott Nolan0:14

      Thanks. [audience applauding] Yeah, thanks for having me. Excited to be here.

   3. SPSpeaker0:20

      So if you remember, we started the class by talking about how we're going through a great transition, right? So we have the old system stack that is transitioning to the new system stack. And to go back to our organizing mental model and metaphor for the class of the AI factory, you guys remember this, right? This is how intelligence is being manufactured, the frontier, pre-training, mid-training, post-training, deploy to agents, rinse and repeat. And for the last few weeks, as you guys have heard from folks like, um, you know, Matty at ElevenLabs, Robin, uh, sorry, Andy at Black Forest Labs, and Amit at Luma, right? Those are all different types of intelligence that are being figured out in the field right now. Today, we're gonna zoom out a little bit because sometimes it can get easy to forget that what's happening at AI labs, sure, it's exciting, right? We're getting new capabilities that have never been possible before, and that is what's driving so much growth in the industry right now, and excitement and revenue and all of that. Um, but that's just one part of what's going on because to deliver new capabilities to the world, it takes a number of things to come together, right? And we talked about how there are, um, some major bottlenecks on that progress of capabilities, and one of them, as we've talked about before, is compute. But the point of this class is to try to give you sort of a macro systems view of what's going on in the world, not just in model labs, but up and down the stack, okay? And I find the stack, the whole idea of a stack even is quite rigid sometimes because it, it kinda pres- presents this view of, you know, how things work when ul- ultimately it's just one type of mental model and, and scaffolding. And as you know, we're, we've been talking about a different kind of mental model and scaffolding, which is a, a frontier AI pipeline. And what I'd like to do is zoom out a little bit now, okay? This is my, uh, handiwork. I'm not a professional artist, um, but this is my, uh, my attempt to try and be a little, uh, a- as close to, uh, Hayao Miyazaki as I can be. I grew up watching, uh, a bunch of Studio Ghibli movies and, um, this is sort of a stylized mock-up of what I think, you know, is, is a systems-level view of how these capabilities factories are working. And so if you look, right, uh, right at the center of the factory, you've got the pipeline, right? Data, compute algorithms, pre-training, foundation models, mid-training, and so on. But to make that work, it takes a whole other bunch of systems to come together. Now, if you look at the right side of the factory, you've got a little box there that I call, uh, that, that-- th- think about that as analogous to the data center that's providing compute. You know, and we talked about in lecture one how compute is super critical. It's important, but remember, that's just one bottleneck. Sometimes what gets lost in the conversation is that powering the data centers is a whole other important thing called energy and electricity. And to keep your compute running on time, well, somebody's gotta power the data center. And

2. 3:55 – 7:41

   From ChatGPT to enterprise demand: crunches reveal the next bottleneck

   1. SPSpeaker3:55

      we are going through, well, I, I would say we've been now in four years of relentless pressure on that part of the supply chain 'cause after ChatGPT came out in late 2022, um, you know, that turned out to be this, this-- So for a long time before ChatGPT came out and scaling laws had been discovered, big question on everybody's mind was, "What is this stuff? What is AI going to be useful for?" I mean, it's cool technology, but really, what, how is it gonna change the world? And ChatGPT, I would say, was the first sort of consumer killer app, right? It became this, this way to consume the technology of, um, language models that were, that were legible to everyday people. But the supply chain wasn't ready for that. You know, it takes, like, two years to tape out chips and stand up data centers. And so in early 2023, a few months after ChatGPT came out, there was a huge compute crunch and, for a short window of time, also a huge energy crunch. At that moment in time, a bunch of us in the industry who were paying attention to what was going on started realizing, "Wait, if this continues, we're not gonna be able to keep the progress going." Because at some point in the future, cool, we had a consumer killer app now with ChatGPT, but at some point somebody's gonna figure out an enterprise killer app. You know, so- some tool or way to use this technology that's useful to enterprises and businesses, and that's what happened, right? What, what happened in December 2025, a few months ago? Claude 4.6 came out. Anyone remember that? How many of you were coding over the we- over the sum, uh, winter break? Yeah. Did it feel different? Right? And then all the adults, well, you guys were students, so you had some free time, but all the adults who were, you know, on, on parent duty came back from winter break and started using Claude at work and stuff started to change, right? 'Cause now suddenly you've got enterprises and businesses going, "Hey, this is really useful. We want more of this stuff."And that was a Groundhog Day moment. Um, now for me it wasn't that surprising, 'cause as you know, four years ago when, when ChatGPT came out, that's when I realized compute was gonna be a bottleneck. I started working on a version of, uh, trying to unlock, unblock that bottleneck at a16z. But elsewhere in the industry, there's a guy called Scott [chuckles] who was realizing that energy was gonna go through a similar problem, because if you just keep going down the supply chain, you realize that that's gonna be a huge bottleneck. And so the reason I have the electricity part of this map so much bigger than the data center map is actually from a urgency perspective, even if you have a data center ready to go, if you can't get power to it, doesn't matter. It, it's over. You can't train models. And so, um, for this class, we wanted to make sure you got a, a view into that part of the world as well. And so for the next, um, few minutes, we're gonna get a, a sort of an expert deep dive into this part of the factory, right? Uh, i- ideally all of this is just happening in one place, and at some point in the future maybe we can have modular data centers, like on campus next to the lab with a modular reactor or something. We're not there yet, and so instead we have data centers in one part of the world and e- energy, power generation in other parts of the world. Um, so this is a glorified, sort of idealized utopia schematic here. Um, but for this lecture, we're gonna be zooming in to energy. So with that, um, why don't we start with you, Scott? Thank you for coming. Tell us about yourself. How did you get here? [chuckles]

3. 7:41 – 9:12

   Scott Nolan’s path: engineering → VC → nuclear fuel supply chain gap

   1. SNScott Nolan7:41

      Cool. Yeah, thanks for having me. Um, so Scott Nolan, CEO of General Matter. We are a uranium enrichment company for nuclear energy. I started off as an engineer. I was mechanical, uh, undergrad, aerospace masters. Uh, that was Cornell, and ended up coming to Stanford for, uh, a second master's degree in business of all things. Um, but sat in on a lot of engineering classes. They were pretty much all of my electives, uh, including some CS classes. So, uh, did that, wrapped that up in 2011, joined Founders Fund, the VC firm. Was there for over a decade, uh, just fully focused on anything hard tech, anything engineering, technology-driven, um, and that included energy. And so [clears throat] you know, one, one part of energy I had always been interested in was nuclear. It always felt like this branch of energy production that just had gotten completely forgotten and sidelined as, you know, it being a massive mistake for like the past 50 years. And for the, for that decade, I would meet with so many different nuclear companies, and by 2020, there were starting to be some pretty interesting ones. Um, but they all said the same thing, that they had no fuel, and that they had to get their fuel from Russia, which was really shocking to me. Um, I dug into it for the better part of 2023 and realized it was all because of this one missing step, which is what we're working on. So we'll, we'll get into it, but for today's class, I think the interesting thing is just this energy topic in general, how much of a bottleneck is this? How do we solve it? And we'll go through that.

   2. SPSpeaker9:11

      Yeah, sounds great.

4. 9:12 – 11:27

   Industry leaders converge on a thesis: energy cost becomes the universal limiter

   1. SNScott Nolan9:12

      So we're gonna, you know, you don't have to take my word for it. We're gonna start with three pretty smart people, um, who talk about energy a bunch as bottlenecks to their, to their businesses. So first one is, um, is Sam from, from OpenAI, and this is him testifying to the Senate. So this is, uh, you know, you, you can't, you can't-- You have to tell the truth when you testify to the Senate, so you know this is true. Um, so everything is going to converge to the cost of energy, to the cost of electricity. Like, chips are gonna get cheaper, um, models are gonna get cheaper, but energy is fundamentally what you consume when you're running these models. And, you know, one version of this is Balaji, uh, who was a Stanford professor at, you know, for a time also, has argued that everything, all costs, all, you know, monetary things should be denominated in joules. Um, and so this gets back to the same sort of, same sort of thing. And then, you know, then you, then you think about Jensen, and probably his, his incentive should be to say that chips are the bottleneck or that something about what he's doing is the bottleneck. But even he would argue or admit on, you know, on the Joe Rogan podcast that energy is actually the bottleneck. So that's pretty powerful. And then, you know, you go to, you go to Elon and, um, there's, you know, many bottlenecks that he could talk about, but the one that he wants to highlight is, is energy. And I think you're seeing this now in, in some of the plans with SpaceX. Um, and so I guess I left that out of my background. I was an engineer. I worked at SpaceX right out of school, um, and then did, did a bunch of other stuff before Founders Fund. So, um-

   2. SPSpeaker10:51

      That was before you came back for grad school, right?

   3. SNScott Nolan10:53

      Before, yeah. I did everything backwards basically, but it's-

   4. SPSpeaker10:56

      Better late than never, man

   5. SNScott Nolan10:57

      ... it's okay. Um, and then, you know, and then it's like, okay, well, these are people at the very forefront of data centers, of, of the models, thinking about what's coming next. Um, but then you go mainstream and you realize, well, even the "Financial Times" is realizing this. They're realizing that actually what's upstream of data centers and all the compute is power, and you really need power, and then where are we going to get it from? Um, and we'll have some time after these slides to talk about some theories about this. Um, [clears throat] but

5. 11:27 – 13:29

   Demand growth vs. grid reality: why scaling electricity is harder than it sounds

   1. SNScott Nolan11:27

      you, you then might ask, "Well, okay, how big a problem is this really? Is this really like something that we can easily tackle?" You know, you mention, "Okay, let's talk about energy, electricity." It just sounds to most people like so unexciting and boring and, "Oh, it's big metal wires and infrastructure, and why do we care about this? Certainly someone has this solved. How could that possibly be a problem? We've been doing it for 100 years." Um, and you know, but then you look at the demand and you realize, wait, this is like way super linear, and how are we actually gonna keep up with this? And then you say, "Well, okay, you know, maybe it gets to a terawatt, but, you know, in a decade it gets to a terawatt. That's, that's pretty fast, but maybe we can keep up with that. Maybe it's not so hard."And then you look at what we've actually done over the past, you know, in this chart, you've got over 50 years X-axis, and you look at, like, the last 20 years, and you realize, "Wait, we haven't done much of anything." And in fact, like, one terawatt's kind of a problem based on what we've been doing. Um, we need to be much more on a China-like slope, where you look at the, the yellow portion of this, um, and you realize, "Wait, we need to be on a very different slope even than China." And so we have to go from almost a complete standstill on grid expansion to nearly vertical. And so that's gonna require some very different activities than what we've been doing as a country for a long time, for longer than pretty much anyone in this room has been around. So I think with that, you, you quickly realize, you know, okay, it does seem like maybe electricity is the bottleneck to AI. Maybe, maybe Jensen and Sam and Elon are all on the same page because this is so overwhelmingly obvious that you have to solve this. And then you would say, "Well, okay, how are we going to solve this? This is clearly a big problem. Um, you know, we haven't done much. How do we, how do we go really quickly on, on ramping production?" And if you rewind to, like, five years ago, um,

6. 13:29 – 15:40

   Stranded energy and the Bitcoin-to-AI infrastructure bridge

   1. SNScott Nolan13:29

      stranded energy was enough. Uh, so there's plenty-

   2. SPSpeaker13:32

      Can you define stranded energy?

   3. SNScott Nolan13:33

      Yeah. So there's plenty of stranded energy, and stranded energy would be things like, you know, a hydroelectric dam in some s- you know, rural region that there's no population nearby really consuming it, or maybe it's geothermal, um, isolated geothermal with existing technologies that no community consume it, or stranded wind in West Texas. Um, the list goes on and on. But an- anything like that, something where there's supply without real demand. And so what you saw late 2010s, early 2020s, that was completely dominated by companies that said, "Okay, I see that stranded power. I'm gonna go build something there." The very first builds that happened were typically Bitcoin, uh, Bitcoin mining centers.

   4. SPSpeaker14:14

      Yep.

   5. SNScott Nolan14:14

      Um, you know, you didn't have the really huge AI data center demand, but you did know that, okay, what can I do with stranded power? I can mine Bitcoin. I don't need that much connectivity. I don't need fiber. I can get by with iridium or something if it's middle of nowhere. I can get, I can get, you know, enough connectivity to actually perform that. And so you saw companies like, on the left, um, is a company called Crusoe, which now-

   6. SPSpeaker14:40

      Right

   7. SNScott Nolan14:40

      ... has, you know, is doing the Stargate project in West Texas, and that project is linked up with wind and natural gas and all sorts of things, some of it which was stranded. Um, and so that was, that was a great strategy for a long time. At this point, most of those great resources that were stranded without nearby demand have been claimed. People have gobbled those up. And, you know, the capacity that we need is increasing quite a bit. And so even those small chunks of electricity that were available would not even be enough today to satisfy things. And so, um, things are really moving to ask the questions of, how can we create massive net new power production? And so this was something I was starting to think about, both the stranded topic and the bigger topic, um, at Founders Fund late 2010s, early 2020s, and coincidentally, um, invested in... If the top left is Crusoe, uh, then invested in all of these companies. And so top left is a data center just like Crusoe. Um,

7. 15:40 – 16:41

   What data centers actually need: uptime, economics, and near-term gas constraints

   1. SNScott Nolan15:40

      I don't actually think it's a Crusoe one. Uh, you've got SpaceX, which is now talking about in-orbit power production, and then you've got a company called Pantalaassa doing distributed energy in, in the ocean. And so lots of different angles on this. People have different theories. We can talk about in-orbit, we can talk about other options. But today we'll talk about on land because that really dominates things, and that's what, that's the reality that we're living in. And so you say, "Okay, well, we need to produce a lot of power on land. What are, what are the constraints? What are we designing for? Um, what are the things that the data centers actually care about?" And one of the big things they care about is uptime. So, you know, data center, can you run it on solar? Can you run it on wind? You could, um, but you're gonna need a lot of batteries. And by the time you had enough batteries to get this uptime, at least as batteries exist today, grid scale, um, your cost is gonna be pretty high. And so people have, have gone away from that. Uh, what you're seeing today, the last couple years, is a lot of natural gas-powered data centers running on turbines. Turbines are getting pretty scarce.

8. 16:41 – 18:12

   Why hyperscalers are turning to nuclear: baseload, safety, and carbon math

   1. SNScott Nolan16:41

      The lead time for turbines is a few years now, um, which has increased drastically, and the producers of turbines generally are not ramping production quickly enough to even remotely keep up with this. Um, and so then you say, "Okay, well, we need, we need something that's not natural gas, can be base load. Where do we look?" And you might say, "Well, okay, what are the other factors? Maybe we don't wanna put out a lot of carbon. Maybe we want it to be pretty safe." And so then you look at the historical statistics factoring in, you know, every plant that's ever been built, and you realize that, um, here's, here's the base load chart. Then you realize looking at safety and cleanliness of power source, that actually nuclear is pretty good. Um, it's actually lowest carbon emission of any of them, [chuckles] and it's essentially tied for safest with wind. Um, and so those two things together, if you care about safety or, or emissions, it's gonna push you pretty hard towards nuclear, and that's why all the hyperscalers are, are looking to that. I think they all realize nuclear is not gonna be something where you build a plant overnight. It's not a one-year project. It's something that we're gonna see ramping in the next five to 10 years, truly ramping and moving the needle. Until then, it's kind of a, a race. Who can find stranded power? Who can find enough turbines? Who can maybe stand up solar with enough battery storage if they're less cost-sensitive? Um, but long-term, everyone's looking to nuclear. And so then, then you say, "Well, okay, well, if nuclear's the long-term, you

9. 18:12 – 20:13

   Nuclear’s hidden bottleneck: fuel and the five-step uranium supply chain

   1. SNScott Nolan18:12

      know, scaling limiter to electricity, five to 10-year timeframe-"And electricity is the bottleneck to AI, then you probably realize, well, that's kind of unexpected, but maybe nuclear is actually the bottleneck to AI scaling, um, if you're talking about here on land at least. And so then you might ask the third question, "Well, okay, is there a bottleneck to nuclear?" Uh, which brings us to what we're working on, and every nuclear reactor runs on fuel. I think a lot of people hear nuclear and you would think it's a magical technology. It's like a perpetual motion machine. But no, you actually need to refuel it every, every year or two, depending on the reactor. For more advanced reactors, there's some that design for five to 10 year refueling cycles. But, um, it does require constant fuel, and it constantly burns up fuel, just like any other type of engine. And that fuel comes from five different steps. You s- you start by mining, you turn it into a gas, you enrich it, uh, you turn it back into a solid, and then you make your fuel pellet. And you might then think, just like electricity, "Well, may- this is a solved problem. What could be the issue?" Um, but you actually look at these five steps, and it turns out that the U.S. has less than 0.1% market share today of enrichment, which is the middle step. And so the U.S. is actually unable to produce its own nuclear fuel at any scale whatsoever, and we rely completely on European firms and even to this day, Russia. Um, even though there's sanctions, we still, we still import, uh, because we really need to. And, um, you know, so there's this missing piece right in the middle. And so we can't really scale nuclear fuel as a country, which means we can't really scale nuclear, and which will mean that we can't scale, uh, data centers and AI. Um, and you know, if scaling is one thing, cost is another. At some point, the cost will matter a lot. People will start being more price sensitive. It won't just be an arms race for who can stand up a data center the fastest. There'll be margin compression. Cost will matter. But in fact, cost is the

10. 20:13 – 21:49

    General Matter’s approach and the policy tailwind: rebuilding enrichment at scale

    1. SNScott Nolan20:13

       biggest, you know, of the cost of, uh, advanced nuclear fuel is the biggest cost in many cases, and the biggest portion of that is actually enrichment, which is why we're working on it. And so you, you know, you do the build one more time, and you realize enrichment is kind of the bottleneck all the way through to, to AI on a, on a five-year timeframe. And so that's why we're almost in a race against time at General Matter, going as quickly as we possibly can to bring enrichment back online in the U.S. at scale, like with a highly scalable method that we think can completely win on cost. Um, and we're getting a lot of support from that. So when we started the company, there was, uh, no ban on Russian uranium. There was no AI data center boom. Um, it, it was under Biden administration. We started by working on advanced fuel for advanced reactors, and that was a big push. And then now this administration is very focused on energy production, and there's kind of follow through on that push, um, across administrations. And bottom right, you can see our August groundbreaking of our facility in Kentucky. Um, in that image, there's people from, like the full range of political spectrum all getting together around this. And so going from the very beginning, you can see the tech leaders are realizing energy's the bottleneck all the way to DC. Everyone realizes that energy is k- upstream of everything, not just AI, but also manufacturing and pretty much any in, any industry that you want does rely on it. And, uh, the current state of it in the U.S. is, is far worse and far less ready to scale than a lot of people realize. So that's what we're working on.

11. 21:49 – 30:38

    Rehabilitating “stigmatized” tech: Bitcoin as dress rehearsal, nuclear beyond memes

    1. SPSpeaker21:49

       Th-thank you, Scott. Uh, why don't we take a beat there because you said a few things I wanna kind of double-click on. Scott mentioned Bitcoin mining, [chuckles] and he's me- you know, sort of mentioned that in passing. But, uh, the reason I wanna zoom in on that is because, um, you know, sometimes the cultural commentary around a piece of technology can often make the underlying progress that's quite real and, you know, clearly sort of fundamental, um, confusing. Um, you know, nominally from a memes perspective, you know, the way this manifests itself on the timeline and so on is people saying SBF funded, you know, Anthropic. SBF was running FTX at the time. Um, like, you know, the fact that people in the crypto community were investing in the AI stuff, you know, you can-- we, we, we can disagree on whether crypto ended up delivering on its promises or not, but what we have to acknowledge is that, um, you know, c- Bitcoin mining was, was a bit of a dress rehearsal for AI.

    2. SNScott Nolan22:53

       Mm-hmm.

    3. SPSpeaker22:54

       Um, and sometimes, you know, I, I, I get all these questions where there'll be a, a, a team working on a pretty important fundamental bottleneck at the infrastructure layer, but just because they've raised money or something, or have done some political donation or something with somebody from the crypto community, their underlying progress just gets thrown out. You know, it's like a baby, throw out the baby with the bathwater sort of moment because people go, "Oh, if, if crypto people are involved or Bitcoin mining is involved because that didn't work out." And yeah, right, who knows? At, at some point we may have this decentralized, you know, uh, sort of, um, censorship resistance and so on.

    4. SNScott Nolan23:29

       Mm-hmm.

    5. SPSpeaker23:29

       Uh, and then we, we will have truly decentralized computing. Uh, these things take a long time, but the, f-f-from a first principles perspective, I, I find it quite sad and, and disappointing when people aren't able to decouple those two things. Um, you know, uh, you, you m- you mentioned Crusoe as an example of, of a company that's been, that you've worked with before.

    6. SNScott Nolan23:50

       Mm-hmm.

    7. SPSpeaker23:51

       Um, I think Crusoe was originally a Bitcoin mining-

    8. SNScott Nolan23:54

       Yep

    9. SPSpeaker23:54

       ... company.

    10. SNScott Nolan23:54

        Yep.

    11. SPSpeaker23:54

        Right? And then they, they sort of, some of the, many of the innovations that they ended up realizing, uh, during the Bitcoin era have ended up translating into, to, uh, building infrastructure for the AI era. Um, and I, and I think those learnings have ended up becoming valuable. Um, you know, venture capitalists sometimes like to call these evolutions pivots, and I think there's a-... unnecessary stigma around that, when in fact pivots are just one step of the continuous feedback loop we've talked about before, in my view, right? Um, and it, it's an update, and the best leaders update their priors. Similarly, as, as you've been approaching the sort of en- energy, um, discussion, you know, nuclear is, is another one of these areas that ha- has been unfortunately, uh, plagued by a bunch of confusion, politics, you know, s- social divisiveness. Um, w- what advice would you have for people here who are, who, who believe that, uh, you know, they, they'd like to work on energy, they, they'd like to work on nuclear, but for whatever reason feels like because of the past, um, uh, political climates or social objections to that technology, uh, the fundamental progress is not legible. Am I making sense? Is my question making sense?

    12. SNScott Nolan25:12

        Yeah. Yeah, yeah. I mean, you can even go back to that chart, the emissions and the safety track record of nuclear, and then what we'll talk about nuclear. But going back to what you were saying before of these pivots, I think, you know, pivots is one thing, but I would say if a company is building something that you can think of more like a primitive-

    13. SPSpeaker25:29

        Right

    14. SNScott Nolan25:29

        ... like a fundamental building block, which you might say, well, utilization of stranded electricity feels like a primitive. And yes, what we might do with it today is mine Bitcoin.

    15. SPSpeaker25:41

        Right.

    16. SNScott Nolan25:42

        Um, we think that this is gonna be really useful, and that's what Crusoe's approach was, and they went from Bitcoin mining to saying, "Well, actually, you know, yeah, we're mining Bitcoin, but we're also massively reducing emissions-

    17. SPSpeaker25:54

        Right

    18. SNScott Nolan25:54

        ... that are occurring just because this, this gas was not just stranded." Because it was stranded, people were just burning off methane straight into the atmosphere with both carbon emissions and particulate emissions.

    19. SPSpeaker26:05

        Right.

    20. SNScott Nolan26:06

        And they took it, and they ran it through a turbine and made power and mined Bitcoin and reduced emissions. And so, um, they felt like, "Hey, no matter what, even if you discount the value of mining Bitcoin to zero, we're still creating value."

    21. SPSpeaker26:17

        Right.

    22. SNScott Nolan26:18

        "And we're making money, and we can invest in this infrastructure," and they took that and they built enterprise s- um, you know, cloud deployments. Slightly larger scale, they would go after bigger projects, not just stranded oil wells in North Dakota, but stranded wind in West Texas. And then they took that and they leveraged that into something else. So it's, it's really building this up over time, I think, um, on top of a basic primitive is, is probably the way to think about it even more than a pivot, even though maybe the final end-state product that people interacted with looked different.

    23. SPSpeaker26:46

        Yep.

    24. SNScott Nolan26:47

        And so, you know, I think, I think of that as something we're basically doing. Um, it's something lots of companies have done in the past. It's something SpaceX did. It was really, how can we do s- re- how can we reduce the problem of commercializing space into a fundamental piece? And that fundamental piece was launch capacity, and-

    25. SPSpeaker27:05

        Right

    26. SNScott Nolan27:05

        ... you could denominate that in dollars per kilo to an orbit. Um, and, and that was a really powerful thing. If we can just bring, make this cheaper, we can do a lot of really cool stuff with that. And make something cheaper, you get more of it, and people will build on this, and we'll, we'll push forward the commercial space economy. So that was that thesis. For us, our fundamental building block that we're working on is enrichment, which is really just refining. It's refining of fuel, it's refining of uranium based on its isotope. And you wanna get the fissile isotope, um, in enough concentration that you can run a reactor. And so that's a very, very fundamental thing to do in a whole sector of energy that's been unfairly, uh, you know, put on the sidelines. Uh, and we can talk about why that's happened. But if you can enrich, you can make fuel. If you can make fuel, you can make 5% fuel, you can make HALEU. You can make these different grades that different reactors run on, and you can supply to anyone. And so you can supply to the existing reactors that are powering 20% of the grid in the U.S. today with zero carbon emission. Um, and those utilities are very eager for, uh, you know, to work with new entrants and to support the expansion that's gonna happen. Um, or you can work with advanced reactors, which probably are what most people hear about, all the small modular reactors or microreactors, and you can make the more enriched fuel that they need to get their smaller form factor.

    27. SPSpeaker28:25

        Yep.

    28. SNScott Nolan28:26

        And so, um, I think back to your question of like, what should people in the room think about when working on a problem, um, I wouldn't worry so much about what the, what the public narrative of it is or what very surface-level treatment of it tells you. I would go a lot of clicks deeper, like just go all the way to the bottom and figure out, okay, well, what are we actually solving h- for here? If we want baseload, if we want it to be clean, if we want it to be very scalable, uh, and safe, let's look at the numbers. And you look at the numbers and you realize that despite a lot of, um, you know, a f- not even a lot, a few very famous nuclear accidents, um, you know, and famous partly because it's a hard thing to understand, uh, the safety track record of nuclear is so much better than anything else.

    29. SPSpeaker29:12

        Right.

    30. SNScott Nolan29:12

        And even accidents like Three Mile Island had, uh, you know, I think based on all, all analysis, like no direct measurable deaths from that accident. Um, um, same thing with even in Japan with Fukushima was, you know, maybe there was one, one fatality, but thousands from the tsunami that caused it. And so, um, nuclear's just been this technology that if you look back to the '50s and '60s, obviously we were supposed to do two things. We were supposed to go to space, and we were supposed to have, you know, energy that was abundant and clean-
12. 30:38 – 33:05

    A repeatable career heuristic: work on important problems where you’re uniquely useful

    1. SPSpeaker30:38

       But then the other s- spectrum is, you know, so- something happens, which always, something goes wrong in the physical world, and then everybody panics and overcorrects, and that sets us back for the next decade. Um, you know, where in the spectrum should, should the, the students... H- how, how do you... I- is there a repeatable way for people to calibrate on where the right place is to be so that you're not just o- overindexing on the memes and instead actually landing at the right place?

    2. SNScott Nolan31:03

       Yeah. I don't, I don't think, I think it's a mistake to get too caught up in the moment. You have to be somewhat aware of what's going on, and if, you know, if you have an idea that's clearly 20 years too early, I think that's, that's not gonna be a good thing to work on. You're probably better off working on something that's more immediately necessary and then come back to that idea later. Um, but I would just focus on the fundamentals. And so, like, the, the f- the framework I always go back to, I've always found it compelling, is, you know, what's the really important problem that's, that's not getting solved, um, that's not going to get solved by someone else, that somehow your skill set lines you up to, to be really useful for? And it's really just work on those things.

    3. SPSpeaker31:42

       Yep.

    4. SNScott Nolan31:43

       Um, that could be at an existing company, it could be at a new company. You could start your own company. It could even be, uh, in a nonprofit, in the government. It could be in lots of different places. Um, but I'd say work on whatever you're gonna be the most useful for that's actually an important problem, and find the right place to do that.

    5. SPSpeaker32:01

       Um, I'm guessing questions are piling up, so I'm going to take a... I'm gonna ask Scott a couple more while people get their questions in. Um, as a proof point for how powerful it is to truly internalize... Like, when this lecture is live, I would encourage you to go back and listen to every word Scott said, internalize it, and then try and practice it because as a proof point of how powerful that framework is. You know, you started, um, General Matter in January 2024, was it?

    6. SNScott Nolan32:33

       Yep.

    7. SPSpeaker32:34

       Right?

    8. SNScott Nolan32:34

       Yeah, that's when we became a company. Before that, we were working on this in fall of '23. And I, I had been starting on this even in December of '22.

    9. SPSpeaker32:42

       Right. So you spent about a year marinate- like, truly understanding the problem, doing the five whys-

    10. SNScott Nolan32:47

        Mm-hmm

    11. SPSpeaker32:48

        ... in 2023.

    12. SNScott Nolan32:49

        Mm-hmm.

    13. SPSpeaker32:50

        Scott then started the company, General Matter. He's ne- remember, he's, Scott's never started a hardware business before. He worked at SpaceX, of course, and got a ton of really great lessons and worked at, um, Founders Fund. But really, uh, is, is this not, is this the first company you started?

    14. SNScott Nolan33:05

        Mm-hmm. Yeah.

13. 33:05 – 37:24

    From zero-to-$900M DOE award: execution playbook, team DNA, and site selection

    1. SPSpeaker33:05

       Yeah, first company Scott started, okay? Uh, J- January 2024. Twenty-four months later, 24 months, Scott announced, this is January of this year, that General Matter has been awarded a $900 million contract from the DOE to do uranium enrichment. Can we get a round of applause for that for a second? [clapping] The rate of progress that Scott single-handedly and the General Ma- how big is the team?

    2. SNScott Nolan33:42

       Uh, we're close to 100 now.

    3. SPSpeaker33:43

       100 people have accelerated in, in such a short amount of time that s- that, that's so fast that the US government is saying, "We're gonna hand this 100-person company, startup, almost a billion-dollar contract to help us move the country forward." And so, you know, sometimes the timelines on which you can make a difference, especially if you do the right systems analysis and you focus on alignment between your mission, your business model, the technology, are quite extraordinary and can surprise people. But maybe you could take us behind the scenes a little bit on what it took to go from that moment when you founded the company to that contract.

    4. SNScott Nolan34:24

       Yeah. And I would, I would highlight that, you know, you talked, you just mentioned alignment. And the thing that's really aligning is this is a multi-billion dollar project, and the DOE has said, "Hey, we wanna help. We wanna help accelerate this and help you go even bigger than you would otherwise."

    5. SPSpeaker34:38

       Right.

    6. SNScott Nolan34:39

       So the, the contract itself is to help us build that capacity as quickly as we possibly can. And so the aligning thing is we'll, we'll bring even more private capital to the project than that amount. Um-

    7. SPSpeaker34:48

       Right

    8. SNScott Nolan34:48

       ... and so I think if you, if you ask, "Okay, well, how does this come about?" We, we chose to work on a problem that we knew was completely, we believed would not be solved and was completely important and required urgent action. And fortunately, the DOE Congress had already been thinking about this. They had already funded these programs. We didn't have to convince them that these programs should exist. They knew that they should exist, and they were open to new entrants coming in and helping solve it. And so what it looked like was identifying the problem in 2023, uh, really asking ourselves if, if this was a thing to work on. We concluded that, yes, it was. Um, pulled the team together in, in late '23 with all the right people from the industry. We, we asked ourselves, "Okay, what does the right team look like for something like this?" Then we handpicked those people from a bunch of different companies that included national labs, other companies in the nuclear energy space, and then people from Tesla and SpaceX because we're gonna run a pretty similar playbook-

    9. SPSpeaker35:44

       Right

    10. SNScott Nolan35:44

        ... to break into a really capital-intensive, incumbent-dominated, stagnant industry. And so, uh, we wanted those exact type of people with that DNA and that experience. And so it was pull the team together, and then, then we evaluated, should we, do we wanna, you know, put our hat in the ring for this program? And it was completely on, on, on the direct path of what we were going to do anyway, and we said, "Yes, let's put our best effort forward to do this." And so, you know, first few months of the company was legitimately 100-hour weeks, just living and sleeping at the, at the headquarters and, and doing all the work that we were gonna do over a few years.Um, to get the plan extremely, uh, buttoned up, and then, then became the search for the right site. So the other thing with nuclear was we knew, yes, we can have the best technology, we can have the best overall plan, but you also need a really supportive community and a supportive location for what you're doing. And so we're headquartered in LA, but our facility won't be in LA, our facility will be in Western Kentucky. And so that's where we're doing construction and actual enrichment and manufacturing. Um, and so we found a, a site there that's in the, the same city as the last place the DOE, that the US did commercial enrichment in 2013 before it was shut down.

    11. SPSpeaker36:58

        Hmm.

    12. SNScott Nolan36:59

        It's called Paducah, Kentucky.

    13. SPSpeaker37:00

        Right.

    14. SNScott Nolan37:00

        There's a DOE site there. We originally went there looking for some old buildings that we could use, um, but then we found that there was 100 acres at the south end of the site that had not ever been developed and was perfect for what we needed. And so that was the beginning of the partnership with, with the DOE. Um, and yeah, like, you know, like you said, they've been extremely supportive of someone new coming in to help try and solve this problem.

14. 37:24 – 1:00:22

    Government support, job creation, and the near-term scaling timeline

    1. SPSpeaker37:24

       Uh, I'm gonna ask you a follow-up sort of last question on this. You know, there's a lot of anxiety and, uh, fear, uncertainty, and doubt about the current administration not supporting science and engineering in the country. Um, but what you just, uh, outlined is a direct counterexample to that. Um, what, what... I- is there-- Like, how supportive is the f- was the federal government in this? You know, DOGE, my understanding is there were ind- members of DOGE that helped sort of smooth things along for you. Is that true, or do you feel like, you know, the United States is asleep at the wheel and actually not helping entrepreneurs make progress on a bunch of critical infrastructure like the one you're working on?

    2. SNScott Nolan38:02

       Yeah, I'd say definitely not asleep at the wheel. I think, you know, going back to something I said earlier, the, the support for this has been ever since the Biden administration in [clears throat] 2022, 2023. Um, and so I don't think it's a political thing. I think, you know, we can, we can get into some of the details there. But it's been something where there's been congressional support for first doing HALEU, which is the advanced reactor fuel, and then doing LEU, which is what the grid currently consumes. Um, and so it's a known problem. It's a known opportunity. We really need to bring this back as a country. And so, um, yeah, there's just been a bunch of support from across the political spectrum. And then, you know, that's the political side. Then within the government, you have people who are- been putting their whole careers into this. And I think, uh, within DOE and the Nuclear Energy Department, those are people that are in it not because nuclear's been growing, because it hasn't since the '90s, but because they really believe in it. And I think, um, yeah, there's just been incredible support from across DOE for what we're doing also. So I'd say it's, it's the type of thing that, um, you know, to your question of, like, should people be worried about what's happening day to day and memes and, um, you know, public opinion, there's, there's certainly gonna be ups and downs for nuclear over the next few decades. I think it's gonna be drastically ups. Um, but there's been the same sort of support, like very consistent support, uh, from everyone in the government.

    3. SPSpeaker39:27

       On the topic of jobs, so there's a bunch of jobs you've now created in California.

    4. SNScott Nolan39:32

       Mm-hmm.

    5. SPSpeaker39:32

       But you also create a bunch of jobs in Kentucky.

    6. SNScott Nolan39:34

       Yep.

    7. SPSpeaker39:35

       Over the next four years, how many jobs do you think General Matter is gonna create?

    8. SNScott Nolan39:40

       Uh, it's pro- I mean, it's hard to say. It's certainly hundreds and hundreds of jobs. Even in LA, it's probably close to 500 over the next few years. In Kentucky, it's, it's that much or more. Um, you know, if you go back to the really early days of SpaceX, apparently they thought the company would ever only be, like, 200 people. Um, clearly that's not true. It's, like, close to 20,000 now. So these things have a way of, you know, when you're working on a really important problem that, uh, can just keep scaling, I, I think, you know, that's maybe one, my one lesson from over a decade at Founders Fund was things can scale much more than you think, and they often need to scale much more than you think. Uh, which is, you know, goes back to the SpaceX example, off by two orders of magnitude on-

    9. SPSpeaker40:21

       Right

    10. SNScott Nolan40:21

        ... on what headcount would someday be. And for us, I think just near future, we look at, you know, hundreds of people in LA, hundreds in Kentucky. That probably puts you at, like, 1,000, uh, for doing what we need to do.

    11. SPSpeaker40:34

        So 1,000 new jobs created by a startup whose path is definitely accelerated by AI, right? Uh, to do the five whys, you know, Scott kind of wa- walked us through how arguably uranium enrichment is the bottleneck on AI. As you guys have heard multiple times, there is a, there's a narrative that AI r- you know, eliminates jobs and reduces jobs, when in fact, Scott is sort of living proof that entirely new jobs are being created in real time, in the thousands, to unblock the bottlenecks for AI scaling. And I think this is an important sort of alignment mechanism everyone should be aware of more and more, which is this is not some dream that AI can create new jobs. It is literally creating new jobs, both in the sort of knowledge sector in, in California, people who are working on engineering systems for you, but also in the construction industry halfway across the country. And so I expect to see more and more companies like General Matter, assuming the public understands that AI is actually net new, it is igniting a renaissance in, in physical, in the physical world, that, that we will end up in a place where jobs that didn't exist before are gonna be created. Uh, but I don't know if you'd agree or if I'm being overly optimistic.

    12. SNScott Nolan41:48

        Uh, I, I'm, I'm pretty optimistic. I mean, in our case, we c- we have dozens of open roles, and, like, we're looking for, to hire hundreds of people. We can't find enough good people, not quickly enough. And so in our experience, like, you know, it's, it's obviously different for every company and every person, but our experience is that we want to find more good people and give them jobs. And so we're in a huge, we're in a deficit, and so how do we find enough great people? So for people that wanna work hard and, uh, are good at what they do, there's plenty of, at least at our company, tons of opportunity across pretty much every type of engineering, every type of construction-type role, finance. Like, you name it, uh, we'll hire people.

    13. SPSpeaker42:29

        I mean, we could do a quick poll before we go on to questions. Like how many people now feel like they'd be interested in a job working on uranium enrichment? Great.

    14. SNScott Nolan42:38

        Pretty good.

    15. SPSpeaker42:39

        All right. So-

    16. SNScott Nolan42:39

        Looks like nine-95%, I think I saw. Great.

    17. SPSpeaker42:42

        [laughs] We'll get, we'll get people connected.

    18. SNScott Nolan42:45

        Cool.

    19. SPSpeaker42:45

        Okay. Uh, first question.

    20. SNScott Nolan42:47

        Yeah, the question is essentially, um, DOE contract originally was all the way out through 2034. That's a long time. Uh, we're here today, you know, almost a decade ahead of that. What do we do? People are doing turbines. [clears throat] How do we scale up to actually make this relevant? And then what about space? And so, uh, you know, our timeline is much faster than the 2034 timeline, so our whole goal, because the industry needs it, is to be online before the end of the decade, and then to be scaling very rapidly from there. So we hope we can be on a useful timeline for any reactor that's trying to launch and scale up. So as they're doing the deployments, you know, first criticality in many cases this year, demos next year, really scaling 2029, um, we hope to be, to be really ready for them as they're really scaling. I think most of the real hockey stick that you'll see on these big picture charts that we looked at, that'll be early 2030s into 2035. So we're gonna see one-off deployments, you know, I think in the next couple years, tens, not hundreds, of SMRs. And then for the really big builds, those do take five to 10 years to do, um, gigawatt scale reactors, and so there's a little bit more time there. But we're trying to be well ahead of everything. So our timeframe acknowledges that. I think, you know, getting back to then the, the turbine question and, and natural gas, yeah, it does take five years plus to build a gigawatt scale reactor in the U.S., um, you know, and that's probably being optimistic. And so in the meantime, you do need to find something else, and so people have found the stranded wind. They've found, you know, natural gas pipelines that they can hook up to, and then you need the turbines, but now the turbines are sold out a couple years. You know, you might need grid interconnect, like a lot of that power el-electronics equipment is, is out a couple years at industrial scale. So I think the next couple years are almost gonna be the hardest of how do we keep scaling, how do we not hit the wall, uh, while we wait for nuclear to come in in a few years' timeframe. And then you asked about, uh, space, and I think the space approach is one that really only one company can do, and it's an answer to all these questions. And there's some technical challenges that they're gonna have to solve, but I wouldn't bet against SpaceX in solving technical challenges. But that'll be their solution. I think it'll be uniquely their solution to just put sun-synchronous, uh, you know, data center satellites in orbit. Other people really can't do that. And so I think everything else will be fought either as, like that's the-- that's by air. Everything else will be a ground game. Um, and maybe some, some in the ocean, but I think it's gonna be dominated almost with every, every other company by who can scale power on land, and therefore, who can scale nuclear.

    21. SPSpeaker45:29

        You, you don't, you don't think our friend Jeff Bezos is gonna find a way to also find a comparable solution in space?

    22. SNScott Nolan45:37

        Um, I, I think everyone's-- I think even, even SpaceX would say they hope for that. Certainly in the early days, it was like, "We don't want this whole industry just riding on us. We want-- Let's..." The whole goal of SpaceX is make humanity, you know, multi-planetary. So end goal is that SpaceX felt like they had to do it. If other people could chip in, that's something they would want. But if, if you just look at the actual launch volume of SpaceX versus Blue Origin, it's just drastic and, and Blue Origin started before SpaceX.

    23. SPSpeaker46:06

        Well, Blue Origin has the advantage of using AI now to accelerate all this ma- engineering operations, which SpaceX didn't. You gotta-- You guys had to do it all from scratch.

    24. SNScott Nolan46:13

        Fair. Fair. That's fair. Yeah.

    25. SPSpeaker46:15

        Okay.

    26. SNScott Nolan46:15

        We'll see how good the AI engineering agents are, though. Yeah.

    27. SPSpeaker46:19

        I guess this is what next year's class is gonna be about, like s- the space race.

    28. SNScott Nolan46:23

        Yeah.

    29. SPSpeaker46:23

        Um, okay, next question.

    30. SNScott Nolan46:25

        Yeah. So quest-- two-part question. One was what was it like early days SpaceX, and how did that shape how I thought about engineering? And then two, why did I decide to leave SpaceX? So, uh, step one was, part, part one of the, the question, really when I joined, I was an intern at first in college. The-- It was like 35 people, roughly. Um, you know, we were just trying to get the very beginning parts built and, and working. And so it was everything from let's build test stands that we're gonna test the, the engines on. My-- The part I worked on was propulsion systems, and I was like a structural thermal analyst on the propulsion team, which was low single digits sort of team. Um, and so we had to design the test stands. We had to design our very first most primitive engines, um, you know, like heat sink-based engines. We weren't even doing full nozzles. It was just, can we get the combustion to work right? Let's build the test fixtures. And so it was relatively scrappy. It was, how can we make a lot of fast progress? Uh, we don't need to make the fanciest test stand ever. It just has to work, and so let's do what's fast and relatively cheap, um, and optimize for the things you're trying to optimize for. And so back then, it was purely schedule optimization and some cost optimization with a hard line on safety. Uh, and so if you satisfied those things, it was, yeah, let's get it built, and let's get it out there, and let's test it, and then we'll learn a bunch, and then let's-- we'll do the next thing. And so it was really just like, okay, how many of these steps can we just chew through and, and get to the finish line? And so fast-forward all the way, um, through 20, you know, 2025, 2026, 2027, uh, we got the engines developed. They were working great. We got the Falcon 1, the first rocket built, uh, launched a couple times. Uh, first time it didn't make it that far. It had a fire inside the engine bay area due to, um, a broken, uh, like a, an aluminum, uh, nut on a, on a fitting on a, on a fuel line that was hooked into a different part of the engine and, and that crack led to a, a fuel leak which caught on fire and, and took down the rocket.Second one basically worked. Uh, it got all the way to orbit, not, not full orbit, but second stage deployed. Then you had a fuel sloshing issue, uh, where a lack of extra baffles allowed basically a spiral to form and, and second stage went out. Um, and then at that point, everything, you know, short-sightedly to your second question, I felt like, okay, the rocket works, the engines work, and maybe it's not gonna be as exciting as it was in the early years. You know, here's this example of this really important company, SpaceX, founded by someone who's an engineer with some business experience. Maybe I need to go get business experience. And so that was my conclusion, but I think it was the wrong one. As it turned out, [clears throat] the company scaled another, you know, over 10X. Um, it got to do... Like, people who have stayed there, a lot of my friends have gotten to work on some of the coolest projects, um, that anyone could work on in the past decade. And it was absolutely the right place to be, uh, for a lot of reasons. Um, so I think at the time, though, I felt like, oh, 100% company, that's, that's a big company. Like, you've gotta be at startups when there are three people. And, you know, I, I felt the same thing about, uh, Palantir at one point, about Square at one point. Thought about, you know, dropping out of different things to go work at these places, but felt like, oh, maybe, maybe 50 or 60 people or 80 people is too big. And again, completely incorrect. Like, 100 people is actually just where you get into the really hard stuff of scaling a business, seeing how you go from ideas and just product market fit to actually operationalizing and executing. Like, the people who I know who were at SpaceX during that window of, like, 100 people to 1,000 people, those are the real operators. Like, they know how to build and run teams. They kn- know how to do manufacturing. Like, even the people all the way up to 10,000. So there's, yeah, there's still, um, yeah, two more orders of magnitude to go-

Episode duration: 1:00:27