00:03:54 · Sebastian Johnson, Alex Higginbottom
[00:03:54] S0: I think... Can you... Maybe if you can't share those names, can you talk about, you know, within fusion, there are different schools of thought. And even within those schools of thoughts and approaches, there are even more sort of different... Are there approaches where your technology makes more sense? Is it with tokamax or whatever? Like, know, other particular simulations or or approaches where your technology is being used, you know, at the moment? [00:04:16] S1: So, yeah, this is something that we've been really... From day one, in fact, much broader than fusion. But within fusion, we've wanted to be as comprehensive as possible in covering... Being a true foundation model for plasma. So that means being useful for, tokamax, but also laser fusion, every kind of confinement type. That's And really important because as I said earlier, we don't know who the winner's gonna be, really. So we need to be able to work with with all of them. And this is... You know, we'll be launching our first world model next week, and this is the first time that any... Like, this is really quite a quantum leap, I would say, in in the field of AI for... In general, but also in in fusion. It's the first time that we've had different confinement types in one model. And, you know, we're going much much broader than that still. We're building world models for extreme physics overall. So this obviously has massive applications in semiconductor manufacturing and aerospace and beyond, which we are just as excited about as we are fusion.
00:04:16 · Alex Higginbottom, Sebastian Johnson
[00:04:16] S1: So, yeah, this is something that we've been really... From day one, in fact, much broader than fusion. But within fusion, we've wanted to be as comprehensive as possible in covering... Being a true foundation model for plasma. So that means being useful for, tokamax, but also laser fusion, every kind of confinement type. That's And really important because as I said earlier, we don't know who the winner's gonna be, really. So we need to be able to work with with all of them. And this is... You know, we'll be launching our first world model next week, and this is the first time that any... Like, this is really quite a quantum leap, I would say, in in the field of AI for... In general, but also in in fusion. It's the first time that we've had different confinement types in one model. And, you know, we're going much much broader than that still. We're building world models for extreme physics overall. So this obviously has massive applications in semiconductor manufacturing and aerospace and beyond, which we are just as excited about as we are fusion. [00:05:24] S0: And you you spoke about, you know, your own frustration in that these simulations can take such a long time. You almost, like, program it. You get them up and running, and then you kind of have to just, like, leave them to to work. That I imagine that's very painful as like an academic or a researcher, even more so for kind of building these companies. How short can you bring that that time frame down to? Like, what can be the real impact for somebody who could be using this technology?
00:05:24 · Sebastian Johnson, Alex Higginbottom
[00:05:24] S0: And you you spoke about, you know, your own frustration in that these simulations can take such a long time. You almost, like, program it. You get them up and running, and then you kind of have to just, like, leave them to to work. That I imagine that's very painful as like an academic or a researcher, even more so for kind of building these companies. How short can you bring that that time frame down to? Like, what can be the real impact for somebody who could be using this technology? [00:05:46] S1: Yes. That's really, right now, our key value proposition. And if you... Just to kind of set the stage here, you're building a fusion reactor, and there are literally trillions of different ways to put it together. You know, different shapes, different temperatures, different, you know, magnetic field shapes, all of this kind of thing. And right now, a single simulation on a high performance computer takes ten hours to multiple days. So how can you ever build something optimal if you're if you're trying to search trillions of combinations, but you can only search... You know, like, it's like picking up random grains of sand on the beach. Whereas what we've developed gives you the same results but in milliseconds, So it's a million times faster.
00:05:46 · Alex Higginbottom, Sebastian Johnson
[00:05:46] S1: Yes. That's really, right now, our key value proposition. And if you... Just to kind of set the stage here, you're building a fusion reactor, and there are literally trillions of different ways to put it together. You know, different shapes, different temperatures, different, you know, magnetic field shapes, all of this kind of thing. And right now, a single simulation on a high performance computer takes ten hours to multiple days. So how can you ever build something optimal if you're if you're trying to search trillions of combinations, but you can only search... You know, like, it's like picking up random grains of sand on the beach. Whereas what we've developed gives you the same results but in milliseconds, So it's a million times faster. [00:06:31] S0: Wow. That's crazy. That's not even like... That... That's not... Yeah. That's like a... Not even order order of magnitude. That's crazy. That... That's so much faster. And so where are you at in your journey? Right? So, you know, I know you're you're releasing this model next week. How closely are you working with certain companies? Are they starting to see value from it now? What does that look like in terms of, like, product development and and real value being used by... Being realized by end users?
00:06:56 · Alex Higginbottom, Sebastian Johnson
[00:06:56] S1: Yeah. So this is, you know, a really, really hard problem. And this model we're releasing next week is really the first step. And just like other, you know, Frontier Labs, we'll be releasing new iterations of the model every month, every couple of months, and the... It'll just get better and better, a broader and broader capability. You know, I mentioned the speed is the first value proposition. The second one increasingly will be training directly on experimental data, and there's this idea of closing the sim to real gap. And then you won't just have something which is a million times faster, but also more accurate to reality. And that ties into a bigger vision that we have of the company, which is, you know, maybe one day, ten years, maybe less, we won't need to build five practice Starships. We can do a million in a world model and then build the final one straight away. That's really the kind of North Star that maybe we'll never hit, but that's really what we were going for. Yeah. And then in terms of... Sorry. What... And then and then what what... Was there other points to your question? [00:08:02] S0: It was... Yeah. It was what stage of the product development or, like Right. Are there users out there using some of the things that you've built already?
00:08:02 · Sebastian Johnson, Alex Higginbottom
[00:08:02] S0: It was... Yeah. It was what stage of the product development or, like Right. Are there users out there using some of the things that you've built already? [00:08:09] S1: Yeah. Great question. Yeah. Of course. So, yeah, this first year of the company, you know, we... We've been hiring, like, the a team, you know, building our product, our initial product, which was huge effort. You know, some of the best researchers in the world, massive conviction, extremely long hours to build this. But still, yeah, we've been fortunate to work with some of the leading fusion companies. We can't share exactly who that is right now, but we will be sharing that very shortly. And already, they are getting value from it. They are using it in their day to day workflows. And, also, we'll be announcing shortly various academic partnerships that we have with leading institutions as well, and they've they've played a a strong role in shaping, you know, how... Where... What is the most useful for for advancing the state of the art. [00:09:00] S0: Amazing. And and let's talk about the round itself. Right? So you raised $10,000,000. You're still pretty, like, relatively early on in the company's journey or history. Backed is backing you, Lunar, Seraphim, MMC. What gave this roster of investors the conviction to invest?