00:16:06 · Sebastian Johnson, Alex Higginbottom
[00:16:06] S0: That's amazing. And it's a... It has... You've got some... You you... Yeah. You've got some great great investors. As... So now what's next? You know? What is the immediate thing? Right? Like, you've this model released. You've got some exciting news coming out. You know, what is the next priority for you? [00:16:22] S1: Yeah. Well, as I said, we're we're still gonna be always improving the model. So, you know, there's obviously... This is a massive step for us and for the world with this model that we're releasing next week, but it'll get better the next month, get better the next month, increasing the scope, increasing the fidelity of what we can do. A huge goal is is in... Is closing this into real gap as well. That's a kind of a large objective of ours. So that is one branch. And then now we really are in a in a great position to get this in the hands of customers. So, you know, working with a select few customers in fusion and in semiconductors in particular on on how this can accelerate their workflows today. [00:17:08] S0: And what does it look like for semiconductors? I think with with fusion, I kind of have a clear view of the impact that that can make. To your point, Amanda, like, so many different sort of parameters or data points that can be slightly adjusted and build slightly adjusted. What does that look like for for semiconductors? What what is The UK... Use case for them?
00:17:08 · Sebastian Johnson, Alex Higginbottom
[00:17:08] S0: And what does it look like for semiconductors? I think with with fusion, I kind of have a clear view of the impact that that can make. To your point, Amanda, like, so many different sort of parameters or data points that can be slightly adjusted and build slightly adjusted. What does that look like for for semiconductors? What what is The UK... Use case for them? [00:17:24] S1: Yeah. So that's a great question. We've seen a lot of progress in AI for design of semiconductors. So, you know, this is... NVIDIA have done some work here in Synopsys and and and some very good strong start ups. But really, you know, we have not seen that much work on the manufacturing side, which is just as big. It's got something like a, you know, a a multi trillion dollar market cap for, you know, companies like of TSMC, Applied Materials, and Research, like, all of these massive manufacturing companies. But they have an equally hard problem almost as we have in fusion where etching out these wafers and and constructing these wafers is getting incredibly complicated. You know, the the CTO of Lam Research gave a speech a couple of years ago where, you know, we're now at a 100,000,000,000,000 different ways that you can make a wafer, and plasma is a huge part of that. So if we want to continue to have better chips, you know, scale AI, then we need much, much, much better ways of building these chips, and that's where we're really excited.
00:17:24 · Alex Higginbottom, Sebastian Johnson
[00:17:24] S1: Yeah. So that's a great question. We've seen a lot of progress in AI for design of semiconductors. So, you know, this is... NVIDIA have done some work here in Synopsys and and and some very good strong start ups. But really, you know, we have not seen that much work on the manufacturing side, which is just as big. It's got something like a, you know, a a multi trillion dollar market cap for, you know, companies like of TSMC, Applied Materials, and Research, like, all of these massive manufacturing companies. But they have an equally hard problem almost as we have in fusion where etching out these wafers and and constructing these wafers is getting incredibly complicated. You know, the the CTO of Lam Research gave a speech a couple of years ago where, you know, we're now at a 100,000,000,000,000 different ways that you can make a wafer, and plasma is a huge part of that. So if we want to continue to have better chips, you know, scale AI, then we need much, much, much better ways of building these chips, and that's where we're really excited. [00:18:32] S0: And and if this goes well, what what would be the larger impact in the... In, I guess, the entire supply chain, the entire market? Would it be cheaper, faster? What does that look like? [00:18:44] S1: Well, you know, Moore's Law is bending, and our mission is to keep Moore's Law or the equivalent of Moore's Law going throughout the rest of the century. We want to continue the pace of exponential innovation that humanity has been on. And to do that, we need new tools. So that's that's really our mission.
00:18:44 · Alex Higginbottom, Sebastian Johnson
[00:18:44] S1: Well, you know, Moore's Law is bending, and our mission is to keep Moore's Law or the equivalent of Moore's Law going throughout the rest of the century. We want to continue the pace of exponential innovation that humanity has been on. And to do that, we need new tools. So that's that's really our mission. [00:19:05] S0: Amazing. Well, look, thank you so much for taking time to chat with me. This is amazing news. Super exciting. I love to see sort of, like, frontier technology being being built out of Europe. This is about, like, Europe has actually got such a big advantage, especially with our huge sort of industrial history datasets. Phenomenal talent. And so, look, thank you very much, and congratulations. [00:19:25] S1: You so much, sir.