00:10:33 · Adam Miller
[00:10:33] S3: I want to thank Notion for sponsoring this episode. Without companies like Notion, these episodes wouldn't happen. They're ambitious and they cost money, and Notion backed us early. But the other way that Notion helped us is that we've literally been using the product since day one. We've been using it for media, operations, product. Within media we organise all of our videographers, our sponsors, our episodes on Notion. It's an absolute lifesaver. It's basically where our whole company operates. But the thing that was a real game changer for us was Notion AI, because our company is bigger now. We've got 25 plus people, different divisions, so there's a lot of docs, systems and structure. That's helpful, but with Notion AI, I can simply prompt something in a chat bar, so I don't even have to go into docs anymore. It's a lifesaver. Think episodes like the one you're watching today about PsiQuantum and Pete, it's really reiterated this idea to me about focus. If you want to be a standout company and do extremely ambitious things, you've got to focus on the one thing that matters. And for PsiQuantum, it's building a 1,000,000 qubit quantum computer. It's not docs, it's not administration, it's not boring paperwork. And that's what Notion allows you to do. As a founder, focus on the things that only you can do, people, culture, your product, and then let Notion take care of all the boring stuff in the background. We've got a special offer at notion.com/sachanandatom. Give it a try. I promise you, I've never heard anybody that's regretted it.
00:11:59 · Sachin
[00:11:59] S1: I think there's a really interesting analogy there, particularly with TSMC, one of the most important companies in the world, not many people actually understand how it works, and they understand that NVIDIA uses a lot of their chips, etc. I think for the audience watching, can you really clearly articulate what this world may look like in ten years? Obviously, you have dedicated your career to this. What is the use case that gets you out of bed every morning going after this problem? And what do you think the world will actually look like in ten years?
00:12:30 · Pete Shadbolt
[00:12:30] S0: Yeah, so again, to this point of these iceberg like technological capabilities, fabs are now all over the news. But even six, seven, eight years ago, nobody cared about semiconductors. Nobody cared about fabs. Most politicians, if you show them a wafer, they don't know what they're looking at. And and that was that was a trillion dollars. A trillion dollars of investment over fifty years to build that semiconductor industry. That happened in a deeply unsexy way. Nobody cared. And it, you know, gradually became this geopolitically significant world changing capability. Similarly with AI, as you guys know very well, AI was a failed field, multiple winters, defunded by DARPA, defunded by UK government, had a bad reputation as a science project that was always over promising and under delivering. People would go to... And it's it's, like, hard to conceive of today, but only, like, you know, ten years ago, people would go to AI conferences and they'd write statistician on their badge because they were so embarrassed to work in the field of AI. And it took decades of work, and it took sustained improvement of the algorithms and architectures, transformers and attention and all this stuff that we read about on LinkedIn now. And it also took people building huge GPU clusters at enormous expense. And again, prior to GPT-three, nobody cared. Somebody in that Microsoft CFO department was saying, Why are we buying all these bloody GPUs? What's this AI crap? And so quantum computing is at that stage where we haven't delivered anything yet. There are no useful quantum computers on the planet. We're spending a lot of money. We're building huge machines. There is a very strong scientific consensus that that's gonna bear fruit. But you're absolutely right. We're asking people for a challenging amount of patients. And that's kind of the nature of the beast. These technologies, again, if we think about TSMC, ASML, SpaceX, Nvidia, they all took decades to really get there. And now we're really delighted that we've gotten. And yet quantum computing absolutely has the same dynamics.
00:15:01 · Adam Miller, Pete Shadbolt, Sachin
[00:15:01] S3: Why is PsiQuantum's approach the right approach? Because there's a number of different approaches in the field that Google, IBM, different companies at PsiQuantum are doing. You've sort of got this approach of trying to build this enormous 1,000,000 qubit machine, which means that is this really long time an investment to then show this almost final product that causes technical milestones along the [00:15:22] S0: way? [00:15:22] S3: Why go with that approach? [00:15:24] S0: Because it's scientifically correct, is the short answer. So there are no known applications that are actually worth doing for small quantum computers. [00:15:38] S1: And you actually did one of first ones, right, with the API that you released? [00:15:41] S0: Yes. So you probably felt [00:15:42] S1: this visually that probably was there any good use case of it?
00:15:46 · Pete Shadbolt
[00:15:46] S0: -Yeah. So the thing is, this has been the scientific consensus for twenty five years that you need about a million qubits to make money, to have impact, to solve valuable problems, to change people's lives with these downstream products of machine. Like, that was the consensus. That's what I learned when I took my undergraduate quantum information courses at Leeds University seventeen years ago. And so, you know, it's a great question. Why did PsiQuantum take this kind of provocatively bold approach of going straight for the big machine? The answer is that the big machine is the only one that's gonna make any money or have any impact. So you gotta build the big machine real quick. And that's an unpleasant reality. I don't like that. I'd much rather make money with a small machine, but there are no useful applications for the small machines. And so I think, you know, I'm very grateful actually to my co founders and for having had that experience that you mentioned of messing around with small machines in the university. So we put the first quantum processor on the Internet at University of Bristol fifteen years ago. And for a moment, we convinced ourselves that maybe that was worth doing. Like for a couple of years, we got real excited because we had these real quantum processors running. We could run code, people could get API access. And we thought, you know, if we're lucky, maybe there's actually real impact from these small machines. And basically, we burnt out that optimism in the university. And we went and did our arithmetic again, did our homework again and said, you know what? You gotta build a big machine. And so when we founded the company, it was with this sort of violent insistence that every hour that we work, every dollar that this company spends is only gonna be in pursuit of the machine that is actually having a real impact and making money and paying our investors back. Like, that's the promise that we made when we founded the company. And it's challenging, but that's necessary. I would point, and Alex is going to stop me from doing this, but I would point to Waymo as a very analogous example. You know, Waymo had to spend enormous upfront capital, and they were very extreme. I would say they were the most extreme in terms of the, you know, spectrum of self driving car companies in saying, we're not going to kill anyone.
00:18:22 · Pete Shadbolt, Sachin
We're going to be incredibly methodical. We're going to throw every tool at the book every tool in the book at this. LiDAR, you know, enormous teams, capital, the whole thing. And, you know, they were doubted for a long, long, long time. Even when they were doing demos, driving the thing around, people would laugh at the prospect of them pulling this off. Now if you've sat in a Waymo, you know, like, they're coming for every major city in the developed world. And and, you know, that that was the right strategy. They understood that a half self driving car isn't worth it. It's to real be thing. Yes, quantum computing just has the same dynamics. [00:19:06] S1: So you mentioned that going after the 1,000,000 qubit computer is the most scientifically rigorous thing to do. Why approach it with photons? Obviously, there's a lot of smart people in this field that don't think that's the best approach. What's the secret you guys know about this that others don't?