The Exchanges

Q there's a common sense About what a computer is. It has to have memory. It has to have networks. It has to have storage. It should be able to read and write, but there's a programming model associated with computers. I wonder if it's just a wrong mental model. What do you think about the positioning of quantum as it's evolved through time and how should it be labeled today?

A I think that Jensen's, um, use of the word instrument is very well, um, is, is very sensible, and it, it's, uh, it's pretty instructive, actually. Um, When people think of computer, like the average person, they think of laptop, cell phone, something like that. Um, the, the applications of quantum computing are similar to the applications of high performance computing. They're about seeing into the future or about seeing into some system that you otherwise can't access. And so thinking about a, Quantum computer as a telescope or a lens or an instrument or a measuring device or something. That's a very helpful analogy just to differentiate from PowerPoint and Microsoft Excel and TikTok, right? Like it's really got nothing to do with that stuff. Uh, although TikTok would be really, quantum TikTok would be really good. Um, but, uh, yeah, so I think, I think that's, that's, I like, and I, I've said before, I've said earlier, I really worry that CEOs of this, these, these hyperscalers and, um, leadership of, you know, here in Silicon Valley, I worry that they're going to get completely detached from reality on what quantum computing is for. And I've actually been honestly pretty impressed that they know you need about a million qubits. They know you need error correction. They know that it's not for PowerPoint and Excel. They understand, you know, these guys have got 20 other things…

AI assessment note: “thinking about a, Quantum computer as a telescope or a lens or an instrument”

Q With this round, what was the process like and who are the investors involved?

A We're obviously, uh, firmly in the deep tech, uh, regime as a company. Uh, we've been around for a decade, so I've, uh, learned a lot about fundraising and so on in the Valley, uh, over the last 10 years or so. I don't think it was a pretty, particularly unusual fundraise, really. Um, we've had, so BlackRock, Bailey Gifford, Tamasek are all involved in the rounds, and then we have a bunch of new investors also coming into the rounds. Um, but a lot of familiar, uh, names from, from Silicon Valley, and then also some maybe slightly surprising late stage crossover type money that's coming into this, this funding round. I think it's nice to be doing it in a context where, you know, a decade ago when I said the words high performance computing or supercomputer, or talked about a building sized machine, 10 years ago when people were doing apps, like that was a deeply unpopular thing to talk about. HPC is like from the eighties, like don't talk to me about supercomputers. Um, but of course now we're doing that in a context where building a megawatt, uh, supercomputer is like child's play and people are much more excited about hundreds of megawatts and gigawatts and whatever. So to be doing that, you know, surrounded by the current excitement and also the kind of Understanding and comprehension of these big AI systems has been pretty helpful to our, to our process, yeah.

AI assessment note: “BlackRock, Bailey Gifford, Tamasek are all involved in the rounds”

Q Well, I thought that was a really, I thought that was a really good point. It's like, so what do you tell your team like in presentations and everything?

A Oh yeah. Just be, I mean, like, I, I'm not, I, I don't, you know, I don't have any wisdom on managing people. Uh, but, uh, my, my refrain endlessly is, is to be impressive. Like people ask, And it's a little bit to Ashley's thing in quantum computing, you get all of these founders, they all show up and they all think that their way is the only way to do it and sling mud at everybody else. Everything else is crap. Um, uh, like, you can't win that game. Like, nobody wins in that game. Uh, somebody walks out of that meeting completely convinced that the photon is the right way to build the qubit, and then they'll go and meet with the ion trap people, and the ion trap people will talk about nature's perfect qubit and all-to-all connectivity, and you'll walk out of that meeting saying, what was Pete even talking about with these photons? It's really ion. It's the God's gift to quantum computing, and so on, and so on. And I'm sympathetic. It's terrible for For people on the other side of that bouncing around between these various different sales pitches. Um, and so, yeah, like, like the sort of turn of people focus so intently on the turn of phrase or the PowerPoint slide that's going to win the deal or whatever. And I think it's more like you can tell if people are sincere and impressive and like for real, and if they've done things that they said they were going to do. And so I try…

AI assessment note: “my refrain endlessly is, is to be impressive.”

Q Company that is publicly traded. He just recently started a new company to take advantage of the new architectures. So how do you feel about that?

A Yeah. So I have a, PsyQuantum is pretty contrarian on a few things. Like my life over the last decade probably would have been easier if I had just taken that chip I had in Bristol, put it online and made it available to people and then tried to raise money off of that. Um, uh, instead we said, no, you need to go straight to a million qubits and I need a billion dollars to do it and so on. I'm also pretty contrarian on this AI stuff. So I think probably there's a good fraction of this audience who would love to hear me say, Thanks to AI, now we can have the quantum computer much sooner. You're going to clip that. I know you are.

AI assessment note: “PsyQuantum is pretty contrarian on a few things. [...] I'm also pretty contrarian on this AI stuff.”

Q What would be the main value drivers of potential customers, and who are your customers now?

A I think it's helpful just to think about what is currently done with conventional computing and especially what's currently done with AI. When I look at language models as an outsider, I see those language models sort of consuming territory really quick, right? Like they're getting stronger and stronger and they're starting to take over things that people have been doing either with human beings or with Regular computing at a very fast rate, but we also know there's a limit to that. Like that kind of expansion of territory will stop at a boundary where the stuff on the other side of that boundary is for us from my point of view, right? Like we're going to go after the stuff that people don't do with language models, et cetera. And as far as we're concerned, the low hanging fruit is really materials and chemistry. Uh, that's where our, so we have about a 50 person applications team who engage with car companies, materials companies, energy companies, et cetera, um, to prepare them for the existence of that big machine. And a lot of that work is on small molecule drug discovery, uh, catalysts, uh, basically small, uh, hard molecular or like reaction chemistry, material science problems. When you talk about quantum computing, people sort of tend to list the same categories of application. And that's one of them. They often talk about optimization problems. They often talk about qu…

AI assessment note: “we have about a 50 person applications team who engage with car companies, materials companies”

Q You've definitely got some support from the public side and government, but has the public side been overall very supportive to this industry?

A Yeah, so I think sometimes people are surprised to see, like, BlackRock and Bailey Gifford and people like that on our, on our cap table. Obviously, like, those guys, that category of late stage crossover type people, they were in SpaceX, they were, they were in NVIDIA, they were in ASML when ASML was pretty, uh, crazy. Uh, prospect. Um, uh, and again, like just look at that list of companies. Like it's not, I don't think it's as surprising as people make out. And with quantum computing, like there is this sort of additional mystique. Every time you talk to people, they say they kind of give up before they've even started, right? Like they say, oh, quantum computing, I can never understand this. It's just crazy. Spooky action at a distance and so on and so on. I'll never understand the physics. I can't engage. When I talk to people like that, I sort of like to, um, like my co-founder particularly likes to make the point that if you go to the average technology conference, you'll find thousands of people who are very comfortable talking about GPUs and, you know, transistors and three nanometer and so on and so on. And then you ask these people, okay, like you love AI, you love computers, you love GPUs. Please get on the whiteboard and explain to me how a transistor works. Like talk me through Fermi levels and electron hole pairs and the physics of a transistor. And it's like hop…

AI assessment note: “people are surprised to see, like, BlackRock and Bailey Gifford and people like that”