Quantum in Action: Insights and Applications with Matt Kinsella

Daniel Newman:
Hey everyone. Welcome back to the Six Five Summit. Daniel Newman here, CEO of The Futurum Group. Very excited to have you here with us. Thanks so much for tuning in. It’s been a great event and we have another great conversation coming your way. I am joined today on the quantum track by Infleqtion CEO, Matt Kinsella. Matt, welcome. First time Six Five Summit. Great to have you here.

Matt Kinsella:
Daniel, great to see you again and thanks for having me. I’m really excited.

Daniel Newman:
Yeah, it’s a really fascinating track. I know it’s been the years of AI, but quantum is fast approaching and I think it’s a great session in the conversations we’ve had in the past and tracking and following what Infleqtion is doing. Great opportunity to have a conversation about quantum and it’s real world applications where it’s at right now, because of course sometimes people mistake quantum as like, oh, it’s cool, but it’s like 10 years out. Well, Infleqtion is a company that’s been very adamant that no, it’s not. It’s here today. There’s commercial applications, there’s things that people can buy. Talk to me about that. For years we have been talking about this. I think you like to frame it a bit differently to help people understand where are we with quantum right now.

Matt Kinsella:
I find it helpful to think about quantum in phases, and so we are squarely in phase one of what I’d call the quantum revolution and the dates all the way back to the early 20th century. We don’t need to go to the history of quantum mechanics and how this was all discovered, but we’re just using the near past as our guide. We are in phase one. Phase one I view as quantum sensing, and phase two is quantum computing. As you pointed out, phase two quantum computing has always seemed like it was a rolling five or 10 years in the future. It may very well be, there are reasons to believe with some of the new error correction data that’s come out more recently that it may actually now be the real definable five-year time period before we enter phase two in earnest with quantum computers that can do things that you or I or anyone at this conference would say, oh my gosh, that’s amazing.

We aren’t there yet, but where we are is in phase one where we have reached quantum supremacy for a number of various sensing applications. So Infleqtion focuses on both phase one and phase two, and so we’re building for phase two, but we are selling products in phase one today, namely timekeeping devices as well as radio frequency sensors.

Daniel Newman:
All right, let’s dive into that a little bit. You gave a really good analogy, I think, for people with telling the story of where we’re at comparing it to. I think we could compare it to some of these different compute phases that have come out. This in particular with quantum, and then you drove in this idea that we’ve got the sensing phase and then you’ve got the computing phase, but you also, as I alluded to, you are firmly of the belief that there are near term quantum applications. Talk a little bit about what those are. What are the sensing applications? What are the things that people can do today? What are the market opportunities and impact that this is going to have that you see for Infleqtion?

Matt Kinsella:
When a lot of people hear the word quantum, they assume the next word that follows is compute. For a long time I thought that as well. What I didn’t realize was that there were all sorts of applications and use cases that the amazing things that you can do when you can precisely control the quantum phenomena that allow for quantum computing. Those can be used to do other things and those things are here today.

So one of them would be timekeeping. You might say, huh, timekeeping, how interesting is that? Well, it’s actually pretty darn interesting. Let’s talk about some use cases. If you think about GPS, what is GPS? It’s a number of things, but at its core, it’s a time distribution system. What you can do with quantum clocks is you can keep time orders of magnitude more precisely than the existing atomic clock standards that a lot of what GPS is based on today.

So really the use cases here are from a military perspective, being able to have a redundant system in the case where you may be in an environment where GPS is denied. So if you were to go to any hot war today, if you go to Ukraine, if you were to go to Israel, you would find that GPS doesn’t work like it should, and that’s because it’s being spoofed or it’s been shut down entirely. If the US were to find itself in a hot war, we would have to be navigating a world in which we likely wouldn’t have GPS. So if you could put timekeeping, highly accurate timekeeping devices on your assets locally, you could be in a redundant environment for GPS. So that’s something the military is highly focused on, and that’s one of the use cases that is a large part of where we supply our product to. So our biggest customer is the DOD today.

Now, there’s also other commercial use cases. I’d mentioned data centers use time to synchronize how workloads are done. As more and more pressure is being put on data centers because of the training of AI models, because of all the inference work that these data centers need to do, and because of the shortage of GPUs out there, people are trying to figure out how can we eek more performance out of our existing infrastructure. One of the ways to do that is by having a much more finely grained definition of time. So if you can chop your workloads up into smaller and smaller bits and then share them across all of your servers within your data center and then share those across data centers as well, using a master clock to act as the conductor of all of that movement, you can actually gain a lot more efficiencies out of your existing data center assets. So we’ve sold Tiqker, our first product, to some of the cloud scale vendors for that very use case.

Daniel Newman:
Yeah, it sounds like you have a really compelling out the gate opportunity in defense. So that sounds like… And by the way, it sounds like you’ve already commercialized, you’re already driving revenue in that particular space. I see some other great examples that we could probably point to in things like commercial transportation. So in fact, I believe, aren’t there parts of the world that are looking at actually using PNT or focused on PNT for commercial travel, commercial flights, commercial aviation?

Matt Kinsella:
Very much so. It often will come down to we have a system today and we have GPS and it works well, and so people aren’t jumping to get rid of that system. That said, we are seeing more and more examples where commercial aircraft are experiencing GPS spoofing or GPS denial as they fly over territories where that might be an issue.

So actually just a couple of weeks ago, Infleqtion alongside our partners in the Ministry of Defense flew our Tiqker device up on an aircraft where it experienced turbulence, it experienced takeoff and landing, a lot of bumps and a lot of movements. Our device today is about the size of three pizza boxes, call it. It’s called a 3U. It sits inside a server rack. So that was on the plane and it kept time better than GPS during that flight trial. So why that’s really exciting is because if a plane were to find itself in a GPS spooked environment, which many pilots in the interviews done around this last couple of weeks ago, many pilots have found themselves in those environments. Having a system on board that could act as a PNT, a position, navigation and timing system, in the absence of GPS is a very handy thing to have. Ultimately, as this technology gets better and hardens it can be much more accurate than GPS because it is local. That’s what we’re working towards with our broader PNT vision. Now, when you think about PNT, I only referenced one, which is T, timing, right?

Daniel Newman:
Position, navigation, timing, for those of you out there that are-

Matt Kinsella:
Exactly, so our Tiqker clock is just the T in that system, but there’s a process known as dead reckoning where you’re basically, if you know where you were and you know which direction you’ve gone and you have a highly accurate precision view of time, you know where you are. So that’s where this holdover is really important from a GPS null environment, you can use dead reckoning until you get back into a place where you can have a GPS signal.

Daniel Newman:
Yeah. You can get quickly lost in the weeds here. But I think the zoom out scale is that these are applications that are very important. They’re difficult, and quantum is uniquely positioned to support the improvement in reliability and of course critical need for some of these areas. Now let’s go back, let’s think more broadly about this. The company has been heavily focused on commercial readiness. I worked with you prior to your appointment since your appointment, and that has been a consistent idea within Infleqtion, and you’ve doubled down on this since the first time we’ve had a conversation. Talk a little bit about the commercial readiness, building out the ecosystem and supply chain and how all these things tie together as it pertains to quantum.

Matt Kinsella:
So Infleqtion’s history goes back into academia, and there were several Nobel Prizes won on how to trap and control atoms in a very precise matter by hitting them with lasers that were tuned to the exact frequency that those atoms respond to. So there were Nobel Prizes won in the 90s. Nobel Prize won in the 2000s. Our history is rooted in academia and research. I’ve really been focused on taking Infleqtion from that research phase into the production phase. That means building products that you can repeatedly create that have warranties, that have user manuals, all the things you’d expect for a hardened product. So I view the event that we were just talking about as a big step forward for Infleqtion because we have a product in the form of Tiqker that is sturdy enough to go up into a plane and withstand turbulence, withstand take off and landing, perform better than the global standard of GPS, and can be in many other environments, can be put onto a Humvee and bumped, bounced around. It can be put on all sorts of moving vehicles.

So I view Tiqker really as our first product, and that’s very different than a project or something, a prototype, something that you can build one of. This is something that now it’s on the truck and we can sell it. If I think about the market opportunity for quantum, I think I used this analogy to you before, but I view an exponential curve. At the beginning of that curve, actually I have one of them right here, is our glass cells. Everything we do comes down to one of these vacuum cells and this allows us to trap atoms inside of this cell, remove any external forces that may be disrupting the quantum state, and then we hit those with lasers and then we can then precisely control them. So that’s the core of everything we do. At the other end of that curve is quantum computing.

Along the way there’s cascading curves that come along. The first one is timekeeping, like we just talked about. That curve is in and of itself a very large market opportunity to address which we are addressing with Tiqker. The next one is RF. So our next product will be called SqyWire. It is an RF antenna that can pick up all frequencies across the spectrum instead of having to utilize a very dedicated antenna for getting AM radio versus high frequency signals. Then ultimately there’s that big pot of gold at the end of the rainbow, which is quantum computing.

Daniel Newman:
All right, Matt, so I’m going to throw you the money question here. This event is AI Unleashed at the Six Five Summit. We’re talking quantum, we’re talking sensing, and of course I can always make sensing into data and data into AI. But I want you, we’ve got a couple of minutes here, to give me the way you would tell a story about the relationship that exists between quantum and AI. What are the realistic synergies that people might be able to get from this?

Matt Kinsella:
There’s two off the top of my head. One is straightforward and one’s a little more out there, which is probably what we’re looking for here. So I’ll do the straightforward one first, which is clocks. I already alluded to, but we can flush out a little bit more. Highly accurate clocks that are orders of magnitude more accurate than the existing standards can help you just eek lot more performance out of your infrastructure, which allows you to better train and then use better inference on LLMs, which is a big problem for everybody today. So there’s just the practical enabling use case of having better clocks within your data center.

Probably a more fun answer that I can give you is how quantum computing may intersect with AI. So if you think about what the basic building block of a quantum computer is, it’s a qubit, right? It’s the quantum analog of a binary bit in our classical computers. In classical computing, these bits can be zero or one. It’s the presence or lack of presence of a current. Then you can use that to do all sorts of logic, right? There’s basic logic gates and/or.

A qubit’s different in that instead of zero or one, it can be zero and one or anything in between. There’s a lot of other really interesting idiosyncrasies about qubits as well. One of them is that they have memory. So when a quantum processing unit, or a QPU, processes a qubit, the qubit actually can keep track of context and they’re called context clues. That’s essentially what were other qubits doing while I was being processed? This property is called contextuality. There’s several applications that you can utilize contextuality for, and one of them has to do with large language models. So context clues are actually one of the fundamental bottlenecks to scaling large language models. So let’s think about as sentence like Daniel died laughing. It’s really important that the context window for that LLM gets all those words, right? Because it can be very different if it was just Daniel died versus Daniel died laughing.

Daniel Newman:
You put the comma in the right place.

Matt Kinsella:
That’s right.

Daniel Newman:
[inaudible 00:14:53] not at all, right?

Matt Kinsella:
Exactly. So that context is just highly, highly important. Now where there’s three words, that’s not that big of a deal, but when that scales up to millions and millions of words, because the LLM needs to have the context between each word pair, that scales exponentially. Becomes a big, big challenge. Which is why you can drop PDFs that are certain links into ChatGPT and have it summarize that for you, but there’s only a certain link that it can abide by.

So what contextual machine learning allows you to do is that, because of those context clues, it can enable much more efficient processing of those large context windows. So rather than needing to explicitly capture every pair, we find that qubits, through that contextuality, can actually natively model those large context windows much more efficiently. But here’s where it’s really, really interesting is that our software team has discovered that that property can be achieved not just on QPUs, but also on GPUs if you use software that causes those GPUs to act like quantum processing units. So this led to the development of our contextual ML software product, which is an advanced technique for tracking those context clues in data sets. So here where we are today in phase one, before we have really well-working quantum processing units, we can do it with GPUs, and then in the future we can do that with GPUs.

Daniel Newman:
Yeah, that’s pretty cool. I’ve seen a little bit of that with what we’ve seen some of the cloud providers offering simulation of quantum in the cloud or access to quantum in the cloud. Some different ways that you can start to play with quantum using classical computing interfaces is super important. Hey look, Matt, it’s been great. Unfortunately we’re at time. We got to do this again. Talk more about how things are progressing. I can’t wait to come back, check out what Infleqtion is doing, watch the growth. Congratulations of course on your recent appointment to CEO and really appreciate you joining us here at the Six Five Summit.

Matt Kinsella:
Thanks, Daniel, it’s great to be here.

Daniel Newman:
All right, everybody, you heard it here, Matt Kinsella from Infleqtion. Interesting conversation on quantum. We got into the details, how money is made in quantum, but we also talked about the future and how it ties together with AI. But I’m going to send it back to the studio. Stick with us.