In this exclusive interview in theCUBE + NYSE Wired’s Mixture of Experts series, Infleqtion CEO Matt Kinsella sits down with John Furrier to reveal how quantum is shifting from research to commercialization as the company prepares to go public with Churchill Capital X. Kinsella explains why quantum leadership is a must-win global race, where Infleqtion already holds an edge with sensors and how the path to 100 logical qubits will unlock new computing breakthroughs. He also highlights partnerships with NVIDIA, the commercialization of clocks, RF antennas and software products and the energy efficiency of Infleqtion’s neutral atom modality that’s enabling field-deployed solutions today.
Kinsella and Furrier discuss how quantum will integrate with CPUs and GPUs in data centers, creating new possibilities in material science, drug discovery, national security and beyond. Kinsella also shares exclusive insights into encryption risks, GPS timing vulnerabilities and the enterprise and government stakeholders who must prepare now for the post-quantum future.
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Matt Kinsella, Infleqtion
Alexander Gallego, founder and Chief Executive Officer of Redpanda Data, discusses the company's recent developments and strategic positioning at the forefront of data streaming technology in theCUBE's "Mixture of Experts" series, filmed at the New York Stock Exchange.
In this insightful episode hosted by Dave Vellante, co-founder and co-Chief Executive Officer of SiliconANGLE Media Inc., Gallego shares the latest updates at Redpanda Data, highlighting its Series D funding led by Google Ventures. The conversation delves into the challenges and innovations within data streaming, as well as Redpanda's position in the market, particularly through its significant partnerships and technological advances such as the rollout of Apache Iceberg.
Key takeaways from the discussion include Redpanda's strategic milestones and growth, as highlighted by Gallego. Notably, Redpanda now powers the New York Stock Exchange's cloud data feeds, underscoring its capability in mission-critical environments. Furthermore, the conversation addresses the shift from batch processing to real-time streaming, an essential change driven by new capabilities in AI and the innovative use of data for business process improvements, which Redpanda enables, as Gallego explains.
In this exclusive interview in theCUBE + NYSE Wired’s Mixture of Experts series, Infleqtion CEO Matt Kinsella sits down with John Furrier to reveal how quantum is shifting from research to commercialization as the company prepares to go public with Churchill Capital X. Kinsella explains why quantum leadership is a must-win global race, where Infleqtion already holds an edge with sensors and how the path to 100 logical qubits will unlock new computing breakthroughs. He also highlights partnerships with NVIDIA, the commercialization of clocks, RF antennas and s...Read more
exploreKeep Exploring
What recent developments have occurred regarding a company's plans to go public and its involvement in quantum technology?add
What types of products are being developed with quantum technology and what is the current status of quantum sensors compared to classical technology?add
What is the fundamental premise of quantum computing and how does it differ from classical computing?add
What is the anticipated role of quantum processors in future data center architectures and their relationship with CPUs and GPUs?add
What recent advancement was made in the application of logical qubits and GPUs in material science?add
>> Hello, I'm John Furrier with theCUBE. We are here at our New York Stock Exchange Studio on the East Coast of the NYSE, part of the NYSE Wired program and community. This is our mixture of expert series. We've got a great guest talking quantum. Very timely conversation as the world gets ready for quantum. Quantum Readiness Day is actually tomorrow around the world as a top scientist and businesses prepare for the quantum changeover upgrade revolution, whatever you want to call it. Matt Kinsella, he is the CEO of Infleqtion. Big news as well going public with Churchill Capital X. Matt, thank you for coming on theCUBE remote from Colorado.
Matt Kinsella
>> Thank you, John. It's great to be here. I'm excited for this.>> Well, I'm super excited to chat with you. One big news, you guys are going public. I saw that on your LinkedIn. I saw the press release. Quantum is not supposed to happen for 10 years. What's going on? Of course, everyone has walked that back three years. NIST is doing great work. The world is getting ready for quantum. As it starts to emerge in the scene, you guys are commercializing it. Give us the update on the big news and what you guys are doing.
Matt Kinsella
>> Well, we chose to go down this path because it is clear to us that quantum is indeed at an inflection point, well, pun intended, and no pun intended. And this is a global race, John. It's a global race and the stakes are very high and it's one that we at Infleqtion view and the US views is a must win for the country. And so right now, the way I see the world playing out is really in two distinct buckets. When we say quantum, we're talking about the world of the very small and taking advantage of the very strange things that happen down at that atomic and subatomic level and then harnessing those quantum mechanics and then using them to build products. And most of the time when we talk about what products are we building with quantum, we're talking about computers. And as you referenced, quantum supremacy and computing is sometime in the future, but getting closer. There's a whole other class of products that can be built utilizing those strange and wonderful quantum mechanics called quantum sensors. And we have quantum advantage today in those sensors. And those sensors can range from clocks to RF receivers to inertial sensors. And quantum already provides between 10x and 1000x improvement in performance over classical standards. So to answer your question, on the sensing side of the quantum world, we're at quantum advantage big time already. And then on the computing side of the world, it's relatively widely believed that we will have some form of quantum advantage in a quantum computer in the three and a half year timeframe. And it all comes down to logical qubits, which I'm happy to talk about. And we've shown logical qubits and we just need more of them, and it's 100 logical qubits where we can start to do interesting things.>> It is very interesting. There's a lot of misunderstanding around quantum. So I'd like you to explain, because most people think quantum is like a computer, it gets shipped in a box or it's a big data center, super computer. Your mind kind of goes there. It's going to break all the keys on cryptography when actually it's a multi-step process. Explain the quantum supremacy race and the progression of the science, the technology. Because if you go back even a few years, even last year, so much has changed and it's like little wins that become big wins over time. Take us through the progression of what is quantum computing.
Matt Kinsella
>> The fundamental premise of a quantum computer is the following. Even the most powerful GPU cluster or super computer based on classical computing is ultimately boiled down to the flipping of transistors and zeros and ones. And it's all based on that binary logic. And what we've been able to do as humanity based upon that very simplistic binary, yes, no logic is astounding, but it's not how nature fundamentally works. The way nature fundamentally works is via quantum mechanics. And so what quantum computing does is harnesses the power of nature, how it actually works and turns that power into products ranging from sensors to computers. So what does that mean? We talked about these strange and wonderful things that happened down at the world at the very small. You may have heard terms like superposition or entanglement. What we're doing is taking advantage of those and being able to really control them for the first time ever as humanity and point them at problems. And so for things that work like nature works, for instance, the discovery of new materials or the discovery of new drugs, that is the type of problems that quantum computers are very uniquely suited to solve because you're not using a zero in one binary heuristic. That's not actually the way the world works trying to solve them. You're solving them in the way they actually work. And so that's the underlying principle of quantum. And your question on the history, I mean, this goes back to the late 19th century when quantum mechanics was just starting to be discovered by humanity. And some people, including Einstein, didn't necessarily believe it. They thought it was just too wild to actually accept to be true. And Einstein famously called entanglement spooky action at a distance. He thought this just can't be possible. And so to answer your question is taking advantage of the fundamental building blocks of nature and turning those into products, that's what quantum is.>> The market opportunity is huge. I mean, think about the use cases that quantum can go after. And again, the small binary mind would think, "Oh, yeah, I'm processing a bunch of processing." You think GPU, you think CPU, but quantum is different. Explain the relevance of the use case targeting you mentioned because it is different. So some things are going to be really immediate and some won't. How should people frame the scope of quantum I'll say from a use case standpoint?
Matt Kinsella
>> If I think several years into the future, the way I envision the data center looking is just as GPUs sat on top of CPUs to enable new use cases that we could do from a computing perspective. Quantum processor units or QPUs will now be layered increasingly into the data center, and workloads will be sent into the data center and then provisioned off to the appropriate level of that stack to the computing modality that's best suited to solve it. And so I don't foresee quantum computers necessarily eating into GPUs or even CPUs market share. It's going to be expanding what we can do and starting to allow us to do those types of applications that I mentioned like material science, drug discovery, things we just have never been able to really point classical computing at. And they'll work in tandem with GPUs and CPUs. And so you can think about it as just another tool in the data center toolkit, for lack of a better term, that allows us to do a broader range of things. And those things are kind of everything. And so like you said, the range of things we can point quantum computing at is going to be absolutely massive.>> You mentioned at the top about it's great for our country, the supremacy angle. It's kind of like a space race. If you look at the space race, what that enabled, what the discovery came out of that was incredible. You mentioned life science, application, material science, life sciences. These are areas that you're starting to see GPUs nip into a little bit, because they can.
Matt Kinsella
>> Yes.>> This is where quantum shines. So I'm sure you have lots of commercial activity going on around government contracts, life sciences. Can you share some of the momentum with your business as you guys start to commercialize the quantum race or the start line if you will, however you want to call it? I mean, still early innings.
Matt Kinsella
>> Yeah, let me talk about three examples that actually are a good example from each of the pieces of our business and we cover a very full spectrum of quantum. So let's start with computing. Back in December of last year, Infleqtion alongside Nvidia announced the first time a material science application had ever been run on a logical qubit. And we did that alongside NVIDIA's GPUs. And so this was an application called the Anderson impurity model, which is a very basic photovoltaic application. And so think of it as a precursor to what we might be using to develop better batteries over time. And this is something that couldn't have been solved on a GPU itself or on a QPU itself, but working in tandem it could be solved. And so you can imagine, as the QPUs get more and more powerful paired up with GPUs, that's a great example of how we'll be discovering new materials, making better batteries, discovering new drugs in the future. So there's an example of just how you see quantum starting to layer into the existing data stack. So there's one commercial example. Commercial example number two is software. So we've been writing software for our quantum computers and it turns out when you write software for our quantum computer, you have to write it quite differently because you have to code around some of the laws of quantum mechanics. There's things that are present in the quantum realm that aren't an issue when you're writing software for traditional computers. For instance, there's something called the no cloning theorem. You can't copy and paste quantum data. Copying and pasting data is a very big part of classical computer software writing. So when you architect the memory, you have to work around these things. It turns out when you apply that quantum software to GPUs, it actually enables some pretty incredible new use cases specifically around the enlargement of the context window, and that's one of the fundamental blockers of scaling GPUs. And it's really kind of like the memory of a GPU. Can it remember what happened 10 seconds ago, two days ago, 10 years ago? And so applying this quantum software to GPUs allows that context window to be expanded. And what we've pointed that out in the first case, and this gets to the national security use cases is with contracts with the Army and the Navy for very interesting use cases with the Army, it's ingesting massive amounts of multimodal sensor data onto NVIDIA Jetson GPUs, which are field deployed small form factor GPUs and making sense of all that data that could never have been done locally on the edge. And so that's a huge performance advantage. And then number two for the Navy, ingesting huge streams of RF data that again would not be able to be processed by traditional large language models. So kind of quantum advantage pulled forward to today via software.>> I love the NVIDIA tie-in. One of the things we've been covering with NVIDIA is physical AI, a term that they talk about a lot. You mentioned the relationship there and working with them. The convergence of some of these software problems at scale opens up digital twins, opens up in ability to ingest data, solve big problems. Starting to see NVIDIA getting into things like automotive, life sciences, a lot of needle moving stuff on the GPU side. And when you look at NVIDIA, it's like a monster supercomputer, the super chip. They've got the Blackwells, they've got all the technology. The question is on quantum, is there modalities that you guys can run in that can go to save the edge, or is it like a big room with a quantum computer? How does the sensors and some of these advances get deployed today? And how do you see that evolving? Because you can have centralized machines, these supercomputer clusters, large AI factories, computing centers, and then you also got real world with sensors and some of the quantum. How does that translate? How do you guys see that evolving? What are you seeing where the traction and momentum is today?
Matt Kinsella
>> So the answer will depend, John, based upon the underlying quantum modality, and we don't need to get into the specifics on the modalities, but let's just focus on our modality, because this is the one I'm most familiar with, which is neutral atoms. Neutral atoms are a very energy efficient quantum modality. We run our quantum computers on the equivalent of six hairdryers. And so while you're seeing nuclear power plants be fired back up to run AI data centers, we can do a lot with a very small amount of power. So there's one key ingredient to being able to remove this from the big, big data center environments. Number two is, as I said at the beginning, when we talk about the world of quantum, we're talking about the world of the very small. We're also always talking about the world of the very cold. And the world of the very cold, because those strange phenomena down at the quantum mechanical level are very fleeting in nature. And so they disappear if they get interfered with by all the noise in the world. So you have to remove that noise. And a great way to do that is by freezing them. But that will occasionally make quantum really only good to reside in the data center, because you need a big freezer to freeze them. But if you think about what frozen is fundamentally, it's the lack of motion of atoms. And so what's so unique about our approach is we freeze our atoms by holding them in place inside ultra-high vacuum cells with lasers such that they move so little that they become the coldest place in the known universe, exhibit their quantum properties, and then we can take advantage of them and build products. So that allows us to shrink our technology to cost our technology down to field deploy our technology. If you look at our clock today, we've taken something that used to be the size of a room and we've made it into the size of, call it, a three pizza boxes. So a three U rack-mounted form factor. That'll soon be 1 U, so one pizza box, and then ultimately it'll be chip scale because everything we do is based upon photonics, electronics, and then a little vacuum cell. And so that can all be shrunk and ultimately field deployed. So right now, we have quantum products that are out in the field, that are ruggedized and moving around, and I think that's the path all of our products will follow.>> That's awesome, and that's a huge accomplishment. I wanted to bring that up, because that can illustrate where this is going. Talk about the business now and some of the challenges you have, problems you're solving. There's a lot of young folks coming out of the market, out of school. They love to work on hard problems. Quantum is one of them. How do you hire people? Is it quantum? Are you looking for certain people? I mean, what does it take to be a quantum engineer? What do you guys look for in the makeup of candidates to hire and to build out this next wave?
Matt Kinsella
>> Well, quantum physicists are a big part of our workforce as you'd imagine. They have to understand all those strange and wonderful things that we take advantage of and they are a bottleneck. I think the US has been doing a better job of promoting STEM over time, but we don't graduate that many quantum physicists a year as a country. And so we make sure we hire our fair share of those great quantum physicists and then also have offices in the US and Australia, close US allies where they graduate a lot of quantum physicists as well. But there's many more jobs that need to go into making this work. And so just engineers and you have to engineer these systems, you can understand the physics, but you have to put them into products that work. And you need technicians, you need sales folks. And so there's a whole range of types of people that will work and are working in the quantum companies today, but at the core of it all is the physicists, because they have to actually understand how this stuff fundamentally operates.>> Yeah. It's great to see the sciences go there. I have to get that question because a lot of people ask me, what should I go into? And everyone is at the AI race going on now, but this clearly is the next step function. And now that you guys are finally to go public, what are some of your goals? What are you guys looking to do? Can you share on the business side and the commercial side what you guys have on the docket? What's your strategy? What's the vision?
Matt Kinsella
>> We have really moved from that research/development phase into the early commercialization phase. We did about $29 million in revenue in 2024 and are growing from there. And so what we are going to point some of this fundraising at is a few different buckets. Number one, continued commercialization. So our clocks, our RF antennas and our software products are commercially available today. Building out go-to-market channels and sales folks to help meet the demand for those products out in the market, so that's one go to market. Number two, R&D continuing to both shrink and cost down our commercially robust technologies. And two, continuing to push us to the 100 logical qubit threshold, which is where we'll get quantum advantage on our quantum computer. So R&D is number two. And then number three, which kind of encompasses all of this is just continuing to hire and build out the workforce. And then finally, having some cash on the balance sheet in case there are interesting acquisition targets that might have technology that it's smarter to buy instead of build.>> That's awesome, Matt. So for the folks watching, who should be leaning into quantum, in your opinion? Who should have on their radar? Obviously, we saw the readiness now we're going into connect pre-deployment. I know there's a lot of software being built, algorithms, the NIST standards, there's a lot of cryptography out there, people are scared about that. They see the upside on life sciences in the areas you pointed out. Who should be not only having their antenna up on this but really leaning into looking at paying attention to preparing for starting to be their client zero call it? People are leaning in. You have to get in there. All the success we've been seeing on the prep side, it's a client zero, meaning they got to do it themselves and work with the best. What's the advice and what's your view on who should be leaning in first and this first wave?
Matt Kinsella
>> Well, you've mentioned the harvest now, encrypt, decrypt later movement. And so I think all of modern-day encryption is based upon a fundamental inability of classical computers. And that is to factor a very large string of numbers down to their two prime numbers that when you combine those, it gives you that string. Just something that a classical computer, I have an interesting stat, I'll get them a little bit wrong, but it would take a CPU, something like 5 trillion years to perform that calculation. It would take a GPU 200 billion years. It would take a QPU a week. That fundamental step function is going to render a lot of data at risk. And so obviously, anybody who's dealing in encryption or sensitive data needs to be taking this quite seriously, because it's not an issue today, but it will be in the not too distant future. So there's one. Number two, anyone who deals in those applications like we talked about drug discovery, material science, and those are just what we can conceptualize now. It's going to be similar to AI where we aren't going to know exactly what we can point this at. So the answer is, for sure, those people, but really anyone, financial markets, et cetera, this is going to be revolutionary for all of those end markets. And then here's one that it might not be as apparent on the surface, and that's for the sensing technology. So, of course, nation states, the US and our allies need to have advantage on the sensing side, because it will be a real difference maker if we've got for good there was ever a hot war. But let's take GPS as an example. GPS is a position navigation timing system, but really it's a lowercase p, lowercase n, capital T. And the timing stamp that comes from GPS is incredibly important for what we do down here on planet Earth. We synchronize all of our trades, I'm sure we were talking about before. The NYSE would be very interested in the clocks because every trade has a highly synchronized time stamp that comes from GPS. Number two, the electricity grid. Number three, the RF networks. Number four, data centers. They all rely on GPS for timing to synchronize. And GPS unfortunately is becoming increasingly prone to being spoofed and denied. And so being able to have the ability to not rely on GPS for your incredibly important timing is something people need to start to be prepared for. And quantum clocks are one of the only ways to accomplish that.>> I'm really glad you brought that up because people think about the world we live in, what we rely on the atomic clock and the sensing, that makes the timing piece of it possible to be completely distributed. You don't need to have ... I mean, it's an amazing concept because people just can't really grasp that. It's like imagine having accurate clock on everything to that precision. That's what quantum does.
Matt Kinsella
>> Exactly. And not having to synchronize. Ultimately, time does synchronize to quantum. They're just room sized clocks on the Earth's surface, which beams their time stamp up into the GPS network, which synchronizes the clocks on the GPS networks and beams it back down to us. And so what we're able to do is give you that quantum timing locally and then take that reliance of the GPS network away.>> And this is why I have my watch I'm on now, but I think this is why I like the NVIDIA AI factory tie-in, even though it's a little bit different, but it does promote ... Supercomputing definitely promotes quantum, because people now can understand when they see NVIDIA, what quantum could be. You gave that status. It's huge gap between what GPUs can do timing-wise with quantum. And when you look at the advertising that's being done for quantum, I think AI has been a great tailwind for quantum because it creates awareness like, "Wow, what if?" A lot of these what ifs are coming big time.
Matt Kinsella
>> Yeah, they are. And I think if you try to frame it on the timeline that AI was on, and I'm not saying we're going to have a ChatGPT moment in quantum, I do think it might roll out into the world a little more organically as opposed to that, "Oh my gosh, I just interacted with a Turing test breaking machine like the ChatGPT." But I do think it's helpful to look at it along a similar timeline. Everybody remembers late 2023 when ChatGPT first exploded onto the scene, but not a lot of people remember 2017 when that paper, the Attention Is All You Need paper was published, and that's what laid the foundations for large language models being built and ultimately led to that ChatGPT moment. I'm convinced we're past that Attention Is All You Need paper moment in quantum. And that took place actually in late 2023 by a researching group, which showed logical qubits for the first time. And before that, it was unclear as to whether logical qubits were even going to be possible. Now that we have logical qubits, it's just a matter of time to the scale to the number of logical qubits, which again, minimum viable number 100. We just announced that we have eight at Infleqtion. As we get to 100, then we'll start to see quantum advantage in computing. So it's coming and it's just a matter of time and we're past that Attention Is All You Need paper. I may have gotten my dates wrong in there, but generally speaking, you get the point.>> Well, yeah. I mean, in 2018, 7017, that's when all the work was moving along and then boom, the bit flips so to speak. That's what's happened. And again, the acceleration coming is why I'm so bullish on quantum right now. And again you mentioned the cryptography. One of the comments we had on the series, we just ran from a tech alpha nerd, I call him, he's genius. He said, "It's kind of like the Y2K, but we don't know which K, what year it's going to happen, but it'll probably be by the bad guys who will find the use cases."
So people are paying attention now to the realities of quantum, both good and bad. So congratulations, really appreciate you taking the time, and congratulations on ongoing public and getting the working capital and the momentum. Thanks for sharing.
Matt Kinsella
>> Thanks, John. It's been a pleasure talking to you. It's always fun to talk about quantum. It's one of those things where once you start going down the rabbit hole, it's hard to talk about anything else.>> Quantum's hot. It's going to be hot. Soon, the year of the quantum, 2026. Matt, thanks for coming on. Congratulations.
Matt Kinsella
>> Thanks, John, appreciate it. Great to meet you.>> I'm John Furrier here at theCUBE. We are at our NYSE Studios part of our NYSE Wired series. Of course, we've got our Palo Alto Studio connecting technology and Wall Street together. Thanks for watching.
