Technology, Connected - The Quantum Clock That Could Replace GPS

Episode Date: March 9, 2026

Infleqtion CEO Matt Kinsella joins Thinking on Paper to explain neutral atom quantum computing, quantum clocks, and why the future of computing may depend on synchronisation as much as raw processing power. The conversation moves from GPS spoofing and UK submarine navigation to Nvidia’s hybrid quantum AI stack, quantum sensing, edge computing, quantum error correction, and the growing race to build commercially useful quantum systems.Please enjoy the show.--Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping the future. 🏠 Buy us a beer on Substack🎧 Take us with you on Spotify🎧 Remember steve jobs on APPLE📺 Get the clips and outtakes on Instagram --Timestamps:(00:00) Trailer(01:50) GPS(04:48) What is a quantum clock?(07:18) How atoms keep time with laser precision(08:14) Room temperature quantum(12:38) The Rydberg state(14:03) Quantum clock on a UK submarine(17:06) Quantum in space(18:48) Hybrid quantum-classical workflows(23:18) Software layers(25:32) Drug discovery (29:03) The bridge between classical and quantum(31:54) Quantum Clocks & Quantum Computers(33:48) Nvidia(35:42) Quality or Quantity of Qubits (38:00) Quantum mechanics and free willLove it.Thanks. 

Disruptors and curious minds. Today's guest is Matthew Kinsella, CEO of Inflection. The central question, how does quantum computing technology help humanity coordinate? We speak about quantum clocks and GPS vulnerability, UK submarines, Nvidia, qubits, QPUs, the hybrid classical data center and quantum consciousness. Matthew, of all the guests that we've had on quantum computing, explains the concepts and the technology in a way which resonates and is easy. to some extent to understand.

Please enjoy the show. And now you are at the point where one of the last things that we don't understand as humanity is, is quantum. It doesn't intuitively make sense to anyone. We'd never shown logical qubits as humanity before 2023. And now we have them. The most precise way to keep time and the most stable way to keep time is the energy transition of an atom. The underlying photonics and the underlying components are really the same to build a quantum clock and to build a quantum computers. That's actually really taking advantage of the superposition of the atom.

Sometimes I joke that the only thing better than quantum is quantum in space. Yes. Yes. But it's actually there is a huge, huge market for quantum in space. Neutral atoms has indeed emerged as the leader on most of the metrics that matter for quantum computing. Welcome to the show, Matthew. Thank you for thinking on paper with us. Great to be here, Mark. Great to be here, Jeremy. And thanks for having me. It's our pleasure. It's our pleasure. I want to start high level and think about what all of this means. But I want to root that in something relatable. So I want to talk about coordination. How important is just the idea of coordination to your work and what you're doing? I love that question because I can go many different ways with it. So let me take a couple cracks and I'll talk about coordination internally at inflection. And then I'll talk about what.

quantum can do to help coordination for humanity. Inflection has a different strategy than most quantum companies, and it's largely due to the flexibility of the neutral atom modality, which you both mentioned, you mentioned that modality in your introduction. And so unlike spin-kubits or superconducting or in some ways trapped ions, neutral atoms is useful for tasks beyond just quantum computing. And the neat thing about that is the underlying components and the underlying technology is the same. And so when we build some of our quantum sensing products and we can get into more depth into what those are or why they matter, that directly impacts how we're doing on our quantum computer as well.

So there's a deep, deep coordination in the underlying R&D that we need to do here because it cuts across our different various product families. So coordination internally, even in just that one example, is incredibly important. If we zoom out to how quantum might help us coordinate to better get our kids to lacrosse practice, or in other types of ways. And you think about time and what role time plays in coordination. Part of it is obvious, but much of it is not.

And let's talk about GPS for a minute. So what is GPS? GPS is a position, navigation, and timing system, a PNT system. In reality, it's a lowercase P, lowercase, and capital T. The time that comes down from GPS is actually the most important service that it provides. So there are precise clocks in the satellites

that make up GPS. There's about 30 of them. And those clocks are reasonably precise themselves, but they synchronize with these very precise, room-sized clocks down on Earth's surface. And so they have to discipline to those clocks. And then they send that timestamp down to our iPhones or to servers or to basically everything on the planet. And in order to coordinate, we must synchronize. And so we rely heavily on GPS for all of the synchronization and coordination that we do here.

So think about the electricity grid. Think about the RF networks. Think about GPS. Think about financial markets. Everything has a timestamp that all comes from GPS. And GPS is getting increasingly spoofed and denied. And so we can't rely on it as much as we used to be able to. It's getting fragile.

And quantum, and in particular, quantum clocks, can actually provide better than GPS precision timing locally in an unspoofable, unjamble way, allowing us to, A, coordinate with greater precision because they are more precise than the timing coming down for GFS, but B, guard us against the denial and spoofing of GPS, which could really disrupt coordination globally, which would be a total disaster. What is a quantum clock? And how does that link to GPS? Well, it turns out the most precise way to keep time and the most stable way to keep time

is the energy transition of an atom. And so you can think about the earliest clocks for pendulum swinging back and forth, right? And then it turned into springs inside of stopwatches and the like and then moved onto quartz, which you put an electric signal into a quartz, and it vibrates at a reasonably stable frequency, the actual best and most precise and fastest way to tick time is with the energy transition of an atom. And so what we do is we take advantage of that atoms, effectively, quantum nature by shooting those atoms with lasers. We use ribidium atoms because it actually has really only one outer valence electron, so it's easy to manipulate. We hit that with an ultra-high

frequency laser, in this case, 778 nanometers, and that causes the atom to effectively go into excited ground, excited ground, excited ground, and that energy transition happens at a very stable rate, and it happens very precisely and very, very quickly. And so by hitting these atoms with the right resonant frequency to what it excites them, that becomes a very stable frequency reference, and that's how we build a quantum clock. And it's only been possible more recently because of the advances in laser systems to be able to have that precision to hit those atoms with these lasers at that level of precision. So, Matt, I'd like to insert a musical reference in nearly every show.

So would you say this 778 nanometer laser is essentially the atom's metronome? Nature's metronome. Yes. I think that's a reasonable way to think about it, but I might flip it. I would say that the atom is effectively the metronome. And you have to find the general frequency that excites the atom. and then you have to tune that frequency to get right, just right. The atom is going to do its energy transition the way it does it.

That's sort of predefined by nature. It's the laser that's like almost think of it as maybe like the battery for the metronome to get it going. And then the atom itself is the metronome. And it is nature's metronome. I love that analogy. And you're never going to get more precise than nature's metronome. Is this what allows you to perform your operations at room temperature? Could other quantum computing modalities give the same time?

An ion could. I don't believe superconducting material could. And spin qubits, I don't know. There are clocks built on ions. Ions are really just an atom with a charge. And in fact, it's funny, you know, there's a bit of a... Our founder, Dana, will sometimes refuse to use the term neutral atom. He just wants to say atom, because the term neutral atom really only exists to differentiate it from ions, which carry a charge.

And so Dana sort of like, well, why do we need to be the ones to add neutral? Why can't we just be atoms? So neutral is a marketing term for it. It's more than anything, yeah. It's true. Yes. Yeah, we're just working with atoms that don't have a charge. So you could, good question as to whether you could theoretically use those other technologies.

You could use ions, but you could, I don't believe you could use some of the others. But your question is a very important one and leads really into our broader strategy. And so it's the flexibility of the neutral atom modality that in my mind was so intriguing to me when I was first exposed to it back in 2018. Like I'd said before, the underlying photonics and the underlying components are really the same to build a quantum clock and to build a quantum computer. So let me flush that out in a little bit more detail. So stimulating these atoms with lasers and we're flipping the atom from excited to ground, that's actually really taking advantage of the super position. of the atom. And so if you've had quantum guests on your show before, I'm sure you've used that term

and know that that's one of the fundamental building blocks of a quantum computer. So the clock really helps us master superposition. We can also then turn those atoms into what's called the Riddberg state. So if you remember we were going excited to ground to take the ticking of a clock, the Rittberg state is what is, you could think of it as like the electron way out in outer orbit. And so it's a very, very big atom. And when it's in that state, it becomes sensitive to the entire frequency spectrum. So this is actually completely game-changing technology.

If you've studied classical radio frequency technology, normally you need a metallic antenna device that vibrates at a given frequency. And normally that device needs to match the size of the wavelength that's receiving. So for the very low frequency long wavelength signals, you need these massive, massive antennas to receive them. What we can do is we can turn those Rydberg atoms, those atoms in their Rydberg state, into antennas themselves, and they can receive the entire frequency spectrum. So you can receive a very low frequency, long wave length signal on something the size of a sugar

cube, because the atoms are actually picking up the electromagnetic frequency and then doing all the signal processing that you'd normally need to do. It's sort of magical almost. But what's important about that is that Rydberg state is the state that you need those atoms to be in to entangle them. So now we've got the second building block of compute. You asked is what allows us to do this at room temperature? And the answer to that is what is room temperature and what is cold, right?

And so most of us think of cold as a freezer, but really what is cold, it's the lack of motion of atoms. And since we've already really become experts at controlling atoms with lasers, the next logical step is just to hold those atoms in place, such that they move so little, they become the coldest place in the known universe. So part of what I was saying with, you know, before with atoms in a vacuum and that's like outer space in your hand, these atoms are colder than outer space. They are moving less than they would move in outer space, but the system itself is at room temperature. So we are putting them into ultra-cold states, but by doing it, we're doing it with lasers. And so that's what allows us to do this all at room temperature. And that is actually what gives the flexibility of this modality, because if you need to resolve, inside a freezer, you're not going to be able to shrink that freezer.

You're not going to be able to cost that freezer down. Those are mechanical systems. Everything we build is based on photonics, these vacuum cells, and then electronics, which can now be shrunken to our caucuses, you know, three pizza boxes or so. It's end state will be chip scale because we can integrate all these photonics. And so it's the field deployability, it's the ruggedization, it's the shrinkability, it's the cost down that makes this technology so special. And because we can then engineer those systems and they're all sort of the building blocks

of quantum computing, neutral items has indeed emerged as the leader on most of the metrics that matter for quantum computing as well. Awesome. So is it Rigberg state? Ridberg. Rydburg. So the Redbird state instead of a one in a zero, qubits, you know, has this potential of being in any one of those states between the one and the zero, like infinite states.

So this Redberg state opens up that spectrum. of potential for the atom? Is that where we're headed? The Rydberg state is a state that's close to an ion. So you can think about like if it got a little more excited, it'd become an ion. And one of the reasons why trapped ions got the head start in computing going back 20 years is because it's easier to control ions because of that charge. You can actually, they repel each other. And so you can sort of use that repulsion to get them into their little cubit spots, right, by just using microwaves. And then you can start to stimulate them there. Ridberg state still does not have a charge, but it may be a bit.

makes these atoms easier to control. And so that's why we use the Rydberg state. The superposition and the ability to be in multiple states at once is present in really all cubit modalities. But in order to really harness that, it must be in the ultra-cold state. So the RIDBerg state happens to be, make these atoms sensitive to their RF spectrum. But it's the ability to control the atoms and then

individually address them and then freeze them in their RIDBurg state, which is what allows us to actually harness the superposition of those atoms, if that makes sense. You've just announced that you have an atomic clock in a UK submarine. Yes. And I'm from the UK, so I'm very happy about this. We are the oldest, greatest naval country in the world, don't forget. Indeed.

How did you end up within quantum clock in a UK submarine and not an American submarine? We have a substantial office in the UK, in Oxford, actually. We have about 55 folks there. And so, and one of the reasons for that was the UK has been, frankly, you know, faster moving on quantum than the U.S. They identified it back in 2013 as an absolutely critical national priority. And so we felt it was important to have feet on the ground there. And so we started our office there in 2018 and it's grown to 55 people. So the Ministry of Defense and the UK government in general is one of our largest customers. And we have a great relationship with them. So they had just announced. their first underwater autonomous vehicle, and it was called Excaliver. And they were going to take a native voyage, yes. They were going to sail it on its maiden voyage, and they got the opportunity to put a payload on it. And so they decided what payload would we want to put on this, and a quantum clock was what they wanted to do.

So it not only was it us putting a quantum clock on a underwater autonomous vehicle, it was really the first thing that had been put on this vehicle. And the reason why they wanted to put a clock on there is actually because underwater you don't have access to GPS. And so you don't synchronize the GPS unless you surface. And surfacing is very important to kind of get all of the inertial sensing equipment and range finding and direction equipment that's on a submarine because those aren't quantum in nature. So therefore they have errors and therefore they drift. And that drift compounds. And so if you were to try to sail a submarine from the UK to the US without going up and synchronizing to GPS to get all your systems back in order, you'd be off by hundreds of miles because it starts off small, right?

But then those errors compound and next thing you know you're going, who knows where you're going. So one of the reasons that they wanted to put a clock on there is it's the beginning of being able to build an inertial sensing system, a position navigation timing system that's completely independent of GPS. And timing is a very important part of that. So having better than GPS timing locally on the submarine that doesn't need to synchronize the GPS is critical. What did you learn from that little experiment? We learned a lot of stuff. We learned, and it largely had to do with the engineering of our system. We learned that it could function 30, 50 meters underwater.

We learned it, you know, which we can learn it could function in the very coldness of underwater. And so it wasn't so much we learned too much about the underlying ability to keep time. We learned more about our, how did we engineer? of the system and can it work out in the field. And that was invaluable information. It turns out it worked very well, which is great. And we're actually, we have funding to put these clocks in space also, so to space harden these clocks.

And ultimately, I think it sounds, sometimes I joke that the only thing better than quantum is quantum in space. Yes. Yes. But it's actually, there is a huge, huge market for quantum in space. Is that what you're doing with Voyager? Ultimately, yes. It's the idea is that we will work with them to get clocks up into space and then start

to test them in some of the real estate that they have on the International Space Station. And so the interesting thing about getting things ready to go to space, and we actually were the first company to ever put quantum technology in space. We did it back in 2018. It was part of what they called the Cold Atom Lab, and it still resides up there on the International Space Station. Much of what needs to be done is the mechanical engineering to radiation harden or to survive the crazy shakes that happened during blast off.

And so it's not really fundamentally a different product. It's just engineered to work in the absolutely crazy situation that space is. Link to listeners, we just recently had a conversation with a company who are doing radiation-proof transistors and technology. So I'll put that link in there because it's another thinking on paper node, Jeremy, connecting these. I love it. Yeah, Matt, one thing we wanted to share too is a lot of what we're trying to do after two, years into this, we're creating a knowledge graph of the interdependencies between all of the things that we talk about, the tech side, but also the human element side. So government, equality,

access, that's what Mark is referencing that. Hopefully we can continue to do it. No technology is a silo anymore. No technology is an island. They're all interconnected and they're all very much reliant, dependent on each other. It's so true. So true. Yeah. Mark, how do you feel about going down the path of the hybrid classical. I've got a couple of questions in that world. I think that's good because that relates to AI as well, I think, and what's happening in Illinois. Yes, absolutely.

If we could frame that in a quantum computing workflow, and you have a classical node, and you have a quantum node, and you have a workflow you're trying to organize between the two of them, talk about what you've built and what, interesting things could shake out from that. One of the most important things to understand about quantum computing is it's not going to replace the things or the workloads that we're doing in classical computing. It's going to open up whole new workloads.

And so I don't see this as a necessarily a disruptor to GPUs or classical computing at large. It will be an expansion of what humanity can throw compute at. Let's call it that. So the vision of the future data center that I have is, just like GPUs layered in on top of CPUs to enable new use cases, you're going to have quantum processor units or QPUs sit above those. And workloads will get sent into the data center in the cloud, and they'll be chopped up, and the various parts of the stack are best suited to solve.

The workloads will be sent to those parts. And so the underlying infrastructure to do that is something that we focus a lot on, and we focused a lot on it with NVIDIA. NVIDIA is really taking a leadership position in that bridge between quantum and classical. And so they announced something called NVQ Link in October of this year, which is really exactly that. It is the bridge to allow workloads to pass really

seamlessly between quantum computers and classical GPU clusters. And a good example of how that might look in the future is something we did with them just about a year ago, where we solved a very basic material science problem called the Anderson Impurity model. It's a photovoltaic model. Parts of it were solved on a GPU but parts of it that wouldn't have been able to be solved by GPUs were solved on our quantum computer. And then they recombined to give the answer. And we talked a lot about how nature does quantum better than anyone. Quantum is really the computational method of nature. And so the types of problems

that quantum computers are going to be very good at solving are those that are really rooted in nature themselves. And so the ability to model the interactions of electrons when you're combining different molecules, that's inherently quantum mechanical in nature. And even the most powerful GPU cluster at the end of the day is boiling everything down to zeros and ones, right? And that's not how nature fundamentally works. And so these types of nature-based problems break on classical computers because they can't be boiled down to that heuristic of zero or one. And so a lot, but a lot of the problems, a lot of the parts of that Anderson and Prudy model could be, you know, solved by the classical computer. So it was the combination of the two that was able, what made us able to do something

that had never been done before. I think you can think about that as a very not commercially useful example yet, but you expand that over time. And that's how we're going to build better batteries, right? And so your iPhone having to be charged every night, you can build a battery that lasts for a year maybe, right, or much longer and or help solve the Haber Bosch process, which is what we use to build fertilizer. And we've been trying for 100 years to find a better catalyst, but it's just too complex to model that interaction. That's the type of thing that quantum computers will be able to do in tandem with classical computers.

Is it fair to think about classical computing as a bit of like a brute force modality and then quantum is more of a finesse driven modality? I think that's not a bad way to think about it. You are boiling all of life's problems down to Boolean zero or one logic. And what we can do by boiling life's problems down to. that type of logic is incredible, right? It's amazing what you can do with doing that zero or one billions of times, but that's not fundamentally how nature works. And so, yes, we're kind of brute forcing these problems. And that's why I think you see the power consumption issues when

we're starting to throw classical computing at problems that it maybe wasn't well suited to solve. Can I ask a silly question? Yeah. Part of the computation that was done on the, these were your quantum computers? Yes. So could you explain, because in our heads, obviously we all have the big chandeliers. We've spoken to IBM and have the huge, huge quantum computers. And from what you're saying, yours are much smaller.

Did you speak a bit about the algorithms or the software that you're running on those as well? And are there bridges in place that link the softwares between quantum and classical computers? And that's my silly question because it might not even make sense. No, it does. It does. And I do think software isn't talked enough about in quantum computing. You know, even at the most basic level, we're shooting atoms at lasers. But it's not like I'm sitting there with a laser gun shooting the atoms.

We are programming these lasers with software to do this at very, very precise, you know, literally atomic level precision. And so how does the quantum computer work? Well, at the most basic infrastructure level, it's atoms interacting with lasers. And then there's a software layer that's sort of programming each of those laser shots, right? And so that's the, that you can think of like the equivalent of binary code, right, or binary language. And then there's a stack that abstracts that away because we don't want developers to have to think about how you're interacting with each individual laser and atom. And so now you have middleware layer, which we call super stack, which interestingly, we, we, use on our own systems, but it does work across modalities. So we have spin-cubit customers. We have

superconducting customers who use our middleware layer as well. And then the application layer is really, that's what we still need to do a better job, I think, defining. And that's where we need to get the developer community really activated. And it'll be easier as the computers start to do things that are commercially useful, because they still really are in the realm of doing cool physics experiments and doing things that you can extrapolate commercial value. out of over time, but we're not quite there yet. And we can talk about when I think we'll get there and how we'll get there. But software is absolutely critical.

And then the NVQ link that we were talking about from Nvidia, actually fundamentally is software-based in many ways. And so it's the software translation layer between classical and quantum computing. Okay, thank you. So back to this reimagining of the data center stack. We've got, you know, CPU, GPU, QP. Let's talk through where this bridge lives in a practical example. So I'm a researcher. I've got a question I want to have quantum computing help me with.

Let's make one up. It doesn't have to be right. It's just something to illustrate the process. And when that question goes in, how does it break up? How does that bridge go, hey, this piece goes to the GPU, this piece goes to the CPU, and this piece over here, we're going to let quantum mess with it. So drug discovery is a way to fit that in maybe as an example. Sure.

Yeah, we could try a drug discovery example. And just to caveat everything I'm saying now, we're getting into the realm that I might be getting below my depth. I'm not a quantum physicist. That's all right. We aren't either. So it's all good. Our PTO, Pronov, will probably be able to answer this far more eloquently than I

can, but I'll take a stab at it. Let's use a drug discovery example. So similar to how I was talking about, it's very difficult to model the electron interactions for a material discovery type type process because those are quantum mechanical in nature. The same holds for combination of molecules to combine them to build drugs, right? And the type of problems that quantum computers are going to be good at solving, I usually think of as small data problems. So there's not a huge amount of variables necessarily. But when you start combining those variables, the outcome approaches infinity. And that's the type of problems that just break classical computers.

And those are really the way quantum mechanics work because of the just the absolutely massive range of potentials of these electrons combining and the molecules combining. And so if we use a drug discovery example, let's say we were trying to, I don't know, name the drug, some drug to cure a particular type of cancer. And I'm not an expert on how drug discovery works now. And I know we're utilizing AI to be much more efficient at it. but it's still kind of brute force, right? You're taking educated guesses. You're using it and narrow down the possibility of which molecules might work to help with this ailment. But it's still brute forcing the problem.

With quantum, you can really do it in a more, I guess you use a word elegant way and actually model out how these will interact. And you could probably cut the development time down from months to much shorter periods of time because you can run these simulations simultaneously. So how would the underlying software layer know which parts to send to the GPUs, which parts to send to the QPUs? I actually don't know the answer to that question is probably going to be quite human directed until the software gets better. But I think most of the physicists would know, okay, this is the part of the problem that is really challenging for our computer now. We're going to try to start to dip our toe in the water of quantum and send those workloads to the quantum part of the computer and then recombine them for the answer. And so I think that's really the way you'll see this play out in reality is people like drug discoverers or people like DuPont, who's building chemicals and materials, right? They'll start to experiment with sending small parts of what they're doing to quantum computers.

And then that part of what they're sending there will just grow and grow and grow until they'll figure out how to utilize it in the most efficient way possible. I'm on this thread. I'm not letting go of this thread of bridges. Similar to like traditional simple computing, you have an MCU microcontroller unit and then you have a DSP digital signal processor, right? And I think there's similarities based on what I learned about that where the MCU kind of looks and goes, man, this is really hard work. We need to outsource this and chuck it to the DSP. So I think there's a lot of similar roots in old technology that you're talking about now. That was more of my own connecting of the dots, but I think it's applicable.

Just to stick on your bridge theme here, because I think this is pretty neat, when you write software and going back to software for quantum computers, you have to write it in a fundamentally different way because you actually have to code around some of the laws of quantum mechanics. And one of those laws is called the no cloning theorem, which is very interesting. You can't copy and paste quantum data, which copying and paste and data is like it's all over the place in classical software, right? And so when we write our software for our quantum computers, we write this kind of very different. software that doesn't do some of the things that would be very natural to do in classical software development. And that means we have to sort of re-architect the memory. But what we did was we started to run this re-architected memory software on GPUs. And it turns out that that actually provides some very interesting performance enhancements to GPUs, largely around the

enlargement of the context window, which is one of the fundamental scaling bottlenecks to GPUs. And that's because the memory is totally re-architectedicted. It's quantum in nature. And so, So we've kind of been trying to bridge the gap between classical computing and quantum computing hardware by software and giving some of that quantum advantage to classical computing kind of via software and rewinding or bringing forward the time to quantum advantage by software. So that's a kind of really interesting bridge we've been working on. That's really cool because like you said, the context window issue is real.

It is. That's a real bottleneck to scaling. You'll have to keep us posted there. That's really interesting. We just announced a really cool contract with the Army. It's called Sapient, Secure AI for PNT. And this is based on what we call contextual machine learning software. So it is our contextual machine learning software running on edge GPUs like Nvidia's Jetson,

so small GPUs that don't have a ton of power or memory on them, and allowing them to ingest far more streaming data. So think of like video data, speed data, inertia. motion data and process all of that multimodal sensor data right there on on the edge, which would have normally overwhelmed the memory capabilities of that GPU, but this allows them to expand it and then recreate some of the basic things that GPS is giving you, like where you are in the world, by extrapolating by all the different external signals that can be brought in onto this GPU.

And so that's where the name Secure AI for P&T comes from. And so that's a kind of very interesting near-term use case that we're working with the army on. But yeah, it wouldn't be possible without this software. It's fascinating, fascinating. How can I weave a bridge into this question? What do you believe about quantum computing and quantum mechanics, but quantum computing that your peers and your colleagues and the mainstream media or the mainstream narrative on quantum wouldn't agree with you necessarily? There's a lot of different answers. That's why I'm hesitating, but the one that keeps jumping to the top of my mind is the cohesion and the linkage between the quantum sensing products of the world and a quantum

computer. Because a lot of times, someone might look at classical technologies and say, what the heck does a clock have to do with a computer? Why would you build both of those things? In the world of quantum, though, they are actually sort of the same thing just in different levels of complexity. So we've already talked about that. And if I just think about the message.

messaging that I'm constantly trying to explain to people. A lot of times people will say, well, why are you even doing these other things? Quantum computing is such a big market. Why don't you just focus on that and drop these other distractions? And I disagree with that fundamentally for many, many reasons. One, because these other markets are actually very large opportunities, and we've already talked about the DNA that we need to build in the company. But they're kind of the same thing, right? And so as we build the clock, we harness the superposition of the atoms. We just get better at building the computer. And so I think that is something that is not intuitive, but I deeply believe. And as I, you know, explain it to people, I think they come around to understanding it, but it's not

the mindset people come in necessarily right away with. I like that. I like that, hey, let's, let's, let's, let's ground it in something that people understand that we could apply today and let's learn, because it's the same thing that you're applying just in a different way. It's the same use of a, of a technology that you apply to new use cases. That's why you're a technology company and not a compute company, right? I know everybody wants to compare themselves to in video because it's obviously self-serving to compare yourself to the largest company in the world. But that said, we really did take a lot of inspiration from Jensen's strategy,

which he had this graphical processing unit that he pointed at graphics first, right? He commented on video games, then he pointed it at crypto mining and physics. And then ultimately the crown jewel of, of generative AI came around, but he didn't just wait for generative AI to come around to start to build and deploy. He addressed these markets along the way. And that's kind of how I think about what we're doing

with Neutral Atom Quantum Tech. Having orbited his space and Nvidia's space for a while, I don't want to make it about him, but what do you think drives his curiosity? I don't want to speak for Jensen, but I think the world Jensen kind of boils down to how do I sell more GPUs. And so I think he's curious about how

Quantum helps him sell more GPUs, is my guess. And I think, you know, the idea of expanding the types of problems that we can address with compute, I think fundamentally it'll just mean more GPUs will be needed to work alongside QPUs. And I think that's ultimately why, Nvidia has a really world-class quantum team internally. And a lot of it, though, is in service of figuring out how GPUs play a role in quantum going forward. And there are many, many ways. We talked about the ways that they'll work together to solve problems. But actually, I think, I know AI, GPUs, LLMs will help us get to quantum advantage on the computer faster because a lot of the things we're dealing with right now are just errors in the qubits.

We need higher quality qubits. And error correction is something we focus on as an industry and certainly here on inflection. AI helps you with error correction because these are kind of inference problems. You are having to infer where the errors are coming from and then correct them. and AI can help with that immensely. I've got a question that we ask a lot of our quantum guests. There's just this debate over more qubits or better quality qubits. How do you feel about that one way or the other?

Having a certain level of quality is of the utmost of importance. Beyond that, you can start to solve quality with quantity. And so to me, the ability to scale physical cubits is the most important, as long as they are above that threshold level of quant quality. Now, higher quality is better objectively. So continuing to get to, we're at 99.73%. Gate Fidelity, that's the measure of quality that you use. And that's basically how well do the gates do, what you want them to do, basically, right, the entangled cubits.

We do need to drive that to one nine or they're sorry, three nines, four nines, five nines over time. But when you're at that level, really above 99.5% or so, you can start to solve some of the quality issues by throwing more quantity at them. And the term that I think is the most important thing to focus on to understand where we are on our progression towards quantum computers being commercially useful is a term called logical qubits. And logical cubits are very high quality error-corrected clusters of physical cubits that can actually be used for computation.

Physical cubits themselves are too error-prone. They don't really do anything useful. And this is why I have such high conviction that quantum computing is going to become commercially useful in the defined time period. One of the knocks it always gets is it's, you know, it's always been five years away. And I totally accept that that is the case. It always has been. This is the reason why I think it's actually five years away this time is because of logical qubits.

We'd never shown logical qubits as humanity before 2023. And now we have them. Only a handful of companies have them now when flux is one of them. But all we need is more logical cubits. And so we have the fundamental kernel of the ability to do calculations on quantum computers now. We really didn't have that before. And as we scale logical cubits to 100 logical cubits is about the level. Most people think we'll start to see some quantum advantage in the material science world.

It's not going to be like the chat GPT moment, I don't think. But it will be the first time we've been able to do something that is commercially useful in quantum computing. And so now it's just a matter of engineering, really. It's not any kind of physics breakthrough that needs to happen. We started the conversation on coordination. Let's end the conversation on coordination. We are now going to align our atomic clocks to land thinking on paper. we're playing today. I have one question, and then Mark, you can ask the Kevin Kelly question.

Right. And you can, you can totally say, I don't want to answer this question. Okay. But we mentioned some books that we've read. Irreducible is one of them. Federico Fajun, who basically created the Intel 4004 first microprocessor. Like, he turned down the path of neuroscience. He turned down the path of, dare we say, quasi-spirituality. Quantum information, panpsychism. Quantum information panpsych is. If you haven't read the book, I think you would love it. I wrote it down when you guys said it, Irreducible.

I'm actually fascinated by it. So in Irreducible, Federico Fajin believes that the quantum wave collapse actually proves that free will exists. What do you think about that? Who, that's deep. Let me, as I'm thinking, I'll make a couple of high-level comments. I do, I think the overlap between spirituality, religion, philosophy, and quantum is absolutely fascinating. That Venn diagram overlap is really interesting to me. And if you look at the role religion has played in humanity over the last 5,000 years,

it always seems like it is sort of explaining the sliver of the world that science hasn't yet addressed, right? So thunder claps, you know, thousands of years ago, those were the gods, right? That was Thor. And as we started to understand what those were, that, you know, didn't become associated with the gods anymore. And now you are at the point where one of the last things that we don't understand as humanity is, is quantum. It doesn't, you know, it doesn't intuitively make sense to anyone.

And so I do think, you know, there is a really interesting sliver of religiosity there. I'm religious. I'm a Catholic. And so I'm fascinated by this. But I do think there's something at the very core of what he's saying that makes sense to me because I think there is something, you know, if there is free will or not or some higher power design in the world, they did it with quantum mechanics. They've designed the universe. And so does the wave function collapse equal free will? I'd have to think about why that would be the case.

But it's a really interesting thought. And at the broader perspective, I actually, you know, totally buy into what he's saying. I think it's a fascinating topic to explore. Closer, the thinking on paper, closer, the question that we end every show with left by Kevin Kelly, fired, fired, wired, founder, Maverick, futurist. Most interesting man in the world. That's what they say. That's what Tim Ferriss says. That's what Tim Ferriss says. Yeah, exactly. What do we want humans to be and how, if it does, does technology help us get there?

So our vision at inflection is to harness the power of quantum to expand human potential. And if just, you know, taken at the surface without explaining it, it sounds cheesy. But really, at its core, is harnessing quantum, which as we've talked about is the basic fundamental building block of nature and applying that to allow humans to do things they weren't able to do before. And so maybe this isn't, it's sort of a tangential answer. But what I want is for humans to be able to do things we haven't been able to do before to continue to push society forward and solve some of our hardest problems. And I think quantum is an enabler to do that. And so I guess what do I want humans to be? Maybe the answer is more.

And quantum helps get us there.