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Welcome, everybody. I'm Joe Moore, Morgan Stanley Semiconductor Research. Very happy to have an interesting CFO of INQ. So thank you for coming. Appreciate you being here. I think we haven't had you since the Arm Day, so it's good to see you. So you've been in the CFO seat, I guess, a little less than a year, but you were on the board before that. What drew you to the INQ opportunity?

Well, I mean, like I said, I was on the board. I actually joined the board when the company first went public, and, you know, quantum computing four years ago. Like, no one was really talking about it, and it seemed like it had promised, but you never knew for sure. Over the four years that I was on the board, I got to see the company actually scale the ability to make us a more powerful computing device year after year after year. Peter Chapman, who was the prior CEO, took it from basically almost zero revenue and created a product that was more powerful each time in the market. And other companies had gone public around the same time also. And being an arm, I was like, okay, this could be the future of computing. And wouldn't it be great to have a front row seat as part of it? So I was still a CFO. We had sold ARM to NVIDIA. It was in that holding period waiting for approvals. And this became an interesting company the more I watched it scale. It had the right engineering talent. It didn't need to go to market much because, frankly, sales were still pretty small. And mostly it was like research laboratories in the first few years or so. But to see it come out of the research laboratories. And then importantly, when Peter announced his intent to retire and move on to other things, we faced a CEO succession, and I was lead director at that time. I was on the audit committee. And we were looking at internal and external candidates, and it was hard to find somebody with 10 years of public company, quantum company experience. Like there were none. And so we looked at all of the other candidates, and sure enough, you know, among our choices, we had a really good CEO who I thought, you know, physics major, Cambridge, multidimensional thinker. So early last year, we appointed Niccolo DeMossi as CEO of the company, and today he's chairman of the CEO. And so he very rapidly lived up to my best expectations as someone who's not just going to be like a linear executor, but looks at the market more broadly and says, like, what are all the different things, quantum or quantum related, that we need to have? And kind of like Cisco, if you think about Cisco, the way it became the company, let's try to be that and look at the networking of quantum computers, the security that you need after a quantum computer breaks encryption, the space-based assets you might need to quantum secure, et cetera, et cetera. And so in September, I moved from the board to the company as COO and CFO, And it's been pretty amazing. It's been like, I don't know, five, six months. It feels longer than that for sure. But watching the company not only build a machine that each year was faster, had more qubits, but also a company that is building the applications that go with it. Because what good is the iPhone without the App Store, et cetera? And then you have a portfolio of products. A year ago, we had one product, and now we have a dozen or more. So many vectors of growth. And, yeah, as board members, you know, you get to see sort of like snapshots of the movie, but never the movie. And I wanted to be part of it.

So maybe as a relative newcomer's perspective to the company, can you talk about why investors should care about quantum? And, you know, we're not at the point yet where we're doing things that can't be done classically, but it's coming. What types of applications do you think will happen there? And should we think about, you know, the market cap of AI as being the territory you're going after? Just why should we care about quantum? And obviously code breaking and things like that we get, but the sort of broader use cases.

Yeah, those are great questions. I mean, I think the promise of quantum is around doing things that classical computing can't do, right? And so there's this thing called quantum advantage, and at some point you reach that where classical computing just cannot do that many number of calculations or that many number of simulations of things before giving you the best answer. And forever, that's been like a bit of a moving target, frankly. So NVIDIA isn't standing still. I mean, they keep innovating. So classical computing moves as well. But at some point, you cannot simulate a calculation on a classical computer that a quantum computer could do. We're closer to that than we were three, four years ago, for sure. It's, you know, humble opinion, maybe a year or two away before you get to that point. The power of quantum, as most people may know or not know, is the fact that it's like 2 to the n power versus 2 times n. So the number of qubits that you add have an exponentially more powerful impact potentially. Quantum computers are right now still of different modalities. There's superconducting, and there's photonic, and there's annealing, and yes, there's ion trap, which is what we have. So some start with more errors, some error correct, some start with less errors. The point of the industry, though, is that there'll be one or two modalities probably that will succeed in the longer term to be decided which ones. Ion traps begin with fewer, and I looked carefully at as much as I knew. I'm in a couple of engineering degrees, but enough to make me dangerous to look at the different modalities and realize that there will be some applications that work better on one and some better on the other. For investors, I think right now there are a lot of companies that are private, that want to go public, that are private, that want to stay private, that are public already and available in the market. For me, it's a question of is there a company that is building not just the iPhone, if you will, but the iPhone and the App Store at the same time. The ability to do the application that runs on that computer each successive generation. And what we've tried to do with IonQ is to be that. Build enough applications ourselves to make it relevant either in life sciences or the acceleration of drug discovery or material science, not everything. And then also be able to keep that going. So each successive generation with a roadmap that you can invest behind. So if we were only in quantum computing as we were a year ago, that would be interesting itself. But what Niccolo has done quite rapidly is add the networking piece, as I said, the quantum security piece, as I said, the sensing piece, and the other elements that you may need for different kinds of solutions for different kinds of customers.

Okay, thank you. Those timeframes of maybe being a year or two away, I feel like a lot of your quantum competitors seem to point more to several years away. I guess, is that, would you make the case that your technology is just going to be ready sooner? Or is there just a different, are we different definitional things about readiness? Just how do I think about that?

It's a great question. I think there are a couple of sort of like leading indicators I always look at, right? So when something moves from the lab to a commercial deployment, that's a good sign. When something is a repeat purchase by a customer that says I'll buy your last generation, this generation, and the next generation potentially, that's a validation. When you start demonstrating, for example, as we did with AstraZeneca, the ability, and by the way, that was in partnership with NVIDIA. And you can argue which was the accelerator to the other, and I think it was the QPU probably that was the accelerator to the GPU. There are things you can do on the QPU that you cannot do as efficiently on GPUs and vice versa. So that kind of hybrid computing beginning to be deployed more and more is what I'm seeing. And to me, that's another litmus test for has something reached the ability for it to be deployed in more places. I'm seeing more AI factory data center operators say we want to keep you in there too. And so those kinds of patterns, along with the use cases that I mentioned around AstraZeneca, protein folding with Kipu, and then applications that we will build for an energy grid operator, for example, that is one of our customers who bought our network first and then the computer and wanted us to help them build an application to optimize the electric grid. So data center operators come on, and maybe you saw recently, data centers are falling off the grid just as fast because they sense the electrical current being an imbalance of some sort and they go to a backup power. So grids are having to deal with sudden drop-off loads as much as well. If you're a grid operator, you've got to keep it up no matter what. So those are the kinds of things that I think are real applications today. And for us, like every successive generation, which is one a year, the roadmap that we've built now with a semiconductor base going forward versus lasers in the past allows us to maintain the the cost advantage i think of the promise of quantum computing and also introduce more things in a more predictable way using using a a foundry system that's been built over years and years and years now okay and then the the kind of world

changing applications that you talked about on the earnings call would that be the astra seneca

would that be like what what are those i think those are good good examples of them right when And I say, well, world changing is a very big thing, right? But like looking for the causes of chronic diseases, trying to find how protein folding either affects disease of the brain or memory or not. These are real life things that have already begun to be tried. Some of them get more capable the more qubits you have, as you know. And then others become enabled by more qubits down the road. So our roadmap that we've published is a five-year roadmap. It goes from 100 qubits, which is the next generation machine we're rolling out now. It's our fifth generation machine. The sixth generation moves to semiconductors. And that's where we think that you now start to get economies of scale, lower costs potentially. and then the you know energy consumption as you all know and you know this uh from from all the work that you do on semis um gpu clusters ai factories use a lot of energy yeah um quantum computers of the kind like ion traps that we build you know don't yeah maybe talk about the modalities

and why ion trap i mean it's always seemed to me aesthetically appealing to have something that I can just sit in a box on my desk and do stuff rather than build low-temperature superconductors. But obviously, there's success on all modalities at this point. Like, for technology that's getting relatively far along, there still doesn't seem a clear-cut consensus on which modality is best.

Yeah, I think – and that's fair. I think that there are some who are choosing superconducting, and that's great. I think that it requires, as you say, not just cooling, but, like, down to 0.2 degrees Kelvin. I've been told that it sometimes takes a month to turn a machine like that on and get the temperature down. But, again, it could be something that is a long-term solution. There are others that are, like, still require scientific breakthroughs. Photonics tends to be one of the hardest ones, for example. In the case of ion trap, whether lucky or smart, the founders of this company, like 30 years ago, whenever they thought of this, and wrote the paper on it, started with ions which exist naturally in nature and don't have to be created. Have a charge to them, so you can actually say to an ion, do this, do that, so make it dance, if you will, entangle it, use it for computation. It naturally has fewer errors to correct to begin with. And then, so you don't have the overhead of error correction as much. And then you have the ability to build applications that, as we're doing ourselves as a company, scale with the qubit count that you develop. And it's the logical qubits, or not the physical qubits that companies talk about often, I think. Joe, you know this. It takes standards sometimes for everyone to talk the same language. Those standards don't exist currently. And I think that makes it easy for investors, companies, customers to get confused. Which one is better? This one says I have more physical qubits. This one says I have that. To me, in the end, it's all right. Which application can you run first on which machine? And that's kind of what we're trying to do. Do both. Build the machine, build the application.

And how does having that full suite of, you know, networking, sensing software that you've acquired, how does that help you to get there?

Yeah, so I worked at Cisco, and, you know, one of the things that I learned is obviously, like, be agnostic, like, connect anything to everything. And number two, make sure that you have everything in one roof, and then you can start with a customer buying one aspect of your portfolio moving to another. So we already have examples of that. We have a customer that is an electric grid operator that had built a dark fiber network, high-quality infrastructure, and said, I want to actually put a quantum network on top of this and provide more connectivity to my growing list of enterprise customers in my region. And then said, I now want to buy a quantum computer so I can deliver more services and applications to them as an additional revenue source. And we've had others that start with quantum computing and stay with quantum computing and don't need the networking. We have in Chicago, for example, a computing device deployment leading to, okay, I need to connect to this other place as well. Our networking solution, which we're selling today globally, connects our computer to anyone else's computer. So it's agnostic. And a lot of the work we did over the last four or five years was learning how you do that. How do you take a quantum computer, put it onto a telecom network, same signal being carried as DWDM and other things, and then translate it back to the frequency that you need to have for quantum computing. The other elements around sensing, you know, which is around making sure that GPS, which can be jammed, it has a replacement of some kind in certain environments where, for example, the U.S. can depend on PNT, position, navigation, timing. and not face the same jamming. That was an idea that came to us from a customer, and maybe more than one customer, who actually said, well, if you had that capability, we'd look at you too. So they may start in one place and end up in another place. The cross-selling opportunity, I think, those things, when they start to flow through your P&L and your revenues start to grow, and we just reported, as you know, $130 million, we guided for this year as well. And then, you know, organic growth continues to be 80% or better. And I indicated 2016 could be even 100%, perhaps. That means your core business is growing, and these other businesses are driving more opportunities for growth.

And maybe talk about that 80% organic growth. And I guess how much should we even be focused on revenue as kind of the real value of the company? I mean, obviously, this technology is kind of at a development stage. it seems most important to hit the proof points but you have a lot of revenue as well and and the fact that you broke out organic revenue growth is helpful to understand how much came through requisition so what's driving the organic growth rates that you have and and how much should we care about it

well look as usual product cycles drive revenue growth right so the fact that we keep investing in R&D which for us is like a mantra we have to stick to for my arm days one of the learnings was like 80 80% of every dollar you spend should be on R&D. We're not there yet at INQ. We're trying to get there. But the idea is keep investing in innovation. And you know this better than anyone. And that's how you maintain your advantage for customers. Ultimately, that's what we're trying to deliver. And then hopefully, of course, for investors. The organic growth, some of the metrics that I provided on the earnings call was actually from listening to investors. So it was my second quarter reporting earnings. In the first quarter, I did sort of like a listening session around, what else would you like to hear? And the questions were around, like, is, you know, are you buying things because your organic revenue isn't growing? Or are you still selling mainly to labs? You know, are you still U.S., et cetera, et cetera. So each of the data points was designed to, like, provide transparency into the revenue sources, and we talked about commercial, we talked about international growth, we talked about organic growth. I'll add more metrics as we go along if it feels like it helps investors understand, like, how are you getting all of this growth?

Because I hear both the positives and the negatives, but you're kind of like, it's like judging too much, being too judgmental about revenue when we're sort of, nobody's claiming that we're doing something yet yet that's a breakthrough. Like, we're kind of getting there, but, like, that's when you get paid, really. And so everything up until that point is going to be development and is going to be, you know, there's some related party and all that that goes into any kind of development relationships. But I feel like it's really the technology proof points that I mostly would care about.

Yes, you're absolutely right. And I think that the fact that we have now put most of the scientific breakthroughs behind us, achieved four nines, fidelity, for example. There's a mouse over there. Freaked me out. And all over San Francisco. So, you know, others, other modalities still have some more work to do. I think what we now have to do is ensure that we can get from where we are today, which is our fifth generation machine with 100 qubits to 256 qubits at the end of this year, 10,000 next year, 20,000 up to 2 million. And I think that is a roadmap that we have been working hard to de-risk and execute, if not accelerate. So some of the things we've done are to ensure that we can achieve those sooner and move things to the left. The more you move stuff to the left, the earlier you can deploy some of the game-changing applications you're talking about.

And I don't mean any of that critically. At this point, it feels like, you know, really, this is a technology that isn't really that economic yet. And so the development is going to be what drives the revenue. I guess in that context, you're going to be at GTC later this month at NVIDIA's developer conference. And obviously, NVIDIA, I've sort of seen this evolution from sort of being dismissive of quantum to actually embracing it and potentially making a lot of money from it because he's got a lot of co-processors that sit in these quantum systems. How do you think about that relationship? How do you think about the advances that they're making? And is that something that will help you guys move forward as well?

Yeah, we've been working very, very closely with them, as you can imagine. I mean, our customers also want us to work very closely with them, right? So they may start with an AI cluster, AI factory, data center. And then some of the customers are saying, I want to put the GPU next to it. And so we work closely with them to make sure it interoperates with CUDAQ, of course. But also, like, AstraZeneca was done jointly with them, right? And it was an effort that AstraZeneca benefited from. It allows us to take that and replicate it with other pharma companies also. So I see, like, a QPU, GPU environment where some things are done best forever on GPUs, perhaps. Other things better done or best done on QPUs. And so I don't think one is replacing the other, for sure. I think one is going to be augmenting the other. There may be quantum-only deployments. I can see those happening as well. But like more and more data centers around the world, we announced KISTI in Korea, for example, and they have a GPU supercomputer that they've deployed. They wanted the quantum computer to work with it, sit next to it. And that's what we're deploying there. So, yes, we're going to be a GTC. You'll hear more about what we're doing with them. But I see that as a long-term partnership.

Okay, helpful. Speaking of long-term partnerships, can you talk about the role of the U.S. government and obviously a big federal priority in quantum? How is that helping you guys?

Yeah, look, I think there are many dimensions to that question for sure, so I'm going to take it one at a time. I think one that you're referring to is what DARPA is doing right now in terms of its A, B, and C sort of like, I call it a good housekeeping seal of approval process to say this modality, this technology is ready to be deployed. There are customers that I think in the government that depend on that and look at that for validation of the technology. We work very closely with DARPA, of course, and we've gone through A and B and C lies ahead. What we're starting to see, I'm starting to see, is customer engagement already start to happen with government customers because they've seen you go through A and B. They will continue to look at it, of course. And whenever C happens, you know, they'll either have waited for that decision to happen or maybe made up their choices even earlier. It's good to see that, and it's good to be, frankly, among that process. The other is the QBI, and certainly that allows multiple agencies to also coordinate and makes it easier. I think that, and you may see this as well in what you look at, virtually every country that we have met with, I have met with, is putting quantum up there among their top five, if not top ten, priorities as a nation. And yes, they want AI. Yes, they want the ability to do genomics and other things. And yes, they want quantum also. So it's not just the U.S. It's like virtually every government in the Middle East and Asia. We've hired a new CRO, Scott Millard. He comes from Dell. He worked directly with Michael Dell and helped scale their AI business from like nothing to 20 billion-ish and more. You follow them even more closely, I'm sure. And he's bringing this very disciplined scientific approach to say pursuit and capture, target the right customer, right employee. What I love about one thing he said was, like, follow the AI money. Like, follow the AI money, because that's where you're going to need a quantum computer, either now or in the future. And he was right. We're starting to see that play out. There's a lot of AI money.

Evidently, yes. Seems to me. And then any other countries to highlight? You said other countries outside the U.S. are critical.

I mean, there isn't a country in the world that probably doesn't want to have something. As these machines become more powerful, and I mean, like, beyond 100 kilots, probably 256, maybe 10k. At some point, I think we start seeing similar export control questions that we need to deal with. So, we are starting from the get-go and saying, like, assume that regime is in place already. Let's ensure that we're selling a computer to a country where we will be able to, like, support that customer over a long period of time. So, there are some countries we will just not do business in, as you can imagine. There are many countries, however, that are wanting it. We can do it. But even then, we'll check with the U.S. to make sure that this is going to be something that we can support for multiple generations of machines over time.

Okay. You talked on the earnings call about demand exceeding supply. Can you talk about that a little bit and how you think about the supply chain to serve that demand?

So, like, there is no manufacturing foundry process for classical computing machines. So we had to build our own factory, right? So all of the generations, the five generations I've talked about, including the current one, we build in Seattle. And so we design between College Park and Seattle and build and then deploy at customer sites. So we're a manufacturing company as it is. The demand we're seeing for the 100-qubit machine that's rolling out this year is higher than we had anticipated based on prior demand projections for earlier generation machines. I think the applications and the machine may be hitting the spot for many and more customers because they want to do that. So I started on September 5th, I think. By September 10th, we had already started deciding what we need to de-bottleneck, either in our ability to manufacture or in our ability to deploy. Both are equally important. And, again, the COO focuses a lot on that to make sure that we can meet the demand. And, yes, absolutely, there's demand for more tempo machines than arguably we can manufacture today. Thankfully, that facility in Seattle does have an extra floor that we also own with plenty of real estate if we had to expand. However, as we move from laser-based machines, which are prominent these days, to semiconductor and electronically controlled ion traps, we can start moving into a classical semiconductor foundry with older nodes, not our own factory. So at some point, the manufacturing can be stopped in Seattle and moved over to an existing foundry.

That's helpful. So I just have one more question, and then we can open it to the audience, if there are any. Your cash balance, $3.3 billion. How do you feel about that? Do you want to raise more? The company does continue to be acquisitive. You know, just how do you think about the cash balance and the uses of that cash?

Yeah, look, I think having a strong balance sheet, having cash, gives you a line of sight to being able to invest for the longer term. One of the pitfalls of all public companies is the 90-day cycle and the obsession with this year's financials and, like, you know, what will the world think if I spend more on R&D, et cetera, et cetera. The ability to have enough cash to think, like, multiple years, not just for acquisition, but even just organic investment in R&D, infrastructure, and so on, gives you the confidence, but also it gives your customers the confidence that if they purchase something for you, you're going to be around for a while. In my experience, probably in yours, that's very, very important to have.

When you are competing with IBM, Honeywell, people like that that have a lot of resources as well.

Of course they do. I respect IBM in everything that they do. And I want them to keep investing in this area. I hope they'll keep investing in this area because we need to have an industry. You can't just have an industry with one company. So IBM, of course, superconducting, their solution, of course. What's not to like? Again, what we're focusing on is a bill of materials that is less than $30 million. As the machine gets more powerful, we start making it on semiconductor base. It should get cheaper, not more expensive. Ours plugs into the wall. Superconducting needs a little bit of a grid.

That is cool to see, I have to say, just seeing the facility. It looks like it just plugs in, just sat right next to my desk.

But the point is that when you think about a customer who wants to invest for the longer term and thinks they're getting the $100 now, the $256 then, and $2 million eventually, they're going to be living with that investment choice for a long time. And with Quantum, or as with anything, it's not just about the initial cost of the machine that you buy. It's also the running cost once you have it. And the cooling alone, keeping everything low, temperature, helium-3, et cetera, et cetera. TCO, compared for an ion trap type thing to an equivalent, let's call it generic superconducting, is not even a comparison in terms of TCO. Not everyone's thinking of a TCO, always. But I do think that over time that will become a compelling argument for why doing really, really high-end computing with lower energy consumption and lower cost, frankly, becomes an advantage.

Okay. Great. Let me see if we have questions from the audience. Okay. If not, we can wrap it up there.

Awesome. Thanks for having us. Really appreciate it.

Thank you.