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Podcast with Scott Faris, CEO of Infleqtion

Scott Faris, CEO of Infleqtion, is interviewed by Yuval Boger. Scott and Yuval talk about Infleqtion’s broad product portfolio, CEO tips for turning an organization into a product company, the importance of quantum clocks, and much more


Yuval Boger: Hello, Scott, and thank you for joining me today.

Scott Faris: Absolutely. Thanks for having me.

Yuval: So who are you, and what do you do?

Scott: Wow, that’s a big question. So I’m Scott Faris. I’m the CEO of Infleqtion, a company formerly known as ColdQuanta. I’ve been with the company now about a year and a half. I’m excited to have taken on the opportunity. My last company was really tackling a hard problem. This is ten times harder, and so I always run to the hardest problem in the room. And so I’m excited to continue working on this one.

Yuval: Of the things that appears unique about Infleqtion is that you’ve got such a broad product portfolio. Maybe you can describe the portfolio and how do you see that playing over time. What’s important now? What’s going to be important in the future?

Scott: Sure. So as you recognize when you say the word quantum, people’s eyes kind of glaze over and roll the back of their head and, “What are you talking about?” And so one of the things I’ve learned over the years is how do you really describe the business in a way that people get? And the way I’ve come to describe Infleqtion is that we have a really simple business model.

All that we do is we just simply shoot atoms with lasers. That’s it. Now in that is a lot to unpack, and certainly there’s a lot in there. But from that simple concept of being able to identify, capture, trap, manage, manipulate, and measure atoms individually and in groups, that gives us the ability to really do a lot of things. On the most complex things that we’re working on is work in our gate-based computer. And that’s something that we’re obviously quite excited about, but something that has a longer roadmap associated with it to get to real points of productivity.

On the other end of the spectrum, we do a lot of work in sensors, and there’s a lot of history with the company. The company just celebrated its 16th birthday yesterday. So Infleqtion’s not a startup in a classical startup sense. We’ve been around for 16 years. And so the first 15 years of that history and journey of the company was in research and it was really a lot of research in the area of quantum sensing. Both quantum sensing from neutral atoms but also work in ion traps. Because I like to say we’ve been doing this so long, we’ve actually had to invent a lot of the basic pieces that anybody doing work in neutral atom comes to us for the parts and pieces they need to build their experiments.

Yuval: So if I’m a customer, I can go to you and buy parts and pieces.

Scott: Yeah.

Yuval: If I wanted to build my own quantum computer, I could also buy sensors, right? Or technology for sensors.

Scott: Yeah, so the way we’ve migrated the company, the simple way to think about this again, in the early days it was doing world-class research. We wanted to continue that legacy. We think that’s an important part of the business. We’ve been very fortunate that we’ve been able to partner with the U.S. Government and U.K. government and other governments as well as private companies to do some of the research.

When I joined a year, year and a half ago, it was really with the charge to look into our trophy case of sensors and prototypes that we’ve built over the years, and ask: which one of those actually has commercial market potential? And how do we think about now really building the commercial company alongside the research business? And so part of the name change actually was really to reflect that we are a commercial company. We are focused on bringing products to market, and products to market in volume.

Infleqtion, we thought, was appropriate as a name that shows what we’re about and why we’re here. But again, we’re also continuing on the research front. And so within Infleqtion we have what’s called ColdQuanta Labs, that’s our core old research group. And another way to think about it is that if you’re familiar with Lockheed Martin’s Skunk Works, that is where they take their hardest problems, and it’s a dedicated team of people with just tremendous history.

That’s really the core of our business, where ColdQuanta Labs is our Skunk Works. And that’s a model we’ll continue to grow and expand. But for us right now, we’re focused on bringing our first generation of optical clocks to market, followed by work that we’re doing in Quantum RF, and then a variety of other things in positioning, navigation, and timing – known as PNT – and gravity measurement. And again, these are all things that we built prototypes for. But we’re very thoughtful about it. We like to say we do lots of things, but we don’t do it all at the same time. And so right now, our focus is really about bringing clocks to commercial scale, really bringing the size, weight, and cost down so that we can build networks of clocks.

Yuval: Give me a tip as a CEO. I mean, is it difficult to turn an organization from a research mindset into a product mindset? What’s involved in it, and what would you advise others that might be trying to do the same?

Scott: It is difficult, and it’s really difficult with a company that’s been really great at being a research company for 15 years because that is the DNA of the company. And for me, this was a unique opportunity because I saw the level of research and accolades, and respect that this organization had. And we didn’t want to destroy that. And typically in a startup, you go through an early research phase where you’re trying to figure out what you want to build. You eventually triangulate on an opportunity, and then the researchers need to become product people. They themselves need to go through a transformation.

One of the things that is unique about what we’re doing here, as I said, is we’re preserving that research legacy through ColdQuanta Labs. We want those physicists to continue to push forward on really defining the boundaries of what quantum sensing machines could look like, what quantum computing looks like, and we’re building a commercial organization next to it.

That’s a unique way of doing it. But I think in terms of advice, culture is key. Nomenclature is key. In a research company, you have PIs. In a commercial company, you have product line managers. And so just even titles make a big difference in how a company thinks about itself.  … And I’ve done this my entire career. I’ve done seven or eight large spinouts. The reality is most companies don’t make it to the other side. The casualty rate is like 90%. And a lot of that has to do with culture. A lot of it has to do with commitment of just, “We’re going to be a commercial company.” And in the early days of my career, I was working for a company that time would’ve been called an SBIR mill, for example. You know, we were living on three or $4 million a year of SBIR funding. This was in the ’90s. And so that’s a lot of money then.

And we made the decision to go cold turkey. Because we knew that once you’re in that SBIR process, the whole mentality of the company is, “Let’s go get another grant to last another couple quarters.” And we made a conscious decision that the only way to stop that was to basically stop writing proposals, focus on commercial products, and live or die by whether we could sell anything. I’ve seen that happen time and time again, but it’s that kind of a really dramatic cultural shift that a company needs to figure out how to navigate through.

Yuval: You mentioned clocks. And I can understand why clocks are useful in a GPS setting, but where else would they be useful? And why is that an interesting business?

Scott: Everywhere. You know, it’s funny. I was thinking of my Apple Watch and you know … The reality  is that everything is calibrated against time today. Financial markets, data centers, databases, everything has timestamps associated with transactions. That’s to ensure the integrity of a transaction, to allow matching of transactions.

And so we live in a digital world. Everything is a transaction in the digital world, everything needs to be validated. And again, as we start thinking about machine learning and AI, the amount of data, what we do with data and the ability to manipulate things in a positive way and a negative way, requires more and more integrity.

The foundation of integrity is time. We knew something happened at a particular point of time. And we started thinking about that. It became more than, “Okay, well yeah, I need this, so my car knows where it is. Or I know where my car is.” And I spent seven years in the autonomy business. And again, one of the fatal flaws in that business is you couldn’t rely on GPS. You know when you drive into crowded cities, you lose your GPS signal.

And so this idea of really thinking about time and recreating time as a new standard is really what we’ve started to push on. With atomic clocks, optical atomic clocks, you can tell time a thousand times more efficiently, 10,000 times more efficiently. But I think more importantly is that you can distribute time differently. Right now, the time comes from GPS constellations. It’s a byproduct of positioning, navigation, and timing, known as PNT. You need timing. The T in PNT is timing.

But as we’ve seen with what’s going on in the Ukraine and what we’ve seen going on elsewhere, a space-based time distribution system is no longer enough. And in fact, one of the challenges, it takes time to get time here. So when you broadcast a signal from a satellite to the earth, it takes time. And that latency is now actually becoming a barrier as well. And so what our view is, is that time needs to be rethought. It needs not only to be more accurate, it needs to be more reliable.

And you get there through terrestrial and space-time distribution infrastructure. Which now means you need lots and lots of precision clocks, like tens of thousands, hundreds of thousands of clocks. Highly distributed, highly networked, which now means the clocks need to be inexpensive, they need to be robust, and they need to be accurate.

We can do the precision timing piece. The challenge now in clocks is how do we make them small, inexpensive. And this is really what we’re focused on at Infleqtion, is not only inventing the clocks but, “How do we make them in high volume at really low cost?”

Yuval: At the other end of the scale, you make quantum computers. You’re building quantum computers. Now some would say … and I know the counterargument but would love to hear your perspective. Some would say that companies should focus, right? That you can’t do clocks and sensors and software and quantum computers and many other things. Where is the synergy? Is that because it’s all laser shooting at atoms? Is that because it’s the same customer that needs everything? How do you see the synergies?

Scott: So you hit the nail on the head. We just shoot lasers at atoms, whether we’re building a computer, whether we’re building a clock, whether we’re building an RF receiver. It’s the same fundamentals. Again, I oversimplify it. But in reality, it’s a photonics problem. Again, if you look particularly in the neutral atom space, the ion trap space, to a large degree, the industry is really being driven by a handful of laser companies that are providing scientific grade lasers for this particular purpose.

And that’s great for research purposes. But to really make these things industrialized, to make them hardened, to make them scalable, and really to make them more reliable, the photonics ecosystem around the cores, the photonic cores, or the anatomic cores need to shrink. They need to become smaller, they need to become tightly packed. The lasers need to be better.

And so in our particular case, what’s really unique about our business model is that we’re investing heavily in what I call the photonic core. Our CTO is a laser guy. He’s a photonics guy. He’s an AMO physicist, but he spent 20 years building industrial products and laser systems. And that was really a recognition on our part that we have a tremendous amount of people looking at the quantum physics issues. We were unbalanced in the people looking at the underlying issue, which was the photonics problems.

And so for the advancements that we’re making in shrinking down the sensors, making them more robust, packing more lasers in, we’ve been smart about it that that roadmap actually supports the underlying roadmap for our computer work. So the better we get at lasers and everything we do, the better the computer gets.

Yuval: You mentioned that you were at the company for about a year and a half and came from a different field. What is the thing that most surprised you in the company or in the market relative to where you thought was going to be going in?

Scott: I would say two things. A pleasant surprise is how similar it was to what I just did. It’s the same problems. Right? In many cases, it’s tapping into the same networks of people. Again, the color of light changes. We have a different set of wavelengths that we’re working with now. These are unique wavelengths for quantum. But the fundamentals, the lasers need to be packaged. They need to be smaller. Again, everything I just talked about applied really for my last three companies.

And one of the things when I looked at this company, and I looked at the risks associated with it, I didn’t really see this as a risk. I think others see it as a risk because they don’t necessarily know where to go to find all of these capabilities. And again, they don’t exist with a billboard, but they exist. They exist … You know, my last company was in the LIDAR industry. Again, we didn’t shoot lasers at atoms. We shot lasers at tires 300 meters away in the middle of the night moving 70 miles an hour.

We need to be really good at doing that. Otherwise, lives are in danger. Here, we need to shoot at atoms, we need to be good at that. And so the people that solve those types of problems can move from industry to industry. In fact, we’re starting to see more LIDAR people move into the quantum industry because of this.

I’d say that the other surprise, the other side of the spectrum, was this issue of culture. And it was a 15-year-old startup, and as I said earlier, the culture was deeply embedded. It was ingrained in everybody, and that was great. Everyone’s passionate about quantum. But ultimately, the understanding of quantum research versus quantum product was a much harder road to traverse. Not because the people aren’t smart, not because the people aren’t really passionate about what they do. It’s such a different world. And words matter. I joke that I say the word quality. And quality in a commercial company and quality in a research organization is the same word. They mean entirely different things.

And so you have to recognize that even words and how you use them, and how you think about things and present ideas to the research team to say, “Hey, we need to build a quality organization.” They say, “Wait, we have one.” It’s like, “Well, no, that works for prototypes. It does not work … We can’t repeat problems. Right? The quality system now has to catch things because if we make 10,000 of something that’s expensive to mess up. If it’s just one of something that’s recoverable.”

So that to me, was an exciting personal journey, just really having to relearn a lot of things. And frankly, as a CEO, how to get people to come along and see the bigger picture.

Yuval: We see a lot of fluctuations in the capital markets. You know, stock markets go up and down. Public quantum computing companies may not have preserved the value that they had during their IPO. Lots of money is being spent in Europe and maybe less so in the U.S. How worried are you about that when you’re trying to build so many different things that obviously require a lot of money?

Scott: Yeah. Well, I mean, the bottom line is this is deep tech. Right? Deep tech’s hard. It’s expensive. I think one of my personal frustrations in the United States over the last 30 years is we’ve lost our appetite. And in many cases, we’ve actually lost the knowledge of how to invest in deep tech. It’s hard, it’s bumpy, it’s by nature … These are the hard problems. Again, my nature is I love going to the hardest problem in the room and see that as a challenge. And this is why I do things like this.

But it does require patient capital. It does require visionary capital. Again, a good example is just simply building a production prototype in a traditional venture model would be, “Okay, great, now we can hand it off to someone to make it.” You know, spending someone else’s capital to figure out to make it. The reality is no one knows how to make it. And so not only do we have to invent the product, we have to invent the way to make it. In many cases, we have to invent parts of the supply chain that don’t exist. And we have to onshore parts of the supply chain because there’s also a national security aspect of this that’s quite critical. So we have to onshore capabilities as well.

That’s not a traditional venture investment model. That is a model where sovereign wealth funds and non-traditional investors look at the return for literally creating an industry. And we’re not innovating on top of something trying to make it better. We’re creating an entirely new industry from scratch. And this is, in many ways, we’re sitting in the ’50s and ’60s thinking about the semiconductor industry of today. And I think that’s one of the challenges on compute, frankly, is that we’re sitting in the 1960s thinking about these multi-core processors that we take for granted today.

Again, they’re all possible, but the ecosystem doesn’t exist. The supply chain doesn’t exist. There’s a lot of, in some cases, different modalities. There’s material sciences that need to be solved. They’re all solvable in time, but it’s a long, long investment. What I liked about what we do is that in terms of the neutral atom space is everything that we need to do to build anything already exists. We don’t have to go and invent stuff in material science. It’s already there. We have to figure out how to make it purposeful for what we need it to do, because it’s a general capability. Again, lasers are a great example. People are using these scientific lasers because they’re highly tunable. Because you can’t buy lasers specifically for quantum. The market’s not there. This is the traditional crossing the chasm challenge.

And we as a company have … You know, we’re pushing forward to say, “Look, it’s not only about inventing the product, but it’s also about, ‘How do you make the product?’” And so that takes us into thinking about how we collect capital on a global basis. But like I said, at the end of the day, the efficiency in the model is if we’re solving the photonics roadmap and we’re doing it intelligently, that’s 80% of the problem that we have for most of our product portfolio.

Yuval: As we get closer to the end of our conversation today, I wanted to see if there are a couple of customer projects that you are particularly proud of or particularly happy to describe of the various things that you do.

Scott: Yeah, so I think we had a great announcement at Q2B with our division in partnership with Morningstar, starting to think about on the software side. So again, we also have a software stack, a software layer and application layer of the organization. I’m particularly excited about and I’m proud about that. Again, that team did tremendous work.

Again, it’s early indications of what business models could be. But also at the same event, EPRI had run a competition for white papers. And two of our papers came in first and second place. One was thinking about quantum sensing networks in managing grid infrastructure. And thinking about how we could use clocks to do that, and how time as a service for grid infrastructure could transform the security and the efficiency of grids.

And so again, as we think about quantum it’s not like, “What’s the hardest problem in the world we could throw at a quantum computer?” Right? Those computers won’t exist for a while. What can we do with today’s infrastructure in today’s capabilities, which may not even require compute, but could require some of the algorithm talent that’s working on the compute problem, but now looking at sensing. Looking at distributed time networks, looking at distributing networks for quantum RF for example. And applying those same learnings around compute into these other areas.

What’s nice about that is we’re also continuing to learn about compute as we do that. But we’re doing it in a way where we have near-term products. We can start to try revenues at scale. And again, in the background continue to collect this learning and apply it into our compute efforts.

Yuval: And a hypothetical question, if you could have dinner with one of the quantum greats, dead or alive, who would that-

Scott: Well, that’s a good question. Well, I don’t … You know, I don’t know. That’s a really good … That’s a great question. To me, I think I got to turn the table on you. Again, this isn’t my view. This isn’t a quantum problem. This is a business problem. And I think that my first interview when I came on board, it was my first day on the job, my first hour on the job actually, that I was asked this question is, “I’m looking at your credentials here, and I don’t see that you’re a physicist. I don’t see that you actually have any technical or engineering background. And best I can tell you’re a finance person.” I’m like, “Yes.” And the question became, “Why is a finance person qualified to run a quantum company?” I’m like, “Because we got a lot of brilliant quantum people working on the quantum problem, but we got to figure out how to turn this into a business.”

And that’s what I do. I engineer creation of high-value, high-growth businesses. And so to turn the question around, the one person I would want to have dinner with is Elon Musk, because the way he thinks about problem-solving and the way he is committed to these leaps of faith, we need these leap of faith thinking moments in quantum to make it real. Why? Because it is that hard. 99% of the time we’re faced with failure. And it is hard to keep going on day after day after day when it is so hard and so expensive, and there’s failure after failure, but we need to do this, we have to do this. We have to do this because of national security reasons. We have to do this because this is the future. We have to do this because the semiconductor roadmap is coming to an end. It’s getting more and more expensive to extend Moore’s law. And so again, we have to push through this and it just requires a very different type of leadership and thinking to drive through these hard problems.

One of our corporate values is grit. And we debated a lot about that. But grit is absolutely important, imperative, and necessary to make this happen. And that’s why we said this is one of our values is that we will persevere, we will push through despite the adversity. And that’s a leadership challenge.

Yuval: I certainly hope you will. Scott, thank you so much for joining me today.

Scott: Yeah, thank you. Thanks for taking the time.

Yuval Boger is an executive working at the intersection of quantum technology and business. Known as the “Superposition Guy” as well as the original “Qubit Guy,” he can be reached on LinkedIn or at this email.

March 27, 2023


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