The Next Wave Podcast

Ep 51: Matt Johnson, CEO of QC Ware, on Quantum Computing

November 20, 2021 The Next Wave Podcast
The Next Wave Podcast
Ep 51: Matt Johnson, CEO of QC Ware, on Quantum Computing
Show Notes Transcript

This week we have as our guest Matt Johnson, CEO and Co-founder of QC Ware. QC Ware focuses on Enterprise Software and Services for Quantum Computing with offices in Palo Alto and Paris, and soon, Tokyo. With one of the largest teams of quantum algorithm experts QC Ware strives to make quantum computing easily accessible by classically-trained data scientists and to offer performance speed-ups on near term hardware. Enterprise customers include Airbus, BMW Group, Goldman Sachs, Roche, and Total. Partners include AWS, D-Wave, IBM Quantum Computing, IonQ, Microsoft, and Rigetti. 

Matt as CEO of QC Ware also started and hosts annually the industry conference for Quantum Computing, Q2B, which happens every December, and each year includes the top industry and academic speakers and companies, including theoretical computer scientist Scott Aarronson, based at UT Austin, and John Preskill, Richard P. Feynman Professor of Theoretical Physics at the California Institute of Technology, who coined the term Quantum Supremacy. 

Register here for the Q2B conference, happening in-person at the Santa Clara Convention Center December 7-9, 2021: https://q2b.qcware.com/

Matt is extremely impressive with a very diverse background - he was formerly a partner at Apollo Management based in London and prior to that a managing director at Credit Suisse. Matt holds a BS from the US Air Force Academy and an MBA from Wharton. He also completed a solo crossing of the English Channel and remains an avid swimmer. 


Matt Johnson:

It's the Next Wave Podcast, episode 51. I'm James Thomason here with co host Dean Nelson. And with us this week is Laura Roman. She's covering for Brad Kirby, who's out again with bronchitis. This week we have as our special guest, Matt Johnson. He's CEO and co founder of QCWare. QCWare focuses on enterprise software and services for quantum computing with offices in Palo Alto and Paris and soon Tokyo with one of the largest teams of quantum algorithm experts, QCWare strives to make quantum computing easily accessible by classically trained data scientists and to offer performance speedups on near term hardware enterprise customers includes Airbus BMW, Goldman Sachs, Roche, and total and their partner with everyone AWS D-wave IBM Quantum Computing Inq Microsoft and rigetti. Matt as the CEO of QC were also started host annually the industry conference for quantum computing q2 B, which happens every December coming right up I assume, at each year includes the top industry and academic speakers and companies including theoretical computer scientists Scott aaronson, based at UT Austin John Cresskill, Richard P. Feynman, Professor of theoretical physics at California state of technology who coined the term quantum supremacy Matt is extremely impressive with a diverse background. He was formerly a partner of Apollo management based in London. And prior to that a managing director at Credit Suisse. He holds a BS from the US Air Force Academy, an MBA from Wharton. He also completed a solo crossing of the English Channel and remains an avid swimmer. And that's probably the most impressive thing what was that? Like Matt? Thanks to a woman who coached me and coached a couple people like me who were aspiring channel swimmers, the swim itself was manageable only because the grueling training that she put all of us through in Dover harbor down in Dover, England, was even harder. And it's kind of like I think it was Erwin Rommel, who said something like hard in training easy in battle, some general said that I think it applies to anything that's physically or mentally taxing, you know, trying to prepare yourself by doing things even harder. But anyway, it was a it took me 13 and a half hours, it was cold. But I have to say that the coaching and the team and the people around me were just extremely helpful. It's a very intimate community of people, people, that's when the channel and they're very supportive of each other. So yeah, that's what it was like, you're at the end, you're freezing. What is the first thing you ate or drank? What did you do when you're done? That is a great question. Actually, what happens when you land on the French coast, the first thing you have to do is clear the waterline because to have actually crossed the channel, you have to get up all the water, including the wet sand. So you kind of walk or stumble into dry sand, you grab a couple stones, pebbles, as they call them in the UK, and you put them in your swimming costume, your swimsuit, and then you swim back up to the pilot boat that escorted you across, you know, the kind of plot of the course that you have to go back out again. Yes, you do. You get on the boat, the first thing I ate was the following. In the UK, there's this product like, you know, it's all sugary stuff. It's like a pancake, and it probably is about a pound and it's wrapped in cellophane. And you can buy these things for four or five quid and the supermarket's there. And so I had two or three of those, and I just wolf them down, because your body's calling for carbs. You don't want simple carbs he wants once again, and so you can just eat prodigious amounts. And that is what I ate. Yeah, yeah. And I have to say, you know, we started to record this podcast earlier, we had an audio problem, and you left the office on your bike, and like blaze the trail back to home, so you could record from the home studio. So you ride your bike every day as well to work. Yeah, I mean, I have a commute bike that I happen to ride every day in Palo Alto. So if you see me out there, don't hit me. And then get a road bike that gets used with some friends who are also road cyclists and just west of Palo Alto, which is where I am, or the foothills of the Santa Cruz Mountains. You know, your kind of former hometown is named after that. But anyway, there's good hills, there's good hill climbing out there. And so yeah, but it's, you know, Palo Alto is, it is obviously the tech hub. I feel very lucky to be here, because it truly is the community of people out here who want to build things that really help each other. But it's a very quiet, you know, it's a very actually a really quiet town. It's very green, very pretty. It kind of looks like, you know what you would think everything in America looked like in the 1950s. You know, a lot of smaller kind of bungalows that happen to be nicely preserved here. So it just feels really, yes, safe and quiet. It's a nice little town here in the middle of the Silicon Valley.

James Thomason:

And you know, Laura, you come to us through Laura, like, like so many people do these days. So how do you know, Laura?

Matt Johnson:

Well, Laura might even be better than me at explaining that. Laura, how did we Wow, Matt and I were together a couple years ago, literally two years ago, Autumn 2019 to launch QCWare out of was pretty much in stealth at the time out to the public. And it was a really exciting time. You know, Google had just claimed to reach quantum supremacy, which I'm sure Matt will delve into, but very quickly as the goal of demonstrating the quantum computing can solve a problem that no classical computer can solve in any feasible amount of time. So there was a great deal of public attention on quantum computing, what it means what it can do. So work with Matt from the marketing and PR side to launch the company. And then that same timeframe a couple of months later, he held cue to be which had this tremendously explosive turnout as it does every year. But that year, we had Richard waters, who was the journalist from the Financial Times, and a personal friend of mine, Oxford guy. And he was so keen on learning more about QC, where it is very exciting time. But also Matt and I have a lot in common as people. I have not crossed the English Channel yet as a swimmer. But we have both spent a lot of time in the pool at Stanford for Stanford masters, I thought, I don't think we've ever been in the pool at the same time. I also lived in London like Matt that different times. And I think we have the same birthday, August 28, if I remember correctly, probably not the same year, but I think I remember that coming up in conversation. But you know, it's great to see you again, it's been a while and you know, that was like a lifetime ago, like what you've done since then. I know you have so much to tell us about you just raised funding, you know, you were just in the White House for sounds like it was really amazing experience with being a part of the Office of Science and Technology Policy event they had in quantum computing. But before we get into all that, I think, Dean, you had a question. I did. But actually, I want to state some of it. You did 13 and a half hours across the English Channel. I felt like I did on an airplane in the last 24 hours. So I was in Palo Alto last night. And then I went to San Francisco and then I went to Mexico City this morning. And I landed in Monterey just a little bit ago. So yeah, but that was 13 half hours. I didn't get wet. Just so we're clear. It was a

Unknown:

did you go down there just to get even better weather or what was what's the drawdown there.

Dean Nelson:

There's work down here. Data centers are everywhere. So yeah, my day job and what I'm working on is stuff we're doing here. But the weather is great. It's really nice here. He doesn't conspicuous

James Thomason:

amount of work from Hawaii and Mexico and other subtropical Yeah,

Unknown:

this speech is very suspicious.

Dean Nelson:

I hate to say this, but on the podcast, we kind of journaled the travel here, because I happen to get COVID, two months ago, and I've been so good for almost two years. And then I went to a conference in Texas because nothing ever happens bad in Texas. Kidding. So I got COVID at this conference and came home and then I was basically locked up for 21 days. But since then, I've been traveling quite a bit. I love antibodies, it actually worked out good. So no side effects. Thank God. But anyways, the thing is I did 13 hours on an airplane and my face still looks this way from the damn mascot took it off just a little bit ago. I feel like frontline worker.

Unknown:

A wide awake though he sound wide awake.

Dean Nelson:

Yeah. Oh, good. Oh, good. I think I'm energized on caffeine. But here's my question. So this is really deep, Matt. All right, the majority of our users have no clue what this is all about. So I just want you to explain in kind of third grade English, what is quantum computing, basics

Unknown:

K quantum computing, it's a new kind of computer that has the potential to solve certain problems a lot faster. That's part one of the answer. Part two of it, you know, at its core, a quantum computer like a normal computer, you know, your laptop or whatever is powered by a chip a CPU. And if I took that CPU and put it in my left hand and then put a quantum processing unit, because there are such things that's the core of a quantum computer is a quantum processor, if I put that in Leimert, right. Not many people in the general public would be able to say which is which. So really, at its core, a quantum computer has just like a normal computer. At its core, there's a chip. And it just so happens that with a quantum computer, the fundamental building block is not a transistor, you know, like on your iPhone or Android device, whatever you have, you know, you've got a chip in there that has literally billions of transistors, transistors, like a little gate, well, a quantum computer has something equivalent to that not called the transistor, it's called a qubit. And that qubit is also like a transistor. It's a physical little device. Yeah, let's leave that graphic up. I'm not sure if that'll ever get transmitted into the wild along with this podcast. But there is a draft pick up right now. But before we even think about all that spaghetti wiring for those superconducting quantum computers, the point is physically on a quantum chip, or a bunch of these quantum transistors or qubits. And the reason a quantum computer is so powerful is that unlike in a normal computer where that transistor is either on or off in a quantum computer, a qubit can be in a very, very exponentially large set of possible different states, not just on or off, but kind of, you know, anything in between that now without going into any of the science, it basically means you were computer scientists, he would say okay, I get it. It's just that each of these qubits can store or manipulate a lot more information than you can on an individual transistor. So let's let's leave it right there. So then the question is, okay, I will take it at face value that that's how a quantum computers built were they good for wire their billions of dollars now being invested into building out quantum computing hardware. And the reason for that is if you're a big company, for instance, a big company that has a lot of hard compute problems, you look to avail yourself of the very best compute hardware You can to solve your problems as quick as possible. So there's always this race, it's competition, you want to get to solutions to hard problems quicker than your competitors. So you can act on them. Like if you're a big bank, and you can price the derivative more quickly than the rest of the market participants will you can trade out that information, make money off it. And that same thing happens in a lot of different realms. So the way these potential future customers look at quantum computing is that they say, I just consider a quantum computer to be an accelerator in the same way that I consider a GPU, a graphics processing unit to accelerate other specific tasks. So the smart people out in the enterprise community, the big huge companies around the world who use high performance computing, when they think about quantum computers and the prospects for them, they say, these are processors or chips or machines that we will use to accelerate certain hard computing tasks. So I'll leave it there. And then you tell me if I've confused everything by saying that and then I'll try to take it backwards. And

Dean Nelson:

so the punch line here is that it's much more powerful computer. It is that is the punch line. Yeah. But it's for I think, also for very specific type of use cases today, right? It does certain functions extremely fast, or at least that what it's doing, but it's not really for general purpose computing, is that correct?

Unknown:

That is precisely right. And the real Gotcha. Although Dean, what you described as the punch line is exactly right. The gotcha is this, the very best and very biggest quantum computers that have been fielded today, like if you went around the country and eyeballed physically, every one of the companies and go over to Europe and well, possibly you'd get the China look at there's possibly not, but what you would find is not one of those machines that's been produced and is up and running today has been proven to outperform any so called conventional or classical computers at doing real world problems. And that's the truth. Now, that's not a bad thing. That's like saying, you know, back in 1961, the very best solid state transistor that was built by Fairchild semiconductors to say, well, they're not as reliable as vacuum tubes. So let's just shelve the whole thing and forget about integrated circuits and solid state transistors, that would have been a mistake. So similarly, yeah, that'll never pan out. Yeah, yeah, exactly. Don't invest in any of that. But similarly, you know, quantum computing, as a regime is considered an emerging technology, a deep technology, it's one where there's still a lot of, you know, on the r&d side, there's still a lot of AR. And now there's more D, what there is not yet is any, at least not visible in the public domain, any real world use cases. And for that, we're just going to need quantum computers that are somewhat more powerful.

James Thomason:

Can we use it to predict the price of Bitcoin?

Unknown:

Of course, you know, there are algorithms that are used to do that very thing around crypto Bitcoin and all and certainly there are quantum algorithms running on quantum computers that could do something like that. But again, if you wheeled out the most powerful quantum computer on the face of the earth today, and designed a very efficient algorithm, you still would not outperform what you could do on, you know, a data center, high performance workstation, you still can't do that.

James Thomason:

So these things, we obviously are audio here so that our audience can't see what we're showing. But quantum computers look amazing. They remind me of the bygone era of like the very beginning of computing with like the ENIAC and these huge mainframes back in the day with like, lots of cables. And they look like almost like a piece of Clockwork all the way this is digital machinery. And so there's all these tubes and vesicles running everywhere. And usually, I guess the quantum processor you were speaking of earlier, is like the thing that hangs at the very bottom of this. So can you explain a little bit about what this contraption is? We're looking at why does this thing have so many tubes and stuff coming out of it compared to

Unknown:

gladly? Yeah, so let's take that on. Let's take it on systematically, but quickly, briskly, if you did a Google image search for quantum computers, 95% of the images that would pop up would be this thing, James that you're displaying right now, which is referred to colloquially as a chandelier, it is kind of a set of cylindrical metal forms. And around that are all of these cables, these metallic cables that terminate towards the bottom of that system, which is in fact a vacuum chamber, inside of which is the quantum chip, but then you have all these cables that are harnessed and kind of get scattered around the exterior of that cladding. So in fact, whenever you see something like that, you could say, Ah, that's a particular type of quantum computer that's being developed. That is one where the quantum chip is based on is using superconducting qubits. So what actually has to happen what you're looking at is kind of the exterior of a big refrigerator that cools that chip within 10 to 15 millikelvin of absolute zero, so very close to absolute zero.

Dean Nelson:

Okay, and I need people to understand that so first off what I love about these people Is it reminds me of Star Trek. And the whatever there's a turbo drives and stuff they talk about, you see these complicated things, but it's actually what they're using. But to do that, when you say absolute zero, that means that these things have to be cooled to minus 460 Fahrenheit, minus 460 Fahrenheit. So it's very complicated to go back and make these things where compared to what you put in data centers today, we don't get to minus 4060 Fahrenheit.

Unknown:

That is very true. Now, cryogenic cooling is comparatively well developed technology. And so keeping that system cooled is actually, you know, a somewhat trivial problem compared to the machines. But anyway, back to the main storyline. So yeah, you're looking at how a superconducting based quantum computer is architected. And by the way, all that spaghetti wiring that you see, those are actually control cables, they provide control inputs to manipulate or address qubits that are on that quantum chip. And these control lines you need, I don't know two per qubit, for per qubit, or whatever. So you can imagine that if you could fabricate a chip with, you know, 2000 cubits well, you need 4000 or 8000. Controller, I mean, eventually, that becomes very unwieldy. And so there are even groups that are working on integrating that control circuitry onto a board that can also be super cool, you know, inside of the same chamber as the chip is up,

Dean Nelson:

it sounds like transistors on a chip, eventually, you kept compacting them down further and further and getting more on that is

Unknown:

what is going to happen. So certainly, the first quantum computers that were fielded and that have been kind of built out are ones based on this technology, superconducting qubits. And that's because actually, the actual physical qubit is a couple of loops of superconducting material that could be niobium, aluminum, something like that. And actually, these physically, are, you know, 567 100 microns, the diameter, or the kind of length of these loops of wire, and that's almost a millimeter, right. So they're actually kind of large. Now, there are other kinds of quantum computers that are being developed that do not need all of that cryogenics surrounding, you know, in some cases, they need arrays of lasers around them or other things. But certainly, the long term goal of quantum computing is to have quantum computers designed in a way that doesn't require really sensitive cryogenics or instrumentation. I mean, you want these to be more robust. At the same time, the fact that these things require a lot of infrastructure is not an impediment to them being deployed commercially, because quantum computers, just like most stuff, is effectively sitting in the cloud. So when a big company, an early user, let's say pharmaceuticals company wants to use quantum processing to help calculate properties of a candidate molecule that it will use for a new drug, it's not sort of wedded to the idea of needing to have the actual processor sitting within three feet of the research scientists or research chemist, they're fine to access, high performance compute resource over the cloud, they do that now. So it really for the user, thanks to the miracle of cloud computing, or the miracle of compounding in your finance, you know, that probably will not be a big impediment to having early adoption happening.

James Thomason:

So thanks for educating us on what quantum is tell us about what is QC? Where and how do you relate to what are you guys doing with quantum

Unknown:

we are the group, I'd like to think that we are the leaders in the field of developing algorithms, quantum algorithms that can run on these near term machines, like the ones you depicted or displayed on the screen. So the objective of QCWare is to give our customers a competitive edge, we want to provide them with software, which by the way, is accessible over the cloud in our software runs. Now it's on AWS bracket, it will be integrated soon into Azure quantum and interfaces with other quantum computing hardware systems. But basically, what we want to do is to be the first group that can provide real acceleration to hard compute problems, two bottlenecks, we want to help D bottleneck industrial compute problems. That's what we're up to,

James Thomason:

I imagine that your developers have to be pretty good and pretty low level, these guys aren't writing quantum algorithms and JavaScript, I assume

Unknown:

writes the quantum algorithms. You know, you mentioned developers, which you would kind of usually associated with someone who's a coder, a software engineer, actually, the bulk of the team are what are called Quantum engineers or quantum algorithms, researchers, they're people who have this knowledge base of quantum mechanics, linear algebra, applied mathematics. And what they're doing is working on methods to develop, they start with a customer problem, let's say, a materials company, let's leave that anonymous, that same materials company wants to isolate or identify certain properties of, again, a candidate molecule. To do that, you have to first look at the molecule the mathematical structure of that problem, that system these electrons fermions and try to figure out the way to model that most efficiently onto hardware. And to do that you need an quantum algorithm. So in quantum computing, it's the algorithm that more or less directs traffic on the hardware, it tells the qubits what to do. So we're that bridge are the bridge between this hard problem where it's unclear Hey, can this be shoehorned onto a quantum computer? And can it run faster on a quantum computer than on the machine I'm using now. So between that problem and quantum computing hardware that's exposed and available for us to run,

James Thomason:

that sounds difficult and requiring highly specialized expertise. How many people do you have in the company now?

Unknown:

We have 32. And we're growing, we'll probably be at 50, within the next roughly 18 months. And yes, it is very difficult in the field of quantum algorithms researchers is quite small, but growing, of course, as quantum computing, becomes sexier, you'll find you know, eight years ago when I started looking at quantum computing as something I wanted to, you know, put my shoulder into, if you went onto any campus, let's say a big 10 campus like Purdue or Wisconsin or whatever, right, Middle America and sort of asked any sophomore in college in computer science or physics, have you heard of quantum computing? Most would say absolutely not. If you went there today into some cafeteria, in you know, Bancroft Hall at Indiana University, you know, you would all of the physics undergrads, every last one of them would know about quantum computing, and they'd have a view on it. And some would say, yeah, I really want to get into it. So it's really changing. But the reason I say that is, there will be emerging a very strong and large crop of quantum computing talent in the next five or 10 years in this country and around the world. Because all of these STEM students who are always gravitating to the coolest, the next big thing are now starting to see quantum computing as being one of those next big things that will make it easier. Yeah, go ahead.

Dean Nelson:

I got to jump in on the geek side of this because just along that same Star Trek theme, if you think about what really is enticing to this, or something that just fascinated me, the physics of it. So you got to tell me if this is true or not. This is about teleportation. Okay, and I know that sounds crazy, but teleportation, so they said that quantum teleportation of a qubit is achieved using quantum entanglement, in which two or more particles are inextricably linked to each other. So if that entangled pair of particles is shared between two separate locations, no matter the distance between them, the encoded information is teleported.

Unknown:

Yeah, I'm not a quantum physicist. So I can't tell you if what you've described is technically rigorous if it's technically completely accurate, but for quantum computing purposes, what you've mentioned, not the teleportation part, because that absolutely does not play a role in quantum computing. But in quantum technology, that is obviously a very interesting topic. But what you mentioned, entanglement is at the very heart of quantum computing. And when you ask me early on to say, well, what is quantum computing? Well, what it really is, it's a system of computing that exploits quantum mechanical phenomena. So entanglement is a phenomenon in quantum mechanics, just like superposition is a phenomenon. And so what these amazing engineers and physicists have done is figured out how to exploit these things that happen naturally at an atomic scale, and use them to compute. So I think minus the teleportation side, I think no scientist would tell you that physically, a qubit is being transported from one place to another. But certainly information quantum information is being exchanged between qubits. I think that that is technically rigorous, but accurate. Yeah, yeah. Right. And

Dean Nelson:

not to geek out completely. But to me, what you're talking about with what you guys are working on, is accelerating the processing capabilities with quantum computing, right? Yeah. And using leveraging the cloud model to be able to say anybody can get access to this and basically have the ability to apply whatever their business need is on a quantum computer. Awesome. So that seems like a natural progression, but like, 1000s of times faster than what we have in standard computing today. It seems like right, that's right. The other one, I know we won't dive into this. But the thing that also fascinates me is there's this, pardon the pun, quantum leap and computing that's happening. But you think about connectivity and transmitting data globally. If this entanglement we're just talking about of qubits being able to be in two places, or the data, the information being entangled, if that means that you could have instantaneous transmitted of data around the world that changes everything from a networking standpoint, I everything can be real time.

Unknown:

That's really true. You know, this reminded me of something Arthur C. Clarke was recorded. There's a YouTube video snippet of an interview that he gave in, I think 1961 and keep just painted a vision for effectively satellite communications and the Internet without really, you know, being able to get into what you just described is also it's feasible that if someone listened to what you just described, 40 or 50 years from now, they'll say, yeah, that happened. So that's the point. Let's say somebody cares about quantum technology at a strategic level, like let's say, the United States government or the Chinese government, when people are thinking very, very long term. They look at the basic research that's being done now in quantum communications, quantum networking, quantum sensing, quantum computing. And they think about how all that may stitch together at some point in the future. Now, in some cases, the technology is so immature, that you can't make any accurate or reliable predictions. But you can imagine way out there. And this sounds crazy, right, which is why people shouldn't listen to this for about 30 or 40 years, you can imagine where quantum technology is pervasive in data networking, where it's pervasive in computing, where it's pervasive in very accurate navigation and timing. So basically, where most of the high performing technology resources we have are in some way, quantum powered, quantum boosted. And this is probably going to happen. And when we talk about this in 2021, very responsible scientists may kind of like roll their eyes. But futurists are people that are interested in not saying what cannot be proven today, but rather what is possible tomorrow. We'll think about that and say, yeah, there's a vision. And I do actually think that will happen. So yeah, I think quantum technologies are going to be very pervasive in 20 to 25 years and more than just computing or more than just quantum sensing your timing? Yeah, definitely do. It's going to take off in a big way. Yeah.

Laura Roman:

I was thinking, you know, with your tremendous background in finance in the Air Force, like, what was the tipping point around quantum computers, your first exposure, etc, that made you decide I have to get into this. And then from there, like how you kind of formed QCWare specifically?

Unknown:

Well, I'm glad you asked that. Because first of all, I'm just like, an average guy out the street. So it's not like I had, what I did is listen to some people that inspired me, and motivated me to do a lot of hard work. And the first person that did that I talked to in October of 2012. And his name is Pete warden. And Pete was the center director at NASA Ames Research Center. So at NASA's research center in Mountain View, and Pete had been a brigadier general in the Air Force, and we have a mutual friend. And this mutual friend said, Well, Matt, you're looking for technology, aerospace technology project to invest in to get involved with go talk to Pete. And Pete was gracious enough to make time in his day in January of 13, to talk to me. And when I told him, Pete, I'd love it. If you could introduce me to these companies that are building launch vehicles, small satellites, UAV said, I'll do all of that, Matt, no problem. But you should really, if you really want to do something interesting, you should talk to the group that I have that does quantum computing. And he set me up with a guy named root Pok Biswas, who runs the Advanced Computing Group at Ames, and Rupak. Also, the following day gave me an hour of his time. And this was in January of 13. And Rupak, described how NASA a very responsible research centric organization looks at quantum computing and what they want to do with it eventually. And he painted this picture. And I thought, Whoa, I've looked at roughly 150 technology projects and ventures that I wanted to possibly get behind. This seems like it's going to be much more important, much more. And so it was that meeting, I walked out of that meeting and said, Whoa, this is going to be important. Importantly, I was right in the middle of Silicon Valley. And I'm not a Silicon Valley native. I wasn't living here at the time. And I thought, Well, I'm not seeing any private capital running around quantum computing, not seeing any dimetric capital firms doing anything with it. I'm seeing Lawrence Livermore is doing something Berkeley, Caltech, MIT, Lockheed Martin at the time, Google. So I saw these very intelligent forward looking groups doing that. And for me, that was a very strong signal that said, Okay, some really smart minds that care about this. And so they must perceive having looked at other technologies, as this being worthy of exploration. And so I thought, Okay, what I got wrong, I guess you could say, I didn't realize how long it was going to take for these hardware groups to build good systems. And so when I with two co founders, a guy named Randy corral, who was working in the quantum computing group at Ames, and a guy named KJ Sham, who is also you know, an MIT trained engineer and had some startup experience in Minnesota, the three of us got together to set the company up in August of 14, I thought very naively that you know, within two or three years, we'd be able to run useful problems. In the meantime, though, and over the last seven years, everything that I really wished and hoped would happen to our company has is just taken longer, every single step takes longer than I thought it would.

Laura Roman:

And you've brokered so many amazing partnerships, especially just in the last two, three years, like Goldman Sachs, for example. So maybe you can talk a bit about some of the hotter ones there, whatever you can share what they're about.

Unknown:

Sure, it is true for QC, where what I believe very clearly, is that to be a real business, you need a team of product and customers, you need all those to be a business. You can be a unicorn and a huge company without one of those you probably can be, but we're not trying to do that sort of, you know, that sort of a scheme. I really wanted to develop a real business around quantum computing. And so on the customer side lower, which is what you referenced, we made it our mission to get a customer base of fortune 200 companies, they're all tend to be about that size now that are investing in developing with us in collaboration algorithms and applications that they in the future will be able to use. So groups like Goldman Sachs identify hard competing problems that they have. And we work with them to help get these problems formulated in a way that can run on a quantum computer. And then we run experiments on real quantum hardware. So the verticals that we care about, I mean, I can't go into when I rattle off these names, I can't go into what exactly we're working on with, in some cases, whether they're just an investor or also an investor and a customer. But the names that are public are, you know, in the financial services side, they include Citigroup, Goldman Sachs, de SHA, Wells Fargo, I would say they're also two reinsurance companies, there's an insurance company that we're signing up. So there's a set of financial services firms that we're working with. And then more broadly on firms that use molecules for materials, chemicals, or pharmaceuticals, there's a set of customers that we work with there. And I had guessed, the names that I can disclose include Roche covestro, there's one other top five pharma that's undisclosed, there's a top 10 pharma that I believe is not yet fully disclosed. So those are kind of the sets of customers we have. So that's basically it. It's it's customers that have hard compute problems that hire us now to do two things to develop quantum algorithms and develop a workflow of code base that we turn over to them. And then they also purchase small subscriptions to our cloud service, which allows them to run small examples of their problems on quantum hardware. And in the future, of course, they'll be able to run production scale problems on quantum hardware through our software.

Laura Roman:

Yeah, and automotive customers to remember so But before getting to that, I want to ask how much do you see in parallel is to I see some of the themes that are coming through like these QB webinars that you've been running. And of course, you're ramping up for the conference, which is just like a better month away now. But there was one in particular, which is the, you know, China ahead in the quantum computing race. And I wonder, just the extent to which, you know, obviously, you're driving a business, as you say, and you're brokering these amazing customers, but how much is it important to you for kind of the mission of QCWare that you are also a thrust in the kind of broader thought leadership and conversation around the quantum race, for example?

Unknown:

Yeah, it's highly important, because I do personally, I have very deep views about these things. And I feel these views can be expressed in ways that pull the quantum computing community together. And I'm not the ringleader of it by any means. But what I did see, back in 2017, there had not been any sort of an organized convocation of the quantum computing community. And so we set up this conference called q2 B. And the first year was at actually NASA Ames, this year, it's going to be at the Santa Clara Convention Center from December 7 to the ninth. And Laura, I think you've got the link to it. So whenever the podcast gets posted, or you could also include the registration link to it. But the point is, for Q to be in particular, it's a three day conference where all of the major stakeholders in quantum computing gathered together. And the goal is to help accelerate practical quantum computing. So you know, to do that you need customers with hard problems, software and algorithms, groups, hardware developers, you need all of those groups kind of in a room together to collaborate and to form partnerships, now, so that's why we're doing that it's to help pull together the community every year. And certainly we like being in the center of all that activity. And we're very willing to do this, you know, it's not necessarily a profit making thing. It's like it's a community building thing. The other thing, I am a former Air Force officer, so I do care about national security and national competitiveness. So under the cute to be brand, which is something that we have, we do organize webinars, and this one in particular, had a couple of the leading quantum scientists in the country, Scott aaronson, will Oliver talking about what the implication is of these recent results that have come out of China, where China has an extremely active and very aggressive quantum computing program. And they recently published results through a couple of papers and a couple of venues that provided evidence that suggests the machines that they've been able to build are just as powerful as anything that has been done in the US. And I thought it was I think we all think it's important to put sunlight on that to see, you know, are these claims likely valid? And if so, what is the implication for the US because not only for national security, but for national competitiveness? It is important that the United States leads in these sorts of technologies. Yeah,

Dean Nelson:

I agree with that completely. If you think about whether it's AI or quantum, are we putting enough of the minds on the problem? Are we putting enough money behind it? Right Is there Enough, like just I guess from a country standpoint, focus, because that's really what China does, well, they point the entire country at a problem.

Unknown:

And this is actually really fascinating because through the association I've been lucky enough to have with people in our government, who are looking at this at a policy level right now. So they're thinking about this, what's been fascinating for me to observe through these interactions is the following. In China, there's a very directive, centralized, hierarchical, organized thrust to say, Okay, we're putting this money into the ground, we the government, and we're going to organize these development activities like this, and we're going to oversee it. And here are the milestones. And that's what it appears to me as an outsider to be in the United States, we have this, you know, the invisible hand of the market, these free market forces that have worked well for us for a couple 100 years. And what I see in the executive branch of the government, what I see is their DNA seems to be to say, look, this is a weapon, the free market, we have in the US where capital flows to good ideas, and where people flow to good ideas that have been capitalized, this thing that goes on, we don't want to get in the way of it. So what the US is doing is not trying to do a directive top down sort of thing to say, look, it's got to be all ion traps, or it's got to be superconducting qubits, or photons and forget about algorithms. And none of that what they're really doing is they're trying to listen very closely to see what these market forces are pushing forward, and to seeing where they can supplement and promote and boost the development. And this is a very sophisticated, I don't know if our government gets it right all the time. But it is a very sophisticated thing to do. You know, you can if you're the government, the US government, you can think well, either we can kind of shotgun stuff like we're the NSF will put $20 million into every research university in the country every year, and next year, it'll be 40 million, we'll just see you comes up with something that's a valid strategy that you can do. Or you can do something like John F. Kennedy did back in, you know, the early 60s where he said, I got this grand challenge thing, by the end of this decade, we're going to put a man on the moon and bring them back safely. And so I think, you know, right now, what it appears to me is that the US is sufficiently advanced that they're trying to figure out where is there some gaps in the quantum supply chain? Where is there gap in workforce development, they're trying to understand that where they can help push things forward. There hasn't yet been at the US government level kind of Grand Challenges. DARPA has, you know, maybe some mini Grand Challenges around Quantum. DARPA has not nor has any other agency stood up and say, here's a grand quantum computing channel. So fascinating topic. Yeah, absolutely fascinating.

James Thomason:

As a segue, Dina mentioned artificial intelligence. What if you care to comment? How important is quantum to the future of AI? Do you think

Unknown:

it's uncertain. And so AI is a really, really big word, just like machine learning is a really big word. And it is unclear if you look at all of the machine learning and artificial intelligence workflows are problems or use cases, it is not yet clear which ones of those existing use cases can be accelerated by quantum computing. What is clear is that there's a lot of work being done to look at these machine learning and AI compute bottlenecks and trying to understand at a very, you know, abstract level, what properties of quantum computing the sort of random sampling and the probabilistic nature of the calculation, you know, that's a very elementary description of this, but where can we direct those processes at machine learning or AI workflows. And so there is a lot of work being done, we're doing a lot of work on that. I mean, we've got probably one of the strongest machine learning quantum machine learning teams in the field. And I think what a lot of useful work is being done is simply looking at a hard machine learning problem that has, you know, in a workflow, I don't know, 10 steps, and just looking at which of those steps seem to be able to be accelerated by quantum processing, and then investing a lot of time in developing quantum algorithms to tackle those problems. So your question is like, how big of an influence is actually if you're a responsible person and you don't arm wave? You would probably say, it looks like it will be initially incremental, but it has the potential to really move things quite heavily, but it's really currently uncertain. That's the responsible answer.

James Thomason:

I can tell that clearly you are struggling with the hype around quantum computing. And several times during this discourse. You've mentioned responsible organizations doing responsible research saying responsible things about real science. And I could just tell the, it must be like a constant struggle, the hype cycle around quantum right now versus what you're actually doing in the real world with real engineers who do hard stuff. Is that fair?

Unknown:

Yes, it is fair. It's understandable. There's this you know, providers of capital providers have a lot of capital for deep technologies like this. Proceed there being a very high degree of risk associated with ever getting these technologies off the ground a very high degree of risk. And so to offset that risk, those same investors must perceive that there's a very big opportunity at the end. So the opportunity, the upside outcome must outweigh these big concerns that they have. And the only way to convince these investors that it is worth their while to invest, is by painting as deliberately and with as much conviction as possible, this highly positive outcome in the future. And there's nothing inherently wrong with that there is an optimistic upside case that should be stressed the problem there is, though, a line a very clear line between being optimistic and saying something which is just factually incorrect and saying something which is intentionally misleading. And that is a problem in this industry and everyone where there's where it's tempting to do so. Yeah. So it is a problem.

Dean Nelson:

You know, Matt, you kind of mentioned at the beginning, it's a practical application of quantum computing for a real problem is what you're going after? Yeah, yeah. Like there's a real thing to solve today. And we had a guest on before that was talking about AI. You remember, James, we're talking about Amelia. So there's this big hype about AI. But what they're doing is they zeroed in on cognitive, right AI for enterprise applications. And so that's replacing call centers, I said, like, there's a real problem to say, how do you scale communication back and forth with people to make it like a humanist. And so I think you apply that same principle that AI can go to 1000 different things, right, because you zero in on a real problem today, that's gonna have a business outcome. And so you are focusing on a very similar thing for quantum computing.

Unknown:

That's right. And you do however, because kind of the first application or two that will become visible, probably will not be a $10 billion opportunity, you have to if you want inside of the same organization, to launch and deploy and make money off a future application, you really do have to be good at execution, you know, so there's sales and marketing, operations, research engineering product, there's all of that, that needs to function so that you can really pull off the picture that you're painting. And again, like, I definitely have my feet on the ground, but my eyes on the stars, but I know, to get to the stars, you actually have to build something. And so it's very, very satisfying to me to see the team to see the functional areas in the team working together and all rowing together towards that mission. And you know, I can only hope that because, you know, I'm from the Midwest, so I'm kind of grounded in this way. It would be poetic justice, if our approach turned out to be the one that worked the best, because I kind of believe in it the best, you know, obviously, you were in the Air Force, correct? Yeah, that's right. Yeah.

James Thomason:

And how did the Air Force prepare you for building a company? Would you say that that helped?

Unknown:

Yeah, that's a good question. I would say the Air Force helped me discover how satisfying it is to be part of a really good team with a really important mission. And that got right into my bones very deeply, I always found it really, really satisfying, to be on the same wavelength with people that were going after the same thing. And that's one thing it helped me with. The other one was the importance of being a good leader. And I don't claim to be a great leader, but I definitely tried to be a good leader. And there's responsibility in that there's a lot of pain involved, you have to be very self critical, self aware. And so you know, it's extremely hard, particularly with all this ambiguity we have in this technology area. But that's the other thing that at least the Air Force tuned me into how valuable it is to try to be a good leader to be responsible to help develop people around you, to reward people around you to delegate a lot and give people free rein, because they're really a QC, where they're the people that are driving everything forward. My job is just to build this platform that everyone can perform on and really excel. And again, I don't think I get it right all the time. But I really tried to. And so that's another thing that came out of the Air Force. I think

James Thomason:

that's excellent advice. Can you repeat that advice about being a good leader? What are the characteristics of a good leader, in your view?

Unknown:

Well, I do think in terms of technology, for a technology program like this, I do think you do need to have some kind of vision, you do need to have a view and it can change over time, but where you're trying to get to. So you have to have that solid in your mind. And you have to be able then to connect the dots backwards to figure out the steps to get there. And it's very ambiguous, you know, you can go down a lot. But that's one thing. Another thing is to be a good leader. I think you have to have it in your spirit in your basic core, to actually want other people to grow, to take credit to be rewarded. You should be able to read them to figure out what they're good at and what they're not good at and help them move them into things that they're really good at and out of things they're not very good at. So I also think because I don't have a quantum background, in my case, there's a type of leadership that seems to work best for someone like me, and again, I don't know if I do it really well. But I'm more of a coach than a manager in any way, like the people that have the subject matter knowledge in these functional areas in our company, it's more just trying to pull them together to be cohesive as a leadership team to keep them rowing towards the same goal. This is a leadership challenge, because the personalities are so diverse inside of our company and inside of every company. And so it takes a lot of sensitivity to try to get it right. And I make a ton of mistakes. But I always try to learn from those mistakes. But that coaching thing, I think, you know, for someone like me, who doesn't have the domain knowledge is really important to get right. So those are kind of like the leadership traits that I think pretty important for a technology startup.

James Thomason:

That's really helpful. And you mentioned aligning everyone to the same mission. How do you do that in practice at a small company like QC, where I think

Unknown:

the most important thing is first to listen to people inside the company and outside of the company about what the right and plausible objective is. And then to socialize that in perhaps a subtle way or a direct way over a period of time with the leadership and the full QCWare team to try to make sure people are buying into that? And if not, why not? Maybe they've got a valid point. But I think the most important thing is to get everyone to agree to within, you know, 10 or 15% of optimality, to kind of agree with the basic objective. And to do that, you know, it can't be someone at the top directing it. It has to be people that say, yeah, that's plausible, I believe in it. So that takes time. And it takes you know, me modifying my views by listening more closely. But I think having buy in from everyone is a very difficult thing. But very, it's essential to get,

Dean Nelson:

you know, the parallels you brought there with I keep thinking the NBA, you got all these superstars on a team? How do you keep those superstars aligned to be a team versus a bunch of individuals, because I can imagine a roomful of physicists and very, very intelligent people trying to get something done. But if you can figure out the way that that team starts to grow together, as you said, that magic happens. I bet

James Thomason:

these physicists have no opinions right?

Unknown:

Now. No, we definitely do. But one thing that we do do, there are a number of people, scientists, engineers, whatever's who would not fit in well in our culture, or with our mission. And so we're actually very, very careful about who we bring on board. And we do a lot of the filtering that you just described before they come on board, in a lot of cases, what we do, we have people work for us, like for one day, a week for six months, so they can check us out. And we can check them up and then make them offers. This seems to be working really well, I would say in seven years of QC, where we have only had one employee leave, we've only lost one full time employee and seven years. And this just happened two years ago. And this person will remain nameless, but I have a huge amount of respect. And we work very hard this person, that very particular thing they wanted to do as a next step. And it turned out that the next thing they wanted to do was still in quantum computing, but it was something different than what they were doing. And I just couldn't get as hard as I tried. I just couldn't quite make it fit. So I wish that person all the best. But I never want to lose anyone else. You know, I made a perfect record for the first 6.9 years and I don't want to lose anyone else.

Dean Nelson:

I got to believe that's because it's mission oriented. You guys know what you're going after? And everybody's aligned to that mission?

Unknown:

Well, when you say that, though, Dean, honestly, I think, Okay, we've got even be more than that. So I'm what I'm thinking right now is going into the office tomorrow, I do want to spend some time talking about that listening, reminding my I don't think we can ever, you know, do that enough. So thanks for reminding me that.

Dean Nelson:

Well, you're trading us we're training each other.

Laura Roman:

With your fundraise rate. So congrats. You just raise Series B 25 million, I think, right? How much of that is going to go to growing the team? And then with whatever plans are for growing the team, how much you're going to be looking to get people out of the academy, academia and versus rd practitioners in industry?

Unknown:

Yeah. Okay. So we did Thanks, Laura, we did raise a $25 million round, that the investors we can announce our disruptive technologies, Samsung Citi Group, Pegasus de SHA, there's one or two other groups that are quite large that aren't disclosed yet, but they will be at covestro as well. Covestor is a German materials company, a publicly listed company, sorry about committing them. So I guess probably 80, or 90% of the proceeds will go just to hiring people. And another 5%, three to 5% goes to office and GNA. And there's a couple percent going to IP intellectual property patent prosecution. So that's that most of the hiring is in quantum engineering. Some will be in product, some in software engineering, some sales and marketing. So that's really the plan to build out the product. Because again, when I mentioned what is a business, whether it has a team, customers or product, and for us, I really do want to have our product. I want us to be the first group that has a performant quantum computing product. So that's what's happening there. But they're also even though we've just raised around a finance what I can see is If we had more capital, I could see more things now to do. And I'm just now getting to that point of we've been very capital efficient up till now. And that's because frankly, we've covered 80 to 90% of our operating expenses with customer revenue since inception, like we burn very little cash, actually. But now I'm seeing some opportunities for some consolidation that we could drive. And there may be some opportunity to deploy some capital to do that. And if so, I would probably be raising more, but I'm looking really hard at that right now. But an answer your question, Laura, that's what it's going to.

Laura Roman:

And I know we're getting close to time, but you know, you have Q to be coming up. But I'm thinking again, just from two years ago, this incredible growth for QCWare so you went from, I think two years ago, it was at the sort of hotel rights, I think, at the Santa Clara convention center. So what's on the program for this year?

Unknown:

Well, it's going to be the largest in person, I think, you know, it is in person, first of all, and we are expecting up to perhaps 1000 attendees in person. And the program will feature updates, important and interesting updates from all of the leaders in quantum computing. So that's an who are also sponsors of the conference. So that's Amazon, Google, IBM, Microsoft, Honeywell ion Q. And the list kind of goes on of all the hardware and cloud services groups. And of course, all of our peers on the software side, we'll be talking, there will be a number of academics who will be describing recent work they've done on practical quantum computing. So basically, and there's this very large exhibitor booth area, where there's a ton of mingling that happens. And that's really the value of the conference. It's really the networking, the content, and the speakers and the brand names, those are all really important that draws people. But the real value comes when people have organised kind of one on one meetings together. And there's just a ton of that that happens. So it's always super exciting. It's a super draining, but super exciting three days. So it is right around the corner. Now. It's just about a month away. So yeah, thanks for bringing that up.

James Thomason:

How long have you been running this event? When did you start?

Unknown:

This is the fifth one. So the first year was that the Conference Center at NASA Ames, the second year was the Computer History Museum. That third year was at the Fairmont Hotel in San Jose, the fourth year last year was virtual and this year's at the Santa Clara Convention Center while just getting bigger and bigger. It is getting very big. Yeah, it's getting very big. That first

James Thomason:

year, you think back to your very first year starting this conference. How did you bootstrap that from nothing? How did you get attendees for your first conference and presenters and all of that like was Yeah, that's awesome. That's awesome. You

Unknown:

asked that question. I mean, this is just a sidelight for QCWare but it was in June of 17. I went over to Munich to attend a one half day so called Quantum Leap session, it was in Munich and was a venture capital firm organized it over their local VC firm in Europe, and actually brought, you know, real companies showed up like Daimler and Siemens, and Deutsche Telekom and a few others. And that inspired me. And you know, we had a couple of speaking spots, I thought it was great. And I said, well, we need something like this in Silicon Valley. I'd never thrown a conference, I didn't know anything about conferences in technology. So I said, Okay, we're going to throw one. And I really thought what it would do is just me at Ames, I figured we do it at Ames, just going to Costco and buying a bunch of food and just sending out emails. And board members, again, in Gordon Eubanks, who used to run Symantec, he called me and scared me extremely, and said, If you do it that way, you are going to fail. He said, You need a production group to do this for you. And it's going to take a year to do it. So I took them up on the production group, we had a very good production group that organized it, but I said, No, no, I want to steal the march anyone else who might have this, so I want to do it this year. So we didn't do it in December. But starting in October, I was doing nothing but sending out emails all day, every day to people around the world who I was trying to get interested in this by that point, we had some graphics. And we ended up with 256 registrations. It was a full house, you know, it really worked. So thanks to NASA for that. And thanks also to, frankly, Google, there's a guy named Alan hoe at Google, who I pitched this idea to, I said, Look, Alan, and Alan's got a marketing background. He's in the quantum computing group there. And I said, Look, I want I think there's a need for this. And so I talked about it for about a half an hour, he gave me some guidelines and said, Come back to me in a week, and I did with a more filled out kind of storyboard of the whole thing. And to be quite frank, I thought, well, I don't know how much money I can get out of Google. So I guess I'll ask for 100. And maybe they'll give us 75. Because we kind of calculate how much this whole thing would cost. And so I said, well, we'd like $100,000. And I, you know, did it with a straight face. He said, Okay, we'll give you 130 They're really important. You know, really, I have to say, you know, thanks to Google for getting behind us. And of course, they've been a sponsor every year since then. But they were really helpful to us. They really were Yeah, it wouldn't happen without them putting the money into it.

Dean Nelson:

Well, Matt, I think what keeps popping up to me is what you said earlier, if you keep your eyes on the stars and your feet on the ground, you can can deliver the future but still solve a problem. A business problem from today? Yeah, yeah, that's it. That's awesome. You keep both in mind and you just move.

Unknown:

Yeah, yeah. Yeah, totally agree.

James Thomason:

Well, Matt, I want to thank you so much for taking an hour of your time and spending it with us on the show today. Fascinating discussion, incredibly interesting, company and mission. And if I'm interested in working for QC, where, where should I go to school? What should I major in what impresses the CEO of this company,

Matt Johnson:

really, you should go through the most and the hardest filters you possibly can. Because we get so many applications that it's hard for us to discern who might be good and might be bad, and kind of the easiest filters are just to look for people that have intentionally sought out very, very hard challenges. And that might be educational, or it might be some research that they've undertaken, just through their own high motivation, but go through as many hard filters as absolutely possible. And of course, where we have an appetite to hire, the thing we care about most is people that have quantum algorithms, design expertise. So anyone who has that should go to the jobs careers, part of our website of the QQCWare website and respond to that under I think it's info at QCWare.com or whatever the link is. And I see all of these things. And so to the technical heads of our team, so that's it if you in particular, you know, my shout out is for anyone who has quantum algorithms background, that is what we're looking for more than anything. Wonderful.

James Thomason:

To learn more about QCWare please do go online to QCWare.com. That's right QCWare.com Matt, thank you so much for being on the show. This podcast is sponsored by infrastructure Masons, uniting builders of the digital age. Learn how you can participate by going on the web to imasons.org that's iMasons dot org. And of course, by EDJX, we're building a new edge cloud made for planet scale to create smarter, faster apps, websites and data pipelines on EDJX to secure our Global Edge platform visit us on the web at EDJX.io. That's EDJX.io.