Roman Orus, founder and Chief Scientific Officer, Multiverse Computing is interviewed by Yuval Boger. Roman and Yuval spoke about developing quantum applications for customers, whether the right solution for the customer comes from a vertical-specific company or a quantum-centric company, their operating philosophy, and much more.

Yuval Boger: Hello, Roman. And thank you for joining me today.

Roman Orus: Hi, how are you?

Yuval: I’m good. So who are you and what do you do?

Roman: Okay, well, so let me then introduce myself. I’m Roman Orus, I’m a physicist, I’m the co-founder and chief scientific officer of Multiverse Computing, and I’m also a professor of theoretical physics at the DIPC, which is a research center here in Spain.

Yuval: And what does Multiverse computing do?

Roman: Yeah. Well, so let me explain a little bit about our company. So at Multiverse Computing we do software for quantum computers. And in particular, we are focusing on applications for industry. We want to build applications for real problems, for useful problems for different industry verticals. And we want to solve these problems using quantum technology, and also quantum-inspired technology as it is today.

Yuval: I saw a recent presentation that you gave, and you spoke about democratizing quantum.

Yuval: Isn’t it too early to democratize quantum? I mean, I think you gave the example of your grandma. Does your grandma really want to use quantum computers?

Roman: Why not? I mean, if she’s given the chance, why not? Yeah, absolutely. Well, first, to answer the question, I don’t think it’s too early. One of the things that you learn when working in such a disruptive field, such as quantum computing, and this is something also that I’ve learned over the years, is that the future always comes faster than what you expect. You always hit it sooner. And many people think, “Well, it’s still many years until we can do something useful, until this is mainstream.” Well, you need to start thinking about this early, because otherwise, you may be too late. And I don’t think it’s too early to democratize quantum computing.

At Multiverse, we are obsessed with different things. One of the things that we are obsessed with is with solving real problems, so not academic problems, real-life problems, really the dirty thing, try to reverse engineer and see how we could solve this with quantum technology. But then the other thing, which is extremely important, is to make the technology accessible to everybody, to the people. And this is why we talk about democratizing quantum. So quantum technology cannot be something just for quantum engineers, let’s say at the bank, or for a quantum specialist, or for quantum physicists. Quantum technology needs to be something that at the end of the day, the people that are working at companies and startups like us, we have to make it accessible to everybody. We need to make it accessible to everybody.

This is the same as saying that, imagine that you want to switch on the radio and listen to the radio and that’s it, but to switch on the radio and listen to the radio and listen to some music, you don’t need to be an electronic engineer and know about all the details of how all the secrets work and so on. So this is exactly the same, we need to make the technology accessible for everybody or otherwise, this is not going to work. And yeah, I don’t think it’s too early. The technology is still under development, but it’s going to be under development forever, and we can start to see already the first useful applications in the industry of quantum computing, and therefore it’s just the right time to start thinking about this.

Yuval: The reason I ask about too early in democratizing, let’s take an example, for instance. I think one of the examples that’s brought up often with quantum computing, and I think you guys talk about it as well, is portfolio optimization. Take a basket of assets and optimize the allocation between them to achieve target returns and risks. Who is your customer for such a program? Is it the 55-year-old employee that’s starting to think about retirement in 10 or 15 years? Or is it the company that’s managing the assets for that person?

Roman: Well, at this point is the company at this point, but still, if you go inside of the company, it makes a lot of difference whether you are targeting the technical quantum engineers inside, or you are targeting the traders and the brokers, since you were asking about this. Even the highly skilled technical quantitative analyst inside a bank, they don’t need to know how to program a quantum computer. Not at all. You need to provide the solution in the language and with the tools that they are already used to do, to use in their everyday life. Of course, they know a lot about financial theory, but they have no clue about quantum and you have to make life easy for them as well.

So, in this case, in the particular case of portfolio optimization, actually what we did was to develop a plugin for a spreadsheet, which is one of the typical tools that many, many people use at financial institutions where you can download directly the data from Bloomberg and so on, and just make it work as an optimization engine where you don’t need to know exactly how are the inner workings. Now, if somebody wants more detail, we can also provide that. We can provide the explicit libraries, we can provide all the details of how the program is built or the details about the code. We can also do it. Now looking forward, I can imagine that eventually, this thing, right now this is commercialized by banks. When you go and you want to buy an investment fund or something like this, typically, this is the bank that is managing the performance of this, but eventually, people also want to take care of their own finances and in this sense for those people, I can also imagine that the tool that we are building could also be useful for them.

Yuval: When you look at portfolio optimization, obviously you want to have more than one customer, and every customer might have their own preferences or maybe even their own proprietary algorithms on how they prefer to do it. Do you go in and sell a shrink-wrapped solution, “Here’s our solution for portfolio optimization?” – just picking on that particular topic – or do you work with the customer to integrate into their systems in the way they like to think about portfolio optimization?

Roman: Yeah, we work directly. Well, actually, we do both things. So we have an optimization engine, which is the core of our technique, which is, it was with quantum technology, and it’s actually hybrid, it’s combining quantum and also quantum-inspired technology, and this is why it’s working so well. But then, every client is like a little baby. So at the beginning, we typically work first with the client directly on a given project, and then we understand the specifics of what they need. Because even for such a specific problem as portfolio optimization, you may find lots of differences between one bank and another because they may apply different restrictions to the problem and so on and so forth. And therefore, this makes the problems, the mathematical formulation different. So we can tailor the problem to the specific needs of the bank and then run our optimization algorithm.

Now, what we are doing actually is that by working with different banks in different projects, we have right now a pretty good sense of what are the most common, let’s say, constraints that most of the banks, I will say 90% of the banks, are actually applying. And we can incorporate this into our solution. And in this sense, we are building a product which is customizable up to some point but which is already integrating most of the things that the banks are requiring. And then eventually, and a posteriori, if some client needs a little bit of fine-tuning, we can also provide it.

Yuval: I spoke recently with an industry analyst about quantum adoption at the enterprise, and we spoke about who’s delivering the solution. One concern that he raised, and I’m curious about your perspective, is that enterprise companies don’t trust quantum vendors to truly understand their business. Because a company, a quantum vendor, can say, “Well, I work in optimization, and I work in chemistry, and I work in finance, and I work in supply chain. And because of all these different things, you might be sort of a jack of all trades and a master of none.” How do you respond to that? Do you think that a company like Multiverse is best positioned to deliver these solutions? Or do you want to work with a partner specializing in supply chain or chemistry?

Roman: Yeah, I think we are the best position, and let me explain you why, because I think we have a different approach than many quantum vendors out there. So the point is the following, I have the feeling that many of the content companies in industry out there, they have… Well, obviously, they come from very abstract ideas, there is a lot of people from academia involved and so on. And then it’s a natural thing that they just develop solutions, and then they go and try to sell them to the industry. And then they face the problem that the problems in industry, the actual client, may have a very different problem to what they were expecting.

So this is something that at Multiverse, right from the beginning when we started the company, it was completely clear to us, the client is the first thing. You have to understand the client. The client rules, it’s a client who tells you the use case, not the other way around. And it’s the client who tells you the problem and you have to work out the solution. So from the very beginning, day one, we are obsessed with the client, we’re obsessed with that. And it has worked really well for us because from the very beginning, the problem that the client is proposing you, maybe it’s not the thing that you have in mind, but that’s the actual problem that they have to solve. And then obviously, it may be very difficult and you may think that, “Well, maybe this is impossible,” but have to work and think very hard to actually reverse engineer and see how you can solve the problem actually with quantum technology.

And in that sense, if you manage and succeed in doing this, at the end of the day, you will end up having a solution that is actually useful for the client, and the client will understand you, and you will understand better the client. But obviously, this is a very hard thing to do because it’s not like, “Okay, I come here with all my wisdom in quantum technology and I’m going to tell you what you have to do.” No, this is not the way of selling anything because maybe you build a fantastic machine, which is completely useless because it’s solving a problem that nobody cares about. It’s actually the other way around, it’s the client who is telling you what you have to do. And since we started with this philosophy from the beginning, it went actually very well.

Now also, we started with a very strong focus on finance. When we started Multiverse already three years ago or three and a half, we were 100% focused on finance, that was our knowledge. And then in finance, we were really very good. We had a lot of domain expertise and it worked really well for us. And now what happened is that since we were so successful in finance, people from other verticals came to us and said, “Hey, could you do something like this? I have a problem in optimization, but in the vertical of energy or in manufacturing. Do you think you could help me?” And obviously, if you’re a startup and clients start to come to you and say, “Could you help me with this problem and I’m going to pay you?” Obviously, you say yes, and you start to escalate your business.

So we took this approach in Multiverse with finance, we were very successful. And after specializing and being successful in one vertical, then we started exporting the solution to other different verticals. And this was extremely easy to do because we had the engine, the core of the solutions that we are offering, it was already built. The same optimization or machine learning algorithm that we use for finance is the one that we use for energy or for manufacturing and so on. So in this sense, we didn’t have to build anything new. The only thing that we had to understand was the specifics of the problem, the jargon, what were the relevant variables, what is the context, and so on. And this is something that, well, in some cases it was easier than others, but we also managed to do it pretty well.

Yuval: How is the company organized? I mean, how large is the company, and is it organized by verticals? Is it organized by people who work on the engine and then others that do client-project delivery? What could you share about that?

Roman: Right now, Multiverse is a company with 80 people, 80-plus actually. We have the headquarters are in San Sebastian in Spain. Then we also have more or less one-third of the companies in our office in Toronto, in Canada. And then we also have offices in Paris and in Munich. Now, we have different teams, obviously, we have a business team, and then we have a team that is for sales and grants. There is also a research team. And then there is a team, which is extremely important, which is the rest of the tech team, which is essentially, it divides into two: one parties for services that is for projects with clients. And there is another one that is the product team, that is the one that is dedicated to actually building the product. So that’s how we are organized right now.

Yuval: We didn’t speak about hardware yet. Do you find that particular types of computers, of quantum computers are better for one problem, whereas others are better for other types of problems?

Yuval: And does the customer care? Does the customer say, “Well, what are you using”? Or does the customer really just care about “Give me a solution”?

Roman: Yeah. And the customer, I’m going to start by the second question, what the customer, typically, what they want is just a solution to their problem. They don’t care if it’s quantum, if it’s classical, it’s with AI, if it’s with whatever, they just want to find a better solution to what they have. If it’s on quantum, it’s with quantum. If it’s with quantum-inspired, it’s with quantum-inspired. So they just don’t really care. That’s if you go to the actual business line of your client, which is the one that is more relevant here, the business line in banks, and in energy providers, and companies, and so on, these are the guys that are really, they have the money, they have the power to put the solution into production, and they just want a better solution to whatever problem they have.

It may also happen, however, that if you touch the innovation departments, they’re more interested in exploratory projects, and that’s more research-related. In that case, yes, they care about, “Okay, let’s use, I don’t know, a photonic quantum computer, or let’s try neutrals atoms or something like this.” Now, having said this, and to be pragmatic, it’s true that different types of quantum hardware adapt better to different types of problems. And this is something that we have tested and seen by ourselves. And this is the reason why at Multiverse, we are what the people call quantum agnostic. This means that we don’t stick to one particular quantum hardware provider. Instead of that, we have partnerships with essentially everybody, with everybody who has a quantum computer on the cloud and has access to it, because of different reasons.

First of all, obviously, there’s still no standard on how to build a quantum computer. But second, and most importantly, because, as I told you, different types of problems are better solved with different types of quantum hardware. I mean, for instance, if you had to solve a problem that has a large, let’s say it involves a quantum circuit with many quantum gates between qubits that are highly localized, let’s say, then probably it’s better to use an architecture that has full qubit connectivity such as ion traps or neutral atoms, instead of let’s say superconducting quantum circuits, because there you are limited to the connectivity of the actual topology of the circuit.

However, I don’t know, if you want to solve an optimization algorithm, maybe you want to try quantum annealers. If you want to try some other type of Quantum machine learning algorithm that is variational, then probably superconducting qubits are your choice. So it exactly works like that.

Yuval: You’ve been with the company for almost four years, I think. The company is about almost four years old?

Roman: Yeah, it’s three and a half, essentially. Yeah.

Yuval: What is the project that you’re most proud of, of all the things that you did?

Roman: I’m proud of all my projects. They will kill me if I said something different. No, I mean, obviously, yeah, I’m proud of all my projects. Still, there are some projects that are very interesting. For instance, recently, we’ve been working on two very interesting projects with Credit Agricole Corporate and Investment Banking, also in collaboration with Pasqal in France. And this was a very satisfying project actually, that went really well. Actually, it was a couple of projects because we could explore a lot of quantum and quantum-inspired techniques that ended up being very, very good. We also did a couple of projects on quantum artificial vision in manufacturing, which I’m also very happy about them because we could beat actually some benchmarks that were very hard to beat in artificial intelligence. And yeah. So I mean, I will be lying to you if I told you that I have a preferred project, actually. I mean, like all of them. Yeah.

Yuval: It’s like asking you which of your kids you like better.

Yuval: What do customers think about IP? Do they worry that their IP is somehow going to get leaked inadvertently to a competitor?

Roman: This is something that you need to negotiate with the customer. Yeah, absolutely. So obviously the serious clients care about IP, the typical story is that they try to keep the IP, which is obviously normal, but then it’s always possible to reach some type of agreement with them. The previous IP, whatever you developed previously, obviously there is nothing to do about that as the previous IP. And then, when you go on a project, then you can negotiate. Typically, you can reach agreements of having co-ownership of the IP between the two institutions and so on and so forth. And that’s typically how it works. But yeah, they care a lot about IP. Absolutely. Yeah.

Yuval: Some of the classic consulting organizations like Deloitte or Accenture take a customer through the discovery phase, through understanding, “Well, here’s what quantum is about. Let’s educate you, let’s determine the use cases, and then let’s move to a solution.” Is there a conflict between what Multiverse is doing and what such a company is doing, or is it a natural handoff from them to you?

Roman: I mean, I think it’s fine if other companies have this approach because the more people know what quantum mechanics and quantum computing, the better for everybody, and in particular to us. Having said this, this is not the approach that we follow at Multiverse because we think that, from a business point of view, this is wrong. I mean, this is correct if you are running a school on quantum computing, you educate the people. But as a company, you are not the one to educate the client. And this is to be related to my previous answer, it’s exactly the other way around. It’s a client who is educating you. And for some reason, many people don’t manage to understand this. I mean, obviously, you know a lot about quantum mechanics, but this does not qualify you to really understand the problem that these guys have. So you really have to hold on and tell them to explain to you what is the actual problem they have.

And you don’t have to tell them, “Well, we have quantum computers. We can do…” Obviously you have to explain them, but you don’t have to educate them so that they become experts so that they can tell you what they could do. No, that’s your job, that’s your job. They come to you, and they say, “Hey, I have this problem. Can you do something about this?” And that’s where you enter as a quantum expert and start thinking about, “Okay, how the hell am I going to solve this with quantum computing?” But it’s your job, not the job of your client. So in this sense, I think it’s fine to educate people, but from a business perspective, I think it’s exactly the opposite what we should be doing.

Yuval: As we get closer to the end of our conversation, I wanted to ask you what you need from the rest of the industry. Obviously, your success also depends on where the hardware is at any given point in terms of the development, the number of qubits, the noise, what the software tools are doing, and what the cloud providers are doing. What help or what would you like to see from the rest of the industry to make your job easier?

Roman: Wow. That’s a tricky question. Well, obviously, the hardware is going to be developing further and further. I think this is really important, and that’s the main thing about the hardware. We need to reach that point and have this breakthrough in order to understand how to make the technology scalable. Right now, we have Quantum computers with 10, 20, 30, 50, 400 qubits. Maybe next year or this year, 1,000, and so on. This is fine, but what I would like to have, and this is perfectly fine because we can find applications that are already useful for business with these machines, but we would like to see quantum computers with 10 million qubits. Now, how do we do this? This is the real problem in hardware. I mean, how to jump from these NISQ devices, Noisy Intermediate-scale Quantum devices that they are limited in capability, yet they are useful as we are proving at Multiverse.

But I mean, if I had to ask Santa Claus, what would be my wish? I want a quantum computer with, I don’t know, 10,000 million qubits for instance. So how do we do that? This is something that I would like to see from the hardware companies, but obviously, this is one of the hardest problems that we have at this moment, but that obviously will help the whole quantum computing community to move forward. Also, from the business point of view, and perhaps more from quantum software companies, there are many quantum software companies out there focusing on different things, but I think it would be very useful if we could start to see new, even more quantum software companies emerging. So right now, there are lots of quantum software startups going on, and this is very nice, but perhaps also big vendors, people such as IBM, they did a lot on quantum computing, Microsoft, and so on. But there are also other technologies giants, which would be nice to see in the game.

Yuval: I wanted to end with a hypothetical question. If you could have dinner with one of the quantum greats, dead or alive, who would that person be?

Roman: One of the quantum greats. Schrödinger.

Roman: Well, obviously, I will ask him about his question about his cat, whether it’s dead or alive, but he was also an interesting personality, so I wouldn’t mind having a dinner with him and asking him a couple of questions.

Yuval: Roman, how can people get in touch with you, and what kind of people would you like to hear from?

Roman: Yeah. Well, it’s very easy to get in touch with me. Just send me an email, you can find it easily on the internet. I also have a Twitter account, it’s pretty easy to find me. So that’s fine. And I’m happy to hear about anybody who wants to talk about quantum computing.

Yuval: Excellent. Well, thank you so much for joining me today.

Roman: Okay, you’re welcome.

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.