Yianni Gamvros, Head of Business Development at QCWare is interviewed by Yuval Boger. Yianni and Yuval talk about Q2B, the annual trade show that QCWare produces, intellectual property ownership when providing professional services, the importance of investments in software benchmarking, and much more.


Yuval: Hello, Yianni, and thanks for joining me today.

Yianni: Hi, Yuval. It’s great to be here.

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

Yianni: So my name is Yianni Gamvros. I’m the head of business development for QCWare. So I handle all of sales and business partnerships and marketing for QCWare, and I also handle all of the decisions and all of the execution and the management that goes behind Q2B.

Yuval: So Q2B is a trade show that QCWare organizes, right? And this is now its fifth year? Sixth year?

Yianni: It’s actually its sixth year. So actually, our CEO, Matt Johnson, started the show back in 2017. Back then, there were really no other business shows that dealt with quantum computing. So pretty much everyone that was interested in quantum computing would meet at the academic conferences. And those conferences are typically made for technical talks. And he had the insight to realize that we really need a place where business people can meet and can understand the value proposition for quantum computing at a high level and can understand potential use cases, ROI.

But obviously, the technical credibility of the show is also important, and having talks and speakers that are credible is also important. So Q2B tries to essentially be both a place for business people to understand the value proposition, but also we invite technical speakers and some technical talks to inform, essentially, on the technical aspects as well.

Yuval: How much has it grown? How many people were, if you know, on the first show, and how many do you expect this year?

Yianni: Yeah, so it’s been quite impressive, and it has really grown beyond our expectations. So the first show had about 250 attendees, and this last show that we did in Silicon Valley had 609 attendees.

It was the first in-person show we had after the virtual show in 2020. So the virtual show, obviously, had more attendees. We were up to a thousand, but we quickly returned back to an exclusively in-person format in 2021. It was actually a little bit aggressive to do it in 2021. We managed to do it even though it was a little bit risky, and we fell between the Delta and Omicron waves, but still had a very good attendance. And the show actually has grown now. For the first time this year in 2022, we went to a different geography. So we just had a successful show in Japan. So we had Q2B ’22, Tokyo, which also had 370 attendees.

Yuval: So the show aside, how has the quantum computing industry changed, in your mind, over the last one or two years?

Yianni: Yeah, so it’s been unbelievable. The amount of new people coming into the industry, the startups, the announcements and the projections, it’s impressive. I think it’s much more professional. We’re now getting to the point where we have projections and roadmaps from both software and hardware vendors. And I think that’s interesting because now it means that people have a stake on the ground, and they’re making projections of what the technology will be able to do and what their products are going to be able to do. And now, it’s basically hard to say exactly where we are, but it’s always important to have these projections because you can always go back and look back at the last year or last two years and say, “Okay, I know where the projections were two years ago, and I can see where we are today.”

So I think that’s going to play out over the next couple of years where we’re going to be able to say, “Okay, well, these hardware roadmaps were good, or maybe they were too optimistic, or maybe they were pessimistic, or they were just about right.” But we’ll see.

Yuval: To me, Q2B is a great show and a great service that you’re doing for the industry, but I know that QCWare does many other things except Q2B. So could you speak about those a little bit?

Yianni: Of course, of course. Yes.

So QCWare is primarily a quantum computing software startup. So we build quantum algorithms and quantum applications that run on quantum computers and deliver, essentially, the promised value of quantum computing. So Q2B, as you just said, it’s basically one of our three go-to-market areas and one of our three, essentially, business lines. The other two being professional services for quantum computing and software for quantum computing.

So for professional services, what we typically do is we talk to large enterprises, large industry end users in finance, pharma, automotive, aerospace, many other industries. And we advise them on how quantum computing will potentially disrupt their different business processes and what they can do to get ready for this upcoming computing disruption. And this might be in the form of a workshop, some educational workshop in the beginning, or use case discovery. It might be a little bit more advanced where we do some proof of concept, applying a known quantum algorithm to their data and looking at the results. Or the most advanced thing that we do for many of our clients are these joint development engagements where we effectively act as an augmented research R&D arm to their current R&D program. And we engage in active research, we try to break new ground, we try to do things that haven’t been done before, and design new algorithms that can run on quantum computers and deliver value.

And in many cases, these engagements have led to publications on very significant journals and have led to patents and have led to maybe also some press for both us and the customer. And so we are very happy to, basically, be able to do all these kinds of professional engagements for our customers.

So this was the professional services side that I just talked about. The other thing that I mentioned is software, because primarily we want to be a software company. And we already have a software product, it’s called QCWare Forge. And QCWare Forge right now runs on Amazon Braket. And it’s essentially an algorithmic layer, an application layer for quantum algorithms and quantum computing on top of Amazon Braket’s platform as a service layer.

So we take all the algorithms and all the knowledge that we discovered during the professional service engagements that I just mentioned earlier, and we distill that into our software product. We package it, and we make it readily available for everyone that’s coming fresh and new into quantum computing and even advanced users to, basically, see what we’ve done for other customers, see what the new algorithms can do and how they can execute and then use the Amazon Braket infrastructure to be able to run that either in simulators or on real hardware.

Yuval: When you spoke about the professional services, you mentioned that one of the outcomes sometimes are patents. And I’m curious, what do you do with the IP? Meaning, when a customer brings you in, wouldn’t they want to keep the IP that’s generated from a project? Or is it somehow shared between QCWare and the customer?

Yianni: Great question. Yeah, so we always go in and we try to have this discussion as early as possible. Sometimes we have it on the very first call because this does come up. So everybody has this question, and it’s good to basically clear the air very, very early on.

So our position is that we like for the customer to be able to use the IP that’s generated, for ground IP that’s generated through a professional service engagement. But we also like to use the IP in any way, basically, that we want. So we like to be able to put the new IP into product and potentially resell it to other customers.

And obviously, this takes some negotiation with the procurement and the legal on the customer side, but it’s typically something that we can achieve because we are in such a niche space that our engagements with these customers are not treated as traditional professional services engagements. We’re doing something that’s very unique. We bring expertise to the table that’s also very unique and very scarce, actually. And therefore, the customer realizes that they do want us to partner with them. And this is a red line that we are putting in there that, “Hey, look, if we can’t use the IP that’s generated out of the engagement, then we are not basically going to engage.”

Yuval: Excellent. Thank you for clarifying that. I wanted to ask both about the types of industries. Is there one or two industries that you see more often than others coming into quantum computing? And also curious about the stage. Do people come and say, “We’ve heard about quantum. We don’t know for sure what it’s going to do for us, please help us.” Or have they seen a competitor or seen an article someplace and say, “Oh, this is the algorithm we need it implemented.” Where do they come in and from? What verticals do they come in?

Yianni: Yes, yes, great question. So yeah, so I think the most mature industry is finance. So we see a lot of different finance players, basically, have very mature quantum computing programs. And we actually see new entrants, basically, coming to the market and very quickly set up dedicated quantum computing teams that are looking into quantum computing, basically, 100% of the time.

I think the next one potentially is automotive, where we again see several players having dedicated quantum computing programs. Maybe pharma comes next. And maybe then you have a few other places like energy, aerospace. To a lesser extent, you have materials, and to a lesser extent, you have pretty much every other industry like telcos, utilities, and everything else.

And to answer the second part of your question, we do see, in some cases, especially with finance and in some cases with pharma, companies coming in and actually dealing with it very strategically and putting in charge of a person that’s going to be a quantum computing director, and they give this person headcount, and they can start setting up basically a program for the company. And in those cases, the discussion is more mature. They typically hire people with some quantum computing expertise, and you typically have discussions at a deeper technical level.

But as you say, there are some companies that are coming in fresh and just want to test the waters, and they might not have anyone that’s dedicated. They might just have someone in the innovation department or R&D department that has a little bit of a budget to play around or is willing to play around with a vendor and some experiments. And in those cases we might do something that’s a little bit simpler and a little bit more short-term just to give them an idea, basically, of what quantum computing looks like and what are the approaches, what can the hardware do at this stage and so on and so forth.

Yuval: Do you see customers preparing to use shrink wrap software? I mean, if there was sort of algorithm as a service, “here is my route table and show me what the best traveling salesperson solution is.” Or do they prefer to try and write their own software and their own algorithms? Which one do you see more common?

Yianni: Oh, we typically see a little bit of both because the two customers that I just described, the more mature ones, want to be more hands-on and want to design their own algorithms. And the ones that are just maybe testing the waters, maybe have an interest a little bit in also seeing the shrink wrap version and the black box version.

And frankly, my belief is that the shrink wrap version and the black box version is the one that’s going to dominate and the one that we as an industry need to move towards. We cannot expect people to write quantum circuits. I think it’s absurd. And again, if you look back at the history of the computing space, obviously, that’s how computing started by writing these very low-level statements. But it has quickly moved on, I think quantum computing will do the same in the future.

I guess I can conclude that by saying that in the meantime, quantum computing researchers need to have hands-on tools and basically dive deeper to technical tools and be hands-on on the code.

Yuval: What’s your best estimate of the time for quantum advantage? When people go beyond, “Oh, I’m playing with the technology, to, “I can move it into production.” Is it two years? Is it 10 years?

Yianni: Yes. So we do have a perspective on that. QCWare has a strong perspective on what will be the first application to exhibit quantum advantage. And we think that’s in chemistry simulation. We think it’s going to take a few years, for sure. We think that with a few hundred qubits and several nines of fidelity on the operations for those qubits, we will be able to get to a point where we can do something that classical computers cannot. And we think in chemistry this is doable, as I said, with a few hundred qubits because there are some exotic chemistry simulation problems, some exotic materials that classical methods simply cannot simulate them. And so we think that’s the most near-term application.

Then all the other applications that people talk about, we are still confident. I mean, we’re optimists, obviously, and that’s why we’re in the space because we believe that quantum computing will change the world and it will impact other areas like optimization, machine learning, other simulations, Monte Carlo simulations, and partial differential equations. But we think those are a little bit further out. Probably in the five-plus year timeframe.

Yuval: Let’s assume, for the sake of discussion, that the first application would be ready for production in three years. There’d be enough qubits, they’d be good enough, the software is there. What do you say to customers that say, “Well, if it’s three years away, call me back in two years, and then we’ll talk.”

Yianni: Great. Yeah, great question. And it always comes up, and my answer is this. I always challenge back with another question to the customer where I ask them, “Well, how long did your last digital transformation initiative take?” And typically, when they think about that, the answer is actually 3, 4, 5, or more years. So if people think back to how long it took to bring in the right data scientists within their organization, essentially get those scientists situated, trained, expose those data scientists to different business processes, to business domain experts within the organization and let them build initial proof of concepts and then move those proof of concepts into production, then that takes a lot of time. That takes more than just three or four or five years.

And so in fact, for chemistry, our position is that, hey, look, if you want to actually be impactful when the first quantum computers arrive and be able to take advantage of that in the market, then in some sense, you might already be late. For machine learning and for, optimization and some of these other techniques, you’re probably just in time. If you start now for chemistry, you’re probably already a little bit behind if in fact happens in three years.

Yuval: As we get closer to the end of our conversation today, I’m curious, if you had a magic wand, what would you want the industry to do that it’s not doing today? Is it more collaboration? Is it to work on something more than the other? What’s your wish for the industry?

Yianni: Yeah, great point. So I have a wish for the government organizations and the government policy, basically, that is supporting quantum computing in a big way. And actually, that’s a great thing. But I think a lot of the focus for those initiatives goes into hardware. And obviously, yes, we do need the hardware. You can’t run any of these things without the right hardware. And hardware does need to improve, and the faster it improves, the better off everyone is going to be. But obviously, being on the software side and seeing also the advances that software can make, I think there needs to be some proportional investment on the software side as well.

Many, many times we as a software company, we see that all these programs are really 100% dedicated to hardware. And there are many, many things, there are many, many open questions that software can answer, and there are many ways that software can, and software companies can benefit from the right policies and the right investment.

So that’s the one thing on the government side. Now the other thing, potentially, also for these government or other consortium or maybe other vendors is the generation of use case-based benchmarks. So we again, we see a lot of benchmarks and a lot of metrics that concentrate on hardware qualities. And again, this is important. And it’s good to have multiple metrics. It’s probably good to have diverse metrics and different metrics covering essentially different areas. It’s impossible in a very complicated field like ours to have a single metric that covers everything. And it’s also important to have benchmarks for the hardware, specifically, for the hardware as well.

But it’s also very, very important to start having some use case-specific benchmarks where software vendors can also basically compete and say, “Okay, we can do this better. We can load on a quantum computer an image of this size with our software, and the other company can load an image that’s smaller maybe or larger and compete on that.” Or, “We can maybe train quantum neural network this quickly on so many steps and this is the accuracy we get on this quantum neural network. Or we can maybe price an asset, a derivative in so many steps to this accuracy and drive really to the specific metrics that the industry is looking to us to provide for specific guidance.”

So the industry end users really don’t care about number of qubits, they care about how big of a molecule I can simulate, how complex of a derivative I can price and so on and so forth. So we need to put the benchmarks, basically, in those terms and provide those kinds of benchmarks.

Yuval: Benchmarks. Very interesting. My next to last question, could you tell me about your personal journey? How did you get into quantum computing?

Yianni: Yeah, that’s quite interesting. So I have a technical background. So I have a PhD in operations research. I started my career doing professional services, doing consulting for a company that built, basically, a software company that build an optimization solver. And I was one of the consultants that would go out and try to build decision support software for different types of industries, transportation systems and manufacturing. So we would build basically optimization solutions that would try to increase the throughput of a manufacturing plant or try to help with transportation dispatchers, basically, dispatching trucks or planes or what have you.

Then we got acquired by IBM. So this company, its name was ILOG, got acquired by IBM. And then, when we got acquired by IBM, I started moving, as I say to the dark side. So started going more into sales and business development. And slowly, within IBM, I moved to some sales leadership roles.

And at that time I’m getting, out of the blue, a LinkedIn message from Matt Johnson, the CEO of QCWare saying, “Hey, I’m in Palo Alto, do you want to join me for coffee?” And I look up this guy and he’s a CEO for quantum computing startup. And that was so foreign at that time. I mean, that was maybe 2016 when there was very little in the news about quantum computing. IBM still not had not announced, basically, it’s quantum computing program. It was so, so, so early. And very, very few people were in quantum computing. It was not really the hype machine maybe that it is right now.

And I was this close to, basically, denying the invitation, but then I said, “Okay, I’ll go for coffee, doesn’t hurt.” And the first conversation was also not very promising. So basically, Matt explained to me, “Hey, look, I know that you’re positioning these optimization solutions to these big corporations and quantum computers will be able to solve these optimization problems in the future. And tell us how you basically talk to these corporate entities about what optimization can do and how you position the solutions and how you get customers.”

And start to talking to them, but very quickly realized that they’re talking about very small problems. I mean, 10 variables. And this was in the beginning for me, it was incomprehensible that someone would try to set up a business where the biggest problem that can be solved is maybe 5 variables or 10 variables. And at the time, classical optimization could already solve problems of hundreds of thousands of variables. And those were the real problems that people wanted to solve. But then slowly we had a few more discussions. I started reading up more on quantum computing, and captured my imagination and the possibilities and all of that. And then, almost a year and a half, close to 2 years later, we talked about potentially moving over to QCWare to deal with sales and handle sales. And at the time, I had drank the Kool-Aid and was happy to join, basically.

Yuval: Excellent. So how can people get in touch with you to learn more about your work?

Yianni: Absolutely. My email is yianni.gamvros@qcware.com. You can reach out to me on Twitter or LinkedIn, Yianni Gamvros, or Y. Gamvros, @YGamvros or you can submit an info request on QCWare’s info page. They come to me actually, so you’ll be reaching directly into me if you actually just email info@qcware.com.

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

Yianni: Yuval, thank you so much for the very, very exciting and very interesting questions. Thanks.

Yuval Boger is a quantum computing executive. Known as the “Superposition Guy” as well as the original “Qubit Guy,” he most recently served as Chief Marketing Officer for Classiq. He can be reached on LinkedIn or at this email.

October 16, 2022