Quantum Finance with The Quantum Pirate, Sergio Gago
Sergio Gago works with quantum algorithms at Moody’s Analytics and tracks quantum industry news in his popular Substack newsletter, Quantum Pirates. The serial interim CTO, investor, and entrepreneur has deep experience in tech but is not afraid to poke a little fun at the industry. On this episode of The Quantum Spin, Sergio shares his expertise in quantum computing and quantum information systems and how he applies quantum tech to risk management for finance, insurance and other major industries.
Sergio is Managing Director of AI, Machine Learning and Quantum Computing at Moody’s Analytics. He founded, ran and sold Qapitan Quantum, an API marketplace. Sergio has studied quantum computing and quantum information systems, earning a degree in telecom engineering as well as an MBA. He enjoys teaching the next generation as Barcelona Technology School Master Director of Big Data and AI.
Host Veronica Combs is a quantum tech editor, writer and PR professional. She manages public relations for quantum computing and tech clients as an account manager with HKA Marketing Communications, the #1 agency in quantum tech PR. Veronica joined HKA from TechRepublic, where she was a senior writer. She has covered technology, healthcare and business strategy for more than 10 years.
Guest Sergio Gago: Hi, my name is Sergio Gago. I am the Quantum Pirate and the Managing Director of Quantum Computing and AI at Moody’s, and you’re listening to the Quantum Spin by HKA.
Host Veronica Combs: Hello, I’m Veronica Combs. Today I’m talking to a person who works with quantum algorithms and tracks the news of the industry in his popular newsletter, Quantum Pirates. He has deep experience in technology, but at the same time, is not afraid to poke a little bit of fun at the industry. Sergio, thank you so much for joining us today.
Sergio Gago: Thank you very much, Veronica, for having me here. It’s a pleasure to be talking on your podcast.
Veronica Combs: You have a degree in telecom engineering, you have an MBA, and I know that you’ve also studied quantum computing and quantum information systems; founded, ran and sold your own companies. How did you end up in quantum computing at Moody’s?
Sergio Gago: That is a fantastic question. I’ve been an engineer for a long time. My usual job was chief technology officer, but about five years ago, I decided that that was not enough. I sold one of my companies and I thought, “I need to learn something new,” so I decided to study biocomputing – finding patterns and building the automation for the biologists to find those relationships on those patterns. Computer scientists, we are kind of the lab assistants to the biologists. They’re the ones whose names appear first on the research papers because they know what’s actually happening with the cells, the viruses, the bacteria and all that.
And I recall well one class: we were with a professor, and he said we had to find a pattern in a very complicated problem for our computers to tackle, but there is a company in Canada that has a quantum computer available, and maybe you can drop this problem into their system, and maybe you can fix it or solve it exponentially. Of course, my mind exploded because I thought quantum was something for the future. I went into that rabbit hole and the rest is history.
I decided to stay at Moody’s and I convinced the CEO of the company that quantum was something very, very relevant for the financial industry. As it turns out, it indeed is, and we can talk in a minute about some of the cool stuff that we are doing.
Veronica Combs: Your weekly Substack newsletter, Quantum Pirates, is definitely one of the must-reads in the industry. I know that everyone looks forward to their Sunday edition to see what news you’ve highlighted. How did you start the newsletter?
Sergio Gago: It’s quite interesting, because I never thought it would be as big as it has become today, and now I go to conferences and people say, “Oh, you’re Sergio, The Quantum Pirate,” and I’m like, “What are you talking about?” I’m not a journalist, I’m not a specialist in communications, I’m not even an English native speaker. It all started as my own work, to stay on top of what is going on in the industry. One of the things I love the most about quantum is how many things happen every week, how fast things go in industry and research and altogether. It was a way to organize my ideas and what was really relevant. What I did was build an internal workflow where, whenever I found an article or a paper that I thought, “Hey, this is really interesting and I would like to share it with my friends,” I basically built a workflow with that; clicked on that and saved that article.
Then on Sunday, I would take all those articles together, curate them, and then write two or three paragraphs where I try to be a little bit fun, a little bit snarky, and to summarize things. But there is a lot of hype and there is a lot of duplicity in the news. One of the things that I am doing the most is selecting or curating things that I believe could be relevant for anyone in the industry, no matter where they work. The newsletter has been growing and growing and growing, now over 150 editions. One of the reasons for that is that I have been publishing it every week, no matter what. Now we have a small army of several thousand people reading it every week.
Veronica Combs: That workflow sounds really fantastic. In all my years of writing, I’ve not come up with anything quite that good. I do really like your sense of humor.
Sergio Gago: I was trying to be a little bit funny about what is going on with the industry, either by building some stupid memes or something like that.
Veronica Combs: You were poking fun at the whole, “Let’s pivot to AI” decision for all the quantum companies. That was definitely a joke that needed to be made. I’m glad that somebody did it.
Sergio Gago: Even from Moody’s perspective, we talk with many, many financial institutions, some of them with quantum teams, and we do see companies moving their focus, their budget, and their efforts into generative AI, first because it is the horizon now. This is happening, this is real, this is something tangible. And second, I think because quantum has had a lot of false expectations on what you could do quickly, maybe by hype-feeders that were looking more for the short-term type of thing. That did not happen, and we are now at the point where some people are even saying, “Hey, maybe we are starting to see the infamous ‘quantum winter,’ of sorts.” I personally have my hesitation on “quantum winter.” We try to be as neutral and balanced as possible: Yes, you need to invest in quantum today, but not for the hyped reasons.
Veronica Combs: All technology has a ramp-up phase, but quantum’s is, I dare say, a little steeper, a little longer than most. Like you said, you have to start now, just getting the basics.
Sergio Gago: We see, every day, new, really interesting stuff from we had our correcting codes that are breakthroughs on the amount of physical qubits that we need do new ways of implementing the qubits themselves all the way to new ways of implementing the algorithms. I’m personally carefully optimistic, and that is the reason why I think companies should be investing in quantum now.
Since we are not a quantum company, but we understand quantum, a lot of our clients that want to buy our data and our products come to us with questions like, “How should we approach quantum computing? When I started doing this research, I was promised quantum advantage, but it did not happen. What should I do next?” A lot of people are reaching out to us because they trust Moody’s, and we tell them, “You can also trust us to be your advisors or your guides in the complex field of quantum.” We deal in data and risk analysis and software for the financial industry, but also insurance, weather modeling and prediction, and so on and so forth.
We try to use the best tools available, whether it’s at the edge, to build those models. Those solutions are what we, in turn, sell to other companies in the industry, other banks and so on. At the end of the day, it’s a company with lots of data, doing lots of calculations on that data, and lots of modeling.
If you want to run an accurate calculation of how much of your debt could be at risk or how much of your equity could be at risk, how much of your portfolio could be at risk, you basically simulate billions of scenarios. Which one is going to default here, there, and what are the relations between those defaults. It’s throwing dice. That’s what Monte Carlo simulations are. I’m oversimplifying, yes.
We have an algorithm, we have quantum amplitude estimation that is quite old already that has an algorithm, but that’s the one that promises certain quadratic speedup on that calculation. I say certain because there’s a lot of quotes and notes and asterisks, but in principle, that is the case, right?
Our goal is to build things that are integratable. Even if it’s with very small problems, with very small complexity, how would that work in the whole pipeline? You can actually demo it, you can show it to people.
Veronica Combs: It is such a dynamic industry, like your newsletter reflects, but also, I was talking to a physicist the other day and he said, “We’re making advances and it’s going along, but the classical computing guys, they’re making advances, too, and so we’re trying to keep up with them and it’s kind of a back-and-forth.“ Obviously, quantum computing relies tremendously on classical computing now, but even the advances with classical supercomputers is another force shaping the quantum industry.
Sergio Gago: All the stuff that we are learning classically, and how the race is pushing everyone, classical development will heavily impact quantum and vice versa, especially when we mix the fields of machine learning and so on.
Veronica Combs: And it is definitely a challenge to look ahead far enough to see what’s possible, what’s in the future. But then again, you do have to watch out for the hype. And I’m curious, do you have sort of a checklist you run through mentally? How do you filter those articles or those promises that seem a little too shaky, or too much air and not enough actual substance?
Sergio Gago: I think the only way to really grasp whether something is real or not is by doing it yourself. You need to do the work. You need to run your own algorithms. You need to code them to start seeing the true limitations. You need to run an algorithm on 127-qubit device, with its noise, and see how that noise really destroys all the beautiful work that you’ve done mathematically. It is really frustrating. A lot of the people who make the hype claims can be divided into the ones who claim that because they don’t really know what is going on underneath, the ones who didn’t do the work; and the ones who are proactively being false about it, who know very well that there is no such thing or such advantage. I can handle one or the other, but you have to be very, very careful with that.
Now, from a corporation perspective, when you decide to invest in quantum, you have to position yourself, as well, on what do you want to do. When you try to convince your CEO or your board that this is a true investment, do you want to play this short-term game and promise ROI out of thin air? Or do you want to build the long path?
What I try to look at, when there’s a company in front of me, is what is for them something specific for quantum? Most of the companies in our field today really depend heavily on quantum happening. If quantum does not happen, they would disappear. There are other companies, like Google or IBM, whose business is not necessarily quantum. They invest heavily in this, they see it as the next generation, but for them, it is one additional tool. They tend to be less biased on what is going on, even though, with Google, of course, there’s a lot of conversation surrounding their announcements and their claims, but usually they’re more on the conservative side — usually, not always. Then companies like us, at Moody’s, believe that quantum computing will be a very disruptive force in the financial industry, but like many other technologies. We turn every stone on behalf of our clients. If quantum does not happen to be the one, it’s OK because we have other bets.
Veronica Combs: What comes to my mind is explainability. How do you explain how this works? Or how do you even explain the results while working with people who don’t have degrees in physics?
Sergio Gago: That is a fantastic question. I think it’s fundamental to leave the scientific realm a little bit and to be able to explain things in a very down-to-earth language that is related to what a company needs, benchmarking the enterprise way. If you think about the algorithms, the benchmark is going to be like the number of T gates and the depth of the circuits, but the reality is that on the enterprise side, no one cares about it, in the same way that people don’t care how the cloud works. What matters is whether you have a process that is faster, more accurate or cheaper to run than any other way of running it. Now I have a problem that I know can have 25% better accuracy or can run 10 times faster, but in order to run it at scale with the size of data that we need, I’m going to need, say, 700 logical qubits.
That is what we are trying to build with a product that we are about to launch. We are calling it the Quantum for Finance platform, and we’ll be able to talk more about this very soon, but basically it is about dropping your different classical solvers, quantum solvers, quantum-inspired solvers, HPC, you name it, and be able to benchmark and compare against the same enterprise metrics. Those are the numbers that your c-level execs will understand and how you validate these types of things. That’s all we need to know now, because financial institutions don’t really care when there is quantum advantage. We don’t mind. The only thing that we care about is that we are right there when it happens and that we are prepared.
A lot of people ask me the usual question, “When do you think there is going to be quantum advantage?” And I always say the same thing: “No. 1, I don’t know. No. 2, there is no quantum advantage as a whole; there may be advantage for one very specific problem. And No. 3, I don’t care. I only care that I am there when that happens.”
Veronica Combs: Can you share any advice on putting together a quantum team for an industry expert like Moody’s?
Sergio Gago: Instead of focusing on deep research, hiring PhDs to keep them working on a very specific problem or a part of the problem, and then coming out with a paper and publishing it, we decided to be a very pragmatic and application-first team. In that sense, we opted for more Jack of All Trades profiles.
When I started hiring people, what I told them was, “In the morning, you may be talking with a Quant, or quantitative analyst, who’s going to explain you a very complex and difficult way of how they calculate risk, using research that they did 20 years ago. Then you’re going to speak with the product people on how they implemented it on a piece of software that we have in the market. Then you’re going to have a call with a client who has absolutely no idea about quantum, and you will have to start by explaining qubits and superposition. Then you may have to go and give a talk to a group of students who are a little bit more knowledgeable. And finally, you will start your coding, and maybe, if you have time after doing the research, you’ll publish a paper or write all the documentation required for a grant, and so on and so forth. Normally, it’s the other way around: you hire one person for each of the different things that I just mentioned.
It’s really important to understand the whole pipeline. Now that the industry is getting a little bit more mature, we start getting a lot of questions from people, from banks, saying, “OK, you convinced me, I want to do this. What do I do now? We say “This is the profile for the team lead that you need, someone who’s business and science and engineering. You need a team lead who’s more on the research side. Then you need a programmer, you need someone with infrastructure knowledge, you need to set up your cloud environment — work with AWS Braket, for example, or with Microsoft Azure or another platform.
Another of the products that we are releasing very soon is a quantum-for-quantum-data-scientists program, which is basically all you need to know, all you need to learn in order to upskill your team. We’re kicking it off with building your quantum team and spreading the word at different conferences.
Veronica Combs: It sounds like a fascinating team of really smart people doing very challenging work.
Sergio Gago: It is a fantastic team. I’m super happy and very honored.
Veronica Combs: In your spare time – which I can’t imagine, there’s a whole lot of – you are working at Barcelona Technology School with a Master’s of Big Data and AI program. What’s it like working with students?
Sergio Gago: I think it’s humbling. It helps you get down back to your roots and meet a lot of amazing people that are going to be the leaders of the world tomorrow. Hopefully, some of them will be my bosses.
Veronica Combs: Thank you again for all your time today. It’s been great to hear about your work and we’ll definitely be keeping an eye on Moody’s and the platform for quants to bring them into the quantum world. Thanks so much for all your time, Sergio, I appreciate it.
Sergio Gago: Thank you very much, Veronica. Have a great day.