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Podcast with Florian Neukart, Chief Product Officer at Terra Quantum AG
My guest today is Florian Neukart, Chief Product Officer at Terra Quantum AG. Florian and I talk about their hybrid quantum/classical cloud and how it is different than quantum offerings of traditional cloud vendors, about his departure from Volkswagen, and much more.
Listen to additional podcasts here
THE FULL TRANSCRIPT IS BELOW
Yuval: Hello, Florian and thanks for joining me today.
Florian: Hi, Yuval. Thank you very much for the invitation. Thanks for having me.
Yuval: So who are you and what do you do?
Florian: My name is Florian Neukart, and I am the Chief Product Officer at Terra Quantum and an assistant professor for Quantum Computing at the University of Leiden. Terra Quantum is a quantum-as-a-service and a quantum technology company. That means we're active in all pillars of quantum technology, but the customer facing ones right now are algorithms as a service, compute as a service and safety as a service. For all of these three, we have products that are commercially available today already and, in the market, and used by customers. We continuously, of course, extend and improve these, and the team and I work in concert with research to develop new products. That means for the more fundamental work that happens in research, for all of the things that we prototypically develop, we need to figure out how to commercialize these technologies, how to commercialize research results. Very often when you look at research - and this is not specific to our company -, then some results are fundamental but a little further away from commercialization now, some have near-term potential, and some are immediately applicable to solve practical problems. Taking early results and prototypes, and building products around them that scale, that are usable, that are secure, product strategy and -marketing, business development, customer engagement, consulting, and some more things are what the organization that I'm responsible for is doing.
I've been teaching quantum computing at Leiden University’s Leiden Institute of Advanced Computer Science for many years now. I enjoy sort of a a comet-like existence at the university. That means I go there at least once a year to teach – all the other work can be done remotely. So the students have the pleasure to listen to me for a couple of hours per day, for a week or more. That's me in a nutshell, I'd say.
Yuval: Excellent. And before Terra Quantum you had an important role in Volkswagen and you and your team did some amazing things with quantum. So why did you go from Volkswagen, such a big company, to Terra Quantum?
Florian: That is a very interesting question. So there are a couple of things. So Volkswagen is a very innovative company when it comes to software development and in my last role I've been responsible for the data lab, which is an innovation hub with about 100 people strong, focusing on any software innovation within the Volkswagen group. That can be algorithms for environment perceptions and self-driving vehicles, that can be any algorithm for predicting market behavior, but it also includes quantum computing because that's part of many of these things that we look into today and either it is already part of it today, or will be sometime in the future. Still, quantum technologies is not the core of what Volkswagen does. So Volkswagen, as I said, they're very innovative and help push the field. But in the end they are like many other industry companies, consumers.
And I've always had this strong passion for quantum physics. And I could live this passion in academia, of course, but I'm also very, very interested in finding ways to commercialize the latest research and make products out of that. That people are interested, that they're using. And Terra Quantum is exactly the place where this happens. So we have exciting research going on. And right now, as you know, we are amidst this revolution. So for all of the pillars of quantum technology we see applications emerging. We see new fields opening up in quantum computing. We see new applications coming up or ideas for new applications every day, and being at the core of that and being able to work on technology that people will use that will help solve complex industry problems, will help improve the society. So this is what I can do with Terra Quantum and therefore I made this move.
So it's a different scale of the company, Terra Quantum is a scale up right now with about 140 people, whereas Volkswagen is a company with almost 700,000 people. So it's a different life, but it's a very, very exciting life.
Yuval: So you want to say that at Volkswagen you didn't know everyone by name and at Terra Quantum you do. That's good. You mentioned that Terra Quantum does algorithms as a service, compute as a service, security as a service. Let's start with the compute part and if we have time we can go to other areas. I saw that you have an offering called the QMware which appears to me, at least from the outside, as a hybrid quantum classical cloud. Could you explain what it is and how is it different than traditional cloud vendors that are adding quantum capabilities to their cloud?
Florian: Yeah, of course. So I need to talk about the whole stack here. So, what Terra Quantum does is, in terms of software for quantum computers, focus on the development, as you said, of hybrid algorithms. And hybrid algorithms, so that can mean many things. So you can look at algorithms, for example, that have a sequential processing where you have a classical part. So you'd have some prediction, say you predict traffic, and then you have some part that is solved quantumly like the optimization, in that case, how to distribute vehicles optimally. You can solve that with a quantum chip.
And then the other perspective that you could have is look at algorithms that are intermeshed. So where you have classical and quantum parts strongly interwoven. For example, a neural network. When you say you have a classical input, you have a classic layer and then you have a quantum circuit as the next layer, and then again a classical layer, and you use the output. So the area that you have to optimize the parameters for the quantum circuit again. And so the latter ones, not only in terms of neural networks, but in all of the aspects that we look into, be it optimization, be it simulation, be it machine learning. The latter ones are those that we are specifically interested in. And we found that not only by splitting parts into classical and quantum, we can obtain an advantage. We found that if we develop a specific hardware architecture, a specific integration with quantum chips, then these algorithms run even more efficiently. And this is the QMware cloud that we have. And now I would just start with what the QMware cloud is from the bottom, from the hardware level.
So from the hardware level, it means we have classical high-performance computing resources, as we know, which is CPU, some GPUs, data processing units, et cetera. Then we have our quantum chips next to them, but not next to them in the sense of coexisting, like many other cloud vendors do. So where you have maybe a QPU in some data center somewhere, and the classical hardware in another data center, and you access the QPU via a web service. No, for us it's different.
So we have an integration on a hardware level with a dedicated hardware interface that we develop for each of the QPUs. So, that means we have integration in a hardware level, and then what we build on top is an operating system. Our operating system is called Qognite and this operating system does many things. So for one, it virtualizes the hardware. So it virtualizes both classical and the quantum chips. And that means what you can do then with this virtualization is access a shared memory infrastructure. So we can share classical memory throughout all these resources. Of course, when the program or the problem is executed or solved, then you push it down to the hardware level. But the hardware level means really these both classical and quantum resources being next to each other, not spread all over the places.
And then on top of this operating system, we have our libraries. So these hybrid algorithms that I mentioned at the beginning, and now this combination of all of these things, this really makes it very efficient and easy to program for quantum computers or quantum assisted software. So in the end, it's very much like programming business software today. If I use my computer that I have in front of me, I do not need to worry too much about how to address the memory, how to address segments on the classical chip that I have in there, because the operating system and my programming language, plus my libraries they solve this problem for me. And that's how we see it for quantum computing. And what that means for an end user is that if they don't want to, they don't need to worry about how to address the quantum or classical resources. They don't need to worry about error behavior. They don't need to worry about topology of the chips because we do that for them.
And another beauty of that whole thing is that right now, so we have both physical QPUs that we can access or that we access, plus simulators. So what that means is if you write software today using this infrastructure, then even as the quantum hardware matures, even if we plug in new chips, even if we parallelize quantum chips, which is also something we do, which is very useful for certain kinds of algorithms, but people only start thinking about parallelization of quantum chips. So you don't need to touch the code again which is also very much different to many other vendors that we see out there. So you have to sometimes with new hardware, take care about newer behavior. We have to take care of that, of course, as integrators. So we need to solve that for the customers, but the end user doesn't have to. That was a very long monologue. I hope that helped a little to explain what it is.
Yuval: Absolutely. This was great. So one of the things I think I heard was almost co-locating the quantum processor with the classical processor. Does that mean that you have quantum computers that you own on premise in your data center?
Florian: So it's different. So we have a data center on our own. We have our own hardware development going on in terms of quantum chips, but you don't see this in the cloud yet what we do for now. So our hardware will come maybe say in two years, two and a half years, but what we do is integrate with any vendor out there. So we have a couple of advanced conversations with vendors out there that we plan to integrate over the next months. And we'll see, from our perspective, some of the most important ones in our cloud very soon. And you're right, that means we bring our classical hardware to wherever the quantum computer resides. But in the end, what we also have is a partnership with NTT, the data center provider, and at some point we will move the quantum chips into that data center. And they're prepared and ready for being able to operate and handle all the complexities here.
Yuval: And in terms of software development to run on your infrastructure, do you have to develop the software for me? If I'm an enterprise I have optimization problem, is that software that you need to develop for me, or can I bring software that I already developed for option pricing or chemical simulations and what have you, and just try to run it better on your infrastructure?
Florian: Yes. So both is possible. So you can run your software on our infrastructure, but ideally we can take one part of your software that you have, or you take the part of the software we have, where you run a complex optimization algorithm and plug in one of our optimization algorithms. So both is possible. So it will benefit already from running on our platform. But ideally you go end to end with the libraries that we provide. So it's always an API-first approach. It's easy to plug it in and just see what happens.
Yuval: And there's always this debate about abstraction versus vendor specifics. So, for instance, if I wanted to use an IonQ quantum computer, I could go directly to IonQ and use their API, or I could go through one of the cloud providers that host them and then use a more generic API. Do you feel that a customer would be losing some performance or functionality when they work through the generic API as opposed to the vendor specific API?
Florian: No, I don't think so. So I would even say they would gain because of the integration with the classical high-performance computing. So, if we look at what it means with today's quantum chips. So we all know that if you process a problem purely quantumly on a gate model chip, you most likely will not find something that is industrially relevant, be that in terms of simulation, be that in terms of optimization, will take us some time. Will take us some time to improve the errors, will take us some time to make chips that come with more high quality qubits. But if you integrate it with QMware then what we do what we always do with our customers is compare to best in business today because we can. So, since we have a significant part of classical high performance compute that executes whatever code you submit.
So if a customer now says we have some option pricing running, we have some collateral optimization running, what they want to see is a better solution to what they have now. And we can show that even with the scale of the chips, the quantum chips that we have today we can for one, run these problems in full complexity because of how we do it, and secondly, outperform existing algorithms. So I don't say we outperform everything that's out there, but for many cases where we give it a try, we outperform existing algorithms just by using punctually the quantum chip and doing everything else classically, or using our simulator which is in some instances also more useful, especially when you want to avoid any error
Yuval: Earlier in the conversation, you mentioned the algorithm as a service is something that Terra Quantum provides. I assume that means that I, as a customer, could go to you and you can develop an algorithm to solve a particular business problem? Is that what you mean?
Florian: Yes. That's one thing, but in the end, we mean also our libraries. So we developed many different algorithms clustered into simulation optimization machine learning, so the things that everyone is looking into, that are optimized to run on our infrastructure. So these we provide ready to use for customers. And we have an API that you can use for that that integrates with our libraries, but it is not a requirement. So in the end, you can also develop your own libraries or we develop software for you from scratch if there is something missing in our libraries. So, of course, we can help with that. We're very flexible in terms of how we work with customers. Some companies have an advanced quantum computing team so they would not rely too much on us to develop software solutions. But then there are others that just start and they may need more support here and then we can, of course, develop whatever is needed.
Yuval: If I take an analogy from the classical world on the cloud, I could use Google Cloud, for instance, for storage, but I could also use a Google API to, for instance, get driving directions from one point to another. Do you envision a situation - or maybe it exists today - that I have an API call for a Quantum Terra service for say a TSP problem, here are the stops that I want to make and tell me which one is the best sequence just through an API?
Florian: Yes. So it's very interesting that you bring this point up because there is something that is on our roadmap and will be released within the next couple months that goes into that direction. So in short months, I would be, "Yes, I can see that," but I won't talk more about what we are developing right now, since we haven't talked about it publicly.
Yuval: Could you give a few examples of customers that are using your QMware offering today?
Florian: Yes. So I cannot mention names since we haven't published anything in consent with customers, but I can give you the industry. So we work with automotive industry, we work with financial institutions, they're very interested in both algorithms that we provide and the hardware, plus cryptography solutions. So then pharmaceutical companies is also something that we have, and then aerospace is also very, very interesting. This is just a brief overview of the industries. So in the end, we have some more some less customers in all the verticals, but I think these are the strongest one right now.
Yuval: Most of the classical cloud providers are headquartered, at least, in the US.
Florian: Yes.
Yuval: And Terra quantum is, I believe, in Switzerland. Does it matter to you, does it matter to your customers that this is a European company as opposed to a US company?
Florian: No. So not too much. So in the end it can be an advantage sometimes because in Europe we have this strict data privacy laws. So no matter who the customer is, because our data centers are in Europe for now. So we'll have data centers here in the US soon as well, but for now they're in Europe. So we apply all these requirements, GDPR compliance, in our data centers. So this is something seen as an advantage, sometimes seen as an advantage, but in the end it's never been a challenge for someone to work with us. And I feel so always compared to the United States. So I know a lot is happening and also in China, a lot is happening in terms of quantum technology in these markets. But then in Europe you also have so many great people and good work going on. So I think we will see more and more quantum technology, quantum computing companies emerging over the next years, also software companies in Europe. So I think it will at some point even out in my point of view. So we'll see if that is true.
Yuval: You guys develop a lot of things yourself, but obviously there are aspects of the quantum computing stack that you don't develop. So if I were to make you, hypothetically, master of the universe, or at least master of the quantum universe for the next 18 months, what would you have your people work on to make your life better in quantum?
Florian: So I think we're on a good track with hardware development as well. So for the next 18 months, if it's possible, if I was master of the universe, then of course I would wish for a fault tolerant quantum computer with significant number of qubits so that we can tackle all the industrial problems that we see today already.
In terms of sensing the same here. So with quantum sensors, very often we're in a prototypical stadium. So, for example, if you look at quantum radar systems, we have these big boxes that are still sensitive to environmental influences, to precautions. So if we could somehow solve all the technical challenges at once, then we had finally would have them mobile. We would have them probably in vehicles, in airplanes. So it goes into all the pillars of quantum technology. I wish, of course, because I want to see this research come to fruition in terms of products, I would wish everything would go a little faster, but you know how it is. It's fundamental work that needs to be done, and then once that is done, engineering still has to solve many, many problems.
Yuval: Absolutely. And when you see the pillars of quantum communication, sensing and computing, sometimes it feels like three different silos. The computing folks only know other computing folks, the sensing guys and gals only know other sensing people. Do you see that merging in Terra Quantum or elsewhere that communication, computing and sensing are coming together for some customer applications?
Florian: Yes. So we see it coming together in the development that we do because many times it happens that you develop something for one pillar that can be reused in another pillar. That's one way to bring it together. But in terms of bringing it together on a customer end, I see that too. Because, so once people start being interested in securing their communications networks, then they also want to understand the threat. And once we talk about the threat, you need to talk about the technology and what it can do, and then people tend to be interested in that as well. So I think it's really interesting. It would be also interesting to hear your thoughts because everything seems to happen within the next years or happen over the last couple of years. So we seem to be in that sweet spot right now where all these quantum technologies mature such that we will have usable products rather sooner than later.
Yuval: Absolutely. Florian, how can people get in touch with you to learn more about your work,
Florian: A good way to do that is via LinkedIn. So I always check my LinkedIn messages and, of course, my email address.
Yuval: Thank you so much for joining me today.
Florian: Thank you very much for having me. It was very nice. Thanks for the questions and your interest.
My guest today is Florian Neukart, Chief Product Officer at Terra Quantum AG. Florian and I talk about their hybrid quantum/classical cloud and how it is different than quantum offerings of traditional cloud vendors, about his departure from Volkswagen, and much more.
Listen to additional podcasts here
THE FULL TRANSCRIPT IS BELOW
Yuval: Hello, Florian and thanks for joining me today.
Florian: Hi, Yuval. Thank you very much for the invitation. Thanks for having me.
Yuval: So who are you and what do you do?
Florian: My name is Florian Neukart, and I am the Chief Product Officer at Terra Quantum and an assistant professor for Quantum Computing at the University of Leiden. Terra Quantum is a quantum-as-a-service and a quantum technology company. That means we're active in all pillars of quantum technology, but the customer facing ones right now are algorithms as a service, compute as a service and safety as a service. For all of these three, we have products that are commercially available today already and, in the market, and used by customers. We continuously, of course, extend and improve these, and the team and I work in concert with research to develop new products. That means for the more fundamental work that happens in research, for all of the things that we prototypically develop, we need to figure out how to commercialize these technologies, how to commercialize research results. Very often when you look at research - and this is not specific to our company -, then some results are fundamental but a little further away from commercialization now, some have near-term potential, and some are immediately applicable to solve practical problems. Taking early results and prototypes, and building products around them that scale, that are usable, that are secure, product strategy and -marketing, business development, customer engagement, consulting, and some more things are what the organization that I'm responsible for is doing.
I've been teaching quantum computing at Leiden University’s Leiden Institute of Advanced Computer Science for many years now. I enjoy sort of a a comet-like existence at the university. That means I go there at least once a year to teach – all the other work can be done remotely. So the students have the pleasure to listen to me for a couple of hours per day, for a week or more. That's me in a nutshell, I'd say.
Yuval: Excellent. And before Terra Quantum you had an important role in Volkswagen and you and your team did some amazing things with quantum. So why did you go from Volkswagen, such a big company, to Terra Quantum?
Florian: That is a very interesting question. So there are a couple of things. So Volkswagen is a very innovative company when it comes to software development and in my last role I've been responsible for the data lab, which is an innovation hub with about 100 people strong, focusing on any software innovation within the Volkswagen group. That can be algorithms for environment perceptions and self-driving vehicles, that can be any algorithm for predicting market behavior, but it also includes quantum computing because that's part of many of these things that we look into today and either it is already part of it today, or will be sometime in the future. Still, quantum technologies is not the core of what Volkswagen does. So Volkswagen, as I said, they're very innovative and help push the field. But in the end they are like many other industry companies, consumers.
And I've always had this strong passion for quantum physics. And I could live this passion in academia, of course, but I'm also very, very interested in finding ways to commercialize the latest research and make products out of that. That people are interested, that they're using. And Terra Quantum is exactly the place where this happens. So we have exciting research going on. And right now, as you know, we are amidst this revolution. So for all of the pillars of quantum technology we see applications emerging. We see new fields opening up in quantum computing. We see new applications coming up or ideas for new applications every day, and being at the core of that and being able to work on technology that people will use that will help solve complex industry problems, will help improve the society. So this is what I can do with Terra Quantum and therefore I made this move.
So it's a different scale of the company, Terra Quantum is a scale up right now with about 140 people, whereas Volkswagen is a company with almost 700,000 people. So it's a different life, but it's a very, very exciting life.
Yuval: So you want to say that at Volkswagen you didn't know everyone by name and at Terra Quantum you do. That's good. You mentioned that Terra Quantum does algorithms as a service, compute as a service, security as a service. Let's start with the compute part and if we have time we can go to other areas. I saw that you have an offering called the QMware which appears to me, at least from the outside, as a hybrid quantum classical cloud. Could you explain what it is and how is it different than traditional cloud vendors that are adding quantum capabilities to their cloud?
Florian: Yeah, of course. So I need to talk about the whole stack here. So, what Terra Quantum does is, in terms of software for quantum computers, focus on the development, as you said, of hybrid algorithms. And hybrid algorithms, so that can mean many things. So you can look at algorithms, for example, that have a sequential processing where you have a classical part. So you'd have some prediction, say you predict traffic, and then you have some part that is solved quantumly like the optimization, in that case, how to distribute vehicles optimally. You can solve that with a quantum chip.
And then the other perspective that you could have is look at algorithms that are intermeshed. So where you have classical and quantum parts strongly interwoven. For example, a neural network. When you say you have a classical input, you have a classic layer and then you have a quantum circuit as the next layer, and then again a classical layer, and you use the output. So the area that you have to optimize the parameters for the quantum circuit again. And so the latter ones, not only in terms of neural networks, but in all of the aspects that we look into, be it optimization, be it simulation, be it machine learning. The latter ones are those that we are specifically interested in. And we found that not only by splitting parts into classical and quantum, we can obtain an advantage. We found that if we develop a specific hardware architecture, a specific integration with quantum chips, then these algorithms run even more efficiently. And this is the QMware cloud that we have. And now I would just start with what the QMware cloud is from the bottom, from the hardware level.
So from the hardware level, it means we have classical high-performance computing resources, as we know, which is CPU, some GPUs, data processing units, et cetera. Then we have our quantum chips next to them, but not next to them in the sense of coexisting, like many other cloud vendors do. So where you have maybe a QPU in some data center somewhere, and the classical hardware in another data center, and you access the QPU via a web service. No, for us it's different.
So we have an integration on a hardware level with a dedicated hardware interface that we develop for each of the QPUs. So, that means we have integration in a hardware level, and then what we build on top is an operating system. Our operating system is called Qognite and this operating system does many things. So for one, it virtualizes the hardware. So it virtualizes both classical and the quantum chips. And that means what you can do then with this virtualization is access a shared memory infrastructure. So we can share classical memory throughout all these resources. Of course, when the program or the problem is executed or solved, then you push it down to the hardware level. But the hardware level means really these both classical and quantum resources being next to each other, not spread all over the places.
And then on top of this operating system, we have our libraries. So these hybrid algorithms that I mentioned at the beginning, and now this combination of all of these things, this really makes it very efficient and easy to program for quantum computers or quantum assisted software. So in the end, it's very much like programming business software today. If I use my computer that I have in front of me, I do not need to worry too much about how to address the memory, how to address segments on the classical chip that I have in there, because the operating system and my programming language, plus my libraries they solve this problem for me. And that's how we see it for quantum computing. And what that means for an end user is that if they don't want to, they don't need to worry about how to address the quantum or classical resources. They don't need to worry about error behavior. They don't need to worry about topology of the chips because we do that for them.
And another beauty of that whole thing is that right now, so we have both physical QPUs that we can access or that we access, plus simulators. So what that means is if you write software today using this infrastructure, then even as the quantum hardware matures, even if we plug in new chips, even if we parallelize quantum chips, which is also something we do, which is very useful for certain kinds of algorithms, but people only start thinking about parallelization of quantum chips. So you don't need to touch the code again which is also very much different to many other vendors that we see out there. So you have to sometimes with new hardware, take care about newer behavior. We have to take care of that, of course, as integrators. So we need to solve that for the customers, but the end user doesn't have to. That was a very long monologue. I hope that helped a little to explain what it is.
Yuval: Absolutely. This was great. So one of the things I think I heard was almost co-locating the quantum processor with the classical processor. Does that mean that you have quantum computers that you own on premise in your data center?
Florian: So it's different. So we have a data center on our own. We have our own hardware development going on in terms of quantum chips, but you don't see this in the cloud yet what we do for now. So our hardware will come maybe say in two years, two and a half years, but what we do is integrate with any vendor out there. So we have a couple of advanced conversations with vendors out there that we plan to integrate over the next months. And we'll see, from our perspective, some of the most important ones in our cloud very soon. And you're right, that means we bring our classical hardware to wherever the quantum computer resides. But in the end, what we also have is a partnership with NTT, the data center provider, and at some point we will move the quantum chips into that data center. And they're prepared and ready for being able to operate and handle all the complexities here.
Yuval: And in terms of software development to run on your infrastructure, do you have to develop the software for me? If I'm an enterprise I have optimization problem, is that software that you need to develop for me, or can I bring software that I already developed for option pricing or chemical simulations and what have you, and just try to run it better on your infrastructure?
Florian: Yes. So both is possible. So you can run your software on our infrastructure, but ideally we can take one part of your software that you have, or you take the part of the software we have, where you run a complex optimization algorithm and plug in one of our optimization algorithms. So both is possible. So it will benefit already from running on our platform. But ideally you go end to end with the libraries that we provide. So it's always an API-first approach. It's easy to plug it in and just see what happens.
Yuval: And there's always this debate about abstraction versus vendor specifics. So, for instance, if I wanted to use an IonQ quantum computer, I could go directly to IonQ and use their API, or I could go through one of the cloud providers that host them and then use a more generic API. Do you feel that a customer would be losing some performance or functionality when they work through the generic API as opposed to the vendor specific API?
Florian: No, I don't think so. So I would even say they would gain because of the integration with the classical high-performance computing. So, if we look at what it means with today's quantum chips. So we all know that if you process a problem purely quantumly on a gate model chip, you most likely will not find something that is industrially relevant, be that in terms of simulation, be that in terms of optimization, will take us some time. Will take us some time to improve the errors, will take us some time to make chips that come with more high quality qubits. But if you integrate it with QMware then what we do what we always do with our customers is compare to best in business today because we can. So, since we have a significant part of classical high performance compute that executes whatever code you submit.
So if a customer now says we have some option pricing running, we have some collateral optimization running, what they want to see is a better solution to what they have now. And we can show that even with the scale of the chips, the quantum chips that we have today we can for one, run these problems in full complexity because of how we do it, and secondly, outperform existing algorithms. So I don't say we outperform everything that's out there, but for many cases where we give it a try, we outperform existing algorithms just by using punctually the quantum chip and doing everything else classically, or using our simulator which is in some instances also more useful, especially when you want to avoid any error
Yuval: Earlier in the conversation, you mentioned the algorithm as a service is something that Terra Quantum provides. I assume that means that I, as a customer, could go to you and you can develop an algorithm to solve a particular business problem? Is that what you mean?
Florian: Yes. That's one thing, but in the end, we mean also our libraries. So we developed many different algorithms clustered into simulation optimization machine learning, so the things that everyone is looking into, that are optimized to run on our infrastructure. So these we provide ready to use for customers. And we have an API that you can use for that that integrates with our libraries, but it is not a requirement. So in the end, you can also develop your own libraries or we develop software for you from scratch if there is something missing in our libraries. So, of course, we can help with that. We're very flexible in terms of how we work with customers. Some companies have an advanced quantum computing team so they would not rely too much on us to develop software solutions. But then there are others that just start and they may need more support here and then we can, of course, develop whatever is needed.
Yuval: If I take an analogy from the classical world on the cloud, I could use Google Cloud, for instance, for storage, but I could also use a Google API to, for instance, get driving directions from one point to another. Do you envision a situation - or maybe it exists today - that I have an API call for a Quantum Terra service for say a TSP problem, here are the stops that I want to make and tell me which one is the best sequence just through an API?
Florian: Yes. So it's very interesting that you bring this point up because there is something that is on our roadmap and will be released within the next couple months that goes into that direction. So in short months, I would be, "Yes, I can see that," but I won't talk more about what we are developing right now, since we haven't talked about it publicly.
Yuval: Could you give a few examples of customers that are using your QMware offering today?
Florian: Yes. So I cannot mention names since we haven't published anything in consent with customers, but I can give you the industry. So we work with automotive industry, we work with financial institutions, they're very interested in both algorithms that we provide and the hardware, plus cryptography solutions. So then pharmaceutical companies is also something that we have, and then aerospace is also very, very interesting. This is just a brief overview of the industries. So in the end, we have some more some less customers in all the verticals, but I think these are the strongest one right now.
Yuval: Most of the classical cloud providers are headquartered, at least, in the US.
Florian: Yes.
Yuval: And Terra quantum is, I believe, in Switzerland. Does it matter to you, does it matter to your customers that this is a European company as opposed to a US company?
Florian: No. So not too much. So in the end it can be an advantage sometimes because in Europe we have this strict data privacy laws. So no matter who the customer is, because our data centers are in Europe for now. So we'll have data centers here in the US soon as well, but for now they're in Europe. So we apply all these requirements, GDPR compliance, in our data centers. So this is something seen as an advantage, sometimes seen as an advantage, but in the end it's never been a challenge for someone to work with us. And I feel so always compared to the United States. So I know a lot is happening and also in China, a lot is happening in terms of quantum technology in these markets. But then in Europe you also have so many great people and good work going on. So I think we will see more and more quantum technology, quantum computing companies emerging over the next years, also software companies in Europe. So I think it will at some point even out in my point of view. So we'll see if that is true.
Yuval: You guys develop a lot of things yourself, but obviously there are aspects of the quantum computing stack that you don't develop. So if I were to make you, hypothetically, master of the universe, or at least master of the quantum universe for the next 18 months, what would you have your people work on to make your life better in quantum?
Florian: So I think we're on a good track with hardware development as well. So for the next 18 months, if it's possible, if I was master of the universe, then of course I would wish for a fault tolerant quantum computer with significant number of qubits so that we can tackle all the industrial problems that we see today already.
In terms of sensing the same here. So with quantum sensors, very often we're in a prototypical stadium. So, for example, if you look at quantum radar systems, we have these big boxes that are still sensitive to environmental influences, to precautions. So if we could somehow solve all the technical challenges at once, then we had finally would have them mobile. We would have them probably in vehicles, in airplanes. So it goes into all the pillars of quantum technology. I wish, of course, because I want to see this research come to fruition in terms of products, I would wish everything would go a little faster, but you know how it is. It's fundamental work that needs to be done, and then once that is done, engineering still has to solve many, many problems.
Yuval: Absolutely. And when you see the pillars of quantum communication, sensing and computing, sometimes it feels like three different silos. The computing folks only know other computing folks, the sensing guys and gals only know other sensing people. Do you see that merging in Terra Quantum or elsewhere that communication, computing and sensing are coming together for some customer applications?
Florian: Yes. So we see it coming together in the development that we do because many times it happens that you develop something for one pillar that can be reused in another pillar. That's one way to bring it together. But in terms of bringing it together on a customer end, I see that too. Because, so once people start being interested in securing their communications networks, then they also want to understand the threat. And once we talk about the threat, you need to talk about the technology and what it can do, and then people tend to be interested in that as well. So I think it's really interesting. It would be also interesting to hear your thoughts because everything seems to happen within the next years or happen over the last couple of years. So we seem to be in that sweet spot right now where all these quantum technologies mature such that we will have usable products rather sooner than later.
Yuval: Absolutely. Florian, how can people get in touch with you to learn more about your work,
Florian: A good way to do that is via LinkedIn. So I always check my LinkedIn messages and, of course, my email address.
Yuval: Thank you so much for joining me today.
Florian: Thank you very much for having me. It was very nice. Thanks for the questions and your interest.
About "The Qubit Guy's Podcast"
Hosted by The Qubit Guy (Yuval Boger, our Chief Marketing Officer), the podcast hosts thought leaders in quantum computing to discuss business and technical questions that impact the quantum computing ecosystem. Our guests provide interesting insights about quantum computer software and algorithm, quantum computer hardware, key applications for quantum computing, market studies of the quantum industry and more.
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