theCUBE + NYSE Wired: Quantum 101 | Yuval Boger, QuEra Computing

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Yuval Boger

Chief Commercial Officer

QuEra Computing

play_circle_outline Room Temperature Rubidium-87 Neutral-Atom Qubits: Identical Atoms, Minimal Calibration, Compact Low-Power

play_circle_outline Aquila Neutral Atom Quantum System on AWS Serving BMW, JPMorgan, National Labs and Universities Since 2022

play_circle_outline AWS Libra 2028 fault tolerant quantum computer: science simulations, limited near-term commercial gains, future encryption risks and restricted access

play_circle_outline Scaling AI Platform: $300M+ Funding, Strategic Partnerships, Systems Integration and Global Expansion by 2028

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Yuval Boger, QuEra Computing

Yuval Boger

Chief Commercial Officer QuEra Computing

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Gemma Allen

>> (INTRO)Welcome back to theCUBE Studio here at the New York Stock Exchange. I'm Gemma Allen, co-host of NYSE Wired's Quantum 101. And today we are talking about how for years quantum computing has lived somewhere between scientific breakthrough and sci-fi. Now, QuEra is putting a date on that transition from one to the other. That is 2028, when it says its first fault-tolerant quantum computer named Libra will come online on AWS. So the question isn't whether quantum computing is possible anymore. It's how soon it becomes commercially viable. What does that transition look like and what will it take to get there? Joining us is Yuval Boger, Chief Commercial Officer at QuEra Computing. Welcome, Yuval.

Yuval Boger

>> Good to be here, Gemma.

Gemma Allen

>> So in the short time I had to prep for this, Yuval, I learned quite a bit about quantum computing that I didn't already know, quite frankly. And maybe we can start by you giving me the 101 on what I learned. So I learned that qubits are actually fickle, fickle fellows. They are sensitive to environmental factors in ways I had not assumed. And also, quantum doesn't necessarily need to live on the chip. Am I correct? Maybe you can start by setting out the 101, demystify this for me somewhat.

Yuval Boger

>> You're absolutely correct. So quantum computing is a new type of computing. We expect it to live alongside CPUs and GPUs in the data center or on the cloud. There are multiple ways to create quantum computers. As you mentioned, the fundamental unit of computation is called a qubit, a quantum bit, and different companies have different approaches to do it. Some use silicon, some use particles of light, photons. We use neutral atoms. And what neutral atoms are, our qubits are individual atoms, rubidium-87 in our case, and they're neutral because they don't have an excess electron or a missing electron that actually makes them pretty insensitive to the environment, which is a good thing. We then control these atoms, these qubits, using miniature laser beams. We can bring these atoms together. When we bring them together, we can make them interact. When they're farther apart, they are indifferent. And so the calculation is moving these atoms around, shooting controlled laser beams on them to make them interact. And at the end measuring them, essentially taking a photo of the atoms, and then we can realize which qubits are 1, which qubits are 0, and that allows us to determine the result of the calculation. Neutral atoms are very interesting. One reason is because they're perfectly identical. There's no atomic calibration. Every atom is identical to the next. And the other thing is that we operate at room temperature. We do not require these massive, expensive, power-hungry cryogenic cooling units. So our system is about the size of two ping pong tables, can sit in a data center very, very comfortably and very power efficiently.

Gemma Allen

>> Wow. So really, in some respects, changes the broad mainstream picture we have of quantum, which is these supercomputers that look like they were designed by Versace. If we're taking the IBM examples that I've seen, and cost $50 million minimum. I could even be wrong about that. It could be a lot more. And I guess the narrative is that it would be very, very difficult to scale those in any sort of commercial fashion. Talk about what this means from the perspective of how you could bring something quantum applicable and efficient to market in this space using QuEra's technology. How close are you to that?

Yuval Boger

>> We are very close. It used to be that quantum computers were always 5 to 10 years away. Someday it will happen. But we're moving from this one day to day one of quantum computers. Our quantum computers are becoming increasingly powerful, so they are closer and closer to being a supercomputer in terms of capability. But they still are not very expensive to make. They don't take a lot of power two kilowatts and not megawatts. They don't require occupying an entire stadium. And so in a sense, we're making sort of the 777 of quantum computing, something that's usable, that's powerful and affordable, as opposed to maybe the B-2 of quantum computing that other companies make, which requires sort of nation-state budgets.

Gemma Allen

>> Wow.

Yuval Boger

>> These—

Gemma Allen

>> I'm just interrupting you there. So you launched a product in 2022 where you brought some sort of product to market, which is Aquila, right? And that was put in place, or I guess brought to researchers and brought to labs or to customers through Amazon Braket. What sort of usage, what sort of use cases and I guess clients has that product had to date?

Yuval Boger

>> Absolutely. So just about 4 years ago, I mean, in 3 days we're going to be celebrating the Aquila's 4th birthday. On the Amazon cloud. We brought our first system to AWS, so anyone with a credit card can use it right now. And indeed, numerous people have. And so we've seen a wide range of applications and companies and organizations use it, from industrial giants like BMW and JPMorgan to research universities to national labs and so on. Dozens and dozens of papers have been published, some revealing new scientific results, some on optimization or machine learning. And one of the things we're really proud of is our operating success. Aquila has been on the cloud for 4 years. It's running at 99% uptime. We've met the stringent Amazon Service Level Agreement. And I think that's one reason that Amazon decided to renew our agreement and become an even more strategic collaboration towards bringing our fault-tolerant quantum machine to the cloud in 2028.

Gemma Allen

>> And that product is Libra. That commercial launch is Libra. So I know you mentioned that it's available to anybody with a credit card, right? I guess my question is, should it be? First of all, somewhat of a spicy question, but talk about, what sorts of use cases you are seeing, like where is quantum actually delivering market and commercial value right now? We hear, we at least sometimes hear of it in the drug discovery space and certain sorts of industries like pharmaceutical and others. But where do you know for sure that Aquila has actually had market impact?

Yuval Boger

>> So the truth is that quantum computers are, if I can say that impolitely, quantum computers are toys. They're toys. They're beautiful, expensive, sophisticated toys, but they're toys in the sense that there's not very much that you can do on a quantum computer that you cannot do on a classical supercomputer, except of course, prepare and learn and understand how quantum works. So one reason that Aquila was made generally available is because it's primarily a scientific instrument. And as we think about upcoming applications, we mean our fault-tolerant systems, systems that could do longer, more powerful more meaningful calculations, systems that can solve problems that are indeed worth solving. We look at the world and see two kinds of problems. We see problems that are quantum in nature. So molecular simulation, for instance, where the system is governed by quantum mechanics. And we see problems that are, say, optimization problems that are not born quantum, but perhaps could be mapped onto a quantum system for solution. We think the initial applications, the initial uses will be of the first type, those that are quantum systems. So it could be a better EV battery, it could be corrosion-resistant coating, it could be new solar cells, of course, new drugs and compounds, or even the ability to understand the behavior of certain compounds as an input to AI systems to enlarge their training base.

Gemma Allen

>> And when I asked you there, should it be regulated? I want to maybe unpack what I meant a little bit, because one thing we know about quantum is that it's very, very powerful, right? And we don't want a scenario where it's in the hands of the wrong actor. Is what you're saying that at this point in this commercial race that we're in, we're not quite there where quantum presents that level of risk? We hear a lot from folks about the risk of quantum to encryption, for example, right? And what that could look like in the world of 2030. How do you think about that side of this frontier, Yuval?

Yuval Boger

>> That's an excellent question. And you're right, today's systems could not be used for dangerous applications. As you think about cracking encryption, the upcoming Libra system is not going to be able to do that. But unlike Aquila, our existing system that's on the cloud for 4 years, Libra is unlikely to be initially available for the global public. It will be a much more selective group of handpicked customers that can both afford the use, have problems that are worth solving, and have problems that, if solved, have a benefit to humanity. Longer term, every new technology, whether it's the internet or cars or drug discovery, has both positive uses, perhaps, as well as perhaps nefarious uses. And we're working closely with our partners, whether on the cloud or on-prem and with various governments to make sure that we use it for the right reasons and for the right purposes.

Gemma Allen

>> So help me understand the business model here. I know you have a very strong partnership with AWS. I guess my first question is, are you AWS agnostic or are there other hyperscalers on the horizon in terms of how this will play out? And secondly, what is the commerciality here? How is this licensed, per se, to AWS, direct to user, which I'm sure is going to be some sort of corporate end user on their end. But help me understand that.

Yuval Boger

>> We have two main paths to go to market. One is on the cloud. The cloud is easy to access, is easy to experiment with. You don't have to pay for maintaining the infrastructure. You can use it on demand. And so our partnership with AWS does that. Today, the system is essentially metered by the number of shots or by the time that you use it. In the future, it may change and may be more on exactly what job you're producing and, more focused on result than the process. The other important go-to-market is on-prem. So we have sold a $42 million system to the National Institute of Advanced Industrial Science and Technology in Japan. That system has been delivered and installed. And we certainly see that some customers wanna use quantum on the cloud and some want to use it on-prem. Just last week, we announced a strategic partnership with HPE, Hewlett Packard Enterprise, which is really the de facto integrator in US National Labs and many other HPC centers. So we can deliver the system the way customers wanna use it. Some wanna use it on the cloud, some wanna use it on-prem, and for others, it may be a combination of both.

Gemma Allen

>> I'm interested in the on-prem use case because we talk to a lot of folks in the AI factory space about moving back on-prem, right? On-prem is having a reimagined moment, I would say. And a lot of that is around obviously data sovereignty, data privacy, data control, and future-proofing their kind of business models. What sort of use case, if you can share, is Japan delivering?

Yuval Boger

>> So AIST is a research institution, and so they open the system to both their customers as well as partners, and maybe eventually to an even wider group. It's still in the scientific exploration phase, but you're right, on-prem systems— there are many reasons for companies to buy on-prem systems. One is control. When you're on the cloud, you're sharing the resources with others, and if someone submits a job that takes 5 hours and you're just behind and waiting for that job to complete. When the system is on-prem, you control your own destiny. The other side, of course, is data sovereignty. And the third side that's sometimes overlooked is that quantum computers are unlikely to be standalone computers. They're likely to work with existing high-performance classical computers. And some of the work we're doing with companies such as HPE shows it's when you achieve that tight integration between a classical supercomputer and a quantum supercomputer, 1+ 1 becomes 3 in a good way and you can take the best of both worlds and achieve results that you couldn't achieve with just one of these components.

Gemma Allen

>> Okay. So you have an interesting investment story, too. You've raised more than $230 million. You have some big investors there. You've got Google's Quantum Lab. SoftBank, NVIDIA, right? You've got great legitimacy in terms of who sees the value in this. I guess my first question on this is how far does $230 million go in the world of quantum? What sort of runway does that give you and what's ahead from the perspective of future investment? Yuval—

Yuval Boger

>> so we are very well capitalized, both from an investor standpoint. As you mentioned, we've raised over $300 million from NVIDIA and Google and SoftBank Vision Fund and Valor and many other fantastic investors. We also sell, so revenue from customers is a fantastic source of funding. And we're also fortunate to be supported by the government. We were selected for DARPA QBI Quantum Benchmarking Initiative Phase A and Phase B, and we're hopeful that we will also be selected for Phase C. We have received support from the UK government, from the Japanese government. So we're well capitalized. Having said that, quantum is expensive. Lasers are expensive. we have 200 people, half of which are PhDs there. We have to pay salaries. We have to pay for many interesting components. So it may be that we will be raising additional money in the not too distant future.

Gemma Allen

>> Okay, so last question to you, Yuval. Obviously 2028 is a short blink away. I'm sure it feels like in your world. I'm guessing the priority for you right now is focusing on Libra and that outcome. But maybe share with us, what does the next 12 to 18 months look like? What does it take to get there? Are you hiring more PhDs? I'm impressed. No, there are 200 or so people, half of which are PhDs. Are they in Boston? help us understand what the roadmap looks like for you from here.

Yuval Boger

>> So one of the things we pride ourselves on is that QuEra is about, we say, more science and less fiction. Sometimes quantum companies paint a very, very rosy future, and the jump between where they are today and where they expect to be in a year or two sometimes stretches imagination. We have proven all the key components that are required to deliver this fault-tolerant computer, the computer that can make long calculations that can solve problems worth solving. So for us, there's a question of system integration, integrating all these components into a coherent system that can live comfortably on AWS. We continue to grow the team. Our headquarters is in Boston, but we also operate in New Mexico. We just opened an office in Maryland. We have a large office in Japan, in the UK, and a new office in Zurich, in Switzerland. So we go to wherever there is significant opportunity and strategic reason to go. So we expect to grow the people. We are building half a dozen systems and perhaps we'll build even more. And obviously we're working very closely with our partners, NVIDIA, HPE, AWS. We're doing some fantastic work with Anthropic. And all leading to a system that will solve problems worth solving in 2028.

Gemma Allen

>> Well, I first of all love to hear that you're hiring and that there is more growth and brain trust going into this space at that pace and also at that global scale. That's also very interesting. And you mentioned some great frontier players there. You're certainly in the right company. So Yuval Boger, I wish you and the team all the best. Hopefully a trip to New York is on the horizon too, and you can come visit us here at the NYSE studio.

Yuval Boger

>> Absolutely. Thank you very much, Gemma.

Gemma Allen

>> Thanks for joining us on NYSE Wired. I'm Gemma Allen here at theCUBE Studio. This is NYSE Wired's Quantum 101. Thanks for watching.

Yuval Boger, QuEra Computing

search

Gemma Allen

>> (INTRO)Welcome back to theCUBE Studio here at the New York Stock Exchange. I'm Gemma Allen, co-host of NYSE Wired's Quantum 101. And today we are talking about how for years quantum computing has lived somewhere between scientific breakthrough and sci-fi. Now, QuEra is putting a date on that transition from one to the other. That is 2028, when it says its first fault-tolerant quantum computer named Libra will come online on AWS. So the question isn't whether quantum computing is possible anymore. It's how soon it becomes commercially viable. What does that transition look like and what will it take to get there? Joining us is Yuval Boger, Chief Commercial Officer at QuEra Computing. Welcome, Yuval.

Yuval Boger

>> Good to be here, Gemma.

Gemma Allen

>> So in the short time I had to prep for this, Yuval, I learned quite a bit about quantum computing that I didn't already know, quite frankly. And maybe we can start by you giving me the 101 on what I learned. So I learned that qubits are actually fickle, fickle fellows. They are sensitive to environmental factors in ways I had not assumed. And also, quantum doesn't necessarily need to live on the chip. Am I correct? Maybe you can start by setting out the 101, demystify this for me somewhat.

Yuval Boger

>> You're absolutely correct. So quantum computing is a new type of computing. We expect it to live alongside CPUs and GPUs in the data center or on the cloud. There are multiple ways to create quantum computers. As you mentioned, the fundamental unit of computation is called a qubit, a quantum bit, and different companies have different approaches to do it. Some use silicon, some use particles of light, photons. We use neutral atoms. And what neutral atoms are, our qubits are individual atoms, rubidium-87 in our case, and they're neutral because they don't have an excess electron or a missing electron that actually makes them pretty insensitive to the environment, which is a good thing. We then control these atoms, these qubits, using miniature laser beams. We can bring these atoms together. When we bring them together, we can make them interact. When they're farther apart, they are indifferent. And so the calculation is moving these atoms around, shooting controlled laser beams on them to make them interact. And at the end measuring them, essentially taking a photo of the atoms, and then we can realize which qubits are 1, which qubits are 0, and that allows us to determine the result of the calculation. Neutral atoms are very interesting. One reason is because they're perfectly identical. There's no atomic calibration. Every atom is identical to the next. And the other thing is that we operate at room temperature. We do not require these massive, expensive, power-hungry cryogenic cooling units. So our system is about the size of two ping pong tables, can sit in a data center very, very comfortably and very power efficiently.

Gemma Allen

>> Wow. So really, in some respects, changes the broad mainstream picture we have of quantum, which is these supercomputers that look like they were designed by Versace. If we're taking the IBM examples that I've seen, and cost $50 million minimum. I could even be wrong about that. It could be a lot more. And I guess the narrative is that it would be very, very difficult to scale those in any sort of commercial fashion. Talk about what this means from the perspective of how you could bring something quantum applicable and efficient to market in this space using QuEra's technology. How close are you to that?

Yuval Boger

>> We are very close. It used to be that quantum computers were always 5 to 10 years away. Someday it will happen. But we're moving from this one day to day one of quantum computers. Our quantum computers are becoming increasingly powerful, so they are closer and closer to being a supercomputer in terms of capability. But they still are not very expensive to make. They don't take a lot of power two kilowatts and not megawatts. They don't require occupying an entire stadium. And so in a sense, we're making sort of the 777 of quantum computing, something that's usable, that's powerful and affordable, as opposed to maybe the B-2 of quantum computing that other companies make, which requires sort of nation-state budgets.

Gemma Allen

>> Wow.

Yuval Boger

>> These—

Gemma Allen

>> I'm just interrupting you there. So you launched a product in 2022 where you brought some sort of product to market, which is Aquila, right? And that was put in place, or I guess brought to researchers and brought to labs or to customers through Amazon Braket. What sort of usage, what sort of use cases and I guess clients has that product had to date?

Yuval Boger

>> Absolutely. So just about 4 years ago, I mean, in 3 days we're going to be celebrating the Aquila's 4th birthday. On the Amazon cloud. We brought our first system to AWS, so anyone with a credit card can use it right now. And indeed, numerous people have. And so we've seen a wide range of applications and companies and organizations use it, from industrial giants like BMW and JPMorgan to research universities to national labs and so on. Dozens and dozens of papers have been published, some revealing new scientific results, some on optimization or machine learning. And one of the things we're really proud of is our operating success. Aquila has been on the cloud for 4 years. It's running at 99% uptime. We've met the stringent Amazon Service Level Agreement. And I think that's one reason that Amazon decided to renew our agreement and become an even more strategic collaboration towards bringing our fault-tolerant quantum machine to the cloud in 2028.

Gemma Allen

>> And that product is Libra. That commercial launch is Libra. So I know you mentioned that it's available to anybody with a credit card, right? I guess my question is, should it be? First of all, somewhat of a spicy question, but talk about, what sorts of use cases you are seeing, like where is quantum actually delivering market and commercial value right now? We hear, we at least sometimes hear of it in the drug discovery space and certain sorts of industries like pharmaceutical and others. But where do you know for sure that Aquila has actually had market impact?

Yuval Boger

>> So the truth is that quantum computers are, if I can say that impolitely, quantum computers are toys. They're toys. They're beautiful, expensive, sophisticated toys, but they're toys in the sense that there's not very much that you can do on a quantum computer that you cannot do on a classical supercomputer, except of course, prepare and learn and understand how quantum works. So one reason that Aquila was made generally available is because it's primarily a scientific instrument. And as we think about upcoming applications, we mean our fault-tolerant systems, systems that could do longer, more powerful more meaningful calculations, systems that can solve problems that are indeed worth solving. We look at the world and see two kinds of problems. We see problems that are quantum in nature. So molecular simulation, for instance, where the system is governed by quantum mechanics. And we see problems that are, say, optimization problems that are not born quantum, but perhaps could be mapped onto a quantum system for solution. We think the initial applications, the initial uses will be of the first type, those that are quantum systems. So it could be a better EV battery, it could be corrosion-resistant coating, it could be new solar cells, of course, new drugs and compounds, or even the ability to understand the behavior of certain compounds as an input to AI systems to enlarge their training base.

Gemma Allen

>> And when I asked you there, should it be regulated? I want to maybe unpack what I meant a little bit, because one thing we know about quantum is that it's very, very powerful, right? And we don't want a scenario where it's in the hands of the wrong actor. Is what you're saying that at this point in this commercial race that we're in, we're not quite there where quantum presents that level of risk? We hear a lot from folks about the risk of quantum to encryption, for example, right? And what that could look like in the world of 2030. How do you think about that side of this frontier, Yuval?

Yuval Boger

>> That's an excellent question. And you're right, today's systems could not be used for dangerous applications. As you think about cracking encryption, the upcoming Libra system is not going to be able to do that. But unlike Aquila, our existing system that's on the cloud for 4 years, Libra is unlikely to be initially available for the global public. It will be a much more selective group of handpicked customers that can both afford the use, have problems that are worth solving, and have problems that, if solved, have a benefit to humanity. Longer term, every new technology, whether it's the internet or cars or drug discovery, has both positive uses, perhaps, as well as perhaps nefarious uses. And we're working closely with our partners, whether on the cloud or on-prem and with various governments to make sure that we use it for the right reasons and for the right purposes.

Gemma Allen

>> So help me understand the business model here. I know you have a very strong partnership with AWS. I guess my first question is, are you AWS agnostic or are there other hyperscalers on the horizon in terms of how this will play out? And secondly, what is the commerciality here? How is this licensed, per se, to AWS, direct to user, which I'm sure is going to be some sort of corporate end user on their end. But help me understand that.

Yuval Boger

>> We have two main paths to go to market. One is on the cloud. The cloud is easy to access, is easy to experiment with. You don't have to pay for maintaining the infrastructure. You can use it on demand. And so our partnership with AWS does that. Today, the system is essentially metered by the number of shots or by the time that you use it. In the future, it may change and may be more on exactly what job you're producing and, more focused on result than the process. The other important go-to-market is on-prem. So we have sold a $42 million system to the National Institute of Advanced Industrial Science and Technology in Japan. That system has been delivered and installed. And we certainly see that some customers wanna use quantum on the cloud and some want to use it on-prem. Just last week, we announced a strategic partnership with HPE, Hewlett Packard Enterprise, which is really the de facto integrator in US National Labs and many other HPC centers. So we can deliver the system the way customers wanna use it. Some wanna use it on the cloud, some wanna use it on-prem, and for others, it may be a combination of both.

Gemma Allen

>> I'm interested in the on-prem use case because we talk to a lot of folks in the AI factory space about moving back on-prem, right? On-prem is having a reimagined moment, I would say. And a lot of that is around obviously data sovereignty, data privacy, data control, and future-proofing their kind of business models. What sort of use case, if you can share, is Japan delivering?

Yuval Boger

>> So AIST is a research institution, and so they open the system to both their customers as well as partners, and maybe eventually to an even wider group. It's still in the scientific exploration phase, but you're right, on-prem systems— there are many reasons for companies to buy on-prem systems. One is control. When you're on the cloud, you're sharing the resources with others, and if someone submits a job that takes 5 hours and you're just behind and waiting for that job to complete. When the system is on-prem, you control your own destiny. The other side, of course, is data sovereignty. And the third side that's sometimes overlooked is that quantum computers are unlikely to be standalone computers. They're likely to work with existing high-performance classical computers. And some of the work we're doing with companies such as HPE shows it's when you achieve that tight integration between a classical supercomputer and a quantum supercomputer, 1+ 1 becomes 3 in a good way and you can take the best of both worlds and achieve results that you couldn't achieve with just one of these components.

Gemma Allen

>> Okay. So you have an interesting investment story, too. You've raised more than $230 million. You have some big investors there. You've got Google's Quantum Lab. SoftBank, NVIDIA, right? You've got great legitimacy in terms of who sees the value in this. I guess my first question on this is how far does $230 million go in the world of quantum? What sort of runway does that give you and what's ahead from the perspective of future investment? Yuval—

Yuval Boger

>> so we are very well capitalized, both from an investor standpoint. As you mentioned, we've raised over $300 million from NVIDIA and Google and SoftBank Vision Fund and Valor and many other fantastic investors. We also sell, so revenue from customers is a fantastic source of funding. And we're also fortunate to be supported by the government. We were selected for DARPA QBI Quantum Benchmarking Initiative Phase A and Phase B, and we're hopeful that we will also be selected for Phase C. We have received support from the UK government, from the Japanese government. So we're well capitalized. Having said that, quantum is expensive. Lasers are expensive. we have 200 people, half of which are PhDs there. We have to pay salaries. We have to pay for many interesting components. So it may be that we will be raising additional money in the not too distant future.

Gemma Allen

>> Okay, so last question to you, Yuval. Obviously 2028 is a short blink away. I'm sure it feels like in your world. I'm guessing the priority for you right now is focusing on Libra and that outcome. But maybe share with us, what does the next 12 to 18 months look like? What does it take to get there? Are you hiring more PhDs? I'm impressed. No, there are 200 or so people, half of which are PhDs. Are they in Boston? help us understand what the roadmap looks like for you from here.

Yuval Boger

>> So one of the things we pride ourselves on is that QuEra is about, we say, more science and less fiction. Sometimes quantum companies paint a very, very rosy future, and the jump between where they are today and where they expect to be in a year or two sometimes stretches imagination. We have proven all the key components that are required to deliver this fault-tolerant computer, the computer that can make long calculations that can solve problems worth solving. So for us, there's a question of system integration, integrating all these components into a coherent system that can live comfortably on AWS. We continue to grow the team. Our headquarters is in Boston, but we also operate in New Mexico. We just opened an office in Maryland. We have a large office in Japan, in the UK, and a new office in Zurich, in Switzerland. So we go to wherever there is significant opportunity and strategic reason to go. So we expect to grow the people. We are building half a dozen systems and perhaps we'll build even more. And obviously we're working very closely with our partners, NVIDIA, HPE, AWS. We're doing some fantastic work with Anthropic. And all leading to a system that will solve problems worth solving in 2028.

Gemma Allen

>> Well, I first of all love to hear that you're hiring and that there is more growth and brain trust going into this space at that pace and also at that global scale. That's also very interesting. And you mentioned some great frontier players there. You're certainly in the right company. So Yuval Boger, I wish you and the team all the best. Hopefully a trip to New York is on the horizon too, and you can come visit us here at the NYSE studio.

Yuval Boger

>> Absolutely. Thank you very much, Gemma.

Gemma Allen

>> Thanks for joining us on NYSE Wired. I'm Gemma Allen here at theCUBE Studio. This is NYSE Wired's Quantum 101. Thanks for watching.