The video presents a multidisciplinary panel discussion on the current status, promise, and challenges of quantum computing. It begins by contrasting different types of quantum computers—optical and electron-spin-based systems—highlighting their scalability, energy requirements, and potential operational temperatures. Experts elaborate on the revolutionary impact quantum computers could have on fields like cryptography, artificial intelligence, quantum mechanics, and life sciences. Applications such as breaking RSA encryption, simulating complex quantum systems like high-temperature superconductors, building advanced neural networks, and reducing energy consumption in AI are discussed. Quantum sensing's growing role in both fundamental science and practical technology, like atomic clocks and brain activity monitoring, is also explored.

This discussion stands out by emphasizing both optimism and skepticism. While some panelists believe quantum computers could solve currently intractable scientific and practical problems within as little as three years, others predict it will take decades or even question whether such progress is possible within our lifetimes. The complexity of communicating these subtleties to the public, alongside the challenge of managing the current hype versus realistic timelines, forms an underlying theme. Critical issues such as quantum error correction, decoherence, integration with classical systems, and the ambiguity of speculative technology forecasts are examined candidly, with experts admitting that even leading physicists struggle to fully conceptualize quantum mechanics itself.

Main takeaways from the video:

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Key Vocabularies and Common Phrases:

1. scalability [skeɪləˈbɪləti] - (noun) - The capacity for a system or process to handle a growing amount of work or its potential to be enlarged to accommodate that growth. - Synonyms: (expandability, flexibility, adaptability)

There is a question about scalability in quantum computing.

2. cryogenic [kraɪ.oʊˈdʒen.ɪk] - (adjective) - Related to or involving extremely low temperatures. - Synonyms: (freezing, frigid, icy)

But when we use electrons and spins for qubits, we have to do low energy physics. In that case room temperature is some room temperature, summer fraction is huge. That's why you have to go to cryogenic temperatures.

3. qubit [ˈkjuː.bɪt] - (noun) - The basic unit of quantum information, analogous to a bit in classical computing. - Synonyms: (quantum bit, quantum unit)

For example, our machine rigging correspond to thousand qubits and 340,000 gates.

4. rsa cryptography [ˌɑːr.ɛsˈeɪ krɪpˈtɑːɡrəfi] - (noun phrase) - A widely used public-key cryptographic system that relies on the difficulty of factoring large numbers. - Synonyms: (public-key encryption, secure encryption, asymmetric cryptography)

So by using such type of technology, we will do Showa's algorithm and break the rsa cryptography in three years or so.

5. decoherence [diː.kəˈhɪr.əns] - (noun) - The process by which a quantum system loses its quantum properties due to interaction with its environment, causing loss of coherence. - Synonyms: (disintegration, deterioration, dephasing)

So, so the idea is that if you can make a topological, and I haven't said what that even means, a topological qubit, because of the way it's made, it is exceptionally resistant to decoherence, which is the enemy of all quantum computations

6. entanglement [ɪnˈtæŋ.ɡəl.mənt] - (noun) - A unique quantum phenomenon where particles’ states are interdependent regardless of spatial separation. - Synonyms: (interconnection, intertwining, linkage)

So in any case, quantum computing is a synchronization of quanta, right? And that synchronization is called entanglement.

7. superposition [ˌsuː.pər.pəˈzɪʃ.ən] - (noun) - A fundamental quantum principle where a quantum system can exist in multiple states at once until measured. - Synonyms: (overlapping, coexistence, conjunction)

So just yesterday when we were at the museum, one of the questions I was asking of the museum exhibitors were how are you going to deal with the problem of quantum mechanical superposition? Something essential to quantum computing, but hard to describe to someone who has not been immersed in quantum mechanics for years.

8. hybridization [ˌhaɪ.brədəˈzeɪ.ʃən] - (noun) - The process of combining two different systems, such as classical and quantum computing, to achieve improved performance or new capabilities. - Synonyms: (combination, integration, amalgamation)

But it goes to just the point that you made about how we need to have a hybridization of the classical computing with the quantum computing.

9. speculation [ˌspek.jəˈleɪ.ʃən] - (noun) - The forming of a theory or conjecture without firm evidence; guesswork about the future. - Synonyms: (theorizing, conjecture, surmise)

All these things that quantum computing is going to do. That is pure speculation at this point.

10. intractable [ɪnˈtræktəbl] - (adjective) - (Of a problem or situation) hard or impossible to manage or solve. - Synonyms: (insoluble, unmanageable, unsolvable)

While some panelists believe quantum computers could solve currently intractable scientific and practical problems within as little as three years, others predict it will take decades or even question whether such progress is possible within our lifetimes.

11. elucidate [ɪˈluː.sə.deɪt] - (verb) - To make something clear; to explain effectively, often about complex topics. - Synonyms: (clarify, illuminate, explicate)

There may be some deeper questions about quantum mechanics that quantum computers will elucidate.

12. Noisy Intermediate-Scale Quantum (Nisq) [nɔɪzi ˈɪntərˌmiːdiət skeɪl ˈkwɑːntəm] - (noun phrase) - Quantum devices that have more sophisticated capabilities than early quantum systems but are still limited by noise and lack full error correction. - Synonyms: (prototype quantum computer, small-scale quantum machine)

If you want to make a, what's it called, a NISC machine, this is a small scale noisy machine that you don't do error correction on, but you can still do some simple problems, then the big problem is making the decoherence small enough that you can do a decent sized problem without doing error correction.

The promise of quantum technology - Nobel Prize Dialogue Tokyo 2025 - The Future of Life

Let's start with the quantum computing side of things. And if I could start with you, Bill and Akira, There is a question about scalability in quantum computing. The promise of quantum computing is enormous. Would you like, very briefly, would one of you very briefly like to sum up what that promise is? Akira, perhaps you could tell us what does quantum computing promise? Okay, so first of all, in any case, we have to have large scale quantum computer. And I think there are two types of quantum computers. One is optical quantum computer, another one is electron and also spins. Those are totally different world. In the case of optical quantum computers, photon energy correspond to very high temperature, like 10,000 Kelvin. So if we do quantum computing with optical systems, we are doing high energy physics. So room temperature is very low temperature for high energy physics. But in the case of electron and spins, that is very low energy. So in that case, when we use electrons and spins for qubits, we have to do low energy physics. In that case room temperature is some room temperature, summer fraction is huge. That's why you have to go to cryogenic temperatures. So in that case there is no scalability, I think.

And so you beautifully defined the two approaches and the distance that they are from where we all live, if you like, at room temperature. But in terms of computing power, what very briefly, what problems will quantum computers solve? If you can manage the scale to scale them up, what will you be able to do? So that is another thing. And I believe that we can do everything, including Showa's algorithm. I mean, so again there are two types of quantum computing or quantum information. One is standing wave, which is conventional qubits. I mean standing wave means the wave wave function stays here. And if you need many, many, many qubits, you need a lot of space. That's why you need a chip. But when we use traveling wave wave function like photonic system, that is totally different. I mean we can use many, many pulses and we can make time domain. So in that case we don't have to have a chip for making a quantum computer. For example, our machine rigging correspond to thousand qubits and 340,000 gates. And it works at room temperature. And by using that one we will do neural network, for example. So as you know at the moment neural network or AI is using digital computers, in that case analog input and ad conversion and and digital computing and da conversion and out. So it is very, very inefficient. But as you know, brains computers without error correction. So in that case analog input, just analog output. So it is very, very efficient. Compared to as a case of digital computing. So first of all, I want to replace digital AI with our quantum AI. And also on top of that, as I said, we are doing high energy physics. And in that case, the error is very limited, just vacuum, noise, and that is Gaussian. So we can easily use the central limit theory to eliminate the errors. So by using such type of technology, we will do Showa's algorithm and break the rsa cryptography in three years or so.

Okay, so you're going to break rsa cryptography in three years. Right. Okay, now, Bill, this is the time to bring you in. So that was a lot of physics in there. And can I get you to address two questions at once, Bill? One is again, this question of what will it achieve if it works? And the second is, will it work? Right. Well, the point is, the reason why people are excited about quantum computers is that there are certain kinds of problems, and I will emphasize certain kinds of problems that can in principle be done much faster on a quantum computer. Factoring Shor's algorithm is an incredible achievement that showed that if you used a quantum computer, that you could factor numbers in a time that grows only like a polynomial, that is like a power. I think it's the third power of the number of digits to be factored. Factoring is hard. Multiplying is easy. And that asymmetry between factoring being hard and multiplying being easy is the reason why public key encryption like RSA is one example, is so effective. This is the thing that protects your credit cards from people stealing them when you make a purchase on the Internet. But perhaps more importantly is the thing that protects diplomatic secrets that are transmitted between countries. So it's really important that this kind of encryption be secure. A quantum computer would make that kind of encryption insecure. And Akira tells us he's going to break into our credit cards in three years time. Right now, I don't believe that, but we'll find out. The great thing about a prediction like that is it won't be that long before we'll find out whether it's right. The thing about optical quantum computing is all the things that you said about it are true. But there are other issues with optical quantum computing because of the fact that the deterministic nature, anyway, it is something that has worked and most people have given up on it. So the fact that you're working on it is fantastic. I'm really happy about that. But this represents a, shall we say, a departure from the standard wisdom, which is often the way you make progress. Well, anyway, what else can quantum computing do? Because it might be that it's irrelevant. We at NIST have developed, not me, but smart mathematicians have developed quantum resistant encryption. So if everybody adopts quantum resistant encryption, then we don't care about Shor's algorithm, except for secrets that have already been sent and, and can't be decrypted. Those will be vulnerable, and people will certainly buy your quantum computer in order to do that. Presumably, quantum computers aren't being developed for breaking cryptography. They're being developed for increased computing power across the board. Well, there's only a few kinds of computations where a quantum computer is better. You know, you see, what I forgot to say was that an ordinary computer is going to take an exponentially longer time to factor a bigger number. That is, the time required is an exponential function of how many digits for an ordinary computer. But it's only a polynomial function of how many digits for a quantum computer, and that's huge. Okay, thank you. So I'm going to bring Matsuko in in a minute, but because this is a conversation starting with a sort of deep physics, but the that I just like to get an example of the sort of problems that you would hope would be solved or the secrets that would be revealed if we had it.

Okay. I'm not actually interested in breaking codes. This is something the spies are interested in. And it's one of the reasons that quantum computing became so popular. What I'm interested in is doing quantum mechanics. So if I want to do a many body quantum mechanics problem, so that means I want to study the quantum mechanics of a system that has many individual parts, and those individual parts are correlated with each other strongly, as opposed to something where I can sort of take an average of what all the other particles are doing to think what one particle does. That's what the 20th century was about. What sometimes would be called a mean field approach to quantum mechanics. But if I need to know about the correlations among all the particles, that's a really hard problem. It's a problem that grows exponentially with the number of particles. And so like factoring. But a quantum computer, in a sense, is ideally suited for doing those kinds of problems. In fact, it may even be a near perfect analog to that kind of a problem. And so. So the thing I'm interested in doing is hard quantum mechanical problems that cannot be solved on a classical computer, but can be solved on a quantum computer that will give me insights into how things like materials work. So, for example, one of the great unsolved problems of today is what makes high temperature superconductors work the way they do. And there are speculations about what kind of a model we could use to describe the operation of a high temperature superconductor. But the trouble is, some of those models, while simple to express, are impossible to calculate with a classical computer. But with a quantum computer, you could calculate those models and you could learn whether these models are good models for high temperature superconductivity. That's what turns me on about quantum computing. Okay, great. Thank you very much indeed. Akira, I'll come back to you in one second. I just want to have Zuko come in on this question of what sort of thing Would you like to know if quantum computing is working?

Yeah, computing. So in my understanding, the quantum computing is extremely delicate and need because of the error occupation of the error. So the quantum error can be essential by many additional qubit are needed. But Ikea's invention is very surprised without any error correction. So within three years. So that will be fine. But I think that to accelerate maybe to use quantum compute, realize that quantum computing the system with quantum and classical computing computing is required. Maybe so for this purpose, two way prayer like Nitoryu, like Shohei Otani and pitcher and hitter those enrolls are expected and however so that a player like him is few. So the classical computing and quantum computing the researcher is maybe the computer. Should we collaborate? Collaborate? Yes, indeed. In strongly. Yeah, but what's okay, I was trying to get to what secrets of nature are you hoping to reveal by if you had the power, what would you like to know? Okay, so my message is what is life? What is life? Yes, because what is life? Yes, topics is future of life. So the Schrodinger, the father of the quantum mechanics Schrodinger. Yes, yes. He wrote what is life? Yes. So what is life? And after 80 years the Nobel Prize biologist. So I don't need Paul Nurse. Paul Nurse also wrote a book called what his life published a book title. This is just the answer of the Schrodinger what is life? But he says there is no answer. No answer. And we need to understand maybe life science and biological phenomena. So we need much more detail of that research and the effort and in my opinion, the quantum technology Quantum science and technology will be contribute to clarify the life science and also the such kind of blame mechanism. And also some kind of material new material for AI computing or something like that. I need. Thank you, Matsuka. So when it comes to the brain, Akira, you're producing Neural networks. You have the idea of producing much more advanced neural networks that will mimic the brain. Would you like to talk about that at all?

So the reason why we stick to optics is that the carrier frequency of optical carrier is more than 100 terahertz. That means we can put 10 terahertz information on that 100 terahertz carrier. So in principle we can make Quantum computer in 10 terahertz clock frequency. So at the moment we don't. Everybody doesn't think about care about the clock frequency of AI and also other things. But clock frequency matters. So in any case we should go to very high clock frequency to save the energy. At the moment, digital computers clock frequency is up 2 gigahertz at most. So if you want to make petaflops operation, you need many, many, many, many cores. That's why the consumed energy is huge. But if we can build 10 terahertz clock frequency, then so it is almost 10, 10,000 times faster. That means 10,000 times low energy consuming. So by using such very high clock frequency computer, we want to make AI to reduce the energy consumption. That would truly have a world changing impact. If you were able to combat this question of the energy consumption of AI systems, which is a tremendous worry now. Yes, indeed. Sorry Bill, you wanted to come in? Well, I'm glad you brought up the question of clock frequency because this is something that often is not discussed when people talk about quantum computing. And for example, atomic systems have pretty low clock frequencies. Traditional solid state systems are faster. You've indicated that these optical ones could be even faster. But it goes to just the point that you made about how we need to have a hybridization of the classical computing with the quantum computing. If you're going to do error correction, then you need a classical computer that is going to do those error correction calculations. Just for those who may not know, the typical thing that happens is that when you do a quantum operation, it's not perfect. In classical computing it's almost perfect, but with quantum systems it's not. And the way you fix that is by a procedure called error correction, which is very expensive both in resources and in time. And you need a classical computer to figure out what the error correction should be. And that classical computer has to be fed faster. Yeah. Than your quantum computer. So if your quantum computer is really, really fast, you may not have a classical computer that can keep up with it. So that's one issue that is sometimes not not brought up, that that this can be a problem. And so co designing of the classical computation with the quantum computation could be a really important thing for the kind of scalability that we're looking for. Now if you. Your quantum computer is so good that you don't have to do error correction, that's a different story. So it's just one more thing that often is not discussed when people talk about how wonderful quantum computers are or will be. Will be. Yes. Or will not be depending on your point of view. Yes, exactly. Thank you very much for bringing that up. Okay. But I'm going to come to the audience in a second. But Matsuka, I just wanted. These are very. These are the near or far future applications of quantum computing, depending on which side you land on. But there are now there are very real applications of just quantum mechanics which Bill has already outlined in some of the discussions already today. But you work with quantum sensors yourself. So would you like to tell us a little bit about that?

Quantum sensing have already. So implication implication of the society counter atomic clock is a standard standard of the clock. And so now we are trying my focus. My research focus on the quantum sensing. So because of the. With higher. Higher sensitivity and Marty of the physics physics and variable and also the dynamic ranges are very wide. And so my goal is to realize quantum life science. Quantum life sciences or so by. For life science the emerging field between quantum physics and life science. And maybe so the purpose is I believe there are quantum phenomena in the life science and in the brain or cell and nerves and hierarchical application of the life science. And so the quantum phenomena in the life science and detective. The quantum sensing and then analyze the quantum computing is my ideal system of quantum. So what exactly? Give me an example of something you measure and something you just you find out through quantum sensing. Quantum sensing of some brain activity and so on. Of what activity? Sorry, the brain of brain activity. Quantum sensory brain activity. Okay. In order to find out what. In order to apply something like the relationship between the brain and emotional things and so on. So long term targeting. But that's the secret to everything. Bill, did you want to. Well, I just like to bring up something much more mundane but is coming to reality even as we speak. The point you brought up about atomic clocks. The trouble. One of the troubles with atomic clocks is that the very best ones have very few atoms because the interaction between the atoms is often a problem in the accuracy of the clocks. The trouble is if you have very few atoms then the signal to noise ratio is not very good and you have to work for a long time. You have to look for a long time before you realize the high accuracy of the atomic clock, you may have to, to average for days or weeks or even months to achieve the kind of accuracy that the atomic clock is capable of. But if you can figure out how to add just a few atoms together so they don't interact very much, and then do some magic where you entangle quantum, entangle the atoms. Now this, we haven't described what quantum entangling is, but it's something that is part of, part of the sort of 21st century Quantum mechanics that is so important in quantum computing. That kind of quantum sensing is an important feature that we're already taking advantage of. So it means that you could make these atomic clocks work better, faster. Same thing is true of, for example, detecting the level of very dilute pollutants in the air. Hard to see because the signal's noise isn't so good. But if you quantum squeeze the light, light has as, as you mentioned, Gaussian shot noise. Unless you do something to fix that. And we can do something again, it's a quantum phenomena where the light has less in the way of fluctuations than would be the case with natural light, the kind of thing that comes from a laser, for example, we would do something more sophisticated and then that light, because it would have less fluctuations, would be better, a better tool for detecting very, very dilute pollutants. So these kinds of quantum sensors are really near term. Thank you. I'm making them now. Thank you very much indeed. Did you want to comment, Akira, before we go to the audience? So speaking of squeezed light, of course, for our quantum computer for entanglement source, we are using squeezed light. So in any case, quantum computing is a synchronization of quanta, right? And that synchronization is called entanglement. So in any case, we have to use entanglement for quantum computing. And our resource is squid light. And again, it is deterministic, not conditional. Thank you.

Let me see if there's. Yes, please. There's a question here or comment here. Could we have a microphone, please? Thank you. Hi, thank you. Hello, sir. Very recently this Microsoft developed topological quantum qubits, which is more robust as compared to conventional qubit, and they use majorana, right? Majorana particles. So how this majorana and the topological can change the world of this quantum computing. Can you tell us something about. That's a question. But this has become a conversation between physicists. Go for it. Well, the problem is that the whole problem of topological qubits, which there's been a recent demonstration and publication about topological Qubits has turned out to be rather controversial, which I guess is what motivated your question in the first place. So, so the idea is that if you can make a topological, and I haven't said what that even means, a topological qubit, because of the way it's made, it is exceptionally resistant to decoherence, which is the enemy of all quantum computations. And then the idea is that if you can make a quantum computer that works with topological qubits, then you may not need to do error correction at all. All. Or you may need to only do it very little, which means that it won't require a lot of resources. So people get really excited about topological quantum computing. The PR that is public relations output about these topological quantum bits is rather different from what you read. If you read the paper, the paper is very clear and conservative about what it claims. And the, the press releases say this is going to solve all our problems. Well, we'll see. So I would say that what has been happened is that they've demonstrated a topological quantum bit. That's great, but it's only the first step in a very long journey to make a quantum computer. So we'll see. But I'd love to hear what anybody else thinks about this. I'd love to. Yes, please hear a comment. You have to distinguish between physical qubit and logical qubit. Just one physical qubit. You cannot make any quantum error correction. For quantum error correction you have to make logical qubit that is entangled state of many qubits. So I'm not quite sure about that major qubit. But if you want to make a quantum error correction, you have to use many physical qubits to make single logical qubit. On top of that, for topological quantum information processing you have to make magic states. So it is rather tricky state and I think it is really hard to create at the moment, I think. Thank you very much indeed for the question. I think this conversation illustrates one of the challenges that quantum technology faces in that as you mentioned earlier, Bill, when Einstein came up with his theory, people were saying there are only three people in the world who understand this. This is a very in house conversation. It's very difficult for people outside of the field to come anywhere close to understanding anything about this. And so all they can understand is the promise. The oft talked of promise. And the promise, like many things, is often, you know. Another good example of course is nuclear fusion where the promise of. The promise of nuclear fusion is always there but never realized as yet. In this case we may be realizing the Promise of quantum computing soon. But how do you have that discussion with the public about a topic that is so hard to get any understanding of? Well, I noticed that you've very carefully avoided using the term hype, which I'm afraid has been an ongoing characteristic of quantum computing. There's a lot of over promising, in my humble opinion, that people say quantum computing is going to solve the energy crisis, it's going to solve the climate crisis, it's going to create new pharmaceuticals. All these things that quantum computing is going to do. That is pure speculation at this point. In my humble opinion that it's. It's wonderful to dream, it's good to dream. But to claim that quantum computers are going to do this when at the moment it's highly speculative, I think that's dangerous because if you promise these things for too long and don't produce, then the people who are giving you money, the minister who used to be here in the front row, you see Mutsuko making decisions about such things. But. Yes, no, yes, exactly. These people may become disheartened with these over promises and change their attitude about funding. Quantum computing is going to be fantastic. It's already fantastic and I don't think we need to overhype it now. This isn't really answering your question, how do you talk to the public about it? But I think the first thing is you do it honestly. And I think there's been a lot of failure to be completely honest about the the promise of quantum computing. Explaining how quantum computers are different and why they're better for some kinds of problems to the general public is not easy because it's hard to understand these features if you don't know something about quantum mechanics. So just yesterday when we were at the museum, one of the questions I was asking of the museum exhibitors were how are you going to deal with the problem of quantum mechanical superposition? Something essential to quantum computing, but hard to describe to someone who has not been immersed in quantum mechanics for years. The idea that something can be in two places at the same time, that sounds ridiculous and it is ridiculous, but in a certain sense it's still true. And explaining that in a short period of time is simply not easy. And I don't know the answer to that. If you're willing to sit down and listen to me lecture for an hour, I think I can give you a pretty good idea of what that's all about. But if you want the elevator speech, the two minute version of why quantum computers work, that's hard. And I don't know how to do it.

Well, that is a problem, isn't it? And quantum science isn't alone in having trouble in having an honest or at least a straightforward discussion with the public. It's always a problem, but certainly in two minutes it's very hard and one understands why journalists, et cetera, just go for the hype. But I should let Akira and Matsuko both comment on this. So would you like to respond to. But yeah, it's really hard to explain what is quantum mechanics? I don't know. Honestly. Even Albert Einstein could not understand quantum mechanics. So I cannot understand quantum mechanics. That is my answer. That's a lovely honest answer. That's a good starting point. Thank you. I think this year is a chance to understand the quantum because of the two as you mentioned in this morning, this year, 2025 in the International Year of Quantum Science and technology and recognized 100 years since Heidenberg published quantum mechanics paper. Okay, so. But my understanding the hundred years of quantum is just starting. Yeah, that's right. Just starting. Yes, indeed. Okay, another quick comment from the audience. Would anybody else like to say anything? I have to, but do I see a hand? I'm sorry if I'm not seeing you shout if you are holding your hand up. Yes. Great. Thank you. What, in your opinion are the largest problems that need to be solved to move quantum technology and quantum computing forward? Kira, what's the largest problem? Very briefly, it's really hard to tell. Of course in some sense everything is a problem because I cannot understand quantum mechanics. But good thing is that I can enjoy quantum mechanics. So I cannot under. I cannot answer the question so everything but I can enjoy. Well, as you point out, the fact that we don't understand quantum mechanics does not prevent us from making quantum computers. There may be some deeper questions about quantum mechanics that quantum computers will elucidate. But to answer your question about what the biggest problem is, it depends on what kind of quantum computer you want to make. If you want to make a, what's it called, a NISC machine, this is a small scale noisy machine that you don't do error correction on, but you can still do some simple problems, then the big problem is making the decoherence small enough that you can do a decent sized problem without doing error correction. If you want to do a fully error corrected problem, the big step that I think needs to be made is to make error correction so that you control the decoherence. You see, the thing is, if you do this process of error correction which we haven't described at all. It requires lots of qubits, as you've described, to make this logical qubit, to make that logical qubit have a lifetime before it decoheres. And we, we haven't really talked about what decoherence is, but it's the enemy of quantum computing. Nobody has demonstrated to make that time so long that it doesn't matter. That's the challenge for making that kind of quantum computer. To make the lifetime of a logical qubit be so long that it's longer than the time of your computation. If that's not true, we're not making a proper, fully functional, error corrected quantum computer. And so far what people have shown is that you can extend the lifetime by a factor of a little. And so we're a long way away. That doesn't mean I don't think it'll happen. But that's where I see the big challenge is, thank you very much indeed.

We're coming to the end of the time. So I think, I mean actually both in this session and the session that went before it on AI, there's a fascinating conversation emerging about progress in the face of some lack of understanding in quantum whether it's, whether it's in quantum science and quantum computers or whether it's in the, in what actually happens within the black box of AI within the, within the deep learning networks. It's an interesting thing to discuss. Maybe it's a future panel, but for the moment I'm just going to, I need to finish by having you two start. Finish where we started. Akira, you think that we're going to have a quantum computer that's functional and scaled up in three years time? Yep. Okay, Bill, what's your bet? 20 years. 20 years. Matsuko, would you like to. 15 years. 15. Very, very wise. Judicious. Coming in in the middle there. And by the way, my, I have a bet with colleagues about when it'll happen and the time scale for the bet is 20 years. And I'm betting on the side that even in 20 years it won't be ready. But what I find is when I talk to people who are experts in the field, about half of them go on the side of no. In 20 years and half yes, on the side of 20 years. So I think 20 years is a good number. And what's the wager? What have you done? The wager is that we're going to put up money and give it to some professional society to keep and accumulate interest. And then after 20 years, when I'll be dead the money will not go to my heirs. If I win, the money will go to a prize for people studying fundamentals of quantum mechanics. Fabulous. Lovely. I have a comment that question depend on the definition of. Ah, yes, yes. And I have a very specific definition scale. Can that computer factor a number that cannot be factored by a classical computer of that era in one year? So you give a classical computer a year to factor a number and the number that's big enough that it cannot do it in one year, 20 years from now, when computers will be faster. The question is, will a quantum computer be able to factor that number? Try a test definition. That's. So I think that's. I don't like factoring, but it's very clear what the problem is. Yeah, I think so. Okay, I think this conversation is going to continue outside. Thank you very, very much, all of you. We now have a short coffee break, so please enjoy the coffee and see you after the coffee break. Thank you. I'm really looking forward to your results. Thank you. Mitsuba. Thank you very much indeed.

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