The video explores the transformative potential of quantum computing, articulated through a conversation with Dr. Chris Ballance, CEO and co-founder of Oxford Ionics. Quantum computers are said to revolutionize computing by solving complex problems unattainable by classical computers. The conversation delves into the intricacies of quantum technology, its applications, and its comparative advantages over classical computing technology. Specifically, Ballance cites improvements in fields such as renewable energy, drug discovery, and optimization as areas where quantum computing can make a significant impact on real-world problems.

Furthermore, the discussion unpacks the challenges associated with quantum computing, such as managing qubits and scaling the technology. Ballance elaborates on how Oxford Ionics is addressing these challenges by using traditional semiconductor foundries to build quantum chips. The video additionally covers the potential threat that quantum computing poses to current encryption methods, stirring debates about cybersecurity. Ballance discusses the proactive steps being taken to develop post-quantum cryptography to counteract these threats.

Main takeaways from the video:

Please remember to turn on the CC button to view the subtitles.

Key Vocabularies and Common Phrases:

1. revolutionize [ˌrɛvəˈluːʃəˌnaɪz] - (verb) - To completely change the way something is done, usually to improve it dramatically. - Synonyms: (transform, innovate, reform)

It's not an exaggeration to say that quantum computers have the potential to revolutionize the world.

2. untapped [ʌnˈtæpt] - (adjective) - Not yet used or exploited. - Synonyms: (unused, dormant, latent)

How this untapped quantum power is harnessed can be difficult to understand, however.

3. dubbed [dʌbd] - (verb) - To give a particular name or description to someone or something. - Synonyms: (nicknamed, labeled, termed)

Chris himself has been dubbed quantum computing's up and coming star.

4. superposition [ˌsuːpərpəˈzɪʃən] - (noun) - A fundamental principle of quantum mechanics where a quantum system can be in multiple states at the same time. - Synonyms: (overlapping states, simultaneous states, concurrence)

The magic of a quantum computer is that a qubit can be both 0 and 1 at the same time, known as superposition.

5. tackle [ˈtækəl] - (verb) - To try to deal with or solve a problem. - Synonyms: (address, confront, handle)

The Oxford Ionics website says quantum computing will improve productivity, sustainability and quality of life by transforming our ability to tackle real world problems across fields.

6. entanglement [ɪnˈtæŋɡəlmənt] - (noun) - A quantum physics phenomenon where particles become interconnected, and the changes in one affect the others. - Synonyms: (interconnection, linkage, interrelation)

It turns out you can get things like superposition or entanglement, things that Einstein famously called spooky action at a distance.

7. baffling [ˈbæfəlɪŋ] - (adjective) - Extremely confusing or difficult to understand. - Synonyms: (puzzling, perplexing, confusing)

Quantum computing seems baffling, but it's no more baffling than normal computing.

8. volatile [ˈvɒlətaɪl] - (adjective) - Likely to change rapidly and unpredictably, especially for the worse. - Synonyms: (unstable, unpredictable, fluctuating)

Let's talk a little bit about qubits, because they are by their very nature volatile.

9. harness [ˈhɑrnɪs] - (verb) - To control and use the natural forces or resources. - Synonyms: (utilize, exploit, employ)

And it just means we can go from problems that look really tough if you look at them in the conventional way and harness new computational methods.

10. encryption [ɪnˈkrɪpʃən] - (noun) - The process of converting information or data into a code, especially to prevent unauthorized access. - Synonyms: (ciphering, coding, encoding)

And it's these mixed superposition states that allow us to do things like cracking encryption efficiently.

Quantum computers pose great risks but their potential could change the world

It's not an exaggeration to say that quantum computers have the potential to revolutionize the world. How this untapped quantum power is harnessed can be difficult to understand, however. So we will do our best to wrap our heads around a subject that for many of us sounds like science fiction. And while this technology of the future could create an abundance of possibilities and may solve problems faster than ever before, it does also pose enormous risks to our online security.

Beyond the Valley let's introduce our guest this week. Dr. Chris Ballance is CEO and co founder of Oxford Ionics, a UK based company which says is building the world's most powerful quantum computers. Chris himself has been dubbed quantum computing's up and coming star. After obtaining his PhD in Physics at Oxford University in 2014. He and his co founder, Dr. Tom Hardy have set new world records while developing techniques and technologies to manipulate qubits at sufficient scale to build useful quantum computers.

Chris, thank you for joining us on beyond the Valley. It's great to be here. On the Oxford Ionics website it says quantum computing will improve productivity, sustainability and quality of life by transforming our ability to tackle real world problems across fields including chemistry, logistics and finance. For our listeners who may be coming to quantum computing for the first time, can you give a specific example of where it could make a significant difference in their lives?

Yeah. So what we like talking about when we talk about quantum computing is saying that quantum computing doesn't compete with classical computers. It solves problems we can't correct solve on normal computers. So we view our competition as people and labs having to test things rather than solve these problems on computers. So a great example is renewable energy. The big problem. We can generate enough energy with the renewables to power the world. The problem is the timing and the distribution problem. And a lot of this problem comes down to how you build better batteries. Right now we know in principle we can build better batteries, but a lot of this is bandwidth limited by people and labs testing out different chemistries. If we can solve those problems on a computer instead, that's incredibly valuable.

What we're pretty confident on is we can't solve these problems on conventional Computers without thousands or tens of thousands of years of compute runtime. And with quantum computers, we know algorithms we can run that can solve these kind of problems in hours. So way out compete the rate of someone playing along in a lab. Okay, well, we're going to explain quantum computing a little bit more. But before we do that, we've got to play stat of the week. Over to you, Arjun.

So start of the week this week is $850 billion. So just think about it, ruminate, and we'll get back to you. We'll do the answer at the end. And there's a lot of honor at stake, Chris. So, you know, no pressure. Our first question, and it's, I think the hardest question to answer. What is quantum computing? That's always a great question. And first of all, I will temp your expectations. You know, I will ask you first, you know, how does your iPhone work? So ultimately, people don't tend to know how computers work because computers are fundamentally incredibly comple. And quantum computing seems baffling, but it's no more baffling than normal computing. It's just very different.

And the way to think about this is to think back to the 1910s, 1920s. So in 1910, we thought we had physics all figured out. You know, we could predict how cannonballs flew through the air, how the planets went around the sun. It all seemed to make sense. And then we found some weird inconsistencies. We found the idea of quantum physics. And this basically completely changed the rules of the game as we know it. And it turns out you can get things like superposition or entanglement, things that Einstein famously calls spooky action at a distance. Where he said, God doesn't play dice, it turns out God does play dice.

We've now pretty conclusively over the last hundred years prove that this theory is weird, baffling, counterintuitive. It's not how the world behaves as we see it, but it turns out those are the rules of the game. This is how the world works. All computers right now, classical computing don't use those rules at all. It uses the rule of classical physics. People in the 1800s would have a pretty good idea of how a modern day computer works. There's no big difference there. They're better, more compact, better engineered, but they're no different than, you know, a steam powered computer back in the 1890s. With quantum computing, we harness the power of quantum physics. And it turns out this changes the rules of the game.

You can use all these different aspects, like Spooky actuator distance and entanglement to compute things in a completely different way that we can conceive of with classical computers. And this just changes the rule of what kind of things are easy to compute and hard. And it turns out there's lots of problems out there which if you run them on a classical computer, turn out to be incredibly hard. Take millions, billions trillions of computational steps, whereas with a quantum computer we can do them in just a few steps. It turns out the other way is true too. There are problems that are really easy on a classical computer and really hard on a quantum computer, but we don't talk about those so much.

So for our listeners here, Chris, you said a lot of people don't necessarily know how their iPhone works. But when you think about some of the big use cases, the way quantum computing may have an impact on our lives, where would you say for you is some of the top two or three things you can maybe say that the industry is working towards? So a lot of the exciting applications we look at just make computing substantially better. These are things like better battery chemistry, you know, replacing P from the labs with things that are solved on supercomputers, quantum supercomputers that just go better, they're better optimization, even down to things like chip design. We know applications for chip design where we can't solve the problems we want to solve, so we have to come up with pretty bad approximations.

We can do that a lot better with quantum computers all the way through to drug discovery. Right now, drug discovery is a 10 year process and incredibly inefficient. And lots of the problems here we can write down the mathematical equations we could solve that would tell us which drugs are better than others. We just can't solve them on classical computers. So we just kind of give up. And there's so many problems out there that are bottlenecked by compute power. Perhaps a glib way of saying this is, you know, look at Nvidia's three and a half trillion dollar market cap that's driven because they've got like a 10x improvement in what you can compute compared to other technologies out there. And that's what a 10x improvement to comp powers worth. And quantum computing offers million to billion full speed ups.

And some of those kind of problems, even if we look in the long term, lots of the problems we have in machine learning, that means we have to use such powerful computers to solve this stuff. We have to do trillions of operations to solve them on a classical computer. We know how to do this in more like four steps, like quantum computer. So it's almost sort of breaking down those steps. You're able to do sort of more at once, quicker to some extent. With quantum computing versus the traditional computing as it stands. Exactly. It completely changes the rule of the game. And it just means we can go from problems that look really tough if you look at them in the conventional way and turn out to be really easy later on.

And a great example of this is cracking encryption is RSA encryption is designed to be really easy to do one way and really hard to reverse the other way. And it turns out we now know that the assumptions behind lots of everyday encryption we use for credit card details online or even use for national security applications, those are incredibly hard to invert on a classical computer, which is why they were chosen in the first place. It turns out they're ridiculously easy to solve on a quantum computer. And this is one of the reasons lots of nation states are pushing quite hard on quantum computing performance. We'll get into the security concerns in a minute, but let's talk about some of the challenges for quantum computing to, to actually work.

Let's talk a little bit about qubits, because they are by their very nature volatile. And that makes making them work a little bit challenging. Talk us a little bit about qubits. Right, So a qubit is a quantum bit. And this is the equivalent of a classical bit in a computer. So in a classical bit, your bit can be 0 or 1. The magic of a quantum computer is that a qubit can be both 0 and 1 at the same time. And this is superposition. This is famously, you know, the idea behind trading as cats. And when we talk about the difficulty of building large scale quantum computers, it's kind of like the difficulty of building up Schrodinger's cat atom by atom and keeping it both alive and dead at the same time.

This kind of weird stuff where we don't see these quantum mechanical phenomena in everyday life, that's because of noise washing out this beat. It's a behavior. What we're trying to do when we build large scale quantum computers is find artificial systems where we really can keep all of this weird phenomena alive. And ultimately, this isn't a physics challenge. This is an engineering challenge. This is how you build out these complex systems and manage the complexity. And ultimately we have in small scale systems that work well enough to solve all of these problems. And the big challenge and the challenge that everyone in the quantum computing space is taking different approaches to solve is how we can build our quantum computers that require the minimum amount of pain and new technology to harness this new physics in our existing supply chains.

And one of the things we focus on at Oxleyonics is working out how to control qubits using chips that we can build out in standard semiconductor fabs. We want to learn a bit more about oxidionics because just before we do, it's super simple question, why should people care about quantum computing? So quantum computers are the most powerful form of compute that the laws of physics allow. What we know time and time again across all aspects of technology over the last 70 years is every time we have a leap in compute power, it changes the world, typically in ways that are first foreseeable and then in ways that are completely unforeseeable. The pioneers of computing in the 1950s and 1960s were interested in speeding up Monte Carlo simulations so they could build better spacecraft and they could replace people in a room solving problems on paper with some computers that could solve the problems 10 times fast.

They could do 10 times more maths. Great massive productivity gains. They wouldn't have predicted Facebook. They wouldn't have predicted the power of networks around the world. They wouldn't have invented artificial intelligence. The pioneers of the 1980s came up with lots of the ideas behind artificial intelligence that's underpinned what we have now. The difference there isn't we've been cleverer. We found new ways of approaching it. It's just we found ways to prove forces with massively more powerful computers. And quantum computers are just the next part of the computing revolution. And one of the really exciting things is we can see how important these things are going to be. And we can kind of work out as an industry how we can speed run through the 70 years of development we've seen over classical computing and squeeze that into 10 years with this massive productivity.

Optics, right? And so Oxford Ionics. Chris, give us the. Give us the pitch. What are you guys doing? So we build quantum computers. The big challenge with this is always how you go about building it. There's lots of technologies out there that work and that you can buy right now and deploy, but they're error prone. They make lots of mistakes. And the challenge with quantum computers is how you deal with these qubits to make sure they don't make too many errors and where they don't cost too much and where you can really scale them and build ion out. And our focus at Oxford Ionics has been how you can build our chips in A standard semiconductor foundry that allow you to do all of these things efficiently.

So what we do is we use completely classical chips, boring, easy to build chips, and then we use them to control individual actions a fraction of a hair's width above the top of the chip. And it turns out this is a pretty magical combination since if you do this right, you can make these chips alongside chips for laptops on high performance computers. And what we've recently shown is chips built out in standard fabs now perform better in our quantum computing platform than anything else out there by nearly an order of magnitude. And that's pretty awesome. So we've solved a lot of the problems of these fragile quantum states by just finding the right way to engineer them. And this is engineering, it's not physics.

When it comes to your competitors, are you leading in that space? I mean, where are we with the landscape of development? Is it still quite early on, or are other companies doing slightly different things, taking slightly different approaches to this problem? Right now the industry is really in a spacency. Lots of people really see the value and everyone's trying to work out the right way of approaching the go to markets. What we can do right now on our hardware platform is we confidently can say we have the best raw hardware ones in the world. There are other players out there who offer better integrated end to end solutions and our play is scaling out as fast as possible to really get to the next generation of systems that really change the world in terms of what they can compute before our competitors. We're feeling pretty good about that right now.

Let's talk about semiconductors. Chris, you mentioned Nvidia at the top, and we know that's a fascinating company for the reasons you said. It's been able to offer the infrastructure, the chips that are able to allow massive compute and allow these huge large language models and everything else to be created. You've developed a chip as well that you say can be mass produced and could lead to the world's first useful quantum computers in three years. What does that mean? So quantum computers scale differently compared to classical computers. Every time you add a few qubits, you add a phenomenal amount of power. So if you look at the most of the quantum computers in the world today, including ours, they can be outperformed by a fairly battered iPhone, which is great technology demonstrators, but they're still not outperforming classical computers.

You double the size of these quantum computers and they go from not being able to outperform an iPhone to being able to outperform a planet sized supercomputer. So if we look just to put some concrete numbers on this, to explain just how wild the scaling is, if we look at 100 perfect qubits, you know, in our platform right now, this looks like a big server rack that draws about the same amount of power as a standard server rack. Then you compare that to the classical computing you need to match that in bore horsepower, you need something like 10 to the power of 20 of Nvidia's top line GPUs. So that's clearly impossible. Although Jensen would be very happy with that purchase order.

But what's even more impossible is the power consumption of that. So that would need to be about powered by 1 billion terawatts of electricity. So that's a large number. And to give an idea of just how large this is, the total power generation capacity of planet Earth, right Now it's about 1 terawatt. So this is about a billion planet Earth's worth of power. So this means that even if we find a way to make classical semiconductors in order of magnitude three orders of magnitude more power efficient and three orders of magnitude faster, it will still need a thousand planet Earths to power that thing. So we can clearly never build a classical supercomputer like that. It's just impossible. And these kind of quantum computers that match that in power, we're building out over the next 18 months.

So what is in terms of the semiconductor themselves, what are some of the characteristics that will set them apart from of course, our classical CPU and in the sort of parallel compute that comes with GPU as well? What, what is it about these new wave semiconductors for quantum that are different? So really, absolutely everything a quantum computer makes a classical computer closer to an abacus than a quantum computer. They're just so absurdly different in how they approach problems. An important part of this is the fact that we can use this superposition in the calculation. You can kind of think of it as doing maths, not just say on like three plus five, but you can have one of the inputs being say three and a little bit of two and someone added to five plus a bit of six plus a bit of seven. And it's these mixed superposition states that allow us to in a way, solve problems in parallel much more efficiently.

Which means you can find ways of sifting out the correct answer in very, very few steps. You know, you think about the supply chain here. When it comes to chips, you can design them and obviously there's one main leading player to manufacture those in Terms of TSMC in Taiwan, Samsung is pretty advanced as well. Are these companies able to manufacture at this point the kind of semiconductor that you're designing and require? So one of the big focuses from way early on in our story was that we wanted to make sure we could multi source these devices. We didn't want to be stuck to working with one player like tsmc. And at the moment the chips we built, even though they're the most powerful quantum computers out there, they're actually really easy to build. So we can build them in like 50 different fabs around the world. And we're already working in fab with a fab based in Germany to build out the best chips right now. So they're not necessarily on what would be considered sort of the leading edge nodes of 2 nanometers.

Exactly. They're boring. One of the great things we always do when we get like semiconductor engineers into the company is to say, wow, this seems really easy. And that's what you need to make any sort of new technology. You need to take existing parts that are easy to put them together to solve these new problems. If you have to develop multiple leading edge technologies in one go, you know, that's a brave bet for a startup. That's incredible because I think my instant thought would have been, well, you know, we're already at or nearing somewhere near 2 nanometers. Right. In terms of the leading edge manufacturers. So you know, where does this go? But that's fascinating that it's. We build on about a 130 nanometer process. Yeah. Which we're doing pretty pedestrian in the year 2000. And that's so important since it means we can make these things cheap and it means we can iterate fast and learn.

Can we go back to use case and we've dug down into the tech side of things and the research and the science. But you mentioned your renewables at the top of the pod. Where else could we see quantum computing really have an impact on people's lives? So one of the things I'm personally very excited about is drug discovery. Just because we've talked about this, just how expensive and slow it is and just how many of these problems are computational problems. Another thing that lots of people are excited about, excited to be less, but still it's very valuable is finance. A lot of the problems we need to solve in global finance generating liquidity are really complex optimization problems. And it turns out quantum computers can solve those really, really fast. And then we can look at a whole range of other things.

You Know, we know we can solve computational fluid dynamics better on quantum computers than we can on classical, which means we can find ways of making, you know, aircraft use less power, use less fuel. We can find ways of designing better chips that allow us to take resources we currently have and get more out of them. There's just a whole range of problems out there that are limited by compute power. This comes back to the fact that every time we found new ways of improving the compute power we have available, normally the people, the killer app that really changes the game isn't the thing people thought about. You normally get good, safe returns on the stuff everyone knows about. And the really valuable thing is the outside chance that people only really think about when they start having these systems out there to play with and really start learning about that.

When it just comes to the research side of things, I imagine doing that research is going to be a lot quicker and easier with a quantum computer. So you've got, you know, reams and reams of data and to find patterns or solutions within that data. Quantum computer could do that much quicker than the computers we had now. That's right. It completely changes the game and it's not so much quicker. It just does stuff that's not possible with conventional computers. And the really interesting market shots are not where we can compete. Classical computers are pretty damn good. We're not really trying to compete with Nvidia. We're trying to solve problems that we know Nvidia can't ever solve on their hardware. And that's the exciting it.

We're competing with people in labs trying as hard as they can to do stuff by hand and trying to turn those problems into problems we can solve on a computer. How do you think or how do you expect business to access the power of quantum computing? Is this something they're going to have on premise? Is it something they have to access to the cloud and cloud providers? Do they have to come to Oxford where you're based, to come and use the services that Quantum will provide? So what we expect is it look quite similar to the AI hardware accelerators we have right now, which is a mixture of everything. Some customers really care about data sovereignty. They really want guaranteed access and they want to have something in their control and they have systems that store their data centers.

We sell systems to customers just like that who really care about their data security already. And a lot of customers, especially later on that are development will just access this to the cloud in the same way as people access high performance computers. Right now, some people really care about having the hardware in their control. Other people just want power by the hour and are willing to pay the premium to have someone else hosting systems ready to work. We work with customers all across this use case from people, people who pay us to host systems for them in our data centers, through the people we work with, like large scale hyperscalers who can deliver compute through their web services all the way through to delivering hardware to people to install on their data centers in their control.

So in theory, some of your services will be accessible through multiple channels then in that respect, even through the hyperscalers and other ways. That's right. It doesn't change much to us. We still have to build out the key underpinnings and this changes slightly how we build out the prettiness of the boxes and how we integrate them into data centers. But it doesn't change any of the core tech and any of the core value gen we're doing right now. Are we going to own quantum computers as consumers, individual consumers, or is this very much a more government sort of initiative that you know, you could imagine that governments sort of take control of this technology or big business, big tech, business businesses. Where does the, where does quantum computing sit within that balance?

That's always a great question and people always try and predict this and people predicting the future of technology is always, always prove out to be wrong. At some point. I will boldly say that I don't think we're going to have quantum computers in our iPhones in the near term. Most of the way people engage with this is the same way people currently engage with supercomputers. You know, most consumer end users, all the stages of their life get that little bit better. You know, their searches will get more accurate, their hardware will get cheaper, drugs will become developed faster or cheaper. Better batteries happen there. People notice their phone battery life goes up with people have worked out how to make better batteries cheaper. All of these kind of aspects of life will happen from kind of large corporates accessing this high performance compute and most of those large corporates will be accessing it through third party retailers in the same way as now most people, you know, most large corporates arm firing, Nvidia, dgx, whatever to install on their site.

They're paying access to someone else to get this raw compute power to make it better. In the long term this will change. Quantum computers get more robust, smaller. But still I imagine these things will look more like data centers where you have your row of data centers with your AI inferences on one side And a different data center which has quantum computers accessed by other customers on the other side. And Chris, you mentioned AI there. Just help us explain the intersection of AI and quantum computing. We're talking now about artificial intelligence and the way it requires huge compute power right now for some of these, particularly the generative AI applications, the Chat GPTs of the world, etc. What does the intersection of AI and quantum look like?

So they're almost orthogonal technologies, they can add to each other. You know, AI really saved developer time. It allows you to be really inefficient with compute by throwing loads of compute at it to solve problems that you don't know ahead of time. What quantum computing allows us to do is massively change the underpinning problems we can solve and massively speed up those problems. So the most interesting thing is some of the applications between AI and quantum computing where you can run AI problems on quantum computers. And this is something people are very excited about right now. And it looks like for really large scale quantum computers we can have billion fold speed ups on some of these crop apps.

And what's interesting is how large a quantum computer we need to we can start seeing up and exactly what timeline now starts disrupting people like Nvidia. Because when a lot, you know, when you spoke about some of the use cases of quantum, there are, you know, those also developing AI applications. Actually we could also use, you know, artificial intelligence to do drug discovery and you know, figure out new drugs because you know, effectively it requires a lot of data figuring out patterns, proteins, et cetera. That could be much done much faster of course through AI. So is it that you know, you envisage well where through perhaps an AI application we we hit a roadblock in this drug discovery path.

But actually, you know, quantum solves it. Do the two technologies work together? So they solve completely different problems? So a classical computer can only sold such types of problems. AI doesn't change that. AI just makes it easier since you're trading off developer time for throwing massive amounts of computer to just attack it from multiple different surfaces of lulls. But lots of the hard problems we know we need to solve to build our drug discovery applications say we can't solve with classical computers. AI doesn't change that. It doesn't change the fundament behind fundamental math behind it. And one of the things we have with computation is some really fundamental theories that we don't even really think about now that say all computers are equivalent.

So your iPhone is not any different in terms of what it can solve. Mathematically than a supercomputer. And in fact, the Turing computers are the computers that were used in the war, World War II to crack cryptography. All of those are equivalent mathematically. And quantum computing is vastly different from that. It completely breaks all the maths behind this. And this is what makes it so exciting and what gives us so many different opportunities to tax so many different problems by really thinking differently. I feel like I've read in a few articles, sort of AI and quantum computing being sort of pitted against one another, that one will win a halt or eat another's lunch or can AI and quantum computing help each other when it comes to investment?

Do you, do you see that working together or do you see you having to sort of compete for that investment, for that attention with AI? Yeah, it's definitely not a competition. We don't see anything like that. You know, I really do see them as just completely separate buckets of stuff. One AI is really good at is taking large amounts of compute power and doing something with it productively. And what quantum computing is good at is really changing how much compute power we have. And those are just different sides of the equation. And ultimately I think the combination of these two things and think differently about compute really will change the way in the world. Perhaps one of the most interesting things that's changed over the last few years is people have suddenly realized just how much value new compute unlocks.

This is a trend we've seen time and time again. But people are now suddenly looking at, say, AI influencing harbor and realizing that, oh my God, if you want to build a data center in the valley in Santa Clara, you can't, you can't get power allocation to do this. You know, people are looking at building nuclear reactors to power data centers to avoid getting over the power hookup problem. And when you start looking at the scaling costs of doing this, even if you can build the hardware, you can't power it. And quantum computers give us vastly more power efficient way of running these kind of computations.

Let's talk about encryption then. Lots of talk about quantum computing being able to crack modern day encryption. You talked about at the top. How big is that threat? How near are we to Q day, as it's been dubbed, the day that when a robust quantum computer will be able to crack the most common encryption methods used that we use today? Is that day coming soon, Just, just before you eyes, like Chris, I think just to set the context as well for our, for our listeners, we're talking about the encryption on, you know, WhatsApp here or your credit card. This is, it's not, it's stuff people use every day. Right. And the encryption that all banks use to transfer money around the world.

So really the very underpinnings of our society, it's a lot. It's a lot. It's a trillion dollar question. So right now this is kind of five years out, but those are kind of the timescales we're talking about. It always depends how much of a betting man you want to be. And a lot of governments are now working very, very hard on changing national security infrastructure to move away from this. Since you know, governments don't like taking a bold bet that technology development is going to be slower than they need it to be to make things work. So yeah, it's in corporate timescales. It's really starting to change and people are now really aware of this. If you go across pretty much any large core for US speeds, they may have a plan for post quantum cryptography and how they go about doing this.

And the US government NIST recently released some new guidelines on post quantum of cryptography over the summer. What's the solution then? Or what are some of the solutions being sort of offered at the moment? So the challenge really is just changing the fundamental maths we use in all sorts of encryption. And this is an organizational problem, it's not a technology problem. We have the technology. The challenge is as soon as you know quantum computers exist, you want to find a problem, an encryption that's not just hard to crack in a classical computer, that's hard to crack in a quantum computer as well. And we know lots of problems that work just like that. The challenge is so much of our society relies on encryption working and one of the things nation state actors are really starting to get quite excited about is store repay attacks. Because ultimately if you think of things like diplomatic cables, they're encrypted.

But if people can intercept those and record those and come back to them in two, three, four years time and crack them, that changes how people think about the world. So there's lots of work going on behind the scenes to worry about this. And we have lots of close relations with different government customers who are very interested in tech development on those fronts. You said sci fi at the start of more like spy movie, cyber warfare, cyber war, like you know, intercepting some messages now in the hope that the quantum comes in time to break the encryption. That's might write a book. It's game changing stuff, isn't it? Yeah, quite mind blowing to be fair. It's quite. And with encryption, is. Is there a way for quantum computing, just how modern days, to figure out an encryption method that quantum can't break?

So there are ways of doing encryption a quantum can't break. There are also ways of using quantum information over five optical cables to distribute information the way that's guaranteed to be perfect, perfectly secure. And this is something quite a few banks are looking into right now, quantum key distribution, which then allows you to use essentially a guarantee of quantum physics to make these things secure. I mean, that when hackers try and even tap into the line, it can be detected, even guarantee, by the laws of physics as we know them, then no information could be intercepted. So quantum takes away, but it also gives. We spent a lot of the last few years looking at the way that technology has been sort of pulled into geopolitics very heavily, and it's become, you know, a big source of competition, particularly between the US and China.

I suspect this is a technology, as you've kind of alluded to, that We've spoken about semiconductors, we've spoken about AI. These are very much as part of this technology battle. I suspect quantum is the next frontier in that as well. There's a lot of geopolitics going on behind the scenes in quantum. Absolutely. And just recently, export controls were brought in for our level of quantum computing performance, which is the government saying that even at the level we're at now, they believe there are significant stakes at play for national security implications. Well, fascinating stuff, Chris. Unfortunately, we've run out of time, but we really appreciate you giving us all that insight and I'm sure that our listeners are. All their minds are sufficiently blown. Mine is. Mine is. I'm speechless. Yeah, I am, I am. But before we let you go, we've got to play stat of the week. So let's hear $850 billion.

$850 billion. So as the guest, you can decide to go first or second. I'm going to go second because I have a good idea and I don't want to give you a clue. Yeah. And Tom's on a massive losing streak at the moment, so this is probably the point where I say how competitive I am. Yeah, no, quite right. I'm going to take this very seriously. Okay, good, good. Glad to hear it. $850 billion. The amount that the quantum computing sector will be worth by 2030. And yourself, Chris. That's what I was going to say, too. Yeah. Oh, so double or nothing. It's a great, you know, answer, but it's the wrong one. But you know what? You're not far off. So. So quantum computing will create between 450 billion and $850 billion of economic value globally by 2040. That's according to the Boston Consulting Group in a recent study. So, yeah, you're on the right tracks that we were. Maybe you both get across infinitely cleverer than me, but I managed to come up with the same answer. I might put that on a plaque somewhere, but for all intents and purposes, your losing streak has still continued. Quite right. Let's not forget, put in my place.

Quantum Computing, Technology, Innovation, Science, Encryption, Oxford Ionics, Cnbc International