[00:00:00] Kris: The first wave of technologies that exploited these quantum phenomena, were technologies like semiconductors, technologies like lasers. Which gave rise to classical computer chips, telecommunications, which are the basis of the internet.
We really want to fund businesses that leverage groundbreaking technology.
[00:00:19] Kaz: Welcome to Zypsy Spotlight. I'm Kaz, co founder of Zypsy, a design and investment firm that supports startup founders with brand building expertise.
[00:00:27] Kevin: In this episode, we discuss the intersection of quantum computing and venture capital. Startups are beginning to use quantum mechanics in more practical applications. Today, we're excited to have Kris an investor at 2xN, a quantum inspired early stage VC fund. The team at 2xN combines the resources you'd expect from big investors, with the personal dedicated support you get from angel investors.
Let's deep dive in. We're your cohosts, I'm Kevin.
[00:00:54] Kaz: I'm Kaz.
[00:00:54] Kevin: Kris spent the last 10 years in quantum technologies. We'll explore his journey from building quantum computers to moving into venture capital.
[00:01:01] Kris: I'm Kris Kaczmarek. I'm a quantum investor here at 2xN. Prior to that, I spent over the last decade in quantum technologies. First in an academic setting, I did my PhD in quantum tech at Oxford here in the UK, then worked as an academic at the University of Geneva for a few years, and then came back to the UK to join the spin out of our Oxford research group called Orca Computing, where we were building quantum computers.
Mostly for AI applications. So there I was part of the management team responsible for product, which kind of covered product engineering, but also business development and sales. So went from an academic to a business person. And then joined 2xN in March this year, decided to make the move into venture capital.
The reason for it was, in a startup, you're laser focused on what you're trying to achieve. And especially as the startup scales and grows and gets into a groove, your work really narrows down to a very specific part of the story. And I just thought after a few years, I wanted to see more of quantum technologies.
Get a kind of bird's eye view of the landscape and venture was a great way to do that. I started talking to Niels and the team here at 2xN and their vision for investing in quantum and where to take that was just super exciting and ambitious. It was a good match.
[00:02:25] Kevin: Growing up with parents who were biologists. Kris knew from early on that he wanted to pursue a career in science. He goes into this in detail.
[00:02:32] Kris: Both of my parents are actually academics. They're biologists. I knew from very early on, I would pursue science as a career. But what I wanted to focus on is maths and applied math and computer science. And I remember having a conversation with a family friend.
And he suggested, if you wanted to do math, you wanted to do it at the physics department in Warsaw, because the math was a lot more applied, a lot more interesting. So I decided to focus on physics, mostly from a math perspective. And the degree I did was quite nice in that it assigned you an academic supervisor very early on that you could work with.
My supervisor was actually a laser scientist. And he gave me the opportunity to work in his lab very early on. I quickly got into the kind of experimental physics side of things and research side of things. And I found laser science optics and a bit of quantum just very fascinating. It was a kind of completely different way of looking at things, which meant you could take a very fresh view on it.
You weren't burdened with your kind of intuitions. You had to learn everything from scratch and learn new rules. So I already got into that. I did a few internships in different labs during my undergrad. And so then I decided to pursue a PhD on the topic. And an opportunity opened up in Oxford. So I took it.
[00:03:57] Kevin: According to Kris, quantum computing has moved from pure theory to practical applications. This marks a significant change in how we approach technology.
[00:04:05] Kris: Quantum technologies are generally can be thought of as technologies that exploits certain phenomena that are only really present in the quantum world. When you look at the microscopic scale of single atoms, single electrons, single photons, single particles of light the laws of physics change from what we experience in our day to day.
So these laws of physics are governed by quantum mechanics. The theory of quantum mechanics has been developed over a hundred years ago, if you saw the movie Oppenheimer, it's a good rundown of all the main characters of that field. And for the longest time, it was just theory with certain simple experiments.
Things really accelerated in the last 20 to 30 years where we suddenly found the ability to control these single particles of nature, these single atoms, single electrons, single photons. That meant we were able to suddenly think about exploiting these kind of unique properties. Such as superposition or entanglement that are only present in the quantum world for technologies.
Where we are at now is we can do this at scale so we can control, very precisely these single electrons, single atoms, single photons, manipulate them and apply them to build faster computers, but also more secure cryptography or more sensitive sensors.
When we think about quantum technologies, we think about something very new, but actually, when people talk about quantum technologies, you can think of it as the second wave of quantum technologies. The first wave of technologies that exploited these kind of quantum phenomena, but at a macroscopic scale were technologies like semiconductors, technologies like lasers. Which, gave rise to computer chips, classical computer chips, gave rise to telecommunications, which are the basis of the internet. We are already very heavily dependent in a way on quantum technologies. Only those kind of first generation ones. And that's what excites us about quantum technologies now.
And the second wave is now we have much more precise control of these single quantum objects. And so the idea is that we can build the next generation of technologies that exploit these quantum phenomena, which might be as powerful or more powerful and more groundbreaking than what we've achieved with semiconductors, computer chips, lasers, telecoms.
[00:06:28] Kevin: Next up, we explore how quantum physics with concepts like superposition and entanglement reveals the universe much different from our everyday experience.
[00:06:36] Kris: We have two different theories of how the world works. We have Einstein's general relativity that describes planets, galaxies, and big objects. And then we have quantum theory that describes single atoms, single electrons, this microscopic world, and there are two very different theories, even though they're both true.
You can think of an experiment where you take an atomic clock that is fully described by quantum physics, and then you send it into space where it can experience gravity described by general relativity. And it will give you the results of this experiment that comply both with quantum physics, both with general relativity, even these are two separate completely theories.
It was an amazing discovery at the turn of last century, right? Where people realize that they already had certain experiments that they couldn't explain with the current physics. And so they had to come up with new theories to explain these phenomena. And these theories invoked the idea that the world is quantized, that it's composed of very kind of tiny packets of energy, single atoms, single electrons, that you cannot divide even smaller.
And it turns out that if you made this assumption that the world works like this, then you could explain a lot of existing experiments and the results of experiments, but that also gave rise to a lot of new weird physics involving, like for example superposition or entanglement. So superposition is this idea that a single particle can be described by multiple states at once.
So a state could be where is that particle? A particle could be in a super position of being in two places at once or, it could be thought of as spinning in two directions at once. It's something we don't have a natural analogy to, but it makes sense when you look at single particles.
And again, quantum theory is the most precisely verified theory we have in a way, what we see in experiments agrees with it to the 10th and further decimal point. The other phenomena that is strictly quantum is entanglement. And here things get really weird because it's the idea, that you can get two particles or two objects so interconnected that if you send them on separate parts of the universe, if you change something in one, the other one will change as well.
[00:09:11] Kevin: Our computers use two types of processes for various functions. CPUs and GPUs to supercomputers will also use QPUs that's good at solving specific types of problems. Kris goes further into this.
[00:09:24] Kris: Quantum computers are another kind of modality of computing. We have CPUs and you have GPUs. And now we have an explosion in AI and that's driven a lot by the improvements in GPUs.
People have figured out that these graphical cards that used to be mostly used for gaming are actually very good at specific mathematical transformations that are the basis for AI, large language models, machine learning, and such. So now, GPUs are the big thing because they can be used for AI.
Any AI system will use CPUs and will use GPUs to some extent. Quantum computers will be another modality in the near to mid term next to CPUs and GPUs. So you'll see super computers that involve all three different types of processors. And the workloads that will run will involve all three different types of processors.
And you'll put the part of the workload that is best, processed by a CPU on the GPU and on the quantum computer. Or QPU, quantum processing unit on the QPU. I think that's a a good way to think about it as another modality of computing that is just going to be very good at solving a very specific type of problem.
[00:10:38] Kevin: Moving from general computing, we go into quantum technologies and they're promising applications in sectors ranging from healthcare to cryptography and materials engineering.
[00:10:47] Kris: You could split quantum technologies in 3 different application areas. So you've got computing which we've been talking about. On the computing side. The things we know that quantum computers will be good for are breaking current encryption. We have specific algorithms we know that, can break the current way we secure our data.
We know how to do search very quickly with quantum computers more efficiently than with classical computers. And there are a couple other kind of algorithms that we currently know that would run more efficiently on quantum computers. A lot of those involve, simulating, fundamentally quantum systems like molecules or drugs or new materials.
Probably the near term application for quantum computers will be in simulating, fundamentally quantum systems like molecules, drugs and materials. On the application area, invest new ways of designing drugs are investigating using AI and the next generation will be using quantum computers to design drugs to target specific diseases and health problems.
And then, new materials like lighter alloys for aerospace, harder alloys for drills, new materials for the energy transition, new battering materials, new alloys for wind turbines. All this quantum computers will help with in the near term. Now, the other two kinds of areas where quantum technologies will apply to is quantum sensing.
So using quantum physics, you can build much more sensitive sensors, for medical imaging or for gravity imaging being able to, find material reserves underground without drilling by just scanning the surface with very precise gravity sensors. Actually, sensors are already a very mature technology. We have demonstrated them working with better sensitivity than what is possible classically in labs all around the world. And they're very primed for commercialization right now.
The final vertical for quantum technologies is in security and cryptography. We also have protocols that utilize quantum physics that are fundamentally secure, where the security is governed by the laws of physics.
With our current cryptography, the security is governed by mathematics. Whenever you connect to your bank or, whenever you send any secure data, you're relying on a very difficult to solve mathematical problem. And again, we know how to solve that mathematical problem with a quantum computer.
That's one of the use cases we have for it. But you can use quantum physics to design new cryptographic protocols that are quantum proof, that do not rely on a mathematical problem, that they rely on the laws of physics, on the fact that what's called the no cloning theorem, which is this principle that in quantum mechanics you cannot exactly copy the quantum state or the state of a quantum particle, you cannot clone a quantum particle. You can teleport it, but you cannot clone it.
[00:13:54] Kevin: Next we discussed the areas that Kris is most excited about when it comes to investing across quantum technologies.
[00:13:59] Kris: We invest in quantum computing, quantum sensing, quantum communications. We also invest in the application areas that we think will be disrupted by quantum. Because when you think about quantum technologies, you can think about companies and invest in quantum technologies.
You can think about companies that are building the technologies, and you can think about companies that will leverage them to get an edge in their particular application area. So one company we recently invested in is a computational chemistry company based in the U S. Which, is not running things on quantum computers just yet.
They're doing very precise chemical calculations using classical cloud infrastructure, but much more efficiently than their competition. But they have also that quantum expertise in house, that when quantum computers become powerful enough to solve some of these problems, they'll be the ones that will be able to leverage them.
We're already taking a very broad view of of quantum and where it can be useful for. In terms of areas we're looking at a lot is on the application side and as I said, computational chemistry, material science and then we're very interested on the sensing side, because really, the technology is really mature there.
And it's about figuring out good business models for exploiting it and good ways in general of commercializing and productizing these these sensors and an area I'm personally passionate about is in in health care. These types of new ways to do medical imaging, or cancer detection, the technology is there. And so it's figuring out how to bring it to market and how to make it useful to society.
[00:15:45] Kevin: The next section, we'll go into how quantum computing might soon play a key role in drug discovery and AI.
[00:15:52] Kris: This is an area of interest for us and where we invest in. I'm not aware that any of these models use quantum computers just yet. Quite frankly, quantum computers are not powerful enough to really compete at this point with classical supercomputers. We can simulate small scale quantum computers with massive supercomputer, and it's probably faster to do so than just running on quantum computers. But with the progress we've seen on quantum hardware, in the next 12 to maybe 18 months, that will change. We will see quantum computers that for a niche and useful application can beat a supercomputer, can solve that as very specific problem much quicker.
And again, the type of problem that we think it will be and quantum computers will be useful for are exactly and computational chemistry for example, drug design. That whole problem won't be solved just by a quantum computer, like the workload will be hybrid involving CPUs, involving GPUs and involving quantum processors where required, and that's another area where we think quantum computers will start benefiting or bringing benefits sooner is in AI, is in kind of certain machine learning models that will involve a quantum component that can just sufficiently solve part of the neural network, that, current classical supercomputers may struggle with. These types of hybrid AI models likely will be applied and applicable to problems such as computational chemistry, such as drug design, such as material science.
[00:17:22] Kevin: Coming up, Kris, we'll talk about how today's cryptography is preparing for tomorrow's quantum challenges, emphasizing the importance of adapting, both technology and policies.
[00:17:31] Kris: I think it will be sometime before quantum computers will be used to enact very specific kind of computational protocols in cryptography. What quantum technologies can be used now is for securing the kind of communication links. So what we have is a quantum key distribution which involves using quantum objects to transmit secure keys between parties to encrypt encrypt the link and encrypt the data.
And that the technology is already there that we know how to do. There are multiple companies that are building, boxes that you can just buy to generate these quantum secure keys. And integrate them with your network. The challenge here is on a regulatory aspect and it's a bit of a chicken and egg and that, banks and other institutions, they won't implement this technology until they're forced or recommended to do so by the regulators, but the regulators won't regulate it until this technology has been deployed and tested in the field.
So there's been a few organizations such as banks and other public organizations that are really pioneering here and really doing interesting proof of concept work with this quantum security that will then hopefully spread around and lead to regulatory approvals and make it a lot more common because it is a challenge. Maybe quantum computers are not powerful enough now to break encryption. But it might be that they will be in 10 years time and, changing security systems from the current ones to a quantum key distribution system won't be easy and will take time.
The other aspect is, of course, these types of store now decrypt later strategies, right? Where a lot of the data now that is secured is being stored somewhere. And then once quantum computers, again, become more powerful, you'll be able to decrypt it. So if there is data that we are sending around right now that we want to keep secure, not just now, but 10 years, 20 years into the future, we need to establish these more secure methods of securing data now.
And it is happening. Here also you see differences between Europe and the U. S. For example, where the U. S. is betting a lot more at the moment on what's called post quantum cryptography. So it's again protocols that are based on mathematics, but just different mathematics than we use currently. These are based on mathematical problems that we don't know yet how to solve with a quantum computer. Is it secure forever? Will we not figure out how to solve these problems with a quantum computer? We don't know. We just know that now we don't know how to solve it.
But these are things you can implement in software using classical computers and classical cryptographic systems. So they're much easier to deploy, but not fundamentally secure. And then Europe is, let's say on a public level, governmental level, a lot more betting on these fundamentally quantum secure methods. And funding a lot of proof of concept works and networks, and then rest of the world is taking either camp.
[00:20:31] Kevin: The next topic, we'll take you through the complicated journey of investing in quantum technologies.
[00:20:35] Kris: Investing in deep tech and specifically quantum technologies is very difficult. That is very technical. It requires a lot of technical expertise because, it's quantum technologies as we've discussed, is pretty broad term that involves not only different application areas, but also different underlying technologies.
You need the technical expertise to be able to a) understand what these companies are doing and b) judge how much progress they've made and what's the rate at which they're growing their systems and to determine whether they'll be successful in the future. a lot of these companies as well are academic spin outs. A lot of this research has been done at universities. Though there are also big companies now like Google, like IBM, that are investing heavily in building their own internal capabilities. As an investor you also have to know how to talk to these academics. Because academics can be very focused on their specific technological solution, but technology doesn't make a business. Technology might, give you an edge in your business, but it's not a business altogether. We also spend a lot of time with our founders and our portfolio companies helping them.
To figure out some of the kind of business problems and business side of things, how to commercialize, how to be really successful, not just as a research unit, that's privately funded, but as a company. We don't make a lot of investments. We are quite selective. We really invest in the best technical teams who also have a very clear vision of where they want to get to with their business. That's one of the aspects we pay a lot of attention to. We don't want to fund research projects. We really want to fund businesses that leverage this groundbreaking technology to be successful.
[00:22:23] Kevin: Beyond funding Kris is hands-on with his investments by providing mentorship, industry connections and strategic advice.
[00:22:29] Kris: We like to be active investors. We really like to support the companies, even post investment, either with follow on funding where appropriate, or with connecting these founders to people in our network, either from a recruitment perspective or from a end user customer perspective, supplier perspective.
Connecting them to people that they need to be connected to, but also from helping them think through some of these aspects you touched upon about, how to build a business around their technology, what to focus on, how to design their roadmap.
We're very fortunate as a team to have experience in this. I went through the path myself from an academic to a startup and to building and delivering products to customers. Niels who's the founder of the fund. He was an early investor in one of the biggest now quantum computing companies in the world, Quantanium.
So he was an early investor in quantum back in 2016 and saw and was chairman of the board of this company and still sits on the board of this mega company. They are now and saw also what it takes and the process of taking a small startup and growing it to a large company. We've seen these routes. We know what works, we know what doesn't work. We really try to help our portfolio companies with that knowledge.
[00:23:50] Kevin: If you liked this Spotlight episode, please leave us a review. We're just starting out, so every review really helps. Follow us on Twitter at zypsycom if you don't want to miss an episode. That way, you'll be able to see every time a new show goes live. That's all from us today. Thank you for listening to this episode of Zypsy Spotlight.
