 Hello, everybody. So I'm really excited for this, because what UHA and IQM are working on just gets me so fired up and optimistic about the future. We're talking about manipulating the quantum states of superconducting circuits that close to absolute zero temperatures to enable a method of computation the world has never seen before, which might enable us to develop new therapeutics and solve the climate crisis and do all sorts of incredible things. And so I'm super excited to learn more about what you're doing in your journey. So maybe first just tell me a little bit how you got started in the world of quantum computing. Right. I would start from the five years ago. I was here for the first time in Slash and looking for funding for the seed round. And actually, it was part of our one year startup phase, or like a funding phase, where we're looking for the investors. We thought that it would be easy just to get the money. It took like a one full year. Eventually, we were able to rise the biggest seed round funding in whole Europe, 11 and 1 half million four and half years ago. So we are actually kind of university spin out from all the university VDD state research center here in Finland. We are four founders. During this first year, we were able to convince 20 of our best people we knew to join the company once we get the funding. There were like a, before this, there is like a 20 years of, let's say, preparatory stage. So first, I was a physics student, studied quantum computing 2001. There was a first set of lectures in Finland on quantum computing ever. My co-founder, some of our employees, took those lectures by Japanese professor, Mikio Nakahara, who actually we hired to the company when he retired from Japan in the beginning of this year. So there had been like a long, long history, a lot of work done in university. And then there was a spin out. And then we started flying. Cool. Love it. So I want to dig into specifics. But first, maybe at a very high level, it useful quantum computers have been two years away for like 20 years. So first, tell us a little bit about the state of quantum computing. And please answer the question, where are all the quantum computers? Well, I can deliver you one in six months, so no problem. So yeah, so they are quantum computers where for a long time they were a university research topic. And they are now taking off from there. They are about to land on commercial side to industry. They are still a bit far away or like one or two years away, as you said. But we, as ICAM, don't care so much about that. It's not a big particular event for us. But we are like those ones who make the shovels for the others who are digging the gold in the gold rush. So there's a gold rush for quantum computing. Someone will find it, someone not. But we will take benefit. Our business is not based on that. Who will find the gold? But we will provide the tools for the others who are pursuing the road towards that. This might be an answer to my next question. You've raised $11.5 million. Google is spending billions of dollars developing quantum computers. IBM is committed to tens of billions of dollars. How does a small startup in Finland fit into that ecosystem where so much money is being spent in such an R&D intensive industry? Yeah, so we have been always being on a two-string budget here in Finland. So that is not the first time. So let's say that why we can do it is that there has been like 60 years of university research. There is a lot of talent around here. There is like a lot of open facilities. We have actually quite an open culture for collaboration. So we don't need to do everything ourselves, but there is a quantum ecosystem. And all those help us to develop things quite rapidly. And of course, we have our own tricks at IQM. And so does the money that Google's spending and IBM's spending, are those dollars that you might see because you're building infrastructure for them? Or how do you fit in exactly? Well, first to say that we have actually now collected close to 200 millions already. So it's not anymore like peanuts. So but this is a capital intensive domain. So we have to build. We have to have those hardware on our facilities. We have to have big facilities. It all costs. But what is good in Finland? We have another company like Blue Force who is building those fridges which are cooling the chips to absolute zero. They are spin out 10 years earlier from the same lab. So and then there are like VTT, state research center, who are doing part of the value chain there. So we don't need to build everything in-house. We collaborate with others. And that way we can reach the complete solution together. Well, so you've already referenced a couple of times that this was built on top of research done in academia. So you're a PhD founder. You have your three co-founders also have PhDs. The CEO of the company is a PhD. In my opinion, one of the most interesting and important trends we're seeing globally is this rise of science entrepreneurship. This rise of PhD entrepreneurship. And so I'm curious in your journey, what were the advantages of coming from a very technical background and what have been the challenges? So yeah, so all in all, we have now about 300 people in IQM and about 40% of them are holding a PhD. So they are very smart people out there. There are obvious advantages that you don't need to tell them twice what to do. They will figure out. So I should say that there is like they are learning quickly. They can adapt quickly and so on. But then of course, I should say that the biggest part of the issues are always the people issues. So you need to make sure that those people, they are usually very stubborn with their own thoughts. Everybody think that they know exactly what to do and sometimes they are conflicting views. How to manage those people, how to make sure that they all fit to the company culture and they are all aligned to work towards the same goals. So that's the biggest challenge I see in this. That's maybe the same for the other teams as well. Some of the muscle memory or habits that make you a great researcher don't make you a great employee of a startup or founder of a startup. No, no. So where are the tensions there between the mindset of academia and research and the mindset of building a commercial startup? Yeah, so the challenge is that many of the university researchers are missing the business muscle. So for them, the perfect product is the goal but for a company, the business, the customer should be the goal. So the happy customer, so we should understand what the customers want to build, particularly that product which might be a different from that what the researchers thinks would be the perfect. Interesting. And then what do you do as the leader of the company to sort of help ferment that kind of mindset, the sort of commercial customer-focused mindset among the entire team? Yeah, so that has been a big, big learning curve for us to convert and I think it will be forever. There is like always this kind of conflict but let's say that how we are tackling that is that we have our business unit, our product teams which are different from our core R&D teams and then we try to make those teams to make them discussing with help of the requirements and some technical documentation. So we convert this mindset problem into technical process. Six months away from some sort of very useful content computer, say over the next two to three years, how should everyone in the room, right, I'm sure we have a lot of investors, we have people from corporate, we've got startups, what should they know about what's coming in quantum computing that might impact their businesses? Right, so yeah, so in IQM we are very humble and we don't overpromise anything. So what we are doing, we do quantum computers, we can do them on relatively low Cupid counts but we will deliver them in six months. So and they are very good for research for educational purposes, but let's say that at the same time the whole field is progressing towards quantum advantage or towards like useful applications. Can you define quantum advantage? Yeah, so the quantum advantage is when someone for the first time shows like exponential speedup what the quantum computer should be capable of delivering. So when the problem size grows, then the speedup should be exponential as a problem size. That's a quantum advantage. Since that is maybe a little bit further away than a year, people have started to talk about the useful quantum computer, which means that you would select the quantum computer instead of any other computer for solving the problem. So it might be that the speedup is not exponential but it provides some advantage, which might be like a better accuracy of the solution or less energy consumed for the solution or some other metrics which make it useful so that you eventually select. And so do you think over the next three years quantum computers are gonna be available enough that it's gonna impact the businesses of people in the room or are we still more than three years away from that? I think still over the next three years we are going to see mostly like a very, very impressive demonstrations but maybe it will take a couple of more years before, let's say, the consumer level. Maybe the investors will see it happening but let's say that before the consumers start to see the first applications where you really take advantage of quantum computer for some everyday problem. If I was talking to an American entrepreneur, they'd be saying, oh, next year for sure. Okay, so at the end of the day quantum computing is about computationally solving useful problems. We've seen over the last couple of years the rise of large language models and just sort of classical computing AI technology and it's had incredible applications in drug development in solving the climate crisis, in security. So where is there a need for quantum computing? Like why aren't we gonna be able to solve all these problems with large language models? So I don't see the AI and quantum being competing against each other but I think they are more like supporting each other. So let's say that quantum computer can accelerate the classical computation and you can be running AI on hardware which is quantum accelerated and that way since those large language models are computationally very heavy, they are super heavy. So they consume a lot of electricity, produce a lot of CO2. So quantum computer can jump in there, can help potentially to accelerate and save a lot of CO2 emissions for example. And on the other hand, AI is supporting quantum. So it can be worked in many roles to develop better quantum computers working between the end user and the quantum computer since end users or let's say software developers don't want to learn yet another programming paradigm. So AI jumps in there, you might ask your large language model, please make me a quantum software for this political application. And are there any classes of problems that quantum computing will be able to solve that you don't believe will be able to solve with sort of classical computing AI? There are many. So let's say the lowest hanging fruits are simulating nature. So simulating molecules, that could be lead to like a drug discovery, discovering better enzymes, discovering some functional molecules which are doing a job for you which are not available today. So there are like two ways to find a new molecule either you synthesize them in a wet lab which cost a lot of money, it's very slow or you try to use a computer simulation to make a molecule and predict the chemical properties. But quantum computer can help there and it's a quantum mechanical, it's very well fits to this kind of problem. Then there are like a bunch of other things like financial sector problems and optimization problems. You can like in logistics for example where you can expect some improvements quite quickly. So you touched on this sort of very briefly but say you have a quantum computer working, right? You have to build applications for it, right? Sort of software but the software of quantum computing looks more like writing algorithms. So what does that look like now? The sort of software aspect of quantum computing and then how do you see that looking 10 years from now? Well, at the moment you, let's say the quantum resources are so scared and let's say those programming interfaces are rather low level. So you go to something which is like assembler or even below that in a classical computing and I think for ages no one was anymore like doing any assembler code for computers. So it takes still few years to develop before let's say all the algorithm libraries are out there. So at the moment there are basically everything available in Python so some let's say tech savvy people can go and start doing it but let's say they are not yet available to that degree when let's say millions of software developers would be able to take advantage of quantum. So not that long ago you basically had to be a sort of mathematician to write software for quantum computing. Is that no longer the case? Can a Python developer actually write applications for quantum computers? Yes, there are libraries available but you need to still know what you are doing. So in that sense it requires usually like a university level education which is a limiting factor for the number of end users but I think that things are developing very quickly so let's say better and better programming interfaces becoming available. Right, so I mean one of the challenges that many not all but many deep tech companies face is that it's a long road to the final product. And if it's a really long road to the final product and you wait until you have the final product to sell that means you have to be completely reliant on venture dollars to fund the company which is kind of scary. I think quantum computing, looking for something that's scalable, low error rate, long coherence time it's one of these fields where it's just gonna take a while to get to the end final product. You found ways of monetizing different steps along the way. So I'd love to hear your sort of philosophy of going to market very early even before you have your final product and then why you chose to take that path. Yeah, so we found that company four and a half years ago and we were able to run it like a half a year before the COVID hit us and we thought okay is this not the end of the company or what should we do? So we were forced to think about how to manage it and then we had hardly nothing. We had a starting team and we had a little bit of technology in the corner of a lab. And the largest seed round in European history. Yeah, so we decided that okay we don't stop here but we become aggressive. So we started a very aggressive marketing. We put together what we had in the corners in the lab and started to sell it. We thought that who would in this world buy a quantum computer? Then we actually found out that when the COVID came there were those COVID rescue funds and in Europe they were like almost every country they were looking at the list of new technologies what are the technologies to invest and they had quantum computing pretty high on the list. So we ended up that actually it's a public affairs what we need to do. So we approached those public entities. We told them that actually there is quantum computing available, the hardware you just need the hardware maybe you would like to have maybe your universities maybe your research institutes want to have a quantum computer in the laboratories that will help them to boost their research and so on. And that actually started to resonate very well. So we were able to close those deals like in Finland, in Germany and we have been selling to Israel, Spain other countries as well. So there is kind of a need for this kind of instrumentation so they can build their own knowledge on top of that. So we were small company, less than 50 people and we were talking to the governments all over the Europe. I love that. That's the only way to survive in that one. You did it because you had to. Many founders are very scared when they have the sort of rough products that are laying around the lab to go and sell that to companies because they go, what if it's coming and they'll like it and they'll judge us, they'll never come back. But I know we've talked before and you found that you learned a tremendous amount from going and having those sort of conversations with customers that even impacted your future roadmap. So talk a little bit about like what is the value aside from the revenue of having those conversations with customers so early? I think they are absolutely crucial. So like we discussed, like usually talking about this quantum advantage which is yours away but when we actually learned, when we started to talk to the universities, we actually learned that this is actually this educational aspect is the key. So they want something for their education for their research. And the same thing happened when we started to think whose business is to host a quantum computer. It's high performance computing centers. We actually found that there are hundreds of them around the world. We were selling them like a faster computer and they said, come on, if you want a faster computer we go to HP or Dell or some other providers with the money they provided more computing power. So it's not a computing power, but it's actually CO2. They want less CO2 emissions. So we go talk to them. You learn a lot of things. Maybe you actually keep on developing the same technology but you make a completely different product, very different marketing out of the same product. Well, and then do you have a sort of philosophy of when those sort of very early sales are a distraction versus when they're a really good idea or do you think it's always good to go and try and sell things early? I think it's always very important to have a customer. It's if you're very isolated, you're like, okay, but there are those companies who are doing this big bank strategy. So they are developing for five, six years. I don't know where they find the investors, but yeah. Cool. No, I agree. So you are solving some just insanely hard technical challenges, right? And so how do you build a team that's capable of solving so many really, really hard problems? Actually, the physicists are very crazy. I can tell you, actually, they don't think that it's hard. So I'm surprised myself. So we made like a customer, like an employee satisfaction survey and we were asking like a lot of questions. And the questions were like, in the end, like some, there was always some red there, like some issues here and there, little bit this and that. And then there was one question, who thinks that your skills are not enough for the problems we are solving? And none say that they don't have enough skills. So they have all, everybody very confident that we have a road map, what they can complete. So that is the thing. But of course, like Ernest is speaking, like what we have been doing, we have been targeting the best people in the world. So we have been like in the very beginning, you are nobody, you are startup. You can maybe attract your best friends and the network close to you. But then after that, you are nobody. It's very difficult to convince someone to move to Finland from far away country. So it brings me to my next question. Well, so first of all, when employees feel like they have a good grasp on the challenges ahead, it means you are not setting the bar high enough. Your team should always feel a little bit underwater, right, because that's how you make sure if they can find the 10th gear. So why did you choose to build a quantum computing company in Espoo Finland? Wouldn't have been on my list of like places I'd expect. So there are like a lot of success factors. So this ecosystem, but why there is an ecosystem, there is like a concentration of talent. So there is a concentration of quantum talent here in Finland in Espoo, in particular. And then there is like funding available. There are maybe some other success factors like good regulatory environments, stable conditions and so on, there is a list of those ones. But then in a company, what is the success factor? You need to have a good enough team. You need to go beyond the tipping point. So actually, we found out that once you are able to attract some of the best people in your company, then the others will follow since they want to work with those guns. So, and we started that in physics. We knew very well who are the best physicists. And, but also it happens now we have been like our marketing team. We found some of the world leading marketers to our company. And also we have got a lot of applications now since they want to work with our head of marketing now. Yeah, no, it's absolutely true. I mean, this was the story of Google in the early days that the first 10 hires at Google were the people in search. So all of a sudden everyone else was like, wait, they're at Google, they're at Google, I got it. What is this Google? And so if you can get the first 10 to be really exceptional, it creates this snowball effect of future talent. So we don't have much time left. I would love to leave everyone with a reason to be excited about quantum computing. So like imagine that quantum computing manifests, right? What is your vision for the world when that happens? Like what sort of impact is it gonna have on longevity, on the climate crisis? Like what crazy cool world are we gonna live in? Yeah, we will find a lot of a lot of applications. Like we will have, as I told you about those molecules will make miracles as drugs or they make us like a fertilizer for agriculture without too many CO2 emissions. And eventually the big thing will be that once you have like a chat GPD on steroids, you have a generative AI and then you run it on quantum mechanical computer, like quantum computer. I think that will be the ultimate solution. So then you have a body, you can ask a question which is more smarter than you. So it can answer the fundamental question, what is the fabric of reality of this world? So quantum chat GPD, you heard it here first. Thank you for joining, this was very inspiring. Thank you very much.