Lab to Market Leadership with Chris Reichhelm

Quantum Computing Scale-Up: How Universal Quantum is Building Million-Qubit Systems | Dr Sebastian Weidt

• Deep Tech Leaders • Season 1 • Episode 26

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What does it take to build million-qubit quantum computers - machines that could fundamentally change how we solve the world's most complex problems?

Dr Sebastian Weidt, co-founder and CEO of Universal Quantum, shares the extraordinary journey from asking an audacious research question in 2017 to building one of the world's leading quantum computing companies. This conversation reveals the unique challenges of scaling breakthrough technology that operates on entirely different principles from conventional computing.

Seb explores why moving from academia to commerce became essential for quantum progress, how to engage customers for technology that doesn't yet exist, and the importance of building supportive culture during long-term, high-risk R&D. With quantum computing potentially 5-10 years away from delivering transformative applications, this episode offers key insights on managing expectations and maintaining momentum during the ultimate Deep Tech journey.

Essential listening for Deep Tech Leaders, quantum computing enthusiasts, and anyone fascinated by how impossible engineering challenges become a commercial reality.

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Podcast Production: Beauxhaus


Seb Weidt:

Actually, if you think about it, it's all comes down to the hiring part. Because if, if you know, you have this, this, this dream of what the culture should be like, then everyone you bring in, you've gotta make sure that that alignment is there. Especially in the early days where we, we've often turned people away who were supposedly smarter on, on, on paper or had better skills than some other people. I, I still truly believe that yes, you can bring them in. They will not be as infected and impactful as someone else who on paper isn't. Quite as strong, but it's got that cultural alignment fits in is a great team player and just, you know, lifts and breathes. What we really want to want to achieve here.

Chris Reichhelm:

Welcome to the Lab to Market Leadership podcast. Too many advanced science and engineering companies fail to deliver their innovations from the lab to the market. We are on a mission to change that. My name is Chris Reichhelm and I'm the founder and CEO of Deep Tech leaders. Each week we speak with some of the world's leading entrepreneurs, investors, corporates, and policy makers about what it takes to succeed on the lab to market journey. Join US Lab to Market Leadership listeners. We're on the road traveling throughout Europe, then hitting the us, then coming back to the uk. We're taking Lab to Market Leadership global. We're speaking to. Entrepreneurs, investors, executives, academics, and of course policy makers to understand from an American, from a European perspective, what does it take to bring innovation and companies from the lab to market? And I'm delighted that we're starting off by talking to Sebastian Weidt, who is the co-founder and CEO of Universal Quantum. Universal Quantum is a leading quantum computing technology company. They are building actual quantum computers, full stack quantum computers. And today I'm gonna wanna get into a. What it actually takes to do really big things, because that is so much of what Deep Tech is about, doing big things, bringing people together with different backgrounds, marshaling them, organizing them, implanting a culture or letting a culture grow and cultivate. But how do you maneuver that? How do you navigate that? How do you try to control that? If you're a young entrepreneur and you haven't had the experience, even if you're a super experienced executive, how can you get people to do really big things consistently? This is gonna be a fascinating episode. Let's get into it. Seb, thank you so much for joining me.

Seb Weidt:

Thanks about for having me, Chris.

Chris Reichhelm:

The, the journey from research to academia to CEO is. Actually still a fairly unique one, even in deep tech, even where you kind of expect it in very advanced science and engineering, but it's still kind of unique. How, how has it been for you?

Seb Weidt:

Yeah, great question. I, I think for, for me, oddly natural, I think if I, if I go back to early days, undergrads and, and so on, I, I, I initially never saw myself in, in academia. I did an undergrad in physics with management. Um, thinking that, you know, after, after my undergrad time, I would go into, um, into the commercial world. Uh, did for a bit, did some, some consulting work and uh, you know, ended up doing a PhD. Did a PhD in quantum, um, and, and very much fell in off with it. Uh, and, and carried on that, that, that journey. And, you know, once you, um. Once things work out, and you are, you are, you are lucky, um, on, on that sort of research, frankly, you become an academic and, you know, at the end I went to to professor level on, on that side. But I think if I look at the, you know, my motivation at the time, you know, driven by, by curiosity around, around quantum, but very much having the, um, the, the sort of ultimate impact that quantum can have in the, in the worlds, in, in my mind, I think it was one of the reasons I, I stayed in academia, uh, because I knew at some point there would be that, that sort of commercial impact that I've always been, been driven by. Um, and it's just been very fortunate to be able to combine a, a lot for quantum and the, the strong desire to do something, something really impactful, um, in, in the world. So whe when then the, you know, so there was a transition from, from researcher to academic, um, and then the journey from, from academic to. Um, you know, someone in, in the commercial world, it fade naturally. It, it felt like, you know, another home for, for me. Yeah. So it, it, it never fed that troublesome, but for sure that there are challenges. That there's huge differences. Sure. Um, yeah. I, I, yeah.

Chris Reichhe:

And so did it feel, and so was it, was it part of a plan? Um,

Seb Weidt:

yes, I think it, there, there was for sure a, a plan, I think timescales, um, maybe less so, but I would say from, you know, halfway to the PhD when, you know, when that realization came through, Hey, what I'm working on here, um, could have a big impact on, on quantum computing. Uh, back then quantum computing was very much in, its in its infancy that there wasn't really anything commercially going on. Um, but I think over time it became, it became clear that this is not something that you can, you can take all the way in academia. So there would have to be a, a commercial component coming in at some point to attract the rights sort of talent and. Um, know money and so on. So yes, it, it was on the, the horizon, but I think it was heads down and, and just keep developing and keep getting ready to actually take it to the next step.

Chris Reichhelm:

That's quite interesting that you make that reference to, in order to take it further, we had to get commercial in a way. I guess so. So there's that kind of love and the commitment and passion. I'm guessing, I'm putting words into your mouth, but I'm assuming they're there to go and try to solve this problem to go and try to realize this future, this quantum future. But in order to do that, there's only so much that research, there's only so far that research can take us at some point. In order to really advance this and realize it, we have to go commercial. Have I overstepped a mark there in terms of my summary or

Seb Weidt:

I, I don't think so. I think for, for quantum computing there, I, I strongly believe in that, um, academia. Had a great, um, place for quantum computing and we'll continue to do so to try things, to, to get your head around what, what the best route forward is. But I think that there comes a time, um, when you realize, well, hey, I, I think I've got a reasonably good handle on this. Um, it's about execution now. It's about, you know, taking certain things to the extra 10%. It's about investing significant money and maybe getting, you know, some, some heavy hitting engineering talent, um mm-hmm. In here to, to, to take this to the next level. And this is, yeah. In my view, academia just isn't, why set up for, for, for that part. Yeah. Yeah, yeah. Yeah. And that's when you, when you've really make that, that switch, obviously the question is then, you know, do you then hand it over and you continue your academic journey or mm-hmm. Do you kind of move with that and, and continue that journey? Yes.

Chris Reichhelm:

Yes. You, you referenced earlier some of the challenges where that it is a challenging transition to make, to move from academia to CEOs. Everyone would acknowledge that. What have been some of the challenges for you?

Seb Weidt:

Um, I, I think for, for me, I mean like, like I said earlier, it was, it, it didn't really fear that much of a challenge, but there's most certainly, um, 'cause I've been so excited about that and it, it, it really felt like, Hey, I'm, I'm, I'm back in the commercial world. This is, this is great. Um, but I think there are big differences, um, in, in the way you communicate. You need to communicate your, your work differently in the commercial world to what you do in academia. And, and that might seem subtle, but actually I think it's, it's huge because at the end of the day, you, you need to convince, you know, non scientists, non physicists to, to, to join you on, on the team. You need to get people to invest in your, in your project. And they, they speak a different language to, to what what we're used to in, in academia. Yeah. They may also be excited about different things. Something that I absolutely find fascinating about, about quantum computing and, and what we've built. Someone else may find completely boring, but they get really excited about something else that we did. And, and, and finding out, you know, how to best position that, uh, to, to take the project forward is, is it's not easy. Um, and, and it takes time. Um, and it, it's definitely a, a different part than, than academia. And obviously the, the other part is you have structures around in academia that there's a HR department, there's a finance department and so on. Um, and you know, as much as, as academics like to, to moan about that sometimes once you don't have it at all and you need to build it from scratch, you know, it, it, it takes some time getting your head around it and a lot of thinking on what you would like that to be like. Um, yeah. How does support your culture? How do you build a culture? Right? You get that? Yeah. I saw as an opportunity. But it's, it's a huge amount of work and how you build a, a a, a culture that just allows you to, to deliver and look after the people the way you see it. It being best for, for purpose.

Chris Reichhelm:

Yeah. Yeah. Is it, is it taxing, I don't know if this is the right phrase, but is it taxing emotionally because to go from the, I don't know, the stability, I mean, there's a risk factor in there because you're moving from the security and fair, you know, stability of an academic institution to something that is inherently risky. Uh, and that brings with it a lot of thrill, a lot of excitement, um, but also a lot of uncertainty. Some people will thrive in that kind of situation and others won't. Um, but to, as you're dealing with that pressure, uh, as young entrepreneurs, as entrepreneurs, sorry, of any age, are subjected to the pressure that startups, uh, throw on on their executives, they come under, they can come under intense pressure. And that has, IM an impact emotionally. And of course, those emotions can impact behavior too. You know, has that been a challenge at all, or are you in fair? You know, are you in control of that?

Seb Weidt:

I mean, it's a great question. I think every, every founder, every CEO will, will feel pressure. It probably comes in, in different ways. Yeah. I think for, for me, that the, the passion, obviously you dominates and, and is a, is a huge driver. So I think I, I rarely looked at it from a security for myself part, but I think I, I most certainly notice as the team, as the team grows, um, you, you do fear that there's, there's livelihoods around, right? You, you convince people to move continents with their families, uh, and and so on to, to join, join your journey. Um, you know, that's, that's something I think is important to be mindful of that. Um, yeah. And, and to not be dismissive of that. We, I, I have that responsibility I, or to feel that responsibility to, to our team, but I think for. For me, myself, not, not so much. Um, I mean obviously I had, um, my, my first kid was born pretty much when we started out, um, with the startups. It, it's, he's roughly the same age as the, that the startup actually. So, you know, and, and you know, the, the listeners who have kids that they will know that sort of sense of responsibility that all of a sudden comes in as soon as you have kids. Yeah. Um, so yes, that, that did come in, that that is the, yeah. But, um, I, I think ultimately for me, it was just following the, the, the passion and, and trying to do something, something really, really exciting and difficult. Just push it, push it forward.

Chris Reichhelm:

Yeah. Yeah. Yeah. Yeah. Yeah. Let's, um, let's, let's segue into Universal Quantum a little bit and talk a about, I suppose the approach that you guys are taking to Quantum. There are a number of different approaches that you can take and we see different quantum plays pursuing. I don't know that kind of operating systems layer, uh, or seeing, uh, I think of companies like New Quantum who are trying to do the networking effect, so bringing lots of quantum compute capability together via a networking layer. Uh, and then we have, uh, we have organizations like your Good Selves who are actually building the machines. Um, it's a, which is probably the most, which is probably the boldest move to actually build actual quantum computers. Why did you guys pursue this approach?

Seb Weidt:

Yeah, sure. I, I, I think just, just to, to, you know, in my view is that we, we have a lot of bold leaders in, in our community across the stack. Um, yeah. You know, on, on the software side, on the hardware side. Yeah. Um, I, I, I respect anyone who actually comes into the sector and, and tries to push it forward immensely. Um, I think the hardware. Side comes with additional complexity around the costs involved. Um, mm-hmm. You know, it, it, it, sometimes the timescales evolved to commercializing that is, is a bit longer. And, and yes, some of it comes with a bit more risk, so that absolutely it is, is maybe a bit more unique in that area. So why did we do that? I think, um, I mean, from, from the beginning of my journey, I've been in that hardware space, um, that that's what I focus on. And I think at the end of the day, without the hardware, without these quantum computers, everything else around it won't be useful, right? Like we, we can, we can develop the software and the applications, um, as much as we like, but at the end of the day, we need these, these useful quantum computers. We need the hardware, uh, to unlock that, um, that happens, that that's where my expertise lies and therefore it was. It was very natural to, um, to focus on, on that, given that that's also where we've been doing a lot of our innovative work, um, to, you know, really push that field forward. So it was just a natural one to Yeah. Push

Chris Reichhelm:

forward. Yeah, yeah, yeah, yeah. Yeah. Just how much of that stack are you looking to build and create?

Seb Weidt:

Yeah, we're, we're what, what people would call a full stack quantum computer. So we, um, we do some application work. We have a big software team, um, and we build the hardware. But I think the, I think the further up the stack we go, um, into the software, into the application layer, the more we collaborate. Um, and I think it's important to, to leverage the great work that's being done in the community as much as possible. Yeah. Um, but yeah, at the end of the day, we like this end-to-end approach. We need to understand. What customers would like to do with our machines. Um, we need to have a level of control of what our software stack looks like and how it interacts with the hardware. So we, we wouldn't want to give that away completely, but we love collaborating, uh, on the high level side.

Chris Reichhelm:

Mm-hmm. On the, the, um, I'm curious about early partner or prospective customer engagement when you're operating in a field as bold as quantum. So we haven't had quantum computers before. We still don't have them. We're building them now. And, uh, and so, you know, in, in working with customers and partners to understand what a quantum future could look like, we're gonna have to make a number of assumptions around capability and then ul ultimately around the applications that are gonna exist and the kinds of problems that are gonna be, that are capable of being solved once we realize this future. How has that worked for you guys? How do you bring that kind of community with you as you're developing your solution? Yeah, I,

Seb Weidt:

I think the, so it's a, it's a, it's a great question and, uh, it probably deserves somewhat of a complex answer. The, if you look at the, the sector as a whole, um, we do have some quantum computing prototypes that people can access today, and they act as a phenomena engagement tool for Yeah. Um, you know, potential customers, end users to start to engage with, to get a feeling for, well, what is this technology about? How do I use it? How do I program it? What can I potentially do? Now, these machines are not at the scale yet where they can deliver true utility. They, they, they're not changing anyone's life yet, um, but delivering a new capability, but they allow you to learn and that's, it's a very important, um, part. There are companies who are. Very much focusing on that. Um, trying to get as many customers to engage with their tech as possible. Now from the realization that, well, maybe these machines aren't useful yet. Um, what, what do they need to look like to be useful? How can we unlock some of these amazing applications? And I think yeah. You know, coming back to, to my personal drive to impact, um, it, it you very quickly realize when you do the math, so to speak on, on that, that we have to dramatically scale up the, the, the machines that we have today. Yes. Um, and you know, I, I, I think we should probably stay away from technical terms, but cubits, you know, these quantum bits Yes. Um, that, that are so, um, fundamentally important to the operation of a quantum computer. You know, people use 10 to maybe a couple of hundred of qubits today, but ultimately we need to get to millions of qubits. And it turns out that that is incredibly difficult, really, really hard. Um, and I don't think many people have a good idea of how to get there, which is one of the challenges of the sector. And this is really where we're focusing all of our energy on, on that scaling part. How can we take these beautiful machines that we have today and how can we open that window of opportunity to scale to a level where we can unlock these amazing applications, um, yes, that we already know about today, that that will unlock. So for, for us, therefore, the, the partners may look a bit different to someone who's ultimately focusing on making a machine available to as many people as possible so they can engage with it. For us, it's more having the, the long term partners on who want to leverage the usefulness as soon as it becomes available. Um, partner with supply chain partners that help us get to that stage as quickly as possible, partner with governments, because at the end of the day that this is a, a national capability that we're creating here. So all of a sudden, when you think about scale, the, the partners that you may be looking for today. Might look different to, if you're looking about pushing as many chronical tooth resources into the market today as an engaging tour.

Chris Reichhelm:

Yeah, yeah, yeah, yeah. Yeah. And do these discussions impact you're having dis, you know, you're having discussions with the different types of partners you've just described. Um, do they impact the fundamental approach you take to the development of the computer?

Seb Weidt:

Yes. They have a huge impact and, and they ought to at, at the end of the day. And I think that's, you know, it gets back to your first question, you know, what's different between academia and, and industry. You know, when we're an industry, we're, we're here to serve our customers. We have to develop our machines in a way that they, they do what the customers would like, um, to use them for. Mm-hmm. And therefore we can't afford to. Too much in love with certain curiosity around the, the quantum nature of certain things. Yeah. Um, and therefore, yes, we, we do like to collaborate and partner with, um, our customers where we're sensible and really do the learning that we need to do to optimize. Yeah. I wouldn't say fundamentally change the desire. Yeah, yeah, yeah, yeah. Okay. But to optimize it and, and make it as useful as possible.

Chris Reichhelm:

I mean, because that's the challenge of taking, of, of bringing something to life that has never existed before. And the customers, you know, we say, yes, we need to listen to our customers. And that is absolutely true, but in a, in a, in a way, they don't know what that future's gonna look like. And they don't have the capability to deliver on that future. And so we're asking them, maybe we're requesting them. I'm, I'm arguing the other side right now in a way, but to, you know, so, you know, but there is inevitably there must be this kind of alright, regardless in the science, we still have to pursue this line. We still have to approach it, we believe in a particular way at, you know, certainly in the application layer. Um, and maybe in the hardware selection too. We may have to make some adjustments depending on which problems within the quantum universe we're gonna go after and try to solve. And, you know, and so I, I just wonder about those, those trade-offs when you're building something that's so potentially bold and powerful, and that is going to represent a new paradigm, a new way of doing things. And yet your partners and customers don't fully appreciate that new way of doing things. And so, you know, they're not gonna be able to share with you all of the answers that you need in order to skew your, uh, your, uh, your development in the right, you know, along the right course. So it's this kind of trade off.

Seb Weidt:

Yeah. So much to say on, on that. I, I think, let me put, you know, to your first, uh, point, let me put that in, in three categories, that that's how I would look at it. Yeah. There's the, the applications that we, that we already know about, um, application areas we already know about, where, you know, we need to engage with, um, the, the potential customers, end users to really nail that down and understand where in their particular area it, it really becomes truly useful. Right. And, and that mapping, um, is really important. That's where you have to listen to them. It's like, look, you know, how do you operate? What's really difficult for you? So we can do that. That last bit of mapping then. So that's one category and I think that, that work has to happen today. Mm-hmm. We then have the second category where, you know. I think one of the, the, the most striking things I find about, about the application side of Quantum is that we already know about lots of amazing applications that make all the effort that goes into this why worth it today, but I'm mm-hmm. I'm absolutely convinced that we haven't found most of the, the, the coolest applications yet, and it's because we, we have to approach quantum from a completely different, different way. We have to change the way we ask our questions when we think about mapping a, a, a problem to quantum because it's, it's a machine that works so differently. That means if, if I go to a, an end user today, what's your computational challenge today? That's in some, some sense, the wrong question to ask because they won't even know about, they've been trained to not ask certain questions because they know it's impossible to do so. It, it's, yeah, that, that, that sort of dreaming, that sort of, you know, being really innovative in that area needs to happen and, and that's not easy for people to get head around. And then I've got the third bucket where, you know, that gets to your scientific point of, you know, doing more academic research in many ways on the application side. Yeah, yeah. And getting better at really, um, understanding the, the, the, the operation of quantum computers and, you know, coming up with new algorithms and so on to provide us and, and end users with the tools to dream a bit more. Right.

Chris Reichhelm:

Yeah, yeah, yeah, yeah, yeah. Yeah. The, uh, I mean, you made some great points there and the one that's really resonating for me right now is almost this, this other language you need to learn or this other, this other skill you need to learn as a user, as a prospective user of quantum computing, to be able to ask the right questions or to think about problems in a quantum like way. You know, we know how difficult it is for anyone to change their behavior in order to adapt a new technology and. There was a time where we didn't have internet and we didn't have software that we didn't have mobile phones with, you know, the world's knowledge and our fingertips. And over time we've become, you know, quite adept at, at, uh, at adapting that technology to the way we think. And we've probably adapted the way we behave to the technology to an extent as well. And I wonder if part of the challenge with Quantum is going to be something along those lines where we're gonna have to start thinking again about, we're gonna have to rethink the way we approach problem solving for the quantum world. There will be kind of a Newtonian, for lack of a better, uh, metaphor, a Newtonian way of looking at the world with, you know, the technology we have right now. And there will be, you know, an s you know, an Einstein way or a quantum way of looking at the world, um, that's gonna require us to think at a different level and ask questions at a different level and express our, uh, the problems we're trying to solve in a different way.

Seb Weidt:

I mean, what, what really? Absolutely right. And I think what really struck me at only a few days ago, and you may have seen this as why the, the, the, the sort of, I dunno if it's news, but um, you know, the, the viral posts around, um, you know, the impact of, of finding other ways of querying ai, right? And, and that's sort of realization in the last, in the last few weeks. And, you know, you can get so much more out of it if you, if you become really smart around how to query, um, a, uh, an I to it. And I think that that AI is just that sort of linear extension of our conventional computing capability. And now we're talking about quantum, which is on a completely different planet, right? So Yeah. Yeah, of course. The way we have to, you know, change our thinking and our, our, our problem framing is, is is just widely different to what we're used to today. Yeah.

Chris Reichhelm:

Yeah. I think that's a great, I think that's a great comparator. Um, this is called the Lab to Market Leadership Podcast. So let's learn a little bit more about your lab to market journey so far. How did you guys start? What was kind of the catalyst and can you talk a little bit about what that founding team looked like?

Seb Weidt:

Yeah, so there's um, there's two founders, um, myself and, um, with Wilfred Hensinger, uh, both coming out of the, the academic space. And I then, uh, took the lead, so to speak on the, the sort of commercial journey, um, here. And basically what's happened at, I think around 2017, um, is that so, so us as an academic research group for, for years we've been focusing on, um, you know, finding ways to remove the roadblocks to scaling our particular technology, which is, um, trapped iron based quantum computing to the million qubit scale. And that, that was a, it was almost ridiculous thinking at the time. You know, people were working with one or two qubits and were very happy with the, the work that they were doing there. Um, and we always got Elizabeth. Worried about, well, would that work at the, the, the million qubit scale? Probably not. We couldn't really see how that worked. So most of our research focus was, was really focusing on, on finding ways, um, that that would still work at the million qubit scale. Now, in 2017, we then asked this, this really audacious question, audacious question, um, would it technically be possible today with, you know, lots of money, lots of great people to build a million Cupids trapped iron quantum computer with the, the great work that's been happening in the community at the time, the work that we've been doing? Would that be possible? Um, and so we teamed up with a, a number of great minds and um, went out to find the answer. And it, it turned out once we went through that and, and a lot of hard work that it would be possible really difficult, really hard, no doubt. Um, but we, we saw a a, a way of doing that. Um, and I think with that realization also came the realization. Oh my God. It's, it's most certainly not gonna be a, just a group of physicists building a very cubicle computer. You need great engineering minds and you know, j just people you would never be able to attract to academia. You, you need a, a fantastic supply chain and lots of money, basically, academia was made for that. So it, it has to really be that, that sort of commercial effort. And we, we really use stats as, as the starting gun for universal Quantum. Yeah. To then embark on that journey on, on commercially scaling up, um, our, a sort of approach to, to quantum computing.

Chris Reichhelm:

Yeah. And, and did you have the, the question that you asked, which I love by the way, something really super bold and then let's look at the obstacles that would be in our way and could we in theory do this and, um. I'd love to talk about supply chain a little later, but let's stay with this for right now. But looking at the, you know, was that then approach that you guys went on the Trapped Iron approach, had that been based on your research up until that point? So then you could use that research as your starting point if you want, we're gonna build on this stuff that we've already done and take that forward as opposed starting with a completely fresh slate.

Seb Weidt:

Yeah, absolutely. It, it, it was that, that blueprint that we came up with and we published at the time is, is why we became the foundation of the approach that we then yeah. Followed at Universal Quantum. I think one of the, um, it was interesting actually that the sort of scary moments in the, the, the early days was obviously why once we bring these great engineering minds, um, on board, would they look at this and be like, well guys, you missed this obvious thing and you can't do that. What, what are you doing? Right? Um, yeah, yeah, yeah. You know, I, I reasonably humble physicist to, to appreciate, I definitely don't know everything and, and, and that was. That, that was a, a scary moment. But I think what we found is, you know, more and more people joined and, and we had this, and still continue to have this strong engineering, um, focus and it just kept getting more validation that no, that, that it would be hard, but this can be done. And by the way, there might even be easier ways to doing it than what you guys thought because you weren't aware of this particular engineering technique and, and so on. So it, it started to look even better than what we had. Okay. Initially. And I think if I look at where we are today to where we were back at the beginning, it's a completely different place. It, it's far more, um, you know, manageable and, and, and exciting in terms of, you know, how quickly we, we can get there and was the cost involved and so on. Absolutely.

Chris Reichhelm:

Yeah. Yeah, yeah. Yeah. The, the, um, lots of questions here. The, that core team, it was you and your co-founder. When did you start hiring the next parts of the team? Immediately?

Seb Weidt:

So for, for me it was, um. Absolutely key that there were a, um, there were a few people from the research group I, I pulled over quite, quite early on. Um, yeah. But actually the, the, the focus already in that, that spin out phase was to find, um, some key engineers to, to come on early on. But crucially, I was keen on operations. Um, I, I'm a culture fanatic, so to speak, and, and I always have been, and I was absolutely convinced that operations is where it always starts. Um, we're actually not the sort of company where tech, tech, tech and yeah, I need to have an ops team to, to pay people. It was the other way around. Um, and I made the, the decision to actually hire a, I mean, a phenomenon, um, great senior obsolete as, as one of the very, very first hires, and he's still with us now. Um, yeah, he speared a, a fantastic, um, operation, uh, that, that, that was, I think one of the best hires I've made. I've made early on. Yeah, yeah, yeah, yeah. And then build, you know, then started hiring more, more tech people and so on. Build up the engineering function, et cetera. But ops, I think it's key if you wanna build a, a great culture.

Chris Reichhelm:

What do you mean by ops? Operations can mean different things in different types of anything, not technical. Okay, okay. Oh, that's interesting. Yeah. And so what was there, and so talk a little bit more about that. What was, you know, what fell under their remit? What were the core things that you were looking for? Uh, in hiring this person? Um, culture and fit, I had

Seb Weidt:

in my mind what, um, and, and he would maybe say, oh, sometimes a bit naively, but I'd had in my head what was sort of culture. I would, um, I would love to, to, to create. Um, and so I, I spent a long time, and this is probably one of the, the slowest hires, and it took me a long time to, to make a decision there, but to find someone where. Um, that, that cultural lineman was then he was also, you know, much smarter on, on the culture side that than I am. I didn't actually mm-hmm. Try to look for the best finance person or the, the, the best, you know, technically minded person on, on HR systems. Yeah. It was the, the culture piece, the emotional intelligence, um, that was absolutely key in, in that early hire. Um, and then have them actually run all the non-technical side, take as much away from, from the technical people as possible. The tech guys should just have to focus on their particular bit, on their expertise and not worry about anything else. Right. And that, that's, that's what what is very keen to, to build that self operational environment, um, yeah. As quickly as possible and not be too scrappy in that area.

Chris Reichhe:

Okay. Okay. So to put more, a little bit more support around that. And so I'm an engineer. I joined your company at this ver at this very early stage. And you've got your operations group within there. What would I have found? How would my experience have been? Um, I mean, definitely asked our guys. Um, yeah, yeah, yeah. I would hope that did the surf answer they, they would give you is, um, cared for, well looked after that, that we mm-hmm. You know, we don't just care about them being, you know, delivering a great technical output, but we want 'em to be happy. We, we want them to feel supported, looked after, nurtured, cared for. I, I think is, is number one. I, I think the next bit is to, to find processes, um, that, that make their life as easy as possible. Allow them to focus on, um, on being effective. And usually when you hire great people, they, they get a lot of energy out of being productive and, and not being slowed down by processes and, and distractions. And I think the other part is to, to have a great. Growth support around, right. E everyone loves to, to grow as a person, um, yeah. Grow their technical skills, you know, how do we do that? How, how we, how do we do that as, as seamless and, and, and, and easy as possible. So it's, it's these sort of things, but I think ultimately they should just fear that, that everyone cares about them, right? That that's, we spend so much time at work that that's something that I think everyone should feel at work. Um, so that was, that was close to our heart. And so, um, again, let me kind of drill down a little bit more into that. Is that around, is that around, I don't know, you know, benefits, is that around, it sounds like it's around some training and development. It's around maybe an onboarding experience. Um, uh, it's, uh, you know, can you kind of expand on how does it manifest? How does love and care or, or support, not love, but maybe support and care manifest itself in an early stage company? When resources are often limited, where, uh, management experience is often limited and where the task at hand is almost existential, we either do this or we die because our, our, our next financing is predicated on us being able to deliver against this milestone, whatever it is. But, you know, so, so, you know, this is wonderful because it's so unusual, um, to hear this kind of approach taken at the early stage, but you've gotta, you know, help me understand how that support manifested itself early on. Sure. If, if I could, just before I do that, pick up on your last point, because I think that is, that is part of the crux of it. I, I strongly disagree with the premise of. We just have to get this done. Otherwise, we, we die. I actually think you get way more done if you have happy, well looked after people like it. It's, even if I was completely selfish and I only cared about the success of the company, you should look after your people because it makes it more productive. Um, and, and care for the company and, and go the extra mile. So it, it's, that's not, wasn't really my drive. I, I I, I love our guys and I, I, you know, really, really care for them. But even if you weren't that way inclined, you should still take that approach. Um, but maybe to, to your first points then the, um, yes, of course it is around the, the sort of standard fundamental, it's on, you know, fair pay and, um, you know, not having to worry about that. And, um. Benefits, but I think it's, it comes down to to, to smaller things, right? The day-to-day interactions. Um, what are the values that we, that we not just slap on our website and our, you know, standard boiler plates that we find everywhere, but what are they really, what does that mean day-to-day? How do we bring that in, into the, the interactions that we have and, and team meetings and, you know, outings that we have in, in, you know, how we deal with failure, how, how we deal with successes, um, all these sort of things. I think it actually comes in, in so many different ways across the organization on a day-to-day basis outside of the, the, the big fundamentals, of course, that you mentioned as well. I get it. I get it. So it's, it's something that has got to be, and, and you're right, it's carried through those human interactions Absolutely. And soly if you want. Yeah. Yeah. And, and therefore hiring it actually, if you think about it, is all comes down to the hiring part. Because if, if. You know, you have this, this, this dream of what the culture should be like. Then everyone you bring in, you've gotta make sure that that alignment is there. Especially in the early days where we, we've often turned people away who were supposedly smarter on, on, on paper. Yeah. Better scared than some other people. I, I still truly believe that yes, you can bring them in. They will not be as infected and impactful as someone else who on paper isn't quite as strong, but it's got that cultural alignment fits in is a great team player and just, you know, lifts and breathes what we really want to want to achieve here. So that wow. All begins with the hiring. I think that's really, really important. And then obviously once you have that, then you start having a, a bigger group of people who can hire people and can carry that culture and, and this can grow more sustainably. Yeah. Is that your North Star? Oh yeah, very much so. Oh, absolutely. Um, I, I think the, it would obviously be, um. Be, be a fairy title. Also not point to that scalability part in the million qubit, which is, you know, what, what we kind of center our work around. But the, the culture part and, and what I, and, and the, the team spend so much time on is really that, that North Star. Um, and so that together, I think that's the, the key bit. How do you test for that? How do you test that some that a manager you're hiring or an individual you're hiring has got that capability? Because that Yeah, let's just leave that as the question. I, I, I could keep going on in that, but how do you do that? It, I think it's really hard and I, I, I, I don't have a, a standard playbook. I, I think a lot of it, um, comes through a, a, a rigorous process. So we, you know, we don't just have two rounds or three rounds that they get to talk to a lot of people from different areas. It's not always from the same team that they may get hired into. Mm-hmm. Um, there are certain questions I think we've, we've come up over time that help us test mm-hmm. Mm-hmm. Certain things. And again, where, where the, the, the ops people that we've hired in particular also the, the first ops hire that I mentioned, um, had a lot of experience in, um, how to tease that out in, in an interview process. Um, it, it's, it's really, there's so many different facets to it. I, I, I couldn't just give you, look, these are the three things you need to do and you're gonna be done. And I think a lot of it is also you, you just get a, you just get a sense for, for, for these sort of things once you spend sufficient amount of time with the candidate. And I think the other part is to also be really open and honest, because it's a very interesting natural filter once you do that. Where some people will look at us like, I don't want that. What, what are you doing? I, I just want this, you know, cold, clear cut. You know, just delivering sort of culture. Just be who you are and, and, and show that in these interviews and see what you get back. It's very interesting what happens in that sort of process. I bet. I think, look, I, I think it's super, super interesting. You know, you guys are trying to do something that, from an engineering perspective is so fricking hard, um, and has, has not been done before. And, um, other people are doing it. And so you've gotta build this team. You want to keep, I'm guessing you need to kind, you know, one of the, one of the challenges is keeping that team together so that, that knowledge is, is, you know, you build up your base of knowledge and then you're able to do different things with that knowledge. Mainly learn from it. But you need those same people around. You need them to continue to build on that knowledge. You need them, you know, failure is gonna be the norm. The failure is gonna represent a large chunk of. The outcome for a lot of what you're doing. And that's entirely right because you know, you're, you know, but hopefully over time you wiggle your way towards a, up into the right trajectory in terms of progress. Everyone wants that, but you've also gotta somehow keep this team together and you gotta keep 'em working together and you want it to be enjoyable. And I think a lot of, a lot of experienced managers really, uh, especially in the deep tech industries broadly, I think they, I think my observation would be that they've struggled with that, especially within r and d departments, especially within engineering. They've struggled to create that culture where people are happy to come in, they feel free to do their best work. They're the kind of environments where people wanna stay, um, so that they're not having that regular turnover.'cause once you get that regular staff turnover, man, it is so hard to get that knowledge sharing back. So, you know, you've, you need these really unusual people who have that emotional intelligence and are able to translate that into behavior and create the kind of environment where engineers are gonna feel happy working and doing great work.

Seb Weidt:

Yeah. You, you've made it, I, I, I wholeheartedly agree with everything you've just said that's, this is an interview on, I think

Chris Reichhe:

that's, I keep on kind of talking my way through this and just, you know, I really get it. I really get that approach. It's just, it is not common. We don't see that approach very often. And I think, you know, remember as well that the one we, we need. We have a very interdisciplinary team. Right. It it, it's not just about building a, a great electronics engineering team or a great software team. It, it's, they all, you know, need to work together. We we're covering the full breadth of what you, you'd find in tech. I think in, in one team, they speak a different language, right? Yeah. And then how do you, how do you deal with that? Um, how do you make sure that that doesn't cause all sorts of. Um, conflict. How do you, and to your point on, you know, how long people stay around, what, what's your, what does your churn look like? This is a long-term journey that we're on, right? Yeah. That this is, we, we don't have six months sprint to get a product out. It it, it doesn't work that way. So how, how do you, you know, look after that retention parts, um, and how do you keep people motivated?'cause there's sort of failure and even the things that work just take so much longer than what many of the engineers who come from, you know, the, the, and the average of this wide, you know, it's a bit faster to see the output of their, the, the labor. And I think that these are always, it's faster where you are. It's, or it's faster where they are. It's faster where they are. I mean, you know, if, if you, if you have this audacious goal, sure, you know, it, it takes some time to get there and it, it takes a while to, to iterate through the different generations of chronic abuse. So it, it's, you know. It's a bit different to I've got a next generation phone coming out or whatever someone may have been been working on. Yeah. And that, that just requires it, it means if, if you already think about it, it's therefore our, our job to look after them even more. Right. Yeah. It, it's because it's not easy for them at all. So there's that extra, um, I think ask on us to, to make extra sure that they're well looked after. Yeah. Is there a case for varying the management style at, at times, let me, let me, um, maybe there are certain types of individuals who perform well. When the pressure's really on and there's a bit more fear injected into the proceedings, you get that extra, it's not. It's not advisable for the long term, you're not gonna get very far in the long term. If people are constantly running on adrenaline, that burns 'em out and eventually it'll, you know, they'll burn out and kick over. But if I think about what, let's say Elon Musk has done, I mean, he runs through management teams like no one's business. He's, you know, he is not. Um, and, uh, you know, I admire what he's done with SpaceX and, and, uh, and, and partly with Tesla as well. Uh, so he, you know, the, those teams have achieved results, but it comes at a, at, at a price. Is there, is there ever, is there ever a point at which varying the management style to eke out that extra 10 to 15%, if it's even that, that might result in a, in a, in a critical milestone, is ever worth it? So my, my view on that, and I've, I've thought about this and I think the, the Elon Musk example is, um, is a really interesting one that, that I have wondered about. I think. There's lots of different management styles that, that give you success, but I think that the question is how you define success, right? You, you can go by output and, and clearly SpaceX has been, has been very successful. Yeah. The human cost to it. I, I, I do wonder about, um, and I think at some point it becomes some, what I personally, and everyone has their own style. I can, I can kind of sign off and, and, and you're comfortable with, and, and that's maybe not something I would be that comfortable with. But actually the where my core belief comes in, because also as a leader of a company, you have responsibility to shareholders and so on. Mm-hmm. You know? Yep. To, to do the right thing there is that. If you look after people really well, there are always points in time where, look, it's all hands on deck. Like we, we've got to get this thing done right now. But you don't go through fear. You go through people caring about each other, caring about the company wanting to come to be successful, and they will go the extra mile. So they, they don't need the stick of being like, you get fired. If you don't do that by next week, they will just do it because they want to do it. And that's, yeah. Yeah. Yeah. I think the, you don't have to convince them, get them moving fast.

Seb Weidt:

Exactly. You don't have to spend the

Chris Reichhe:

energy on, on, you know, on, on. Riling them up on scaring them. It's already there. They're ready to do it. Exactly. No, I would agree that there will be people who would maybe take advantage of that. Yeah. And you know, be like, oh, but this is just so comfortable and No, I just won't do that. And it again comes back to the hiring and making sure that you make the right decisions at that point where you know, you know it, you look after them and they will come through for you. No doubt about that. You may not even have to ask them because they know. Yeah. Yeah, they know and they will do the extra mile. Yeah. Yeah, yeah, yeah. I get that. Let's, um, let me change tack a little bit. The, the, the journey you're on is, is a long journey. That's not unusual for lab to market companies, especially in the, you know, and there aren't many that are bolder than them. Quantum, um, the commercialization pathway or the root. Uh, and you know, there are different companies that are equally as moonshot oriented. Nuclear fusion is one. Uh, we had a guest recently, uh, from the nuclear fusion industry and talking about the challenges of putting together a commercialization program. When you still don't have reactors, you still don't have this new form of energy generation and with quantum computers. I'm curious as to how that works as well. How do you continue to build the enthusiasm amongst the investor base and amongst, you know, what kind of commercial activity can take place? When you're still trying to get to, as you say, to a million qubits where actually, you know, and, and as I understand it, it's a million qubits where you can start to enjoy some of the benefits of quantum, of real quantum computing. A million to 20 million is broadly the kind of sweet spot. Um, how do you guys handle that? How do you think about that? Yeah, so I, I mean, for, for us personally, um, as an, as a, as universal quantum, we, we try to be, I think honesty is really important. You, you need to give people the, the upside and, and the vision, um mm-hmm. And, and be optimistic. Uh, we certain the timescales involved, but you don't want to go too far, you don't wanna get too hype on, on that. Um, so I think honesty is, is really important. There again, it acts as a, as a filter in, in getting the right investors on board and so on. Um. That was a difficult part for us at the beginning, um, because the, there were a lot of promises made in the field early on. It's like, Hey, two, three years, small number of qubits will actually, you know, change the world already. This will be amazing. Um, and we start to, again, it's painful at the, the beginning for sure nowadays, where that realization of, oh man, we do really need to scale because these promises haven't, haven't stood up to, to, to what we thought would happen. Um, it's making us our life a little bit easier because we, we don't have to change our messaging. We, we, we are just who we are and we, we've always communicated in that way. But I think the, this is also, you know, one of the challenges as a, as a founder and an an academic founder is finding that line between, you know, really strong hype and being like, look, this will happen to two years. Just, just believe me so I can get my next round done where I can get the new customer in and let's deal with the ramifications of that later to, I'm just gonna be really honest and maybe even a bit too pessimistic as an academic. In how fast we can go. Finding that line is, is, is a moral conundrum I sometimes find, um, and, and not an easy one. Mm-hmm. Uh, because you know what investors would love to hear, really? Mm-hmm. Um, but you have to be honest as well. So I think we've taken a, um, you know, we're, we're very optimistic. Um, we're very ambitious, but we're being very clear where the journey needs to go. Um, yeah. Now I do actually, we, we, you know, nowadays we understand that yes, we need to get to millions of qubits, but there's, there's some lower hanging fruits along that journey that, that we start to deliver some interesting impacts. So we can, we can tell a nicer story, always a slightly more short term story, but it's, it's just convincing people, make people, people realize it's not all about the low hanging fruits. You've got to think long term. You've gotta think two millions of qubits, because that's where the really big applications are. And this is why I mentioned governments initially as well. Who, you know, if you have to think about protecting your, your economic prosperity, um, having access to this sort of technology in the future, you can't be distracted by low hanging fruit. It, it's a nice to have. Yeah. But you, you've gotta have something that goes all the way. Yes. And, and that's where we gravitate much more towards that then maybe some shorter term thinking in, in some companies where they just want a POC for two years and, and, and move on and say, yeah, we've done quantum. Yeah. Um, so I, I think you've gotta be careful with your messaging, but it is our job to, to dream for them a little bit. Yeah. And this is where, you know, I, I, I, in terms of saying, look, these, these are the things that may be possible. Let's dream a little bit very comfortable with mm-hmm. Timescales where people really over promise is, I think counter counterproductive for the sector. And unfortunately it's, it's very common in the sector at the moment. It's for sure an issue in my, in my opinion. Yeah. Yeah. You're right. I think, uh, I think a lot of that hype and there's a lot of hyperbole around deep tech and, uh, we start to pay the price for it when these things don't deliver and then it impacts everyone. And, uh, and so it's this kind of self perpetuating, uh, cycle of, of, uh, of bs. And so we need, there's a sense that we need leaders, and you're certainly following this, but we need leaders of these, of these young companies, uh, to have some responsibility when it comes to messaging and, and the setting of expectations, um, that we will realize a lot of benefit from this, but this is gonna be a long journey and we have to be patient. And, you know, it's difficult if you're an inve, you know, it's difficult if you occupy a role anywhere along that value chain. If you're an entrepreneur, it's difficult if you're an investor hoping to realize a, you know, a return in five years, 10 years, whatever. That's difficult, especially in deep tech. If you're a policymaker, it's difficult if you're a corporate exec looking to benefit from innovation and partner with young startup, it's di so it's all difficult. Uh, and when it gets difficult, we tend to want to move a little faster and cut corners and hope for the best and close our eyes and stick our hands in our ears and hope it's gonna be okay. And it really is. And so we, we need to, you know, we need to exercise that control a little bit and say, calm and be patient and we'll get there. But it's, you know, these are long journeys, you know, these are really hard things we're trying to do. Um, agreed. Absolutely. The, um, the, tell me a little bit about your approach to kind of building your team. You've, you mentioned you've got quite a multidisciplinary team. There are some approaches in deep tech when it comes to building out the team and it comes to scaling where I've heard people, uh, you know, some companies think, look, we're gonna keep it nice and small for as long as we can. I. And we're gonna learn as much as we can. And we're only gonna hire when we accomplish certain milestones, and we're gonna learn our lessons and we're gonna build on those lessons. But we want to be really conservative with, uh, with our capital. So, uh, we're really responsible with the money we raise. And then I've heard lots of others where, no, we need more brains on this. We need more hands on this. We just need to scale much faster and we're gonna, and we're gonna fail faster and we're gonna learn our lessons faster and hopefully we're able to keep our momentum going and keep the investment coming in. Where do you guys sit, uh, in that, you know, on that question, it most certainly, initially it was a, a bit of both. Breadth was really important to us at the beginning. Um, 'cause we wanted to make sure that we, that we didn't, we didn't miss something across the whole stack. Um, you know, coming off academia, being very physics focused, quantum focused, you know, there, there were huge areas of what was honest that, that we were not experts in. And we were just so keen to, to get eyes on that and be like, look, you know, are we thinking about this in the right way? How should we structure that? Um, so it was actually about focusing more on, on senior hires in the different areas. And I'm a strong believer anyway to, um, you know, get, get their heads in first and then they can structure the team the way they would like to do it, rather than hiring junior and then putting a head on and being like, good luck. Have fun with what I saw. Yeah, yeah, yeah, yeah, yeah. Maybe wanna have. So it was actually going that way first and, and hiring people who were yes, senior, but very happy to get their hands dirty. That was always really important to me because you can get manager types who, you know, great brains, but they're just used to managing, but they can't go down and get their hands dirty. So if you want bread, but you don't have the money towards the higher big teams, you've gotta find the people who can, who can go deep. Um, yep. So there was a strong focus on that initially. Nowadays it's, it's. You know, getting the, the number of people in particular areas of, of focus in as quickly as possible to, to scale is, is becoming more of a, yeah. More of a thing. But initially it was, it was that spread step that we were Yeah. But relying on people being able to perform as ics, as individual contributors. And also in terms of building the trust amongst that early eng, especially with engineers. Uh, if you want to build trust with the engineers, then the engineering leader better be able to engineer him or herself. Right. It better be able to get their hands dirty and kind of get stuck, get fully stuck in and not just sit there on the sidelines managing. Right. And it, it, it made a lot of sense to, you know, when thinking that through, it just made doubly sense because I always felt like the, um, and we, we have a strong push to, to incur, encourage growth and, and promotion, um, internally to turn ICS into managers and so on. Mm-hmm. But I've got this strong belief that the people who. Who resist me the most are actually the best, the best managers and the other people who don't really wanna be, uh, necessarily a manager who don't strive particularly just for that are actually really good managers. So it, it's therefore looking for people who, you know, would, would look at me with a smile when I said, lookie, you're not gonna manage a team at the beginning. I, I, I need some, some I, I see, uh, you know, skills here. Yeah. That, that was a natural fit to again, that they might be, that the right people to, to bring, to bring on Yeah, for sure. Yeah, yeah, yeah, yeah, yeah. The people who were, so what you're saying is the people who were initially reluctant to manage, who are actually some of the people who wound up being the best managers. And that doesn't surprise me. I think so. Uh, that doesn't surprise me, but, uh, from the sound of it, in the early days, you went a little bit because of the breadth that you were trying to deal with. And given the nature of the build out the, of, of your plan, which is to build full stack. Then, um, except at the application later, later on, you know, then, you know, then to partner up. But the nature of your buildup meant that you had to be broader, and so you needed people from different domain areas, different disciplines. Yeah, that's right. Um, and, uh, okay, that makes, um, that makes sense. Um, supply chain with, uh, a field like quantum when you're building a quantum computer. Talk a little bit about suppliers. Do you know, do all of the technologies and materials that you guys require, do they currently exist? Um, or are you waiting for stuff to be developed as well that's going to be critical for the performance of these ultimate computers? Yeah, for, I, I loved you asking this question. So, so for us, this universal quantum, the answer is a resounding yes. Um, and I think that it, it's been part of that early work to get our architecture into a. Shape where, where we can say yes to that. And I think not just for what we need today, but for what we need at the million qubit scale, that that is the absolute critical thing. I think the, the, it's often I feel like underrepresented in the, in the community people say, oh, you know, I'm making my chips in the standard Foundry, and so on, but that's maybe today, but not really talking openly about, well, what does that look like at the Marion Ubid scale? What do you really need at that scale? Because they may not think of it in that way. They may have different aims as a, as a business. For us it was just all about the Marion Cupid scale and work backwards from, from there and making sure that, that the key technologies do exist. We don't have to invent new materials or completely new processes and the, the semiconductor paths and so on. Um, to be able to leverage as much as possible of what's out there. Now, that doesn't mean that everything is easy, what we're doing, everything is hard, what we're doing. Um, and sometimes, you know, suppliers need to. Um, you know, they obviously have a roadmap and it it's about aligning yourself with their roadmap. Yeah. And, um, you know, not being a burden to them and being like, look, can you please do something completely different to what you would really like to do? It? It's all about that. And aligning yourself with, with those sort of, um, suppliers and, and roadmaps, that was really important to us. Um, so a lot of energy goes into it because we don't actually, we don't make our own chips. We, it's all in the supply chain. We're integrate it in many ways. That's how you can think of it. Yeah. Yeah, yeah, yeah. Can you give us a sense, uh, Seb of, of roughly where you are in your journey? Um, yeah, so high level, the, um, we are basically at a point where we have demonstrated, um, all the key fundamental building blocks of a, of a million Cuba device from a, um, you know, from a. Gate perspective. Um, one of the key things in, in scaling is modularity. Um, can you connect individual modules together in a quantum way? Again, some people don't like talking about we, we've developed an error-free way of connecting, um, modules together in, in a, in a quantum way, which was pretty thought is, is a impossible. Um, we're doing all that integration work, the chip level integration work, uh, for our modules, um, at the moment. And, you know, soon we'll have some, some really cool announcements on, on that as well. So we're starting to move into the, the, the sort of scaling phase where we can really start to, um, you know, scale these systems up, which is, which is really important. Yeah. But that requires a, a. A different approach. We, you won't find our machines in the cloud right now, but that, that's not been our focus. Yeah. You can, you can go to some great people who, who will allow you to do that. It's actually getting the, the engineering, the architecture into place on which we can then scale and get to these low hanging foods initially as quickly as possible. Yes. And ultimately all the way to, to the million qubit scale. I get it. I get it. And when do you think, two more questions. What, when do you think we're gonna have a quantum computer, a million qubit scale, quantum computer, a million qubit scale chronical be done? I'm, I'm almost in two minds if, if, if I should really answer that question because if I answer it, it, it would be, it would already be wrong. Because if, if one is completely honest, I couldn't nail it down to the, the, the month or maybe even exactly the Yeah. Um, sure. With sufficient confidence right now. Yeah. I think. The, um, you know, from a roadmap perspective, what's nowadays I think, you know, from an investor point of view is, is becoming interesting, is why, is that these sort of things start to fit into a fund life cycle. And I think that Okay, that is a, is a really interesting change in, for us at least. Um, yeah, from our roadmap perspective. So five to 10 years, yeah. Maybe closer to the upper end of that, but, um, you know, familiar. Yeah. Yeah. That's sort of timeline one starts thinking about. Yep. And what do you think the first problems are gonna, where will we see quantum computing apply? Sorry, let me rephrase that. What problems, what will be some of the first problems we solve with quantum computing? I think some of the low hanging fruits you, you find in the optimization space. Um, so, you know, that can be around supply chain optimization. Um mm-hmm. So optimization in general has some, some lower hanging fruits. I think then we get mm-hmm. More into some of the simulation space, maybe around drug discovery chemistry in particular stuff to, to understand materials more, more complex, um, materials and, um, and, and chemical reactions and so on. And then you keep going further up towards drop design, uh, synthetic testing all the way to the end of code breaking CFD simulations, which, you know, have some of the, the, the more, um, tougher requirements on the, the hardware. Yes, yes. I wonder about the increased defense spending that we're gonna see now in Europe and the uk and given the geopolitical landscape. Uh, increased defense spending historically has led to additional innovation in science and technology. And I do wonder if that's going to focus mines particularly in quantum, given the benefits that quantum can potentially usher in within defense. It's a really interesting area at the moment. I think what I, what I really like about that, that defense focus is that when you map out the applications of, of quantum computing for, for defense, they on average come with, with the, the higher ask. So really pushing to, to very large number of Cupids. Um, and I think that is maybe disappointing on the short term for, for defense, but actually really helpful because like you said, it focuses the mind on Yeah, really trying to take that technology all the way and not getting so distracted with, oh, what can I do with a hunted cubits or a thousand cubits, which certainly for defense is, is is somewhat irrelevant, right? Yeah, yeah, yeah. But then they can be, they can help too. They can help to calm the behavior of certain nervy other investors by saying they, yeah, we're not stopping. Or they step in like DARPA has done in the past and they say, sorry, but we're gonna continue to fund this. And uh, I think they can, they can step in, they can step in. And they're also used to longer development cycles and, and technology taking some time. If you think about how long a, a weapon system takes from initial idea to actually being out in the field, these are really long timescales e even compared to quantum computing in in many cases if you look at the submarine program. Right, exactly. It's so, there's far more accustomed to, to the timescales we're about. Exactly. Exactly. Seb, I could keep on talking. Thank you so much. This has been, we've, we've covered a lot of ground, um, and uh, and it's been wonderful to have you on the show, so thank you so much for giving me and us your time today. Thanks so much, Chris. Really enjoyed it. This is great. You've been listening to the Lab to Market Leadership Podcast, brought to you by Deep Tech Leaders. This podcast has been produced by bowhouse. You can find out more about us on LinkedIn, Spotify, apple, or wherever you get your podcasts.

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Chris Reichhelm

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