 We'll love it. Mark, it's an absolute pleasure to have you here today. Thanks for coming all the way from SF to Helsinki. It's been great, yeah. We've been given a rather wide topic to discuss today, which is how to build the next big thing and predict what is the next big thing. So since we only have 25 minutes, I would suggest that we focus more on the how to build the next big thing part and a bit less in the predicting what it is. How does that sound to you? That sounds good. Predictions, they're too hard, and somebody always comes back and says, you totally blew that. Right. So before we dive deeper into the topic, I'd like to ask you something else, though. During the last few days, me and you have been visiting quite many teams here in Helsinki, both domestic and teams from abroad. But I'm especially curious about the teams that you have met here and the Finnish teams. What do you think of them? What's the state of the Finnish tech based on what you've seen so far? Yeah, so I had the opportunity of visiting VTT, as you know, before Slush. And that was amazing, because it's everything from quantum computing to synthetic biology and all kinds of crazy stuff in between. That was super inspiring. I didn't know, frankly, I didn't know Finland was doing that kind of stuff. And this is ignorance from being in Silicon Valley where all things are supposed to be there. And then now that I've been at Slush, I'm just blown away by this whole operation. I mean, from every aspect of it, the teams that I've met here are doing everything from vertical wind turbines that can survive in harsh, cold, frozen environments, which seems like a great place to be testing it, is here, to carbon markets, carbon sequestration, recycling of electronics in marketplaces. I mean, it's fascinating, excellent, all really well done, well thought out, I will say it, it's a little, but very Silicon Valley caliber, which is super impressive. Happy to hear that, but folks out there don't get too confident, keep working hard. Look, I do have tons of questions to ask, really we could talk for hours, but I try to pick the most relevant and the best ones. So to kick off, when you look at those teams, both the ones that have been meeting here and those that have got to meet during the recent years, do you think that the founders of, and the scientists are really looking at the right things, looking at the right problems and even, or do they even look at, I mean, try to identify those or are they just going after something and hope to end up in building something such as Tesla? Yeah, well, I mean, that's one of the purposes of an entrepreneur or one of the key focuses is to figure out how to take a technology that exists and sometimes the technology gets created first and then you're looking for the problems that it has to solve. And sometimes you're creating the technology to solve a specific problem, but it really is about the entrepreneur finding that right product market fit, finding exactly the thing that is solving the problem for the customer. And the customer may not really even perceive it as a big problem, but once they see it, they go, oh my gosh, this is making my life so much better. So we see a lot of companies, both in certainly Silicon Valley, where they have a really neat technology. They've come up with something really clever technically, but they don't know what it's gonna solve and those are difficult. And that's the role of the entrepreneur is to figure out how to take that technology and make it into something that actually has meaning for people and has real value. Right, so it's no secret to anyone what a success Tesla has really been. It's been two decades now since you guys went to find Tesla. Did you back reflect them to back then? Did you really think that you are at a big problem right now or was this like some sort of coincidence? Well, we were pretty sure that we were gonna have to electrify transportation. I mean, that's a big problem. You know, it was really, really clear that oil was not a good thing for the world. I had lived in Saudi Arabia for years. I had seen what the oil economy was doing there and how much wealth and power was being transferred to the Middle East and not necessarily stewarded well there, as well as obviously the carbon thing, which in 2003 was much less clear. The global warming, if you were a scientist, it was becoming clear. If you were kind of not in that community, it was much less clear. But we were getting there in 2003. So decarbonizing transportation, and when you talk about transportation, it's really about cars, because that's where most of it comes from. So we had to do something about that. And we realized that the technology was just barely possible. You know, our background, Martin and I, my co-founder, have a background in consumer electronics, and we saw that batteries getting better every year. A little bit better, and when you do the equations, and you actually work out the math, and you say, can you make a compelling car that's electric with these batteries, because batteries are what limits it, that the batteries were just barely good enough in 2003. So it was perfect, because we knew that, oh, God, if we could do it now, by the time we get into production, it's going to be even better. And by the time we get big, it's going to be really great. And we're just going to have better margins, better performance. Everything is going to be better in the future if we can make it work now. Let's dive a bit deeper now in the building part. I think not many of us can really imagine the endless amount of trade-offs you guys have had to really make in order to get the first car out there and work. Can you describe a bit the path? How does the path look like to get from lab to fab and building something to really last, and something great such as Tesla? Yeah, I mean, there are so many trade-offs along the way, particularly with something as complicated as a car. One thing that we did early on is we did have a North Star. We were talking about this backstage a little bit. A North Star in the US is the star that you navigate by. So when a company has a North Star, they have some statement which keeps everyone alive. And so Tesla's North Star would have been building an electric car that delights the customer. And 20 years ago, there had never been an electric car that delighted anybody, except maybe a golfer someplace. I mean, it was like a disaster. So to make one that delighted the customer, that was always our North Star. To do that, we figured out all the pieces of that puzzle to do that, but each one of those technical challenges had trade-offs. Whether it was we had to make the car a certain width because our manufacturing partner, their machines could only grab cars of a certain width. And we really wanted it to be wider, but we couldn't do that because their machines, their manufacturing machines couldn't grab it all the way to whether we had to redo the chassis to make it easier to get in and out for customers. And that was, it was a million dollar decision we made. That was a huge trade-off. It was a delay in production. It was a very expensive decision, but we didn't think we could delight the customer if they had to fall into the car. This was not going to work. So we had to redesign part of it to make it easier to get in and out of. Because the original Tesla was a small roadster. The best we could do at the time. Right, because the industry has been there for quite a long time already when you guys started to work on it on the first car. How did you balance between quick and dirty and perfectionism? So everything's a compromise, right? And the most important thing is getting a product out into the marketplace and getting that feedback back from the customer. Now for something like a car, there are things you can't compromise on. Safety being the obvious one, right? Safety, we've made certain compromises on performance in order to make it happen in time, but you have to get the product out because you just don't know how your customers are going to use your product. And whether that's on a website or a physical object, we were really, really pushing to get the production as quickly as we could because we wanted that feedback. We even, when we had prototypes, because we only had 10 of them as a drive, we would send them on a sleep away program, is what we called it. So any employee could check out one of the cars and take it home, but the deal is that they had to take it home and drive it around and park it in their garage and plug it in and then they could come back the next morning and they had to report on everything that didn't work the way they expected. And ideally, we'd have different employees each time who had never gotten to really experience the car because we wanted to have that sort of feedback at a time before we could actually sell a car to somebody and ask them, by the time you sell it, it's kind of too late. So we were always tweaking things, trying to make it more perfect, if you will, but we weren't going to wait, we weren't going to not ship cars once they were safe and certified because we felt the interior paint wasn't right or something, we really, really had to get them out. And there was, of course, economic reasons for that as well, but you just got to have that customer feedback. Right, the time seems to be flying. I try to be faster with my questions. I'll make my answers shorter. No, don't worry about that. I'm going to be jumping a bit from a thing to another, please bear with me, but so moving forward to, came to my mind, this one interview with Jeff Bezos and he was describing the strategy, they emanate strategy and their approach in acquisitions and he was saying that how Amazon really looks into, every time they purchase a company, they look whether it is run by missionaries or mercenaries. So my question really here is that... Which one does he like? Well, good question. The mercenary one or the missionary? Okay, that's good. But you can ask him as I guess, you know he better than I do. Oh yeah. But founders often operate with certain assumptions and my question really here is that, what's the balance between clear mission and some sort of bias coupled with optimism and curiosity? Well, so, you know, we sparrow the bunch of firm that I'm with, we really focus on mission-driven founders and it's a cliche, right, you know, mission-driven, but we really are looking for people who really believe in their product. Whatever that product is, you know, they really like it, they want it to be out in the world, they want to have other people experience that because we think that that's really how you build strong companies. The mercenary thing doesn't really appeal to us or appeal to us either. The importance of that mission is that you get to, it really keeps the company culture around it, it allows you to recruit easier because people like to come to a thing where they feel that they're contributing to something that has meaning. It makes the fundraising I think easier as well. The customers, it's a great brand play and the customers, you know, sense the mission. So you're like, we're really, really into mission. I'm not sure I answered your question but I don't, you're going to spend all of your time on a startup. Startups are really hard. You're going to be working and working and working at the startup to do a startup that you don't really care about it in some sense and you only want it to have a high acquisition value. It just seems hard to believe that anyone would do that. Right, but you do do, I guess, some sort of forecasting as a founder. I mean, you might under forecaster over forecaster. Up and to the right, it's always up and to the right. Right, of course, how else? But should you as a founder do some sort of, you know, like forecasting where the industry is going, where, you know, all of my chances and where we might be as a company and as a team in the near future? Yeah, so, you know, forecasting is extremely hard, particularly if it's a product that hasn't, you're not competing with other products that are kind of very similar. You know, so the market matrix are not, the market matrix are not very visible. You know, as a founder pitching, you want to make sure that the investors believe that there's a big market for it. Right. But it has to be realistic and any decent investor will do their own forecasting as well. You know, they'll do a sort of bottoms up thing of, you know, how big is this market? And if you say you're going to be selling $10 billion of the product and the grounds up thing says that, you know, the whole market's only a billion dollars. I mean, that is not providing trust for you. However, some founders are really conservative and they really want to keep their numbers really, really small so that they can, you know, beat them potentially and investors have to think that out as well because you don't know which is the founder making the numbers really, really high or is the founder, you know, sort of sandbagging the numbers or doesn't think they can get it. So we always do our own grounds up as a founder what you want to do in my opinion is come up with something realistic as best you can and you want to be looking at what the market is doing. Like we knew that batteries were going to get cheaper and better because they had over 50 years. You know, we had a lot of data to support that and we had some idea of how many cars we could sell. You know, which we were basically production limited it turned out the whole time because the demand was good for that but, you know, forecasting is important. It's difficult. That whole figuring out the future thing super hard. No, of course. But it's kind of like close to forecasting but let's move just a bit to risk taking from forecasting. When I look at those teams that I've been meeting with lately and I mean those very early stage startups or just teams like team of scientists and stuff it seems to me that, and maybe this is a bit tough but it seems to me that perhaps the biggest risk they have taken is jumping into the cold water and becoming an entrepreneur. And what I basically have expected is that you would see that to be the first risk but not the biggest one. Do you think this is the case that startup entrepreneurs already at the early stage stop taking big risks and would you advise them to actually bet more things? Well, if they bet on things that win they want to be doing that a lot. Yeah, that's the problem. What you don't want to do, you've taken the big risk of being an entrepreneur and you're working on your mission, you're working on your product and everything and you want to get that out and get the feedback. If you're taking a big risk on that is that you're coming out with a new product offering? Well, that could be really good. So what you don't want to do is sort of bet the company on a particular product where you don't have any feedback yet. And when you do take risks or at least technical risks in the case that I was most involved with, when we took technical risks we kind of made sure that we had a backup plan. We really wanted to work out this way but if we can't, well, we can still do it in molded carbon fiber or whatever or not molded carbon fiber. We can still handle the carbon fiber if we really, really needed to. But we wanted to do something different that was more efficient or cheaper or whatever, or stronger, whatever the issue was. So there's always risks. What I find interesting is how big companies that have unlimited resources and can absorb lots of losses almost never take any risk at all. And that's the thing that allows entrepreneurs to take them on and crush them potentially. Right, I think we have to move forward with some other questions I have here in mind. So I'm going to jump a bit quite far from the topic we were discussing earlier. But I got to meet with the chief advisor to the NASA's boss back in 2018. I remember him saying something very fascinating and I just picked up the quote here, pretty much a direct quote and he said that back then that in order for people to come up with new things they need to be able to do whatever they want meaning innovate freely because this is how people invent and everyone is needed to complete the big picture. So what is it we needed to build a great company such as Tesla, keeping this comment in mind? Yeah, well NASA, it's funny that you picked NASA because they are historically in the US, the NASA's the space agency and they did a really great job in the 50s and 60s and then they stopped taking any risk at all and allowed Elon, our investor now CEO of Tesla to ultimately completely disrupt the rocket industry if you will because they didn't take any risks and they were way too conservative. So, and I do find it interesting that he says oh, you want the engineers to just do whatever they want. I don't know if you saw the opening keynote by I'm blanking on her name from Swipe, from... No, I can't remember. Oh, I can't remember. Whatever. Yeah, anyway. And she was incredibly good at making things happen but I'm not sure that you could be very creative when you're doing that, you know? And Clara, thank you. And you want to have everything kind of on tight ropes when you're executing. Now, within the team they're creating and being innovative but you really want to keep things rolling along. You can't have them just doing random things, you know? You got to have those goals and you got to have those objectives and keep everything in lockstep because you have this giant team, you have the puzzles really complicated. You got to get all the pieces of the puzzle to come together to make that product. You know, there's a saying in the car industry or in manufacturing that it takes 5,000 parts to make the car but only one part to not make the car. Like everything's got to come together to make that final object. So you got to be careful with being sort of too creative along the way because if anything slips, everything slips. Right, but do you think that the future companies are going to be a bit more like kind of like NASA-minded companies? They still need to produce stuff on time. Right. Yeah, you know, but you can do that and be quite creative. I think Tesla does that fairly well, SpaceX certainly does. Lots of companies do, Apple does it very, very well. Right, and do you have any practical example in mind? How would you advise founders to balance between freedom and mission? Well, freedom should always be in service of the mission. I mean, having that North Star, having that mission that's very clearly articulated is great because it allows you to get rid of distractions that don't advance the mission. You know, at Tesla we got many opportunities to do things for other companies for millions and millions of dollars at a time when we didn't have much money. But we were able to always look at the mission and look at our North Star of, you know, does this advance getting a car on the market that's an electric car that delights the customer? Is this directly helping us or not? And if it wasn't, we had to say no, which kept us very focused. So, you know, but along the way, we're innovating on all kinds of different things, whether it's battery architecture or the inverters that make the car go, for example. And we're redesigning those things because it's always in the service of the mission, right? So you can be very creative that way, but it's always about, you know, how are we going to delight the customer? How are we going to make the car better? How are we going to get, you know, the thing to market and get that feedback? Right. Let's move from the how to be the next big thing to the predicting the next big thing part. Well, with time there seemed to be, there always seemed to be some sort of waves of about tech. And as you all know, there seemed to be a quite a relatively long AI summer in terms of hype. What do you think is AI here to stay? So, yeah, AI is here. I mean, I don't know what the next big thing really is, because if I could predict that really easily, you know, we would just put all of our money in that and, you know, we'd be done for the day. AI has the feel of something that is like the internet was, and like, frankly, electricity was, you know, 100 years ago, that it is super interesting. People can imagine lots of uses for it. And there's lots of hype around it, but nobody knows exactly what it's going to do. And like the internet before, you know, it ended up being in everything ultimately, but it itself, you know, was only the enabling of an entire ecosystem living on top of it. And I think that AI is that same thing and that, you know, 10 years from now, AI is going to be in everything. But, you know, who gets the value for that? Where the money is, if you will, in AI, to me is very unclear yet. And so, you know, we'll see. I think it's incredible, though. I mean, I think we're really at the very beginning of AI. And again, like a lot of things, it's just going to get better and better and better, and we're going to be able to use it for more and more things. And some of those things are going to be amazing, whether it's new materials or new plants or, you know, food or whatever. Right. As we are running out of time, this is my, pretty much, my very final question. Yeah, I agree. It's quite unfair to ask anyone what's really the next big thing as we can't just live only with one sector, right? Whereas we need food, industry, we need the transportation and the healthcare and energy and the other. But if you were to find a company today, what would that be? What would it be? And why? Yeah, I think it's, I think some of the most exciting stuff is in synthetic biology. CRISPR and its ilk are making us the ability to change life itself, which is like, sounds very grand, but we've been doing it for a long time. So I would do a synthetic biology company focused probably on new agricultural products that are focused on delighting the customer. So they'd be very nutritious, wonderfully tasting, and they happen to grow really well in a changing climate. Right. Well, thanks Mark. I think you made building Tesla look easy. So thanks for inspiring everyone here and thanks for coming all the way from us once again. This was fun and pleasure. Yeah, great fun. Thank you. Thank you.