Jennifer Winstel: Welcome to the Purpose Unlock podcast. We are your hosts. I'm Jennifer Winstel, and.
Leslie Kincheloe: I'm Leslie Kincheloe.
Jennifer Winstel: We're with the Winstel Kincheloe team in Charlotte, North Carolina. You can reach us at Jennifer Winstel at UBS. We are financial advisors with UBS, one of the largest wealth managers in the world.
Leslie Kincheloe: We are so excited to have meaningful conversations with a variety of guests. We'll be exploring their passions in business, entrepreneurship and philanthropy.
Jennifer Winstel: Our mission is to bring purpose to life beyond the numbers.
Leslie Kincheloe: Welcome back to the Purpose Unlocked podcast. We are really excited to kick off the New Year with Pablos Holman. Pablos recently wrote a book called Deep Future and it is a fascinating read. Pablo's I have heard you described as an inventor, as a technology futurist, a venture capitalist, a hacker.
Leslie Kincheloe: You have worked at Blue Origin, building spaceships with Jeff Bezos at Intellectual Ventures, using predictive models to help cure infectious disease, and with some of the most well-known names in Silicon Valley. We are really happy to have you. Thank you for taking the time today.
Pablos Holman: Yeah. My pleasure.
Leslie Kincheloe: We enjoy sharing our guests background and purpose. So would you tell us a little bit about your background and your purpose for what you do?
Pablos Holman: Yeah, sure. I think the easiest way to think about it is I started out with one of the first computers you could have at home. Um, when I was like ten and I grew up in Alaska, so nobody around me had ever seen a computer before. And I was trying to, you know, figure out what to do with this thing kind of the hard way, um, in isolation. And, and it really lit up my imagination because I, I could see how someday it would be faster and have more memory, and it would be useful for people. And that's what really got me excited, was putting computers to use Um. Uh. Nobody believe me. It seemed like this crazy thing. In fact, I have, like, letters sent home from school saying, hey, you need to keep this kid from wasting time on this computer thing. He needs to do, you know, his shorthand class or something. Um, so, anyway, uh, that's how I got started. But I learned a lot about computers because I was, you know, um, had to learn by reverse engineering everything. And that turned out to be a the first kind of technology I really felt like was a real superpower. You know, I felt like I could do things other people couldn't do with it, and I wanted to share that. And so my early career was in taking computers into new industries and putting them in lots of places they'd never been before, and advancing computer technology up through the in the 90s, we were, you know, building the internet. And then I started working on cryptocurrency in the 90s and then, uh, AI in the late 90s. And, and then the real big inflection point for me was when we started Blue Origin, uh, I kind of switched from, from advancing computers to using computers to advance other kinds of technology. And that's what I've been doing since then, is what we call deep tech. And that's really about trying to bring technologies to life that can help help to solve big problems and help go after big challenges and big industries and things that that you can't solve with just software alone. And so these days, I run a venture capital fund where I invest in all kinds of mad scientists, and they're working on things from, you know, shipping to mining and construction and manufacturing and, you know, semiconductors and just all and in energy. You know, the things that every human on earth relies on. And so that to me, that's what technology is about. And what, you know, a deep tech in particular is about. So that's what I work on.
Jennifer Winstel: That's great. Paula's, um, I think it would be helpful for our listeners to just get a, a conversation going on. What is artificial intelligence? I mean, everybody talks about it now. It's become part of our daily conversation with clients and neighbors, friends. But I think what is, you know. Can you describe how you think artificial intelligence starts to affect our daily living? I mean, perhaps it already has. And we think through the levels of integration, whether that be layering intelligence or application. You know, I know you can dive really deep into this, but just for our listeners, how would you describe AI today and how it's changing the way we live our lives?
Pablos Holman: Well, in spite of what I've just said. Um, the computers still are
Pablos Holman: the most powerful tool we have in our kind of in our toolbox. Mhm. And, you know, I think it's important to think of these things as tools because we're going to build the future with whatever tools we have. And so the better the tools are the better future we can build. And so what's really exciting about what we call AI is it's this fairly recent inflection point where we've been able to get the computers to do a whole class of things that they really weren't good at before. So the way to think about that is, up until now, what computers were good at is following a very linear set of instructions. You know, you could explain to the computer in code, not in English, but in, you know, esoteric computer languages. If this happens, do that. And that's what programmers have been doing for our entire lifetime is trying to codify processes into that, you know, logical set of sequential steps. What happened with AI is we figured out that if we throw enough computation at a big pile of data, the computer can kind of figure out what to do on its own. And so these the way I think about it is that is these are models and we call them the AI that everybody's chatting with is a large language model. So it's a model of all the, all the, everything humans have ever said or written. But there are other kinds of models. You know, you mentioned earlier we were working on infectious disease, and we created computational models of the developing world. And those models didn't have, you know, children's books in them and blog posts. What they had was climate and rainfall and travel of data and all the things that can affect the spread of a disease. And once you have a model like that in a computer, then you can run simulations. And so we would run simulations on different ways of trying to intervene in the transmission of tuberculosis or malaria or HIV, the things that are taking millions of lives a year still. And when you can run simulations like that in the computer, then it can help you find the best strategy. It can help you find the best approach to attacking a problem. In that case, you know, trying to trying to eliminate a disease. And and that's what's possible. So that's what's really exciting about AI right now is that fundamentally, this is a tool for humans that helps us to make better decisions. And that's, you know, in a world where the decisions involve lots of complexity and more data than any person could get their head around. and and so that's, that's what is going on with AI. And then we can talk about, you know, how that plays out for people. But that's where it starts.
Jennifer Winstel: Okay. Okay. So in your book, I mean you talk about being motivated to solve problems. So what do you think are the biggest challenges that come from AI. And what are the the biggest potential investment opportunities?
Pablos Holman: Well, every time you get a new technology, there's a kind of life cycle it has to go through and you have to build a relationship with it. So, you know, we're probably in like junior high with social media still very right, very immature. Right. We're not even in preschool with AI. But, you know, we're in retirement with hammers and fire and other things that really can kill you. So we've learned and it's not that it's not that, you know, fire is any less dangerous now than it was thousands of years ago. But we've learned as a society how to handle that, and that's a maturation process that you have to go through. And and we're at the beginning of doing that with the eye. So I think one of the biggest challenges is really how do you build a mature relationship with these technologies? Learn to get them doing things that you find valuable and that you think are important, and less of the things that you don't find valuable and don't think are important. And so that's that's really how people should be thinking about these tools. I know everybody gets a lot of crazy stories in their head, but we're just in the early days and like computers, it's going to take us some time to figure out how to put them to good use. So that's that's how I would think about it. And then, you know, what are the opportunities? Well, you know, the first order opportunity is if you look at, you know, what happened when we made PCs and we had to put software in every business. Then we had to redo it for the internet in the early 2000. Then we had to redo it for mobile in 2008, and then now we and we had to redo it for SaaS, and now we have to redo it for AI. But what that just means is now we have a better toolkit to go build the systems that we rely on, and that could be in every business. So if you're in a business and you understand what that business is about and what the problems are and what would be needed and what's important and useful and all that kind of stuff, then you're the person who's in a good position to figure out, how do we use these this new toolkit, these new capabilities to reinvent our business? Because if you don't, your competitors will. And that's what we call disruption. And that's what we've seen in lots of lots of cycles with new technology.
Leslie Kincheloe: You talk about in your book publishers, um, how AI can essentially create new industries, industries that don't even exist today. Um, what do you what do you see? Like, where do you see it going in terms of creating new ideas and not just improving existing ones?
Pablos Holman: Well, I think that a lot of new technologies, uh, new inventions, you could think of them as incremental. And you see that a lot. You know, Toyota gets a little better every year. And if you compare your new Toyota to one from 20 years ago, it's a lot better. But there was never a year where Toyota's got a lot better. Um, and if you work at Toyota, your job is to figure out how to make it a little bit better. Um, but you're not going to figure out what comes next. What comes after a Toyota. You're not going to figure out, you know, Cybertruck or whatever, right? Um, whatever the next generation technology is. And so a lot of times what's happening is the people who are good at figuring out the next generation technology are isolated. They're not in the industry, you know, they're not part of the machinery. They don't. They're there, you know, in a garage with crazy hair and a Delorean. They don't have a way to, like, bring that to the world. And so, you know, so those are the kinds of technologies that might make something ten times better or 100 times better. And so we want to be on the lookout for those. And we want to look at the opportunities we have to reinvent old industries. That's that's the first thing you could make new industries. And you can see how a great example of that right now that people are really trying to do is with robotics, trying to make humanoid robots that can go, you know, operate your dishwasher and fold your clothes and, you know, walk the dog. And even if it's a robot dog, I don't know, go pick up your kids after school. Um, so, you know, those are that's an industry that doesn't exist right now, but that a lot of investment is going into making, because we can see that we have a lot of the puzzle pieces to make that possible. And there's going to be a lot of, you know, fits and starts and different ideas and approaches and, you know, a lot of hilarious fail videos on TikTok of robots, you know, that, you know, folded their laundry backwards or whatever. But, um, but this is, you know, this is a temporary condition. We've kind of gone through that with self-driving cars in the, in the last decade. You know, there was a lot of hype cars that sort of drove themselves but were a little scary. And now these things are dramatically safer than any human driver, and they're going everywhere. And so that's a way of, you know, you could say it's a new industry because new things are possible with those cars that weren't before. Like, you know, like having a, you know, these Waymo type services and things like that. So So that's making things better. And you know, it takes a while to make those transitions. But you have to start with a technology that gives you a force multiplier, that gives you the ability to really make a big difference instead of just a little incremental difference.
Jennifer Winstel: Paavo, how do you feel AI will take the place of humans in terms of jobs? Do you think we adapt and change our careers as a result, or are you just stated? I mean, there may be new industries and new opportunities that AI creates. And further, how do you see AI impacting wealth management as a career and how does it impact clients that we work with?
Pablos Holman: Well, let's let's start with, you know, this is a really hot topic because the easiest thing to imagine is that, you know, the humanoid robot I just described shows up at work, does your job, and we don't need you anymore. Um, it's very easy to imagine jobs that are replaced by machines or that computers can do and or the AI could do and that and that those you're going to lose your job and there's certainly risk of that. And that does happen. And you really want to make sure to be compassionate with people who are in that spot or who are suffering or who have invested a lot in their career, and then find that, you know, it's not what they thought they were going to do. This has happened a lot over all of human history. You know, if you look at one interesting way to think about this is if you look at a chart of population growth in the world, it's crazy. The history of humans is like just thousands, hundreds of thousands, millions for like hundreds of thousands of years. And really, it was only the last 200 years when we went from a few million people to billions and billions of people. And that's it's the most hockey stick shaped, you know, chart you'll ever see. But another way to think about that is that we made like 8 billion jobs in the last 200 years, which is a crazy thing to think about. But, um, but we've done that. You know, we made all these people who never existed before, and now they don't all have jobs. But, you know, unemployment rates are not in the 99%. They're in the few percent in most places. And, um, and so, you know, I think we can make a few more jobs. And when you look at the history of new technologies, every single time that we invent a new technology and bring it into the world, it ends up creating a lot more economic prosperity. And it creates a lot more jobs, because now there's something that people can do that's useful and much more useful than when they didn't have that technology. And so we're again in the early stages with AI. So it is hard to say exactly how it's going to play out. But right now, what's happening? By and large, and what we've been observing is most of what's happening with AI is it's making people a lot more capable at the job they already have. It's being used as a tool. So now instead of wasting a bunch of time filing TPS reports, the AI is doing that for them and then they can do the valuable part of their job. And so we're kind of, um, in this, you know, tug of war between people's emotions and feelings about how this could go and what's actually likely to happen. And I'm for one, very excited because it does mean new jobs. You know, if you think about a lot of the menial, dangerous, repetitive jobs that are out there, one of the poster children for this is, uh, truck drivers, you know, for a decade, more than a decade now, every year, you see headlines about how self-driving trucks are going to put truck drivers out of business. And I started watching this about 15 years ago. And there's still no self-driving trucks in America. Not on highways. Free flying. Um, we're trying to get there, but that doesn't exist the day it does exist. You know, we have to make 100,000 trucks. Um, that's going to take a little while. And the truth is, in the time that I've been watching this, we went from about 50,000 open truck driver positions in America to over 100,000 open truck driver positions. And I don't know anybody who's trying to get their kid to become a truck driver. It's not a job that people want to do. They're not thriving in that. And if you want to drive a truck, great, you can probably finish out your career. We're going to have plenty of truck driving to do, but but over time, what should happen is we should replace those jobs with, um, you know, with a machine or with a self-driving truck that can do a better job. Does it fall asleep and drives all night and those things? And at the same time, I think, you know, if you look at the other side of this, there's things that we say we care about that we say are important to us. Um, that that we aren't doing. So, for example, my kid was in public school. In elementary school, every year there'd be 30 kids and one teacher. And we go complain about the student teacher ratio. And on a good year, you get it down to like 28 to 1. Well, I would have taken a displaced truck driver and a 1 to 1 student teacher ratio any time, right? Her teacher is real good, but I would say a much more important thing would be to have less kids so that you can actually pay attention to one of them and help them out. Any of us could do that, but we don't do it. And so people are too busy watching Netflix season 14 again to go instead of just going and teaching something. If you just you don't have to be a very good teacher if you only have one student, you know. So I think there's things like this that people want to blame technology for, instead of taking responsibility for themselves and aiming our time and our attention and resources that that things we say we care about. So that's kind of what I'm excited about, is we're at a point now. We're okay. We're gonna have plenty of time to watch Netflix and go teach a kid, because you're not going to have to drive a truck anymore or whatever the other, you know, useless thing that you're doing in your job right now. So that's just a framework that I think is a good start. And then you could say for something like wealth managers. What are they actually doing? Well, a huge part of what they're doing is very personal. It's about taking care of people. It's about finding out what their hopes and dreams are, what they you know, their situation is, what their family situation looks like, where do they want to go with it? And then crafting a strategy that not only is good for them, feels good to them. Um, change maybe changes over time, you know, and using your knowledge and experience to map a very human set of, you know, interests and desires to a very, you know, a lot of times, people's nest egg, you know, what you're managing their their future for them. So I think, what if you're a wealth manager, why wouldn't you want a computer to help you do a better job of the technical part of that so that you can be free to do the part that a human is good at, that only a human can do well. Right. And so in a lot of jobs, I think that's really how you should think about it and how how they will go.
Leslie Kincheloe: I think this was really interesting. In your book, you talked a lot about the different sources of power. You know, whether it's solar and wind or nuclear. And clearly all of this AI and computation is going to need more power. Um, and we, you know, we're focused at UBS on that as an investment theme. You know, power and resources as we think about data centers and growing populations. And can you talk a little bit about and you talked about this in your book, but the need for maybe nuclear energy or thinking about nuclear energy in different ways.
Pablos Holman: Well, nuclear reactors are
Pablos Holman: the safest and cleanest form of energy we've ever discovered. It should also be the cheapest form of energy. We've sort of screwed that up in a couple of ways, but a lot of what happened is, you know, when we were kids, the world just conflated nuclear reactors with nuclear bombs.
Leslie Kincheloe: Yeah, right.
Pablos Holman: We outlawed the wrong one. And and if you had done it the other way around, we never would have heard of global warming. You know, we're living on the wrong fork in history. We should we? The plan in the 60s was to build a thousand nuclear reactors. In fact, Kennedy ran on a platform of building that was his number one issue as the Democratic Party's number one thing was build a thousand nuclear reactors, and then it all went off the rails. And and so instead, we're burning lots of coal and gas. We have tried to improve the situation with solar, which has helped to a degree. But, um, nobody's been able to solve the relentless onslaught of nighttime that is screwing with our solar panels, and so we have not been honest with ourselves about what the demand for energy, the scale that we need it and the and what is going to work. And so, um, I think I like to look at this from a global perspective. You know, if you look around the world, um, most people on average, the way I wrote about this in the book is they get about as much energy as one toaster, and that's if you add up all their heating and cooling and travel and cooking and everything combined. Americans get about nine toasters, so we get almost ten times as much energy as the average person on Earth. And for averages like that, you have to have 3 billion people living on less than one toaster. So global energy demand is actually about ten x current global energy production. That's the truth. And nobody ever talks about that. And so what we really need to be able to do is produce enough energy to take care of all these people that we made, right? And we haven't been doing that. So. Um, so what's cool about nuclear reactors is that if you were to power yourself off a nuclear reactor for your entire lifetime, you would generate about one coffee cup worth of waste.
Leslie Kincheloe: Wow.
Pablos Holman: That's how. That's how much energy is in uranium. Instead, it's going to be hundreds of railcars of coal and gas that are burned just to keep you going. And so people don't know these things. They don't understand that. But one really exciting thing that has happened is in the last year, everything changed. The US government, which had no way of approving any new reactor technology, has been completely overhauled. The Nuclear Regulatory Commission is now aggressively helping get nuclear reactors approved and built. The Department of Energy is aggressively helping get them approved and built, and we've been trying to help. We invested in one that I think is the best one I've ever seen called Deep Fission. It's a very simple nuclear reactor, but it gets buried in a borehole a mile deep underground, and this reactor is unquestionably safe. It's literally a mile from anyone's backyard. No, there's nothing that can go wrong. But if it did, there'd never be any radioactivity at the surface. And these reactors are really easy to build, and the Department of Energy is pushing us to get the first ones deployed by July. So we'll have actual reactors in the ground, uh, in July that are, that are running. And this is so exciting. The company has a backorder for 844 reactors.
Leslie Kincheloe: Wow.
Pablos Holman: And so once that gets going, we'll build thousands of them in a Gigafactory, deploy them around the world. And that's even the, the current the current um, wait list for reactors is enough to create all the energy that OpenAI wants and all the energy that their competitors want. So we're really going to be able to make a big difference in the world by providing some real leadership on how to produce energy and hopefully get the rest of the world up to our living standard. Or at least, you know, at least the living standard of a European, let's say.
Leslie Kincheloe: Yeah, well, that's a lot better than building power plants all over the world, right? And a lot faster.
Pablos Holman: These reactors are amazing. Yeah. The the the deep fission reactor goes underground. It takes up almost no real estate.
Leslie Kincheloe: Yeah.
Pablos Holman: It's crazy. Yeah.
Jennifer Winstel: So, Pablo, what's next for you? Are you going to write another book? Are you going to continue to podcast? What's what's your future look like?
Pablos Holman: Well, what I'm trying to do is help out at the very beginning. Usually when an inventor is ready to get out of a lab and into a startup. So we we try to find more of these folks who have real breakthroughs. And sometimes, you know, they can be miraculous. And we try to help get them onto a track where the technology can be commercialized. And so I'm trying to find more of them and, and see if we can be helpful. Can't do all of them, but we can do a lot. And then, um, uh, you know, the podcast, my podcast, I is my way of just picking the brains, really smart people and learning as much as I can. And I share some of that on the podcast, the Deep Future podcast. So that's a good one. Now we'll keep doing that. I love doing that. I don't know if I'll write more books. I said what I wanted to say in this book, it's really about, um, you know, the problems in the world, some of the technologies that can help solve them and how we can invest in them, how we can bring them to life. And, um, and so that's really it's a fun book, but it's really about, you know, giving people a sense of what's possible. Because we have the best tool kit ever. We have the most advanced technologies, we have the most people, the most education, the most money of all of human history. And that's what we're going to use to build our future. And so if we can't figure that out, then, then there's no excuse.
Jennifer Winstel: Right, right. The future is bright and exciting. So we are so grateful for you to join us for this podcast. UBS is publishing a lot on artificial intelligence and its influence, specifically looking to 2026 and what are the investment opportunities that AI is going to to yield. So we appreciate your comments. We will share information about the purchase of your book on our website.
Pablos Holman: And great.
Jennifer Winstel: Thank you. We greatly appreciate your wisdom today. Thank you.
Leslie Kincheloe: Thank you Pablo.
Pablos Holman: My pleasure.