Investing for the AI Shift: Masters in Business with Songyee Yoon

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That's Bloomberg This Weekend. Saturdays and Sundays starting at 7am Eastern. Make us part of your weekend routine on Bloomberg Television, radio, and wherever you get your podcasts. Bloomberg Audio Studios. Podcasts. Radio. News. This is Masters in Business with Barry Ritholtz on Bloomberg Radio. On the latest Masters in Business podcast, my conversation with Sung Yi Yoon, she is founder and managing partner at Principal Ventures, an AI-focused venture capital investment firm. She has a fascinating, fascinating background. All sorts of MIT Corporation advisory board, 50 women to watch in business from the Wall Street Journal, named to the advisory board for the Center for Asia-Pacific Policy, as well as the National Academy of Engineering of Korea. She has a fascinating background in gaming, telecom, and AI. I found this conversation to be fascinating. And I think you will also, with no further ado, my discussion with Principal Ventures, Sung Yi Yoon. That is quite a CV I went through. Let's roll back, though, to where it all began. You get a bachelor's in science from Korea's Advanced Institute of Science and Technology, and then a PhD in computational neuroscience from MIT. That's such a fascinating area. What was the original career plan? That's a very good question. I mean, I think growing up in South Korea, I didn't know what are the career options that I had. I just really enjoyed learning science and engineering subject. So when I was young, I realized for some people, singing is very natural. Some people dancing is natural. I cannot sing. I cannot dance. But speaking to computers and programming was very natural to me. So I started programming when I was nine, and that led me to major in electrical engineering as an undergrad at Keist. And along the way, I realized I just wanted to become a better engineer because I was a student as an engineering student. To be a better engineer, you need to understand how a human brain works. So for example, I was studying signal processing algorithm, and those signal processing algorithms are looked best to your eyes when it's not necessarily mathematically the best, but take into consideration what frequency is most sensitive to human eyes. So understanding human brain and human perception will enable you to become a better engineer. So I was kind of exploring what would be the subject or kind of the major that I can pursue to have a better good understanding both engineering and human brain and perception. That led me to study computational neuroscience at MIT. So computational neuroscience isn't so much about using computers to understand people as opposed to understanding neuroscience to create better software, better interfaces, better human interaction with technology. Is that fair? That's right. Yeah, that's right. So pretty fascinating. Early in your career, you're at McKinsey for a few years, and then you eventually move into SK Telecom. Tell us your focus at both places. Yeah. So I mean, I think after my PhD, I wanted to go into the, instead of staying in academia, I wanted to go into the business world, and going to McKinsey was the kind of best way to transition from being a PhD student to go into the real world. So it was a really fascinating experience for me, very fast-paced, able to work with big conglomerates and the leaders of the businesses and in the areas of strategy and corporate finance, et cetera. And SK was one of the firm's clients, and I don't want to date myself. It was a time that everyone was rushing into 3G rollout, if you remember. Oh, sure. It was an interesting transition, just like we see today, because in 2G, telecommunication is all about voice communication. In 3G, what was promised was data transmission, including videos and images and high fidelity audios. If I'm remembering correctly, it was voice and text, and then it was image and some video, and then eventually, what was it, 4G or 5G was full internet? Right, right, yeah, that's right. So as telcos are one of the big capex investors in making that transition, and we're thinking about how we can do the content delivery in the most personalized content delivery was one of the challenges that requires artificial intelligence and like a data-driven delivery system. So I thought that was an interesting challenge to take on, so I moved to SK Telecom to lead that effort. And then you end up at NCSoft, where you're president and chief strategy officer. I'm curious what those experiences taught you, not just about corporate governance and culture, but just these big institutions that tend to have legacy technology. There tends to be some group that really wants to move forward rapidly and adapt all the latest, greatest tech. And then another group that, hey, this is expensive, what's the ROI on this? How did you find yourself navigating a big telecom like SK or a smaller, more nimble gaming company like NCSoft? Yeah, I mean, that's a really great question. I think it's learned to be persistent and resilient and patient. In both places, I was criticized for like suggesting something that was not the norm at the time. So for example, when I was at NCSoft, one of the things that I, it was very obvious to me was it was full of data in gaming, the businesses and like all offered in a digitalized form. You have transaction data, you have a behavior data of the gamers and everything. So it was possible to do a lot of things in a data-driven way, which is very kind of, not today, it's a lot of the companies are doing it, but back then it was not very common to have understanding in both gaming business and as well as AI and kind of data-driven business process modeling. So when I suggested things like, oh, like it's, let's do a small thing like like a charm prediction of, because you can, you can see the customer player behavior within the game and see how much they're engaged and you can predict if that player is about to turn out or continue with a, with a game and some kind of interventions could help them stay engaged with the game. So that was a one application areas that I, I didn't, I identified which could be very straightforward. But then I was told like there was a strong pushback from the developers and even the business people, they said, oh, you're saying it because you don't understand a gaming business. You're, you're, you're saying you're a kind of, you're not a heavy gamer enough or whatever. But, but you understand, hey, it costs us this much to acquire a client or a gamer. And if we see this behavior, a high percentage of those folks are tapping out, what can we do to keep them in and paying monthly fees? Right, right. Yeah, exactly. So, I think the very clear data and the case presented, it was not an easy task to have get everyone's buy-in. But I think it gradually just, the reason I kind of mentioned that tangible example was a small, very tangible area that we can apply to technology. And once you show the success, I think there is a gradually one by one, we're able to adopt, integrate that into our business process to end up having a large AI lab that does like all of those things in a, in a more centralized way. So what I'm hearing from you is a very systems-oriented framework, both for gaming and telecom. Right. I know the big mobile companies in the U.S. are constantly fighting their own churn rate. So having a top-down systems approach sounds like you could be really proactive in terms of maintaining clients. You would think there's buy-in from everybody, but it sounds like there's a little salesmanship involved to get everybody behind that, that approach. Right, yeah, right, yeah. So, let's talk a little bit about what's going on in the world of AI. I've heard you discuss various things that are just short-term hype. How do you figure out when you're evaluating an AI system, either for an investment or just to use the technology in a company, how do you figure out what's valuable and what's just hype? What are you looking at? I mean, I think we talk a lot about hype cycle and going to bubble being built up in this, in this kind of AI era. But I think it's not unheard of. In every platform shift, there was overcapacity built, not just in AI infrastructure, but it happened with Internet, like fiber optics, you remember? Railroad, telegram, wherever you go. So there is always a kind of excess capacity that's built, and I think that's when people are pointing to is that area, that there is some kind of bubble built up. On the other hand, if you talk about application of the technology, if you find the application and real business problems that you can apply this technology to solve to be more efficient or bring out some insights that humans were not able to do it, and I think there is a great area to apply the technology. I think there are so many of them out there, so that's why we are so excited about the development of technology and the prospect of it going forward. So I've heard you discuss various priorities, whether it's a corporate entity pursuing upgrading their AI infrastructure or just totally AI native startup, you talk about durability, defensibility, real world impact, explain what those three things mean. So in making that adoption of the technology, there are two ways to think about it. One is adopting the technology without really changing the current work process. So you can, for example, there are a lot of talk about co-pilot or augmenting what we do, make it faster, like a search, and if those things are not necessarily changing our current established workflow, but you are fully embracing what the technology can do to make you more productive and efficient. So that's one way of applying it, and I think there will be some amount of the ROI that will be realized from such approaches. And the other is completely design of the workflow. And I think that's kind of, we are very early stage of witnessing that, but I think that will be a more interesting area to look out for and could be more tremendous transformation and value created from such effort. So tell us what you did at NCSOF because a lot of the work you put in there was about transforming them to use AI. Was it, hey, we're just going to make all our developers and gamers and everybody else a little more efficient, a little more productive, or did this require a clean sheet rethink of everything that the company was doing? Yeah, I mean, I think it was 15 years ago, and I think it's back then. I think technology was not ready to fully redesign the game development workflow, but I think back then it was more of augmenting the existing process. So for example, we did things like the marketing and term prediction more efficiently. We had NLP that's designed for gamer, specialized for gamer language. We had an augmenting animation tool that helps animators to animate not just bipedal creatures, but four-legged monsters in a way that's as efficient as you're doing bipedal creatures, etc. So I think it's more focused on augmenting existing process back then, but I think technology has advanced and matured today that I think there are more opportunities to kind of completely redesign and come up with a new type of AI-native companies. So I see an AI-native entertainment firms, they're rethinking about what do you mean by new type of entertainment, new type of engagement that's different from polishing and making higher fidelity graphics in games, but a completely new form of entertainment using fully embracing the technology that we have today. So I keep reading that Claude is writing its own code and updating his own code. If you were at a gaming shop today, I'm assuming do you replace coders? Do you have co-pilot work with coders? There was a Wall Street Journal article last week. I think it was Wall Street Journal that could have been wired about coders in Silicon Valley or just kind of sitting around watching Claude rewrite their code. What is going on in the world of software development now that Claude is capable of updating itself? Yeah, I think it's really fascinating. I think a lot of the coding is done using tools like Claude and it certainly makes it more efficient and productive, which means that we need people in the loop to do the job. In certain areas, such as reviewing, like detecting errors, and just kind of, I think there are certain areas that AI coders can do better, but there are other areas that that needs more kind of heavy hand, like more involvement of like a kind of redesigning that the schema and then the structure and how things are going to work and how it kind of is going to be implemented in providing then the kind of engaging experience for gamers. So my bias is that the humans are very creative and very innovative. And I'm thinking in the sort of storylines we see on all the streaming shows and some of the interesting novel gaming, I don't even know what to call it. I guess it's a narrative storyline. Is that what people are going to focus on and just the blocking and tackling, just the daily grind of putting code into place we're going to let AI use? Is that a today thing or is that a next, you know, is that going to change over the next couple of decades or years? I think that's a really good question. I think if you look at today, I mean, I think a lot of the jobs like YouTubers, like podcasts, these are the type of jobs that didn't exist 10 years ago. I don't know what other jobs are going to be created in the world where like the things that needed like 100 people attention can be done with like a fraction of those people. There could be other type of jobs, other type of roles, but I think that's a evolution that we'll have to see how it roll out and kind of predicting exactly what type of jobs will going to exist in 10 years from now. Really, really interesting. Coming up, we continue our conversation with Song Yi Yun, a managing partner at Principal Ventures, discussing AI and the modern economy. I'm Barry Rithaltz. You're listening to Masters in Business on Bloomberg Radio. Let's talk bonds for a minute. Capturing value in fixed income is not easy. Bond markets are massive and murky. Lots of firms throw a couple of flashy funds your way and call it a day. Vanguard takes a different approach. The Vanguard lineup includes over 80 bond funds actively managed by a 200-person global squad of sector specialists, analysts, and traders. Lots of firms love to highlight their star portfolio managers like it's all about that one brilliant mind that makes the magic happen. Vanguard's philosophy is different. They believe the best active strategy shouldn't be one person. It should be shared across the team. So if you're looking to offer your clients funds that are built to deliver consistent results, go see the record for yourself at vanguard.com.io. That's vanguard.com.io. All investing is subject to risk Vanguard Marketing Corporation distributor. April 29th and 30th, Bloomberg House arrives in Miami at the Formula One Grand Prix. Set against one of the world's most electrifying sporting events, Bloomberg House brings business, investment, and culture together. Powered by Bloomberg Journalism, real-time data, and forward-looking conversations. From on-stage discussions to exclusive networking with global leaders, this is where ideas connect. I'm Barry Rithaltz. You're listening to Masters in Business on Bloomberg Radio. My extra special guest today is Sang-Yee Yoon. She is the founder and managing partner at Principal Venture Partners, an AI-focused venture capital firm. Previously, she was president and chief strategy officer at gaming company NC Soft. So before we start talking about AI in more depth, I just have to mention your book Push Play Gaming for a Better World. I love the concept that, hey, let's not forget about play. It's really significant in terms of innovation and just being an engine of change. Tell us a little bit about what motivated Push Play. Right. I think it's, as you just mentioned, I think we have a tendency of not appreciating the role of the play in our everyday life. My motto is we don't leave to work. We live to play. We live to explore. When you have extra time, are you going to do one more line of work or are you going to play? Play is our natural tendency. Home allude as opposed to being a homo sapiens. I think play is very important. I think it's not only about, we're not only talking about computer games, but in general, I think play has played a very significant role in human evolution. Whenever there is a new artifact that was introduced in our culture, we start with the playing with it. We create, we figure out how to make a play out of it, how to create something out of it. When we have a good understanding of the material and utility in it, then you turn that into utility. I think gaming has been playing that role very diligently over the last couple of decades. For example, if you look at some type of technology that has been, when it was fully tested and baked out, gaming has been always the platform that was brave enough to incorporate in our offering and have our players try out. For example, we had a VP of AI since the early 2000s. AI technology has been not mature enough to apply to applications like driverless cars 20 years ago, but it was okay in gaming because gaming is a very low risk environment. At the same time, gamers are inherently early adopters. They want to try out new technology. I think it's a combination of those things make it possible and almost inevitable for gaming companies to try new technologies. Not just the AI, but like Kubernetes discussions or like a cloud or even free-to-play, freemium business models all tried out in gaming first before they were adopted in other businesses. Let me throw you a little bit of a curveball about gaming. When I was growing up, play was totally unstructured. You go down to the schoolyard, the computer games like Pong and Space Invaders, very rudimentary. Now it seems kids, their lives are much more scheduled, their play is more structured. How does that affect the sort of experience you want to provide from a gaming company? That's a very good question. I think there are many aspects to your question. One is about what is a gaming for today. I think the reason why there's so much opportunity to play game as a novelty is because computer happens to be the most sophisticated advanced device that we have today. I think we're still trying to figure out what is its limitations and what it can do in all with the kind of experience it can provide. I think there are a lot of online digital games out there and the kind of the size of the catalog makes kids and who are trying to go through what kind of play options are there end up choosing a game or two from that. So they have agency, they can select what they want to do with the online. If you think of a game, gaming is not just one thing. There are sandbox games, there are building games, there are a lot of games, there are story based games. There are different types of games that you can choose from. Depending on your preference and what you find the most engagement, you can choose different games. So let's stay with kids, with children and in particular students. There's been a lot of concern about the impact of AI on education, on learning, on training, people to get jobs in the real world. As a quote of yours, I was kind of intrigued with, rather than competing with AI, students should be prepared to leverage uniquely human capabilities. Explain what that means in terms of the real world. I think it's an, if you think about education, our education has been over the last couple of hundred years. It has been optimized for delivering knowledge. I think we are witnessing that the knowledge delivery and memorization is rapidly being commoditized. Is that what students have to spend all their time sitting in a classroom to kind of polish? I think it's what our next generation needs is more of the creativity and the problem-solving skills. And we have to think about, if we can redesign the classroom to really enhance those skills instead of helping them acquire more knowledge. So there's a very different set of targets acquiring skills or just learning things or memorizing things. I'm a big fan of teaching children how to problem-solve. When you say skills, let's think of that from an institutional level. How should schools be using AI to teach children new skills, developing an expertise, developing problem-solving? What's the proper role of AI for educational institutions? I mean, I think what I would like to say is that we have to educate and prepare our students to thrive in the world where AI is going to be more prevalent. But the solution to that is not just AI. It's many different kind of, it could be redesigning the curriculum. It could be redesigning the kind of school system, the kind of thinking about how we evaluate their achievement and how we retrain our teachers. AI could be a tool for doing that, but it's not the solution for everything. So I think there is a huge difference there. All right, so let's bring this now out to the world of the economy and business. Probably the biggest narrative I've been following about AI outside of it's a bubble or we're all going to lose our jobs. And I kind of ignore both of those extremes is that successful companies have wide moats and we're starting to see AI compress those moats over time. Think about industries like lawyers, tax preparers, accountants. There's a lot of stuff AI can do in a fraction of the time and with a greater accuracy level. Everybody knows about reading x-rays and MRIs. So if we know our moats are going to get compressed, how should companies be using AI either to protect and expand those moats or somehow use AI to expand their competitive advantages while they last? I mean, I think that's very interesting because I think there are some of the industries and professions that will become much more productive and probably need a lot less profession to solve certain well-defined problems. But that doesn't mean that humanity as a society is left with no problem to solve. I think we have so many other problems to solve that AI cannot address. For example, I think there are very old problems of the politics is how we are going to redistribute the resources. What is our societal priority in enhancing the agency of everyone and helping them to achieve their full potential? I think those are the things that we don't have a good solution for. While AI can take care of some of the things of a well-defined workforce, providing that expertise to make it more efficient way, we'll have time to work on other problems to progress humanity forward. And I think that we have prepared to accept new type of roles and new type of professions that will exist and enabled by this technology advancement. So I think we're all in agreement. It's going to be a very disruptive technology. Am I hearing you say essentially, hey, it's up to everybody to learn how to use these tools and adapt, but the change is coming. You have to be prepared. Yes, right. Exactly. So you've operated at the intersection of artificial intelligence, gaming, telecommunication and social platforms. That's a great conversion of a lot of different technologies. How is that evolving and how are both consumers and institutions really adapting to that sort of AI driven economy? I mean, I think it's a lot of people recognize that this is one of the greatest platform shift in our lifetime. And there is a lot of excitement. And as many people say, I mean, the camp of seeing it as a kind of we are at the very early inning of how it kind of how it's going to fully pan out. We don't even know what's going to what is coming in in the next three to five years. I'm really excited to see all this kind of the use case and application of technology fully using based on the creativity of this AI native generation. And I think the people who think with AI as part of their tool and at their fingertip will come up with different ideas and kind of apply their creativity. And I think that that's what I'm really excited about. So you founded Chameleon as a corporate venture arm and now you run a fully independent early stage venture funds. I'm curious, what are the differences between being part of a corporate venture fund or an independent? What are the strengths and blind spots that you end up with in each? I think we work with the strategic investors LP. Then I think there is a certain I think the objective is a different depending on what kind of as a GP we work for our LPs and the kind of who is providing the capital and like what is objective with the firm. And I think it's those are very different. So at the PVP, I think we focus more on a type of investors would like to be at the forefront of the innovation and then capture the value being created. I mean, regardless of the kind of the area, it doesn't have to be confined in like entertainment and consumer space. We were able to kind of look more broadly. So corporate is pure strategic and independent is strictly ROI. So let's talk about some of the companies you've backed together.ai, Cartesia, Sesame. These all seem to be pretty core infrastructure plays. Tell us a little bit about those. What was it about each of those that made them so appealing? I mean, I think it's a it's a really tricky time to make an investment because I mean, as we say, I think there is a lot of excitement about this technology. There is a kind of the rushing mentality. So I tried to invest in companies that that's going to be durable in the coming decades. So I really like companies that are building infrastructure technology that has multi-purpose as this platform and technology evolves. So I think together and together and Cartesia are both of them have great founders have have a vision of building infrastructure and foundational technology that's going to be used in many different AI platform companies that are going to be building. And I think Sesame was interesting case because it's building the voice applications that I know from my gaming experiences, kind of importance of it and importance of focusing on certain features that that will provide certain experiences to to the users. And I think the founders got what was important. And I think their their capabilities and talent was singularly focused on making that technology push. So I really like what they were doing. And that's one of the reasons and one of the reasons I ended up investing in Sesame as a company. But I think there are other type of companies as well that we're excited about in this very in this kind of like standing on this kind of shifting grounds. And I think those are the companies who are in a position of building this data flywheel because one of the non-deniable characteristics of the companies that will be durable in this environment are the ones who have appropriate access to data, the data understanding customers and consumers and the business and build a technology unique technology on top of that. So we also are investing companies are building this data flywheel that over time building very defensible mode. Really, really interesting. Coming up, we continue our conversation with Song Yi Yun, co-founder and managing partner at Principal Ventures, discussing the state of venture investing into artificial intelligence today. I'm Barry Rithalds, your listening to Masters in Business on Bloomberg Radio. My extra special guest today is Song Yi Yun. She is the founder and managing partner at Principal Ventured Partners, an AI focused VC. So that's a fascinating phrase. You don't really hear a lot of that. I'm Barry Rithalds, your listening to Masters in Business on Bloomberg Radio. My extra special guest today is Song Yi Yun. So that's a fascinating phrase. You don't really hear a lot of that up until recently. What is the key problem Principal Ventured Partners is trying to solve in the world of AI today? So we started to back AI native companies. And I think when we started when we first talked about AI native companies, that was not a very common phrase. People asked me, like, what do you mean by AI native companies? And I had to explain what it meant. And I think it's these days, I think it's a it's more widely used term. And we would like to build, we'd like to back companies who are fully embracing the technology of today and tomorrow. Led by founders who understand the technology and limitations of it and able to come up with org design that reflect the importance of this. So I think that in terms of the size of the department, I think it will be very different from companies built upon last generation technology. TechStack and I think a type of leaders and talents who are going to lead all those departments are going to be different in terms of the use of technology and their vision. And solving the problems that's relevant in the AI native era. Are the companies that are really excited us and then those are the companies that we're focused on investing in. So every time there's a new technology, everybody just kind of sprinkles a little bit on it to catch the little bit of the buzz. We had it with the dot coms. We had it with the metaverse. We had it with crypto. And now everybody is claiming they're an AI company or at least a lot of companies. How do you distinguish between what is truly AI native and what is just let's put a little dash of AI salt on this? That's a good that's a very good question. I think I have unfair advantage by like working in a gaming company. And I think gaming company actually gave me experience in the gaming industry is like having a lens into the future. Right. Because a lot of the technology and innovation happens in gaming first and it gives us kind of sense of like is this type of technology. Adoptable and will the consumers accept this type of application. So like in terms of application and platform, I think that that's that's really an interesting guiding North Star for me. And then in addition to that, I think that companies that are fully native are built around that tech stack. Whereas if you are trying to sprinkling AI, I think you kind of ask a question like can you do the same thing without AI? Like why do you need it? Why is it indispensable? I think there are there are kind of the businesses and business operations that they're using, for example, like agent technology. But like a lot of the applications and you don't need the agent. You just need some kind of good data analytics. So I think it's that there are many ways that we we try to understand how business operating and see their kind of full potential and like their strategy. So so on the one hand, I know AI has been around a long time. There was, you know, one deep blue beat. Kasparov, that was a big deal. And then I forgot what the name of the AI app that ended up winning Jeopardy. These are like 10 and 20 years ago. So it's not a brand new technology. However, it feels like we took another level jump with chat GPT and go down the less Claude notebook, perplexity, whatever. How do you think about this moment in time? Is this similar to early broadband, early smartphones, early cloud use? Like for someone who's a tech investor, they want to know, hey, is it early? Is it late? Is it so early that nine out of 10 of the startups we're going to see are going to go belly up? Like, how do you think about this moment where we are today? That's that's great. Actually, it's older than that. Do you remember like in 60s, there was a application called Eliza? That sounds very familiar. Right. So telephone or Eliza was was like was it a kind of very early incarnation of chatbot? And I think there was even a newspaper headline at the end of psychotherapist because it was doing so well in terms of like rephrasing what we were asking and kind of giving them comfort when you're asking about very personal questions. And they say, oh, we don't need the psychotherapist anymore because it's doing good enough. And I think since then there was a lot of kind of AI winters and summers ups and downs. And I think there's a lot of hype in terms of like comparing where we are in terms of the kind of platform shift. And I think we are I think we're what's surprising to many people about this time and moment is that the the AI shift is closer to the introduction of the railroad than the introduction of the the PC or Internet. Because the biggest breakthrough that that allowed us to come here was actually the scale. So it's not just a new it's not new algorithm. It's not new software kind of new way of doing things. But it was a scale. Let's do it like kind of pouring a lot of resources to make it really big. And that's that that's where we saw the tremendous jump in Trump jump in terms of the capability of AI. So with that, I think that kind of rolling out that that as an infrastructure has been the focus of the last two, three years. And and on this exciting new railroad that's built out, I think there will be interesting new businesses that will emerge out of it. So yes, I think we are very early in terms of kind of fully appreciating what's possible on top of this. So I love the idea of interesting new businesses. And I'm always fascinated with what do the public markets know? You know, it's they're more or less kind of eventually efficient. And very often, though, when a new technology comes along, they very much underestimate where it can go. So what's a sort of use case that the public markets might be underestimating? Where might this go? You look at dozens and dozens of new companies. What what direction is just mind blowing that nobody is really anticipating? So there are I think it's there are a lot of things happening. One is that one one interesting thing about this technology is that while it has been. Kind of it it beat up many people's expectations about what it can do. However, I think there is a lot more innovation is coming along because in terms of this architecture design and fundamental design of the framework, there is a lot more innovation coming along. So we're not done with what is the most efficient railroad design. I think there could be other type of railroad that can come along online that will allow faster and more kind of more comfortable ride experience. And once there is a railroad, I think there is an interesting business that emerged, like, for example, like mail order or like people. It's really hard to make a connection, but that type of new businesses was made possible because railroad was in place. But when I don't think I don't think it was the kind of first thing that came in mind were kind of rolling out the railroad as a kind of across across different states. Well, broadband and fiber optic led to so many different everything from YouTube. Exactly. To really build out of Amazon web services and online retail. Online games. Right. Exactly. I think so. Like, so that's why I'm really excited about a native generations, a creativity, what they're going to build on top of this. So I think there will be new type of business that we don't we don't comprehend today that will be enabled by this infrastructure. So when you're sitting with a founder of a company that's looking for financing, what sort of questions do you ask? What are you trying to figure out about their model, about their direction, about their team? It's so so unique and cutting edge. I mean, I think that they're it depends depending on what they're building. I think it's a set of questions that I ask when they're building more of the infrastructure technology versus kind of business applications are different. But especially when they're building business applications or vertical applications, I always try to ask what is a real value that they're that that is going to bring to. The end users in set. I'm not we are not investing in companies that are building amazing kind of tech demonstrations and the features are trying to find the companies who are built a kind of solving real business real world business problems and do it in a way that's sustainable and more efficient than and using any other type of technology. So you're looking at infrastructure type companies. What other type of AI applications are you looking at? We're looking at the companies that are building vertical applications by developing data kind of live role in data mode. So so there's been a little bit of a lightning rod from a regulatory standpoint. There's all the LLMs have copyright complaints and issues. You sit in a really interesting intersection when when you look at a term sheet today, how do you think about the regulatory risk? The litigation risks? I mean that when LLMs first came out, I didn't for a moment think, oh no, all that was stolen content in there that that they were crawling over and using as their training tools. How do you think about regulatory framework and geopolitics? It seems like there's a lot of novel moving parts. Yeah, I think that's a really great question. And I think that more than ever understanding how the regulatory body things and the policies going to going to evolve over time is important at making just decisions, especially in the venture space. We are making a bet. We're making investment that should last over a decade. Right. So I think it comes from the kind of the belief and understanding that the innovation and the research is really kind of is very precious for all of us as a humanity. And the kind of the this kind of peer reviewed the kind of the tradition of the peer review and the open forum has has really propelled us to where we are today and it's going to continue. And I think the collaboration and openness will better serve our end customers for so the transparency is important. And I think with all of those beliefs, I mean, I think we don't have we don't have the crystal ball to say like what's going to what the policy framework is going to be like, what is the kind of geopolitical tension is going to be like in the next one or two years. But we have the belief that human kind of our collective work will converge in a direction that serves our humanity in a positive direction. And I think that's that's kind of where I'd like to see that that's the ultimately that's going to what's going to be implemented and incorporated and under under that type of the world, whether this companies and founders can test a pressure test to to sustain and I think that's how I see and when I evaluate the companies, I always going to sustain those kind of policy changes. All right. So before we get to our speed round, let me ask you one last question, which is what do you think in investors in the space are either not thinking about or not talking about, but is important. And perhaps they really should be paying attention to. I think that the saying that says we are very at the very early evening means a lot. I hear someone even saying that we are still in the car getting to the stadium. We are not even in the first thing. That means all this kind of the the models models and structures can change significantly can evolve over time and nothing cannot be seen as kind of engraved in a stone. So with that, I think that a lot of the investment decisions has to be reflecting the fact that there it kind of has to remain like a nimble and flexible because we should be able to adjust to when those changes and new breakthroughs come around. All right. So I only have you for a few minutes. So we'll click through these really quickly our speed round starting with who your early mentors who helped to shape your career. I would say I mean, I think I was fortunate enough to have a lot of mentors. When I was a student, but one person that stand out is Dominic Barton who is who was the global managing partner at McKinsey. When I first started out as an associate at McKinsey, he had his office was right next to mine. So he was literally my mentor. And I think I learned a lot from him as a leader and and as a mentor. And and I think it's still today I reach out to him if I have to make a tough decisions. And I think he has been always very generous with his time. So I'm really appreciate it. Let's talk about books. What are some of your favorites? What are you reading right now? Oh, so I read a lot of books. But I think I kind of read many books. I'm over the type that read many books that kind of simultaneously a one chapter here and then I go to jump to another book. But the book they recommend to everyone these days is our two. But one is the Empire of AI. And the other is power and progress. And I think that those books kind of help us understand the dynamics of what's happening and what we need to think about. As a society. So let's talk about streaming. What are you either listening to or watching these days? So I mean, I listen to I listen to music through like Spotify a lot. My son is a big fan of Taylor Swift. I have to listen to Taylor Swift like like when I'm in a car like driving a lot. Also, I watched K drama on Netflix. Really, really interesting. Our final two questions. What sort of advice would you give to a recent college graduate interested in a career in either artificial intelligence, fasting or gaming? I mean, I think kids just graduating today. I mean, I think it's a. One thing that's not going to change is it's going to be very bumpy and it's going to be like disruptive and the world. They're going to be working in is not going to look like the world today. Like that's that's the constant, right? And I mean, I think what I would like to remind them is like, don't try to find the kind of follow the the the trend. Really have to stick to what you are. I mean, it sounds like a cliche, but like what you're passionate about. I mean, you remember in the seventies, the most popular major to go in was was that is a kind of material science. And then the chemical engineering and then like electric engineering and computer science. Like just to see that those those the popularity of those major kind of plummeting. Like we have witnessed it like so many of those cases. So it doesn't really I don't think it serves well to find what to try to kind of follow that that kind of fashion or trend. So be a generalist and be flexible. Could be. Yeah, right. Yeah. All right. And our final question, what do you know about the world of venture investing and artificial intelligence today might have been useful to know 20 years ago? I mean, I think the patience. So I mean, it's also the power of a compounding is not just in finance, but also in like human capital and our understanding technology and and also the relations to like it. It seems very slow today. But like if it you're persistent and for 20 years, I think that what you can achieve is really tremendous. Well, thank you, Sung Yi for being so generous with your time. We have been speaking with Sung Yi Yoon, founder and managing partner at principal venture partners. If you enjoyed this conversation, well, check out any of the 600 plus interviews we've done over the past 12 years. You can find those at iTunes podcast, Spotify, YouTube, Bloomberg, wherever you find your favorite podcasts. I would be remiss if I didn't thank the crack team that helps us put these conversations together. Each week, Alexis Noriega is my video producer, Anna Luke is my podcast producer. Sean Russo is my head of research. I'm Barry Rithaltz. You've been listening to Masters in Business on Bloomberg radio.