The transcript from this week’s MiB: Songyee Yoon, Principal Venture Partners, is below.
You can stream and download our full conversation, including azny podcast extras, on Apple Podcasts, Spotify, Bloomberg, YouTube (video), and YouTube (audio). All of our earlier podcasts on your favorite pod hosts can be found here.
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Bloomberg Audio Studios, podcasts, radio News. This is Masters in Business with Barry Ritholtz on Bloomberg Radio.
[00:00:15] Barry Ritholtz: On the latest Masters in Business podcast, my conversation with Songyee Yoon. She is founder and managing partner at Principal Ventures, an AI-focused venture capital investment firm. She has a fascinating background — 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.
[00:00:56] Barry Ritholtz: I found this conversation to be fascinating and I think you will also. With no further ado, my discussion with Songyee 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.
[00:01:27] Barry Ritholtz: What was the original career plan?
[00:01:31] Songyee Yoon: That’s a very good question. I mean, I think growing up in South Korea, I didn’t know what the career options were that I had. I just really enjoyed learning science and engineering subjects. So when I was young, I realized for some people, like 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 KAIST.
[00:02:18] Songyee Yoon: To be a better engineer, you need to understand how the human brain works. So for example, I was studying signal processing algorithms, and those algorithms look best to your eyes when it’s not necessarily mathematically the best, but takes into consideration what frequencies are most sensitive to human eyes. So understanding human brain and human perception will enable you to become a better engineer. That was kind of the exploration — what subject or major could I pursue to have a better understanding of both engineering and the human brain and perception.
[00:03:00] Songyee Yoon: That led me to study computational neuroscience at MIT.
[00:03:03] Barry Ritholtz: 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?
[00:03:19] Songyee Yoon: That’s right. Exactly. Yeah, that’s right.
[00:03:21] Barry Ritholtz: Huh. 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.
[00:03:32] Songyee Yoon: Yeah, so I mean, I think after my PhD I wanted to go into the business world instead of staying in academia, and going to McKinsey was the best way to transition from being a PhD student to going into the real world. So it was a really fascinating experience — very fast-paced, able to work with big conglomerates and the leaders of businesses 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 —
[00:04:23] Barry Ritholtz: Oh, sure.
[00:04:24] Songyee Yoon: It was an interesting transition, just like we see today, because in 2G, telecommunication is all about voice communication, and 3G — what was promised — was data transmission, including videos and images and high-fidelity audio.
[00:04:41] Barry Ritholtz: 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?
[00:04:52] Songyee Yoon: Right. Yeah, that’s right. So as telcos are one of the big CapEx investors in making that transition, we were thinking about how we could do content delivery in the most personalized way — because personalized content delivery was one of the challenges that requires artificial intelligence and 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.
[00:05:26] Barry Ritholtz: 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 about these big institutions that tend to have legacy technology. There tends to be some group that really wants to move forward rapidly and adopt all the latest greatest tech, and then another group that says, hey, this is expensive — what’s the ROI? How did you find yourself navigating a big telecom like SK or a smaller, more nimble gaming company like NCSoft?
[00:06:09] Songyee Yoon: Yeah, I mean, that’s a really great question. I think it’s about learning to be persistent and resilient and patient in both places. I was criticized for suggesting something that was not the norm at the time. So for example, when I was at NCSoft, one of the things that was very obvious to me was that it was full of data. The gaming business was offered entirely in a digitized form — you have transaction data, you have behavior data of the gamers and everything. So it was possible to do a lot of things in a data-driven way, which — it’s a lot of companies doing it today, but back then it was not very common to have understanding in both gaming business and AI and data-driven business process modeling.
[00:06:41] Songyee Yoon: So when I suggested things like churn prediction — because you can see the customer player behavior within the game, see how much they’re engaged, and predict if that player is about to churn out or continue — and that some interventions could help them stay engaged. That was one application area I identified, which could be very straightforward, but I was told there was strong pushback from the developers and even the business people. They said, ‘Oh, you’re saying it because you don’t understand the gaming business.’ You’re not a heavy gamer enough, or whatever. But —
[00:07:48] Barry Ritholtz: 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?
[00:08:01] Songyee Yoon: Right. Yeah, exactly. Yeah. So even with very clear data and the case presented, it was not an easy task to get everyone’s buy-in. But I think it gradually — the reason I mentioned that tangible example: it was a small, very tangible area where we could apply technology. And once you show success, gradually, one by one, we were able to adopt and integrate that into our business process, ending up with a large AI lab that does all of those things in a more centralized way.
[00:08:36] Barry Ritholtz: 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 US 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 approach, right?
[00:09:09] Songyee Yoon: Yeah. Right. Yeah.
[00:09:11] Barry Ritholtz: 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?
[00:09:39] Songyee Yoon: I mean, I think we talk a lot about the hype cycle and bubble being built up in this 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 the internet, with fiber optics — you remember the railroad?
[00:10:02] Barry Ritholtz: Yeah. Railroad, electrics, telegram — wherever you go.
[00:10:04] Songyee Yoon: So there is always excess capacity that gets built. But 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 insights that humans were not able to — I think there is a great area to apply the technology, and there are so many of them out there. So that’s why we are so excited about the development of this technology and the prospect of it going forward.
[00:10:47] Barry Ritholtz: So I’ve heard you discuss various priorities — durability, defensibility, real-world impact. Explain what those three things mean.
[00:11:10] Songyee Yoon: 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 — for example, there’s a lot of talk about copilot, or augmenting what we do, making it faster. That’s one way of applying it, and there will be some ROI realized from such approaches. The other is a complete redesign of the workflow. And I think that’s — we’re at a very early stage of witnessing that, but I think that will be the more interesting area to look out for, and could produce more tremendous transformation and value.
[00:12:15] Barry Ritholtz: So tell us what you did at NCSoft, 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 a little more efficient? Or did this require a clean-sheet rethink of everything the company was doing?
[00:12:37] Songyee Yoon: Yeah, I mean, it was like 15 years ago, and back then the technology was not ready to fully redesign the game development workflow. It was more about augmenting the existing process — things like churn prediction, NLP specialized for gamer language, an animation tool that helped animators animate four-legged monsters as efficiently as bipedal creatures. So it was more focused on augmenting existing processes back then. But the technology has advanced today to the point where there are more opportunities to completely redesign and come up with new AI-native companies — AI-native entertainment firms rethinking what new types of entertainment and engagement look like.
[00:13:56] Barry Ritholtz: So I keep reading that Claude is writing its own code and updating its own code. If you were at a gaming shop today — do you replace coders? Do you have copilot work with coders? There was a Wall Street Journal article last week about coders in Silicon Valley just 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?
[00:14:34] Songyee Yoon: Yeah, I think it’s really fascinating. A lot of the coding is done using tools like Claude, and it certainly makes things more efficient and productive, which means we need a lot less people in the loop in certain areas — such as reviewing code and detecting errors. But there are other areas that need more heavy involvement, like redesigning the schema and structure and how things are going to work and how it’s going to provide an engaging experience for gamers.
[00:15:26] Barry Ritholtz: So my bias is that humans are very creative and very innovative. I’m thinking in terms of the storylines we see on streaming shows and interesting novel gaming narratives. Is that what people are going to focus on, and just the blocking and tackling of putting code in place — we’re going to let AI do? Is that a today thing or is that going to change over the next couple of decades?
[00:16:05] Songyee Yoon: I think that’s a really good question. If you look at today, a lot of jobs — like YouTubers, podcasters — these are types of jobs that didn’t exist 10 years ago. I don’t know what other jobs are going to be created in a world where things that needed a hundred people’s attention can be done with a fraction of those people. There could be other types of jobs, other types of roles. But that’s an evolution we’ll have to see how it rolls out — I can’t predict exactly what types of jobs will exist 10 years from now.
[00:16:42] Barry Ritholtz: Huh. Really, really interesting. Coming up, we continue our conversation with Songyee Yoon, managing partner at Principal Ventures, discussing AI and the modern economy. I’m Barry Ritholtz, you’re listening to Masters in Business on Bloomberg Radio.
[00:17:10] Barry Ritholtz: I am Barry Ritholtz, you’re listening to Masters in Business on Bloomberg Radio. My extra special guest today is Songyee Yoon, 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 NCSoft.
[00:17:30] Barry Ritholtz: 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 — let’s not forget about play. It’s really significant in terms of innovation and being an engine of change. Tell us a little bit about what motivated Push Play.
[00:17:56] Songyee Yoon: Right. I mean, as you just mentioned, I think we have a tendency of not appreciating the role of play in our everyday life. My motto is: we don’t live 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? I think play is our natural tendency — homo ludens as opposed to homo sapiens. Play is very important, not only for computer games, but in general play has played a very significant role in human evolution. Whenever there is a new artifact introduced in our culture, we start by playing with it.
[00:19:04] Songyee Yoon: And when we have a good understanding of the material and its utility, then we turn that into utility. I think gaming has been playing that role very diligently over the last couple of decades. Gaming has always been the platform brave enough to incorporate new technology and have players try it out. We had a VP of AI since the early 2000s. AI technology was not mature enough for driverless cars 20 years ago, but it was okay in gaming because gaming is a low-risk environment and gamers are inherently early adopters. Not just AI, but Kubernetes, cloud, even freemium business models — all tried out in gaming first before being adopted in other businesses.
[00:20:33] Barry Ritholtz: Let me throw you a little bit of a curveball about gaming. When I was growing up, play was totally unstructured — you’d go down to the schoolyard. Computer games like Pong and Space Invaders were very rudimentary. Now it seems kids’ 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?
[00:21:02] Songyee Yoon: That’s a very good question, and there are many aspects to it. One is about what gaming is for today. The reason there’s so much opportunity to play games as a novelty is because computers happen to be the most sophisticated and advanced devices we have today. I think we’re still trying to figure out their limitations and what they can do, and we’re in awe of the experience they can provide. So there are a lot of online digital games out there, and the size of the catalog means kids end up choosing a game or two from that. And a game is not just one thing — there are sandbox games, building games, quiz games, story-based games. Depending on your preference, you can choose different games.
[00:22:18] Barry Ritholtz: 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. There’s a quote of yours I was 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.
[00:22:46] Songyee Yoon: If you think about education — our education has been optimized over the last couple of hundred years for delivering knowledge. And I think we are witnessing that knowledge delivery and memorization is rapidly being commoditized. What our next generation needs is more creativity and problem-solving skills. We have to think about how we can redesign the classroom to really enhance those skills instead of helping them acquire one more piece of knowledge.
[00:23:31] Barry Ritholtz: So there’s a very different set of targets — acquiring skills versus just learning or memorizing things. I’m a big fan of teaching children how to problem solve. How should schools be using AI to teach children new skills — developing expertise, developing problem-solving? What’s the proper role of AI for educational institutions?
[00:24:05] Songyee Yoon: I think what I would like to say is that we have to educate and prepare our students to thrive in a world where AI is more prevalent. But the solution to that is not just AI — it could be redesigning the curriculum, redesigning the school system, 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. I think there is a huge difference there.
[00:24:48] Barry Ritholtz: Alright, so let’s bring this out to the world of the economy and business. 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 greater accuracy. 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 use AI to expand their competitive advantages while they last?
[00:25:51] Songyee Yoon: I mean, I think there are some industries and professions that will become much more productive and need a lot fewer professionals to solve certain well-defined problems. But that doesn’t mean that as humanity we’re left with no problems to solve. We have so many other problems that AI cannot address — for example, politics, how we’re going to redistribute resources. What is our societal priority in enhancing the agency of everyone and helping them achieve their full potential? Those are things we don’t have good solutions for. While AI can take care of things in a well-defined workforce, we’ll have time to work on other problems to progress humanity forward.
[00:27:12] Barry Ritholtz: 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?
[00:27:28] Songyee Yoon: Yes. Right. Exactly. Yeah.
[00:27:30] Barry Ritholtz: So you’ve operated at the intersection of artificial intelligence, gaming, telecommunication, and social platforms. That’s a great convergence of a lot of different technologies. How is that evolving, and how are both consumers and institutions really adapting to an AI-driven economy?
[00:27:56] Songyee Yoon: I mean, a lot of people recognize that this is one of the greatest platform shifts in our lifetime, and there’s a lot of excitement. But we are at the very early inning of how it’s going to fully pan out. We don’t even know what’s coming in the next three to five years. And I’m really excited to see all these use cases and applications of technology fully leveraging the creativity of the AI-native generation. The people who think with AI as part of their toolkit will come up with different ideas and apply their creativity.
[00:28:54] Barry Ritholtz: So you’ve founded Chameleon as a corporate venture arm, and now you run a fully independent early-stage venture fund. What are the differences between being part of a corporate venture fund versus being independent? What are the strengths and blind spots in each?
[00:29:18] Songyee Yoon: I think the objective is different depending on who is providing the capital and what the objective of the firm is. At PVP, I think we focus more on the type of investors who’d like to be at the forefront of innovation and capture the value being created — regardless of the area. It doesn’t have to be confined to entertainment and consumer space. I think we were able to look more broadly.
[00:29:59] Barry Ritholtz: So corporate is pure strategic and independent is strictly ROI. So let’s talk about some of the companies you’ve backed — Together AI, Cartia, Sesame. These all seem to be pretty core infrastructure plays. Tell us a little about those. What was it about each of those that made them so appealing?
[00:30:21] Songyee Yoon: I mean, it’s a really tricky time to make an investment because there is a lot of excitement about this technology and a kind of rushing mentality. So I try to invest in companies that are going to be durable in the coming decades. I really like companies that are building infrastructure technology that has multipurpose utility as this platform evolves. Together AI and Cartia both have great founders with a vision of building infrastructure and foundational technology. And Sesame was an interesting case because it’s building voice applications — and from my gaming experience I know the importance of focusing on certain features that provide certain experiences to users. The founders understood what was important, and their capabilities were singularly focused on making that technology push.
[00:31:36] Songyee Yoon: So I really liked what they were doing, and that’s one of the reasons I ended up investing in Sesame. But there are other types of companies as well that we’re excited about. Those are the companies that are in a position to build a data flywheel — because one of the undeniable characteristics of companies that will be durable in this environment are the ones who have appropriate access to data, understanding of customers and consumers and the business, and build unique technology on top of that. So we’re also investing in companies building this data flywheel that will over time build very defensible moats.
[00:32:27] Barry Ritholtz: Hmm, really, really interesting. Coming up, we continue our conversation with Songyee Yoon, co-founder and managing partner at Principal Ventures, discussing the state of venture investing into artificial intelligence today. I’m Barry Ritholtz, you’re listening to Masters in Business on Bloomberg Radio.
[00:33:03] Barry Ritholtz: I am Barry Ritholtz. You are listening to Masters in Business on Bloomberg Radio. My extra special guest today is Songyee Yoon, founder and managing partner at Principal Venture Partners, an AI-focused VC.
[00:33:21] Barry Ritholtz: What is the key problem Principal Venture Partners is trying to solve in the world of AI today?
[00:33:29] Songyee Yoon: So we started to back AI-native companies. When we first talked about AI-native companies, that was not a very common phrase — people asked me, ‘What do you mean by AI-native companies?’ I had to explain what it meant. And these days it’s a more widely used term. We’d like to back companies who are fully embracing the technology of today and tomorrow, led by founders who understand the technology and its limitations and are able to come up with an organizational design that reflects the importance of this. In terms of the size of departments, it will be very different from companies built upon last-generation technology stacks.
[00:34:21] Songyee Yoon: And I think the type of leaders and talents who are going to lead all these departments are going to be different in terms of the use of technology and their vision for solving problems that are relevant in the AI-native era. Those are the companies that really excite us, and those are the companies we’re focused on investing in.
[00:34:40] Barry Ritholtz: So every time there’s a new technology, everybody just kind of sprinkles a little bit on it to catch a 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’s claiming they’re an AI company. 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’?
[00:35:06] Songyee Yoon: That’s a very good question. I think I have an unfair advantage from working in a gaming company. 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 a sense of whether this type of technology is adoptable and whether consumers will accept it. So in terms of application and platform, that’s a really interesting guiding North Star for me. And companies that are fully AI-native are built around that tech stack, whereas if you’re trying to sprinkle AI, you ask: can you do the same thing without AI? Why do you need it? Why is it indispensable?
[00:36:05] Songyee Yoon: I think there are businesses using things like agent technology, but for a lot of applications you don’t need an agent — you just need good data analytics. So there are many ways we try to understand how businesses are operating and see their full potential and their strategy.
[00:36:30] Barry Ritholtz: So on the one hand, I know AI has been around a long time. When Deep Blue beat Kasparov, that was a big deal. And then the AI app that won Jeopardy — these are 10 and 20 years ago. So it’s not a brand-new technology. However, it feels like we took another level jump with ChatGPT, and — go down the list — Claude, Perplexity, whatever. How do you think about this moment in time? Is this similar to early broadband, early smartphones, early cloud use? For someone who’s a tech investor, they want to know: is it early, is it late? How do you think about where we are today?
[00:37:30] Songyee Yoon: That’s great. Actually, it’s older than that. Do you remember — in the sixties there was an application called Eliza? Eliza was a very early incarnation of a chatbot, and there was even a newspaper headline declaring the end of psychotherapists because it was doing so well rephrasing what people were asking. Since then there were a lot of AI winters and summers, ups and downs. And I think what’s surprising to many people about this time is that the AI shift is closer to the introduction of the railroad than the introduction of the PC or the internet. Because the biggest breakthrough that allowed us to get here was actually scale — not a new algorithm, not new software, but scale: let’s pour a lot of resources to make it really big. And that’s where we saw the tremendous jump in AI capability.
[00:39:34] Songyee Yoon: I think there will be interesting new businesses that emerge out of it. So yes, I think we are very early in terms of fully appreciating what’s possible on top of this.
[00:39:46] Barry Ritholtz: So I love the idea of interesting new businesses. I’m always fascinated with what the public markets know — they’re more or less eventually efficient, and very often when a new technology comes along, they very much underestimate where it can go. So what’s a use case that the public markets might be underestimating? Where might this go? You look at dozens and dozens of new companies — what direction is just mind-blowing that nobody is really anticipating?
[00:40:24] Songyee Yoon: I think there are a lot of things happening. One interesting thing is that while this technology has beaten many people’s expectations, there is a lot more innovation coming along in terms of architecture design and fundamental design of the framework. We are not done with what is the most efficient railroad design. I think there could be other types of railroads that come online that will allow faster and more comfortable ride experiences. And once there is a railroad, interesting businesses emerge — like mail order. It’s really hard to make that connection, but that type of new business was made possible because the railroad was in place.
[00:41:40] Barry Ritholtz: Well, broadband and fiber optic led to so many things — everything from YouTube to the build-out of Amazon Web Services and online games, online retail, all that stuff.
[00:41:53] Songyee Yoon: Exactly. Games, right? That’s why I am really excited about AI-native generations and creativity — what they’re going to build on top of this. I think there will be new types of businesses that we don’t comprehend today that will be enabled by this infrastructure.
[00:42:06] Barry Ritholtz: 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, their direction, their team?
[00:42:24] Songyee Yoon: I mean, it depends on what they’re building. The set of questions I ask when they’re building infrastructure technology versus business applications are different. But especially when they’re building business applications or vertical applications, I always try to ask: what is the real value that’s going to be brought to end users? We’re not investing in companies building amazing tech demonstrations — we’re trying to find companies who are solving real-world business problems and doing it in a way that’s sustainable and more efficient than any other type of technology.
[00:43:11] Barry Ritholtz: So you’re looking at infrastructure-type companies. What other types of AI applications are you looking at?
[00:43:18] Songyee Yoon: We are looking at companies that are building vertical applications by developing data liabilities and data moats.
[00:43:27] Barry Ritholtz: So there’s been a little bit of a lightning rod from a regulatory standpoint — all the LLMs have copyright complaints and issues. When you look at a term sheet today, how do you think about the regulatory risks, the litigation risks? How do you think about the regulatory framework and geopolitics? It seems like there are a lot of novel moving parts.
[00:44:11] Songyee Yoon: Yeah, I think that’s a really great question. More than ever, understanding how regulatory bodies think and how policy is going to evolve over time is important in making these decisions — especially in the venture space. We’re making investments that should last over a decade. It comes from the belief and understanding that innovation and research are very precious for all of us as humanity. And the tradition of peer review and open forum has really propelled us to where we are today. It’s going to continue, and I think collaboration and openness will better serve our end customers. We don’t have a crystal ball to say what the policy framework or geopolitical tension will look like in the next one or two years, but we have the belief that humanity’s collective work will converge in a direction that serves humanity positively.
[00:46:15] Barry Ritholtz: Alright, so before we get to our speed round, let me ask you one last question: what do you think investors in the AI space are either not thinking about or not talking about, that is important and perhaps they really should be paying attention to?
[00:46:33] Songyee Yoon: I think the saying that ‘we are at the very early inning’ means a lot. I hear someone even saying we are still in the car getting to the stadium — we’re not even in the first inning yet. That means all the models and structures can change significantly and can evolve over time, and nothing can be seen as engraved in stone. So I think a lot of the investment decisions have to remain nimble and flexible because we should be able to adjust when those changes and new breakthroughs come around.
[00:47:26] Barry Ritholtz: Alright, so I only have you for a few minutes, so we’ll click through these really quickly — our speed round. Starting with: who are your early mentors who helped to shape your career?
[00:47:38] Songyee Yoon: I would say I was fortunate enough to have a lot of mentors, but one person that stands out is Dominic Barton, who was the global managing partner at McKinsey. When I first started out as an associate at McKinsey, his office was right next to mine, so he was literally my neighbor and I learned a lot from him as a leader and as a mentor. Still today I reach out to him if I have to make tough decisions, and he has always been very generous with his time. So I’m really appreciative.
[00:48:22] Barry Ritholtz: Let’s talk about books. What are some of your favorites? What are you reading right now?
[00:48:26] Songyee Yoon: Oh, so I read a lot of books, but I’m the type that reads many books simultaneously — one chapter here and then I jump to another book. But the books I recommend to everyone these days are two: one is The Empire of AI and the other is Power and Progress. And I think those books help us understand the dynamics of what’s happening and what we need to think about as a society.
[00:48:56] Barry Ritholtz: So let’s talk about streaming. What are you either listening to or watching these days?
[00:49:02] Songyee Yoon: So I listen to music through Spotify a lot. My son is a big fan of Taylor Swift, so I have to listen to Taylor Swift whenever I’m in the car. I also watch K-dramas on Netflix.
[00:49:23] Barry Ritholtz: 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, investing, or gaming?
[00:49:38] Songyee Yoon: I mean, I think for kids just graduating today — one thing that’s not going to change is that it’s going to be very bumpy and disruptive, and the world they’re going to be working in is not going to look like the world today — that’s the constant. And what I would like to remind them is: don’t try to follow the trend. You really have to stick to what you’re passionate about. You remember in the seventies the most popular major was material science, then chemical engineering, then electrical engineering, then computer science — just to see the popularity of those majors kind of plummeting. We’ve witnessed so many of those cases. So I don’t think it serves you well to follow that fashion or trend.
[00:50:46] Barry Ritholtz: So be a generalist and be flexible.
[00:50:50] Songyee Yoon: Could be. Yeah. Right. Yeah.
[00:50:52] Barry Ritholtz: Alright. And our final question: what do you know about the world of venture investing and artificial intelligence today that might have been useful to know 20 years ago?
[00:51:03] Songyee Yoon: I mean, I think patience. The power of compounding is not just in finance, but also in human capital, our understanding of technology, and also in relationships. It seems very slow today, but if you are persistent for 20 years, what you can achieve is really tremendous.
[00:51:29] Barry Ritholtz: Well, thank you Songyee for being so generous with your time. We have been speaking with Songyee Yoon, founder and managing partner at Principal Venture Partners. If you enjoyed this conversation, check out any of the 600-plus interviews we’ve done over the past 12 years. You can find those at iTunes, Spotify, YouTube, Bloomberg, wherever you find your favorite podcasts.
[00:51:58] Barry Ritholtz: 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 Ritholtz.
[00:52:14] You’ve been listening to Masters in Business on Bloomberg Radio.
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