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

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  Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Masters in
• 0:11
  Speaker 1: Business with Barry Ritholts on Bloomberg Radio on.
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  Speaker 2: The latest Masters in Business podcast. My conversation with Song
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  Speaker 2: Yi Yun. She is founder and managing partner at Principal Ventures,
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  Speaker 2: an AI focused venture capital investment firm. She has a fascinating,
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  Speaker 2: fascinating background all sorts of MIT Corporation Advisory Board, fifty
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  Speaker 2: Women to Watch in Business from the Wall Street Journal,
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  Speaker 2: named to the advisory board for the Center for Asia
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  Speaker 2: Pacific Policy as well as the National Academy of Engineering
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  Speaker 2: of Korea. She has a fascinating background in gaming, telecom
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  Speaker 2: and AI. I found this conversation to be fascinating, and
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  Speaker 2: I think you will also with no further ado, my
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  Speaker 2: discussion with Principal Ventures. Sang Yi you that is quite
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  Speaker 2: a CV. I went through. Let's roll back though to
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  Speaker 2: where it all began. You get a bachelor's in science
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  Speaker 2: from Korea's Advanced Institute of Science and Technology and then
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  Speaker 2: a PhD in computational neuroscience from MIT. That's such a
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  Speaker 2: fascinating area. What was the original career plan?
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  Speaker 3: That's a very good question. I mean, I think growing
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  Speaker 3: up in South Korea. I didn't know what are the
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  Speaker 3: career options that I had. I just really enjoyed learning
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  Speaker 3: science and engineering subject So when I was young, I
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  Speaker 3: realized for some people, like singing is very natural, huh,
• 1:54
  Speaker 3: some people dancing as natural. I cannot sing, I cannot dance,
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  Speaker 3: But like speaking to computers and programming was very natural
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  Speaker 3: to me. So I started programming when I was nine,
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  Speaker 3: and that led me to major in electrical engineering as
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  Speaker 3: an undergrad at CHIST. And along the way, I realized
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  Speaker 3: I just wanted to become a better engineer because I
• 2:17
  Speaker 3: was study as an engineering student. To be a better engineer,
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  Speaker 3: you need to understand how human brain works. So for example,
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  Speaker 3: I was studying signal processing algorithm, and those signal processing
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  Speaker 3: algorithms are look best to your eyes when it's not
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  Speaker 3: necessarily mathematically the best, but take into consideration what frequencies
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  Speaker 3: most sensitive to human eyes. So understanding human brain and
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  Speaker 3: human perception will enable you become a better engineer. So
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  Speaker 3: I was kind of exploring what would be the subject
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  Speaker 3: or kind of the major that I can pursue to
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  Speaker 3: have a better good understanding both engineering and human brain.
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  Speaker 3: And that was that led me to study competition and
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  Speaker 3: re science that I might say.
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  Speaker 2: So computational neuroscience isn't so much about using computers to
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  Speaker 2: understand people as opposed to understanding as opposed to understanding
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  Speaker 2: neuroscience to create better software, better interfaces, better human interaction
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  Speaker 2: with technology.
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  Speaker 3: Is that rare? Exactly? Yeah, that's right.
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  Speaker 2: Huh so pretty fascinating. Early in your career, you're at
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  Speaker 2: McKenzie for a few years and then you eventually move
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  Speaker 2: into SK telecom. Tell us your focus at both places.
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  Speaker 3: Yeah, So, I mean, I think after after my PhD,
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  Speaker 3: I wanted to go into the instead of staying in academia,
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  Speaker 3: I wanted to go into the business world, and going
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  Speaker 3: to McKinsey was the kind of the best way to
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  Speaker 3: transition from being a being a PhD student to go
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  Speaker 3: into the real world. So it was a really fascinating
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  Speaker 3: experience for me, very fast paced, able to work with
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  Speaker 3: big conglomerates and the leaders of the businesses and in
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  Speaker 3: the areas of strategy and corporate finance, et cetera. And
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  Speaker 3: s K was one of the forum's clients. And I
• 4:15
  Speaker 3: don't want to like date myself. It was a time
• 4:18
  Speaker 3: that everyone was rushing into three G rollout if you remember,
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  Speaker 3: it was an interesting transition, just like we see today
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  Speaker 3: because in two G della communication is all about voice communication,
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  Speaker 3: and three G what was promised was the data transmission
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  Speaker 3: including videos and images and high fidelity audios.
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  Speaker 2: If I'm remembering correctly, it was voice and text, and
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  Speaker 2: then it was image and some video and eventually what
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  Speaker 2: was it for G five G was full Internet, right right.
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  Speaker 3: Yeah, that's right. So as Telcos are one of the
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  Speaker 3: big CAPEX investors in making that transition, and we're thinking
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  Speaker 3: about how we can do the content delivery in the
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  Speaker 3: most personal personalized content delivery was one of the challenges
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  Speaker 3: that requires artificial intelligence and like a data data driven
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  Speaker 3: delivery system. So I thought that was an interesting challenge
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  Speaker 3: to take on. So I moved to SKA Telecom to
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  Speaker 3: lead that effort, and.
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  Speaker 2: Then you end up at NCSoft where you're president and
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  Speaker 2: chief strategy officer. I'm curious what those experiences taught you,
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  Speaker 2: not just about corporate governance and culture, but just these
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  Speaker 2: big institutions that tend to have legacy technology. You know,
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  Speaker 2: there tends to be some group that really wants to
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  Speaker 2: move forward rapidly and adapt all the latest greatest tech
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  Speaker 2: and then another group that hey, this is expensive, what's
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  Speaker 2: the what's the ROI in this? How did you find
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  Speaker 2: yourself navigating a big telecom like sk or a small
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  Speaker 2: or more nimble gaming company like NCSoft.
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  Speaker 3: Yeah, I mean that's a really great question, and I
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  Speaker 3: think it's learned to be persistent and resilient and patient
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  Speaker 3: in both places. I was criticized for, like ask suggesting
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  Speaker 3: something that was not the norm at the time. So,
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  Speaker 3: for example, when I was an NCSoft, one of the
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  Speaker 3: things that I it was very obvious to me was
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  Speaker 3: it was full of data in gaming, the businesses and
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  Speaker 3: like all offered in a distised form. You have transaction data,
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  Speaker 3: you have a behavior data of the gamers and everything.
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  Speaker 3: So it was possible to do a lot of things
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  Speaker 3: on the data driven way, which is very kind of
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  Speaker 3: not today it's it's it's a lot of the companies
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  Speaker 3: are doing it, But back then it was it was
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  Speaker 3: not very common to have understanding in both gaming business
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  Speaker 3: and as well as kind of AI and kind of
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  Speaker 3: data driven business business process modeling. So when I suggested
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  Speaker 3: things like, oh, like it's let's do a small thing
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  Speaker 3: like like charm prediction, because you can you can see
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  Speaker 3: the customer player behavior within the game and see how
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  Speaker 3: much they're engaged, and you can predict if that player
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  Speaker 3: is about to turn out or continue with a with
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  Speaker 3: a game, and some kind of interventions could help them
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  Speaker 3: stay engaged with a game. So that was the one
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  Speaker 3: application areas that I didn't identify it which could be
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  Speaker 3: very straightforward, but then I was told, like there is
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  Speaker 3: a strong pushback from the developers and even the business people.
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  Speaker 3: They said, oh, you're saying it because you don't understand
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  Speaker 3: a gaming business. You're you're you're saying you're a kind
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  Speaker 3: of a you're not a heavy gamer in or whatever, but.
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  Speaker 2: You understand, hey, because this as much to acquire a
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  Speaker 2: client or a gamer, and if we see this behavior,
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  Speaker 2: a five percentage of those folks are tapping out, what
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  Speaker 2: can we do to keep in and paying monthly fees?
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  Speaker 3: Right right? Exactly. Yeah, So even with a very clear
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  Speaker 3: data and the case presented, it was not an easy
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  Speaker 3: task to have get everyone's buy in. But I think
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  Speaker 3: it gradually. Just the reason I kind of mentioned that
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  Speaker 3: tangible example was a small, very tangible area that we
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  Speaker 3: can apply to technology and once you show the success,
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  Speaker 3: I think there is a gradually one by one we're
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  Speaker 3: able to adopt integrate that into our business process to
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  Speaker 3: end up having a large AI lab that does like
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  Speaker 3: all of those things in a more centralized way.
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  Speaker 2: So what I'm hearing from you is very systems oriented framework,
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  Speaker 2: both for gaming and telecom. I know the big mobile
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  Speaker 2: companies in the US are constantly fighting their own churn rate.
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  Speaker 2: So having a top down systems approach sounds like you
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  Speaker 2: could be really proactive in terms of maintaining clients. You
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  Speaker 2: would think there's buy in from everybody, but it sounds
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  Speaker 2: like there's a little salesmanship involved to get everybody behind
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  Speaker 2: that that approach.
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  Speaker 3: Right, yeah, right, yeah.
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  Speaker 2: So let's talk a little bit about what's going on
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  Speaker 2: in the world of AI. I've heard you discuss various
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  Speaker 2: things that are just short term hype. How do you
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  Speaker 2: figure out when you're evaluating an AI system, either for
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  Speaker 2: an investment or just to use the technology in a company,
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  Speaker 2: how do you figure out what's valuable and what's just hype?
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  Speaker 2: What are you looking at?
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  Speaker 3: I mean, I think we talk a lot about hype
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  Speaker 3: cycle and kind of bubble being built up in this
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  Speaker 3: in this kind of AI era, but I think it's
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  Speaker 3: not unheard of them in every platform shift, there was
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  Speaker 3: overcapacity built, not just in AI infrastructure, but it happened
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  Speaker 3: with inter like fiber optics.
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  Speaker 2: Railroad, pelgram, wherever you go.
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  Speaker 3: So there's always a kind of excess capacity that's built,
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  Speaker 3: and I think that's when people what people are pointing
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  Speaker 3: to is that is that area that there is some
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  Speaker 3: kind of bubble built up. But on the other hand,
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  Speaker 3: if you talk about application of the technology, if you
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  Speaker 3: find the application and real business problems that you can
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  Speaker 3: apply this technology to solve, to be more efficient or
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  Speaker 3: bring out some insights that humans were not able to
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  Speaker 3: do it, And I think there is a great area
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  Speaker 3: to apply the technology, and I think there are so
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  Speaker 3: many of them out there. So that's why we are
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  Speaker 3: so excited about the development technology and the prospect of
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  Speaker 3: it going forward.
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  Speaker 2: So I've heard you discuss various priorities, whether it's a
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  Speaker 2: corporate entity pursuing upgrading their AI infrastructure or you know,
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  Speaker 2: just tot AI native startup. You talk about durability, defensibility,
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  Speaker 2: real world impact. Explain what those three things mean.
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  Speaker 3: So in making in kind of making that adoption of
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  Speaker 3: the technology, there are there are two ways to think
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  Speaker 3: about it. One is adopting the technology without really changing
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  Speaker 3: the current work process, right, So you can, for example,
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  Speaker 3: there are a lot of talk about co pilot or
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  Speaker 3: like augmenting what we do make it faster like a search,
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  Speaker 3: and if those things are necessarily changing our current established workflow,
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  Speaker 3: but you are fully embracing what the technology can do
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  Speaker 3: to make you more productive and efficient. So that's the
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  Speaker 3: kind of one way of applying it, and I think
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  Speaker 3: there will be some amount of the ry that will
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  Speaker 3: be realized from such approaches. And the other is complete
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  Speaker 3: redesign of the workflow. And I think that's a that's
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  Speaker 3: a that's kind of we're a very early stage of
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  Speaker 3: like kind of witnessing that, but I think that will
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  Speaker 3: be a more interesting area to look out for and
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  Speaker 3: could be more tremendous transformation and the value created from
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  Speaker 3: such effort.
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  Speaker 2: So tell us what you did at NCSoft, because a
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  Speaker 2: lot of the work you put in there was about
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  Speaker 2: transforming them to use AI. Was it, Hey, we're just
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  Speaker 2: going to make all our developers and gamers and everybody
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  Speaker 2: else a little more efficient, a little more productive or
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  Speaker 2: did this require a clean sheet rethink of everything that
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  Speaker 2: the company was doing.
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  Speaker 3: Yeah, I mean I think it was like fifteen years ago,
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  Speaker 3: and I think it's back then, I think technology was
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  Speaker 3: not ready to fully redesign the game development work workflow.
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  Speaker 3: But I think back then it was more of augmenting
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  Speaker 3: the existing process. So for example, like we did things
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  Speaker 3: like the marketing and Trump prediction and more efficiently we
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  Speaker 3: had NLP that's design signed for Gamer, specialized for Gamer language.
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  Speaker 3: Like we had augmenting, the animation tool that helps animators
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  Speaker 3: to animate not just by pedal creatures, but like four
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  Speaker 3: legged monsters in a way that's as efficient as you're
• 13:17
  Speaker 3: doing bipedal creatures, et cetera. So I think it's a
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  Speaker 3: more focused on augmenting existing processes back then. But I
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  Speaker 3: think the technology has advanced and matured today that I
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  Speaker 3: think that there are more opportunities to kind of completely
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  Speaker 3: redesign and come up with a new type of AI
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  Speaker 3: native companies. So I see like an AI native entertainment
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  Speaker 3: firms that we're thinking about what do you mean by
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  Speaker 3: new type of entertainment? New type of engagement that's different
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  Speaker 3: from polishing and like making higher fidelity graphics and games,
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  Speaker 3: but like a completely new form of entertainment using fully
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  Speaker 3: embracing the technology that we have today.
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  Speaker 2: So I keep reading that Claude is writing its own
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  Speaker 2: code and updating its own code. If you were at
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  Speaker 2: a gaming shop today, I'm assuming, do you replace coders?
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  Speaker 2: Do you have copilot work with coders? It was a
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  Speaker 2: Wall Street Journal article last week. I think it was
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  Speaker 2: Wall Street Journal. It could have been wired about coders
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  Speaker 2: in Silicon Valley are just kind of sitting around watching
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  Speaker 2: Claude rewrite their code. What is going on in the
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  Speaker 2: world of software development now that Claude is capable of
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  Speaker 2: updating itself.
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  Speaker 3: Yeah, I think it's a really fascinating I think a
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  Speaker 3: lot of the coding is done using tools like a Claude,
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  Speaker 3: and it certainly makes it more efficient and like productive,
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  Speaker 3: which means that we need a lot less people in
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  Speaker 3: the loop to do the job in certain areas such
• 14:53
  Speaker 3: as like reviewing a kind of like detecting errors and
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  Speaker 3: just kind of I think there are a certain area
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  Speaker 3: area is that AI coders can do better, But there
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  Speaker 3: are other areas that these more kind of heavy hand,
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  Speaker 3: like more involvement of a kind of redesigning that the
• 15:12
  Speaker 3: schema and the structure and how things are going to
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  Speaker 3: work and how it kind of is going to be
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  Speaker 3: implemented in providing them kind of engaging experience as for gamers.
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  Speaker 2: So my bias is that the humans are very creative
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  Speaker 2: and very innovative, and you know, I'm thinking in the
• 15:35
  Speaker 2: sort of storylines we see on all the streaming shows
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  Speaker 2: and some of the interesting novel gaming. I don't know
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  Speaker 2: what to call it. I guess it's a narrative storyline.
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  Speaker 2: Is that what people going to focus on, and just
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  Speaker 2: the blocking and tackling, just the daily grind of putting
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  Speaker 2: code into place we're going to let ai use. Is
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  Speaker 2: that a today thing or is that a next you know,
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  Speaker 2: is that going to change over the next couple of
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  Speaker 2: decades or years.
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  Speaker 3: I think that's a really good question. I think it's
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  Speaker 3: if you look at today, I mean, I think a
• 16:10
  Speaker 3: lot of the jobs, like like YouTubers, podcast is are
• 16:14
  Speaker 3: the type of job that didn't exist ten years ago.
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  Speaker 3: I don't know what other jobs are going to be
• 16:19
  Speaker 3: created in the world where like the things that needed
• 16:23
  Speaker 3: needed like one hundred people attention can be done with
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  Speaker 3: like a fraction of those people. There could be other
• 16:29
  Speaker 3: type of jobs there are the type of roles, But
• 16:31
  Speaker 3: I think, uh, that's a that's an evolution that will
• 16:33
  Speaker 3: have to see how it how it roll out. Then
• 16:37
  Speaker 3: then I can and kind of predicting exactly what type
• 16:40
  Speaker 3: of jobs we're going to exist in ten years from now.
• 16:42
  Speaker 2: Huh, really really interesting. Coming up, we continue our conversation
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  Speaker 2: with Song Ye Yun uh, managing partner at Principal Ventures,
• 16:51
  Speaker 2: discussing AI and the modern economy. I'm Barry Ridults. You're
• 16:56
  Speaker 2: listening to Masters in Business on Bloomberg Radio. I'm Barry Ridalts.
• 17:11
  Speaker 2: You're listening to Masters in Business on Bloomberg Radio. My
• 17:14
  Speaker 2: extra special guest today is Sami Yun. She is the
• 17:17
  Speaker 2: founder and managing partner at Principal Venture Partners, an AI
• 17:22
  Speaker 2: focused venture capital firm. Previously, she was president and Chief
• 17:26
  Speaker 2: strategy officer at gaming company NCSoft. So before we start
• 17:31
  Speaker 2: talking about AI in more depth, I just have to
• 17:36
  Speaker 2: mention your book Push Play, Gaming for a Better World.
• 17:41
  Speaker 2: I love the concept that, hey, let's not forget about play.
• 17:45
  Speaker 2: It's really significant in terms of innovation and just being
• 17:50
  Speaker 2: an engine of change. Tell us a little bit about
• 17:53
  Speaker 2: what motivated push.
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  Speaker 3: Play, right, I mean, I think it's a as you
• 17:59
  Speaker 3: just I think we have a tendency of not appreciate
• 18:06
  Speaker 3: appreciating the role of the play in our everyday life.
• 18:12
  Speaker 3: My motive is that we don't live to work, we
• 18:14
  Speaker 3: live to play, like we live to explore. When you
• 18:16
  Speaker 3: have like extra time, are you gonna do like one
• 18:19
  Speaker 3: more line of work, We're going to play. I think
• 18:21
  Speaker 3: it's a play is our kind of natural tendency or
• 18:24
  Speaker 3: homolludence as opposed to Homo sapiens. I mean, I think
• 18:28
  Speaker 3: it being an addition in addition to being a Homo sapiens.
• 18:31
  Speaker 3: So I think a play is a very important and
• 18:34
  Speaker 3: I think it's not not only about like we're not
• 18:38
  Speaker 3: only talking about computer games, but in general, I think
• 18:42
  Speaker 3: play has played a play has played a very significant
• 18:45
  Speaker 3: role in human evolution. Whenever there is a new artifact
• 18:50
  Speaker 3: that was introduced in our on our culture, we start
• 18:53
  Speaker 3: with the playing with it. We create, We kind of
• 18:56
  Speaker 3: figure out how to how to kind of how to
• 18:58
  Speaker 3: make how to make a play out of it, how
• 19:02
  Speaker 3: to kind of create something out of it. And when
• 19:04
  Speaker 3: we have a good understanding of the material and kind
• 19:06
  Speaker 3: of utility in it, then you kind of turned that
• 19:09
  Speaker 3: into utility. I think gaming has been playing that role
• 19:14
  Speaker 3: very diligently in over the last couple of decades. For example,
• 19:19
  Speaker 3: if you look at some type of technology that has
• 19:22
  Speaker 3: been when it was fully tested and baked out, gaming
• 19:29
  Speaker 3: has been always the platform that was brave enough to
• 19:33
  Speaker 3: incorporate in our in our offering and have our players
• 19:38
  Speaker 3: test kind of try out. For example, we had a
• 19:42
  Speaker 3: VP of AI since early two thousands. AI technology has
• 19:47
  Speaker 3: been not mature enough to kind of apply to applications
• 19:52
  Speaker 3: like a driver lest cars twenty years ago, but it
• 19:56
  Speaker 3: was okay in gaming because the gaming is a very
• 19:59
  Speaker 3: low risk and and at the same time gamers are
• 20:02
  Speaker 3: inherently early adopters they want to try out new technology.
• 20:07
  Speaker 3: So I think it's a combination of those things make
• 20:09
  Speaker 3: it possible and almost inevitable for gaming companies to try
• 20:15
  Speaker 3: new technologies. So not just the AI, but like kuber
• 20:19
  Speaker 3: netics discussions, or like a cloud, or even like a
• 20:24
  Speaker 3: free to play freemium business models all tried out in
• 20:28
  Speaker 3: gaming first before they were adopted in other businesses.
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  Speaker 2: Let me throw you a little bit of a curveball
• 20:35
  Speaker 2: about gaming. So when I was growing up, play was
• 20:39
  Speaker 2: totally unstructured. You go down to the schoolyard. The computer
• 20:43
  Speaker 2: games like Pong and Space Invaders very rudimentary now it
• 20:49
  Speaker 2: seems kids their lives are much more scheduled, their play
• 20:53
  Speaker 2: is more structured. How does that affect the sort of
• 20:58
  Speaker 2: experience you want to provide from a gaming company.
• 21:02
  Speaker 3: That's a very good question, and I think it's a
• 21:06
  Speaker 3: There are many aspects to your question. One is about
• 21:10
  Speaker 3: what is gaming for today? And I think the reason
• 21:14
  Speaker 3: why there's so much opportunity to play game and kind
• 21:19
  Speaker 3: of as a novelty is because computer happens to be
• 21:23
  Speaker 3: the most sophisticated in advanced device that we have today.
• 21:27
  Speaker 3: I think we're trying to figure out what is kind
• 21:29
  Speaker 3: of its limitations and what it can do and it
• 21:32
  Speaker 3: and kind of in all with the kind of experience
• 21:35
  Speaker 3: that they can it can provide. So I think there
• 21:38
  Speaker 3: are a lot of on nine digital games out there,
• 21:42
  Speaker 3: and the kind of the size of the catalog makes
• 21:47
  Speaker 3: kids and who are trying to go through what kind
• 21:50
  Speaker 3: of play options are there end up choosing a game
• 21:54
  Speaker 3: or two from from.
• 21:55
  Speaker 2: That they can select what they want to do right exactly.
• 21:59
  Speaker 3: But but they're are but but also like if you
• 22:01
  Speaker 3: think of a game, game is not just one thing.
• 22:03
  Speaker 3: They are like sandbox games, they're like a building game.
• 22:05
  Speaker 3: There are like a coss game, the story based games.
• 22:09
  Speaker 3: There are different type of games that you can choose from,
• 22:12
  Speaker 3: So depending on your preference and what you find the
• 22:14
  Speaker 3: most engagement, you can choose different games.
• 22:18
  Speaker 2: So let's stay with kids. With children and in particular students.
• 22:23
  Speaker 2: There's been a lot of concern about the impact of
• 22:25
  Speaker 2: AI on education, on learning, on training people to get
• 22:31
  Speaker 2: jobs in the real world. There's a quote of years
• 22:34
  Speaker 2: I was kind of intrigued with, rather than competing with AI,
• 22:38
  Speaker 2: students should be prepared to leverage unuquely human capabilities. Explain
• 22:43
  Speaker 2: what that means in terms of the real world.
• 22:46
  Speaker 3: I think it's if you think about education, our education
• 22:50
  Speaker 3: has been over the last couple of one hundred years,
• 22:54
  Speaker 3: it has been optimized for delivering knowledge, and I think
• 22:59
  Speaker 3: weird witnessing that the knowledge delivery and memorization is rapidly
• 23:04
  Speaker 3: being commoditized. And is that what students have to spend
• 23:09
  Speaker 3: all their time sitting in a classroom to to kind
• 23:13
  Speaker 3: of to to kind of a polish I think it's
• 23:16
  Speaker 3: what we What our next generation needs is more of
• 23:18
  Speaker 3: the creativity and the problem solving skills, and I have
• 23:21
  Speaker 3: to think about if we can redesign the classroom to
• 23:25
  Speaker 3: really enhance those skills instead of helping them acquire one
• 23:30
  Speaker 3: more knowledge.
• 23:31
  Speaker 2: So there's a very different set of targets acquiring skills
• 23:36
  Speaker 2: or just learning things or memorizing things. I'm I'm a
• 23:41
  Speaker 2: big fan of teaching children how to problem solve. When
• 23:45
  Speaker 2: you say skills, let's let's think of that from an
• 23:48
  Speaker 2: institutional level. How should schools be using AI to teach
• 23:55
  Speaker 2: children new skills, developing and expertise developing problems? So what's
• 24:00
  Speaker 2: the proper role of AI for educational institutions?
• 24:05
  Speaker 3: I mean, I think what I what I would like
• 24:08
  Speaker 3: to say is that we have to educate and prepare
• 24:13
  Speaker 3: our students to thrive in the world. Where AI is more,
• 24:17
  Speaker 3: it's going to be more prevalent. AI is not. But
• 24:21
  Speaker 3: the solution to that is not just AI. It's many
• 24:25
  Speaker 3: different kind of It could be redesigning the curriculum. It
• 24:31
  Speaker 3: could be redesigning the kind of school system, the kind
• 24:34
  Speaker 3: of thinking about how we evaluate their achievement and how
• 24:37
  Speaker 3: to retrain our teachers. AI could be a tool for
• 24:43
  Speaker 3: doing that, but it's not a solution for everything. So
• 24:46
  Speaker 3: I think there is a huge difference there.
• 24:48
  Speaker 2: All right, So let's bring this now out to the
• 24:50
  Speaker 2: world of the economy and business. The probably the biggest
• 24:56
  Speaker 2: narrative I've been following about AI outside of it's a
• 25:01
  Speaker 2: bubble or we're all going to lose our jobs, and
• 25:03
  Speaker 2: I kind of ignore both of those extremes, is that
• 25:08
  Speaker 2: successful companies have wide moats and we're starting to see
• 25:12
  Speaker 2: AI compress those motes over time. Think about industries like lawyers,
• 25:19
  Speaker 2: tax prepared as accountants. There's a lot of stuff AI
• 25:22
  Speaker 2: can do in a fraction of the time and with
• 25:24
  Speaker 2: a greater accuracy level. Everybody knows about reading X rays
• 25:29
  Speaker 2: and MRIs. So if we know our motes are going
• 25:34
  Speaker 2: to get compressed, how should companies be using AI either
• 25:39
  Speaker 2: to protect and expand those motes or somehow use AI
• 25:43
  Speaker 2: to expand their competitive advantages while they last.
• 25:51
  Speaker 3: I mean, I think that's a very interesting because I
• 25:56
  Speaker 3: think there are some of the industries and profession that
• 25:59
  Speaker 3: will be they'll become much more productive and probably need
• 26:04
  Speaker 3: a lot less profession to solve certain well defined problems.
• 26:09
  Speaker 3: But that does mean that human as humanity as a
• 26:12
  Speaker 3: society is not is left with no problem to solve.
• 26:17
  Speaker 3: I think we have, like so many other problems to
• 26:18
  Speaker 3: solve that AI cannot address for example, how were I mean,
• 26:22
  Speaker 3: I think they are like very old problem of the
• 26:29
  Speaker 3: politics is how we are gonna redistribute the resources? What
• 26:34
  Speaker 3: is our societal priority in solving in enhancing the agency
• 26:39
  Speaker 3: of everyone and kind of helping them to achieve their
• 26:41
  Speaker 3: full potential. I think those are the things that we
• 26:44
  Speaker 3: don't have a good solution for. While AI can take
• 26:47
  Speaker 3: care of some of the things of a well defined workforce,
• 26:51
  Speaker 3: providing that expertise to make it more efficient, way will
• 26:55
  Speaker 3: have time to work on other problems to progress or
• 27:00
  Speaker 3: humanity forward. And I think that's we have prepared to
• 27:04
  Speaker 3: accept your type of roles and your type of kind
• 27:06
  Speaker 3: of professions that will exist enabled by this technology advencement.
• 27:12
  Speaker 2: So I think we're all in agreement. It's going to
• 27:14
  Speaker 2: be a very disruptive technology. Am I hearing you say? Essentially, Hey,
• 27:21
  Speaker 2: it's up to everybody to learn how to use these
• 27:23
  Speaker 2: tools and adapt. But the change is coming. You have
• 27:27
  Speaker 2: to be.
• 27:27
  Speaker 3: Prepared, yes, right, exactly.
• 27:30
  Speaker 2: Yeah, So you've operated at the intersection of artificial intelligence, gaming, telecommunication,
• 27:36
  Speaker 2: and social platforms. That's a great conversion of a lot
• 27:40
  Speaker 2: of different technologies. How is that evolving and how are
• 27:45
  Speaker 2: both consumers and institutions really adapting to that sort of
• 27:51
  Speaker 2: the AI driven economy.
• 27:56
  Speaker 3: I mean, I think it's a lot of people recognize
• 27:58
  Speaker 3: that this is one of the greatest platform shifts in
• 28:02
  Speaker 3: our in our lifetime, and there's a lot of excitement
• 28:05
  Speaker 3: uh and uh but as as many people say, I
• 28:11
  Speaker 3: mean the camp of uh seeing and as a kind
• 28:14
  Speaker 3: of we're at the very early inning of how its
• 28:18
  Speaker 3: kind of how it's gonna fully pan out. We don't
• 28:22
  Speaker 3: even know what's gonna what is coming in uh in
• 28:25
  Speaker 3: uh in the next three to five years and uh
• 28:29
  Speaker 3: and really excited to see all this kind of the
• 28:32
  Speaker 3: use case and application of technology fully using based on
• 28:37
  Speaker 3: the creativity of this AI native generation. And I think
• 28:40
  Speaker 3: the people who think with AI as part of their
• 28:44
  Speaker 3: tool and at their finger tip will come up with
• 28:47
  Speaker 3: the different ideas and and and kind of app like
• 28:50
  Speaker 3: their creativity. And I think that that that's what I'm
• 28:52
  Speaker 3: really excited about.
• 28:54
  Speaker 2: So you've founded Chameleon as a corporate venture arm and
• 28:58
  Speaker 2: and now you run a fully independent early stage venture funds.
• 29:03
  Speaker 2: I'm curious what are the differences between being part of
• 29:06
  Speaker 2: a corporate venture fund or an independent What are the
• 29:10
  Speaker 2: strengths and blind spots that you end up with in each.
• 29:18
  Speaker 3: I think we work with the strategic investors LP, then
• 29:22
  Speaker 3: I think there is a certain I think the objective
• 29:28
  Speaker 3: is a different depend I mean the kind of as
• 29:30
  Speaker 3: a GP we work for our LPs and the kind
• 29:32
  Speaker 3: of who is providing a capital and like what is
• 29:34
  Speaker 3: an objective with the fund and I think it's those
• 29:36
  Speaker 3: are very different. So at the PvP, I think we
• 29:39
  Speaker 3: focus more on a type of investors would like to
• 29:46
  Speaker 3: be at the forefront of the innovation and then capture
• 29:48
  Speaker 3: the value being created. I mean, regardless of the kind
• 29:52
  Speaker 3: of the area doesn't have to be confined in like
• 29:55
  Speaker 3: entertainment and consumer space. I think we were able to
• 29:58
  Speaker 3: kind of look more broadly.
• 30:00
  Speaker 2: So corporate is pure strategic and independent is strictly ROI.
• 30:05
  Speaker 2: So let's talk about some of the companies you've backed together,
• 30:09
  Speaker 2: dot Ai, Cartesia, Sesame. These all seem to be pretty
• 30:13
  Speaker 2: core infrastructure plays. Tell us a little bit about those.
• 30:17
  Speaker 2: What was it about each of those that made them
• 30:20
  Speaker 2: so appeal on I mean, I.
• 30:22
  Speaker 3: Think it's a it's a really tricky time to make
• 30:25
  Speaker 3: an investment because I mean, as we say, I think
• 30:27
  Speaker 3: there is a lot of kind of excitement about this technology.
• 30:31
  Speaker 3: There is a kind of the rushing mentality, so I
• 30:33
  Speaker 3: try to invest in companies uh that that's going to
• 30:38
  Speaker 3: be durable in the coming decades. So I really like
• 30:41
  Speaker 3: the companies that are building infrastructure technology that's that has
• 30:46
  Speaker 3: multi purpose us as this platform and technology evolves. So
• 30:50
  Speaker 3: I think Together and together in Cartesia are both of
• 30:54
  Speaker 3: them have a great founders, have a have a vision
• 30:57
  Speaker 3: of a building infrastructure and aunditional technology that's going to
• 31:01
  Speaker 3: be used uh in many different agie platform companies that
• 31:05
  Speaker 3: are gonna be building. And I think Sesame was an
• 31:07
  Speaker 3: interesting case because it's it's building the voice applications that
• 31:12
  Speaker 3: I know from my gaming experience. It's kind of importance
• 31:15
  Speaker 3: of it and importance of focusing on certain features that
• 31:19
  Speaker 3: that will provide certain experiences uh to to the users.
• 31:23
  Speaker 3: And I think the founders got what was important, and
• 31:27
  Speaker 3: I think they're kind of their capabilities and talent was
• 31:32
  Speaker 3: uh singularly focused on making that technology push. So I
• 31:36
  Speaker 3: really like what they were doing, and that's one of
• 31:38
  Speaker 3: the reasons and one of the reasons I ended up
• 31:41
  Speaker 3: investing in Sesame as a company. But I think there
• 31:44
  Speaker 3: are other type of companies as well that we're excited
• 31:47
  Speaker 3: about in this very in this kind of like sending
• 31:52
  Speaker 3: on this kind of shifting grounds.
• 31:53
  Speaker 2: Uh.
• 31:55
  Speaker 3: And I think those are the companies who are in
• 31:57
  Speaker 3: a position of building this data fly I will, because
• 32:01
  Speaker 3: one of the non deniable characteristics of the companies that
• 32:07
  Speaker 3: will be durable in this environment are the ones who
• 32:10
  Speaker 3: have appropriate access to data, the data, understanding customers and
• 32:15
  Speaker 3: consumers and the business and build a technology, unique technology
• 32:18
  Speaker 3: on top of that. So we also are investing companies
• 32:22
  Speaker 3: that are building this data fly will that over time
• 32:26
  Speaker 3: building very defensible modes.
• 32:28
  Speaker 2: Really really interesting. Coming up, we continue our conversation with
• 32:31
  Speaker 2: Sony Yun, co founder and managing partner at Principal Ventures,
• 32:36
  Speaker 2: discussing the state of venture investing into artificial intelligence. Today,
• 32:42
  Speaker 2: I'm Barry Richholds. You're listening to Masters and Business on
• 32:46
  Speaker 2: Bloomberg Right now, Barryerhelts, you're listening to Masters and Business
• 33:02
  Speaker 2: on Bloomberg Radio. My extra special guest today is Samya Yun.
• 33:06
  Speaker 2: She is the founder and managing partner at Principal Mentored Partners,
• 33:12
  Speaker 2: an AI focused VC. So that's a fascinating phrase. You
• 33:17
  Speaker 2: don't really hear a lot of that up until recently,
• 33:21
  Speaker 2: what is the key problem Principal Venture Partners is trying
• 33:26
  Speaker 2: to solve in the world of AI today.
• 33:29
  Speaker 3: So we've started to back AI native companies, and I
• 33:33
  Speaker 3: think when we started, when we first talked about AI
• 33:36
  Speaker 3: native companies, that was not a very common phrase. People
• 33:39
  Speaker 3: ask me like, what do you mean by AI native companies?
• 33:42
  Speaker 3: And I had to explain what it meant. And I
• 33:46
  Speaker 3: think it's these days, I think it's more widely used term,
• 33:51
  Speaker 3: and we would like to build We'd like to back
• 33:55
  Speaker 3: companies who are fully embracing the technology of today and tomorrow,
• 34:01
  Speaker 3: led by founders who understand the technology and limitations of
• 34:05
  Speaker 3: it and able to come up with org design that
• 34:08
  Speaker 3: reflect the importance of this. So I think the in
• 34:11
  Speaker 3: terms of the size of the department, I think it
• 34:14
  Speaker 3: will be very different from companies built upon last generation
• 34:19
  Speaker 3: technology tech stack, And I think a type of leaders
• 34:23
  Speaker 3: and talents who are going to lead all these departments
• 34:26
  Speaker 3: are going to be different in terms of the use
• 34:28
  Speaker 3: of technology and their vision and solving the problems that's
• 34:32
  Speaker 3: relevant in the AI native era. Are the companies that
• 34:35
  Speaker 3: are really excite us, and then those are the companies
• 34:38
  Speaker 3: were focused and investing in.
• 34:40
  Speaker 2: So every time there's a new technology, everybody just kind
• 34:45
  Speaker 2: of sprinkles a little bit on it to catch a
• 34:47
  Speaker 2: little bit of the buzz. We had it with the
• 34:49
  Speaker 2: dot coms, we had it with the metaverse, we had
• 34:52
  Speaker 2: it with crypto, and now everybody's claiming they're an AI company,
• 34:56
  Speaker 2: or at least a lot of companies. How do you
• 34:58
  Speaker 2: distinguish between what is truly AI native and what is
• 35:02
  Speaker 2: just let's put a little dash of AI salt on this.
• 35:06
  Speaker 3: That's a good that's a very good question. I think
• 35:08
  Speaker 3: I have unfaired advantage by like working in a gaming company,
• 35:13
  Speaker 3: and I think gaming company actually gave me an experience
• 35:17
  Speaker 3: in gaming industry is like having a lens into the future, right,
• 35:22
  Speaker 3: because a lot of the technology and innovation happens in
• 35:26
  Speaker 3: gaming first, and it gives us kind of sense of
• 35:30
  Speaker 3: like is this type of technology adoptable and will the
• 35:36
  Speaker 3: consumers accept this type of application? So like in terms
• 35:39
  Speaker 3: of application and platform, I think that that's really an
• 35:44
  Speaker 3: interesting guiding north star for me. And then in addition
• 35:48
  Speaker 3: to that, I think that companies that are fully AI
• 35:50
  Speaker 3: native are built around that text egg. Whereas if you
• 35:55
  Speaker 3: are trying to splinkling AI. I think you kind of
• 35:58
  Speaker 3: ask questions like can you do the same thing without AI?
• 36:02
  Speaker 3: Like why do you need it? Why is it dispensable?
• 36:05
  Speaker 3: I think there are kind of the businesses and business
• 36:08
  Speaker 3: operations that they're using, for example, like agent technology, but
• 36:13
  Speaker 3: like a lot of the applications and you don't need
• 36:16
  Speaker 3: the agents, you just need some kind of good, good
• 36:18
  Speaker 3: data analytics. So I think it's a There are many
• 36:21
  Speaker 3: ways that we tried to understand how businesses that were
• 36:25
  Speaker 3: operating and see their kind of full potential like and
• 36:29
  Speaker 3: their strategy.
• 36:30
  Speaker 2: So on the one hand, I know AI has been
• 36:34
  Speaker 2: around a long time. There was you know when Deep
• 36:37
  Speaker 2: Blue beat Casparov that was a big deal, and then
• 36:41
  Speaker 2: I forgot the name of the AI app that ended
• 36:46
  Speaker 2: up winning Jeopardy. These are like ten and twenty years ago,
• 36:50
  Speaker 2: so it's not a brand new technology. However, it feels
• 36:54
  Speaker 2: like we took another level jump with Chacchi and go
• 37:01
  Speaker 2: down the list Claude notebook, perplexity, whatever. How do you
• 37:08
  Speaker 2: think about this moment in time? Is this similar to
• 37:12
  Speaker 2: early broadbands, early smartphones, early cloud use? Like for someone
• 37:17
  Speaker 2: who's a tech investor, they want to know, hey, is
• 37:20
  Speaker 2: it early Is it late? Is it so early that
• 37:23
  Speaker 2: nine out of ten of the startups we're going to
• 37:25
  Speaker 2: see you are going to go bell? Yeah, Like, how
• 37:27
  Speaker 2: do you think about this moment where we are today?
• 37:30
  Speaker 3: That's great? Actually it's older than that. Do you remember,
• 37:35
  Speaker 3: like in sixties there is a like a location called
• 37:39
  Speaker 3: Eliza that.
• 37:40
  Speaker 2: Sounds very familiar, right, So telephone.
• 37:43
  Speaker 3: Or Eliza was was it a kind of very early
• 37:49
  Speaker 3: incarnation of checkbot? And I think there was even a
• 37:54
  Speaker 3: newspaper headline at the end of psychotherapist because it was
• 37:59
  Speaker 3: doing so bad well in terms of like rephrasing what
• 38:02
  Speaker 3: we're asking and kind of giving them comfort when you're
• 38:06
  Speaker 3: asking about very personal questions and this, oh, we don't
• 38:09
  Speaker 3: need a psychotherapists anymore because it's doing good enough. And
• 38:12
  Speaker 3: I think since then there was a lot of kind
• 38:14
  Speaker 3: of AI winters and summer ups and downs, and I
• 38:18
  Speaker 3: think there's a lot of hype in terms of like
• 38:22
  Speaker 3: comparing where we are in terms of the kind of
• 38:27
  Speaker 3: platform shift, and I think we're I think we're what's
• 38:31
  Speaker 3: surprising to many people about this time and movement is
• 38:37
  Speaker 3: that the the AI shift is closer to the introduction
• 38:42
  Speaker 3: of the railroad than the introduction of the PC or Internet,
• 38:47
  Speaker 3: because the biggest breakthrough that that allowed us to come
• 38:52
  Speaker 3: here was actually the scale. So it's not just a
• 38:57
  Speaker 3: new it's not new algorithm, it's not new software, kind
• 39:01
  Speaker 3: of new way of doing things, but it was a
• 39:04
  Speaker 3: scale let's do it like kind of pouring a lot
• 39:07
  Speaker 3: of resources to make it really big, and that's that
• 39:11
  Speaker 3: that's where we saw the tremendous jump in terms jump
• 39:15
  Speaker 3: in terms of the capability of AI. So with that,
• 39:19
  Speaker 3: I think it's kind of rolling out that that as
• 39:23
  Speaker 3: an infrastructure has been the focus of the last two
• 39:28
  Speaker 3: three years, and on this exciting new railroad that's built out.
• 39:34
  Speaker 3: I think there will be interesting new businesses that will
• 39:37
  Speaker 3: emerge out of it. So yes, I think we're very
• 39:40
  Speaker 3: early in terms of kind of fully appreciating what's possible
• 39:45
  Speaker 3: on top of this.
• 39:47
  Speaker 2: So I love the idea of interesting new businesses. And
• 39:50
  Speaker 2: I'm always fascinated with what do the public markets know?
• 39:55
  Speaker 2: You know, it's they're more or less kind of eventually
• 39:57
  Speaker 2: efficient and very often though, when a new technology comes along,
• 40:02
  Speaker 2: they very much underestimate where it can go. So what's
• 40:07
  Speaker 2: the sort of use case that the public markets might
• 40:10
  Speaker 2: be underestimating where might this go? You look at dozens
• 40:14
  Speaker 2: and dozens of new companies, what what direction is just
• 40:19
  Speaker 2: mind blowing that nobody is really anticipating.
• 40:25
  Speaker 3: So there are I think it's a there are a
• 40:27
  Speaker 3: lot of things happening. One is that one interesting thing
• 40:32
  Speaker 3: about this technology is that while it has been kind
• 40:40
  Speaker 3: of it, it beat many people's expectations about what it
• 40:44
  Speaker 3: can do. However, I think there is a lot more
• 40:47
  Speaker 3: innovation is coming along because in terms of this architecture
• 40:52
  Speaker 3: design and fundamental design of the framework, there is a
• 40:57
  Speaker 3: lot more innovation coming along. So we're not done with
• 41:01
  Speaker 3: what is the most efficient railroad design. I think there
• 41:04
  Speaker 3: could be other type of railroad that can come along
• 41:08
  Speaker 3: online that will allow faster and more kind of more
• 41:12
  Speaker 3: comfortable right experience. And once there is a railroad, I
• 41:16
  Speaker 3: think there was an interesting business that emerged, like for example,
• 41:20
  Speaker 3: like mail order or like people. It's really hard to
• 41:24
  Speaker 3: make a connection, but that type of new businesses was
• 41:28
  Speaker 3: made possible because railroad was in place. But when I
• 41:32
  Speaker 3: don't think, I don't think it was the kind of
• 41:33
  Speaker 3: first thing that came in mind. We're kind of rolling
• 41:36
  Speaker 3: out the railroad as a kind of cross across different states.
• 41:40
  Speaker 2: Well, well, broadband and fiber optic led to so many
• 41:43
  Speaker 2: different everything from YouTube exactly, really the build out of
• 41:47
  Speaker 2: Amazon Web services and.
• 41:48
  Speaker 3: Right on nine games on nine games right exactly. I
• 41:53
  Speaker 3: think so like So that's why I'm really excited about
• 41:56
  Speaker 3: AI native generations and creativity what they're going to build
• 41:59
  Speaker 3: on top of this. So I think there will be
• 42:01
  Speaker 3: new type of businesses that we don't we don't comprehend
• 42:04
  Speaker 3: today that will be enabled by this infrastructure.
• 42:07
  Speaker 2: So when you're sitting with the founder of a company
• 42:10
  Speaker 2: that's looking for financing, what sort of questions do you ask?
• 42:14
  Speaker 2: What are you trying to figure out about their model,
• 42:17
  Speaker 2: about their direction, about their team. It's so so unique
• 42:23
  Speaker 2: and cutting edge.
• 42:24
  Speaker 3: I mean, I think there it depends depending on what
• 42:27
  Speaker 3: they're building. I think it's the set of questions that
• 42:30
  Speaker 3: I ask when they're building more of the infrastructure. Technology
• 42:33
  Speaker 3: versus kind of business applications are different, but especially when
• 42:38
  Speaker 3: they're building business applications or bodical applications, I always try
• 42:44
  Speaker 3: to ask what is the real value that is going
• 42:48
  Speaker 3: to bring to the end users and not we are
• 42:53
  Speaker 3: not investing in companies that are building amazing kind of
• 42:56
  Speaker 3: tech demonstrations and the features. We're trying to find the
• 43:00
  Speaker 3: companies who are built kind of solving real business, real
• 43:04
  Speaker 3: world business problems and do it in a way that's
• 43:06
  Speaker 3: sustainable and more efficient and using other type of technology.
• 43:11
  Speaker 2: So you're looking at infrastructure type companies. What other type
• 43:16
  Speaker 2: of AI applications are you looking at.
• 43:19
  Speaker 3: We're looking at the companies that are building vertical applications
• 43:23
  Speaker 3: by developing data kind of flyable and data mode.
• 43:28
  Speaker 2: So so there's been a little bit of a lightning rod.
• 43:32
  Speaker 2: From a regulatory standpoint, there's you know, all the lllms
• 43:36
  Speaker 2: have copyright complaints and issues. You sit in a really
• 43:41
  Speaker 2: interesting intersection when when you look at a term sheet today,
• 43:45
  Speaker 2: how do you think about the regulatory risks, the litigation risks.
• 43:50
  Speaker 2: I mean that when llms first came out, I didn't
• 43:54
  Speaker 2: for a moment think oh no, oh, that was stolen
• 43:57
  Speaker 2: content and there that that they were crolling over and
• 44:01
  Speaker 2: using as their training tools. How do you think about
• 44:04
  Speaker 2: regulatory framework and geopolitics. It seems like there's a lot
• 44:09
  Speaker 2: of novel moving parts.
• 44:11
  Speaker 3: Yeah, I think that's a really great question, and I
• 44:14
  Speaker 3: think that more than ever, understanding how the regulatory body
• 44:19
  Speaker 3: thinks and the policy is gonna gonna evolve over time
• 44:23
  Speaker 3: is important at making this decisions, especially in the venture space.
• 44:28
  Speaker 3: We are making a bet, We're making investment that should
• 44:34
  Speaker 3: last over a decade, right.
• 44:37
  Speaker 1: So.
• 44:39
  Speaker 3: I think it comes from the kind of the belief
• 44:42
  Speaker 3: and understanding that the innovation and the research is really
• 44:49
  Speaker 3: kind of the is very precious for all of us
• 44:54
  Speaker 3: as a humanity. And the kind of the this kind
• 45:04
  Speaker 3: of peer reviewed, the kind of the tradition of the
• 45:07
  Speaker 3: peer review and open forum has has really propelled us
• 45:13
  Speaker 3: to where we are today and it's going to continue.
• 45:16
  Speaker 3: And I think the collaboration and openness will better serve
• 45:20
  Speaker 3: our end customers for so the transparency is important. And
• 45:25
  Speaker 3: I think with all of those beliefs, I mean, I
• 45:27
  Speaker 3: think we don't have we don't have the crystal ball
• 45:30
  Speaker 3: to say, like what's gonna what the police frameworkwork is
• 45:32
  Speaker 3: gonna be, Like what is a coate geopolitical tension it's
• 45:34
  Speaker 3: going to be like in the next one or two years.
• 45:37
  Speaker 3: But we have the belief that human kind of our
• 45:41
  Speaker 3: collective work will converge in a direction that serves our
• 45:46
  Speaker 3: humanity in a positive direction. And I think that's uh,
• 45:49
  Speaker 3: that's kind of where I'd like to uh to see
• 45:52
  Speaker 3: that that's ultimately that's gonna what's going to be implemented
• 45:56
  Speaker 3: and incorporated and under under that type of the world,
• 46:02
  Speaker 3: whether these companies and founders can test a pressure test
• 46:07
  Speaker 3: to sustain and I think that's how I see and
• 46:10
  Speaker 3: when I evaluate the companies, how it's going to sustain
• 46:13
  Speaker 3: those kind of policy changes.
• 46:15
  Speaker 2: All right, So before we get to our speed round,
• 46:17
  Speaker 2: let me ask you one last question, which is what
• 46:20
  Speaker 2: do you think in investors in the AI space are
• 46:24
  Speaker 2: either not thinking about or not talking about, but is
• 46:27
  Speaker 2: important and perhaps they really should be paying attention to.
• 46:34
  Speaker 3: I think that the saying that says we are very
• 46:37
  Speaker 3: at the very early inning means a lot. I hear
• 46:42
  Speaker 3: someone even saying that we are still in the car
• 46:44
  Speaker 3: getting to the stadium. You're not even in the first inning.
• 46:49
  Speaker 3: That means all this kind of the models, models and
• 46:53
  Speaker 3: structures can change significantly, can evolve over time, and nothing
• 47:01
  Speaker 3: cannot be seen as kind of engraved in a stone.
• 47:08
  Speaker 3: So with that, I think a lot of the investment
• 47:11
  Speaker 3: decisions has to be reflecting the fact that there it
• 47:18
  Speaker 3: kind of has to remain like a nimble and flexible
• 47:20
  Speaker 3: because we should be able to adjust to when those
• 47:24
  Speaker 3: changes and new breakthroughs come around.
• 47:27
  Speaker 2: All right, So I only have you for a few minutes,
• 47:29
  Speaker 2: so we'll click through these really quickly. Our speed round.
• 47:32
  Speaker 2: Starting with who your early mentors who helped to shape.
• 47:36
  Speaker 3: Your career, I would say, I mean, I think I
• 47:40
  Speaker 3: was fortunate enough to have a lot of mentors when
• 47:44
  Speaker 3: I was a student, But one person that stands out
• 47:47
  Speaker 3: is Dominic Barton, who was the global menting partner at
• 47:52
  Speaker 3: McKinsey when I first started out as an associate of McKinsey.
• 47:57
  Speaker 3: He had his office was right next to mine, so
• 48:01
  Speaker 3: he was literally my mentor. And I think I learned
• 48:04
  Speaker 3: a lot from him as a as a leader and
• 48:09
  Speaker 3: as a as a mentor. And I think it's still today.
• 48:14
  Speaker 3: I reach out to him if I have to make
• 48:16
  Speaker 3: tough decisions, and I think he has been always very
• 48:19
  Speaker 3: generous with his time, so I really appreciate.
• 48:22
  Speaker 2: Let's talk about books. What are some of your favorites?
• 48:24
  Speaker 2: What are you reading right now?
• 48:26
  Speaker 3: Oh? So I read a lot of books, but I
• 48:28
  Speaker 3: think I kind of read many books of the type
• 48:32
  Speaker 3: that I read many books that kind of simultaneously one
• 48:35
  Speaker 3: chapter here and then I go to another book. But
• 48:38
  Speaker 3: the book that I recommend to everyone these days is
• 48:41
  Speaker 3: our two but one is the Empire of AI and
• 48:46
  Speaker 3: the other is Power and Progress. And I think that
• 48:49
  Speaker 3: those books kind of help us understand the dynamics of
• 48:53
  Speaker 3: what's happening and what we need to think about as
• 48:55
  Speaker 3: a society.
• 48:56
  Speaker 2: So let's talk about streaming. What are you either listening
• 48:59
  Speaker 2: to or watching these days?
• 49:01
  Speaker 3: So, I mean I listened to I listened to music
• 49:07
  Speaker 3: through like Spotify a lot. My son is a big
• 49:11
  Speaker 3: fan of Taylor Swift. I have to listen to Taylor
• 49:15
  Speaker 3: Swift like when I'm in a car, like driving a lot.
• 49:21
  Speaker 3: Also I watched k Drama on Netflix.
• 49:23
  Speaker 2: Really really interesting. Our final two questions, what sort of
• 49:27
  Speaker 2: advice would you give to a recent college graduate interest
• 49:31
  Speaker 2: in the career in either artificial intelligence, fest thing or gaming.
• 49:38
  Speaker 3: I mean, I think it kids just graduating today. I mean,
• 49:45
  Speaker 3: I think it's a one thing that's not gonna change
• 49:49
  Speaker 3: is it's gonna be very bumpy, and it's gonna be
• 49:51
  Speaker 3: like there's disruptive, and the world they're gonna be working
• 49:55
  Speaker 3: in is not gonna look like the world today. Like
• 49:59
  Speaker 3: that's that's the constant, right, And I mean I think
• 50:03
  Speaker 3: what I would like to remind them is like, don't
• 50:05
  Speaker 3: try to find that kind of follow the trend. Really
• 50:11
  Speaker 3: have to stick to what you're I mean it sounds
• 50:13
  Speaker 3: like a cliche, like what you're passionate about. I mean,
• 50:16
  Speaker 3: you remember in the seventies, the most popular major to
• 50:20
  Speaker 3: go in was what was that was like kind of
• 50:22
  Speaker 3: material science, and then like chemical engineering, and then like
• 50:25
  Speaker 3: electric engineering and computer like just to see that those
• 50:30
  Speaker 3: those the popularity of those major kind of plummeting, Like
• 50:34
  Speaker 3: we have witnesses like so many of those cases. So
• 50:37
  Speaker 3: it doesn't really I don't think it serves well to
• 50:41
  Speaker 3: find what's try to kind of follow that that kind
• 50:44
  Speaker 3: of fashion or trend.
• 50:46
  Speaker 2: Really be a generalist and be flexible.
• 50:50
  Speaker 3: Could be yeah right, yeah, all right.
• 50:52
  Speaker 2: And our final question, what do you know about the
• 50:54
  Speaker 2: world of venture investing and artificial intelligence today? Might have
• 51:00
  Speaker 2: been useful to know twenty years.
• 51:01
  Speaker 3: Ago, I mean, I think the patients so I mean
• 51:07
  Speaker 3: it's also the power of compounding is not just in finance,
• 51:10
  Speaker 3: but also in like human capital and our understanding technology
• 51:16
  Speaker 3: and also the relations too. Like it seems very slow today,
• 51:21
  Speaker 3: but like if it you're persistent and for twenty years,
• 51:26
  Speaker 3: I think that what you can achieve is really tremendous.
• 51:29
  Speaker 2: Well, thank you song Ye for being so generous with
• 51:31
  Speaker 2: your time. We have been speaking with Sung Yi yun,
• 51:35
  Speaker 2: founder and managing partner at Principal Venture Partners. If you
• 51:41
  Speaker 2: enjoyed this conversation, well check out any of the six
• 51:44
  Speaker 2: hundred plus interviews we've done over the past twelve years.
• 51:48
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• 51:55
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• 51:59
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• 52:01
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• 52:06
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• 52:11
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• 52:14
  Speaker 2: listening to Masters and Business on Bloomberg Radio.