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

An episode of [Masters in Business](https://invisiblenetwork.ai/podcast/730188152), 3 Apr 2026, 53 min.

Audio: https://podtrac.com/pts/redirect.mp3/traffic.omny.fm/d/clips/e73c998e-6e60-432f-8610-ae210140c5b1/4e4cd910-40a1-4619-a5f3-ae2b0012ffff/5663fa2c-306a-4c99-9906-b420016a4f44/audio.mp3?utm_source=Podcast&in_playlist=5873a3cb-298f-40bc-b71f-ae2b0013000d

Barry speaks with founder and managing partner of Principal Venture Partners. They discuss her venture firm's focus on AI-native companies, and understanding technological innovation. They also discuss the tech investment landscape and how she determines which companies are native to AI and which are chasing the boom. See omnystudio.com/listener for privacy information.

## Transcript

[0:02] Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Masters in
[0:11] Speaker 1: Business with Barry Ritholts on Bloomberg Radio on.
[0:16] Speaker 2: The latest Masters in Business podcast. My conversation with Song
[0:20] Speaker 2: Yi Yun. She is founder and managing partner at Principal Ventures,
[0:26] Speaker 2: an AI focused venture capital investment firm. She has a fascinating,
[0:31] Speaker 2: fascinating background all sorts of MIT Corporation Advisory Board, fifty
[0:38] Speaker 2: Women to Watch in Business from the Wall Street Journal,
[0:42] Speaker 2: named to the advisory board for the Center for Asia
[0:45] Speaker 2: Pacific Policy as well as the National Academy of Engineering
[0:50] Speaker 2: of Korea. She has a fascinating background in gaming, telecom
[0:55] Speaker 2: and AI. I found this conversation to be fascinating, and
[0:58] Speaker 2: I think you will also with no further ado, my
[1:01] Speaker 2: discussion with Principal Ventures. Sang Yi you that is quite
[1:07] Speaker 2: a CV. I went through. Let's roll back though to
[1:11] Speaker 2: where it all began. You get a bachelor's in science
[1:15] Speaker 2: from Korea's Advanced Institute of Science and Technology and then
[1:19] Speaker 2: a PhD in computational neuroscience from MIT. That's such a
[1:26] Speaker 2: fascinating area. What was the original career plan?
[1:31] Speaker 3: That's a very good question. I mean, I think growing
[1:36] Speaker 3: up in South Korea. I didn't know what are the
[1:38] Speaker 3: career options that I had. I just really enjoyed learning
[1:42] Speaker 3: science and engineering subject So when I was young, I
[1:49] 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,
[1:58] Speaker 3: But like speaking to computers and programming was very natural
[2:02] Speaker 3: to me. So I started programming when I was nine,
[2:05] Speaker 3: and that led me to major in electrical engineering as
[2:09] Speaker 3: an undergrad at CHIST. And along the way, I realized
[2:14] 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,
[2:20] Speaker 3: you need to understand how human brain works. So for example,
[2:24] Speaker 3: I was studying signal processing algorithm, and those signal processing
[2:29] Speaker 3: algorithms are look best to your eyes when it's not
[2:34] Speaker 3: necessarily mathematically the best, but take into consideration what frequencies
[2:39] Speaker 3: most sensitive to human eyes. So understanding human brain and
[2:44] Speaker 3: human perception will enable you become a better engineer. So
[2:48] Speaker 3: I was kind of exploring what would be the subject
[2:51] Speaker 3: or kind of the major that I can pursue to
[2:54] Speaker 3: have a better good understanding both engineering and human brain.
[2:59] Speaker 3: And that was that led me to study competition and
[3:03] Speaker 3: re science that I might say.
[3:03] Speaker 2: So computational neuroscience isn't so much about using computers to
[3:08] Speaker 2: understand people as opposed to understanding as opposed to understanding
[3:12] Speaker 2: neuroscience to create better software, better interfaces, better human interaction
[3:18] Speaker 2: with technology.
[3:19] Speaker 3: Is that rare? Exactly? Yeah, that's right.
[3:21] Speaker 2: Huh so pretty fascinating. Early in your career, you're at
[3:25] Speaker 2: McKenzie for a few years and then you eventually move
[3:27] Speaker 2: into SK telecom. Tell us your focus at both places.
[3:32] Speaker 3: Yeah, So, I mean, I think after after my PhD,
[3:35] Speaker 3: I wanted to go into the instead of staying in academia,
[3:40] Speaker 3: I wanted to go into the business world, and going
[3:43] Speaker 3: to McKinsey was the kind of the best way to
[3:45] Speaker 3: transition from being a being a PhD student to go
[3:52] Speaker 3: into the real world. So it was a really fascinating
[3:57] Speaker 3: experience for me, very fast paced, able to work with
[4:02] Speaker 3: big conglomerates and the leaders of the businesses and in
[4:05] Speaker 3: the areas of strategy and corporate finance, et cetera. And
[4:11] 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,
[4:24] Speaker 3: it was an interesting transition, just like we see today
[4:26] Speaker 3: because in two G della communication is all about voice communication,
[4:32] Speaker 3: and three G what was promised was the data transmission
[4:36] Speaker 3: including videos and images and high fidelity audios.
[4:41] Speaker 2: If I'm remembering correctly, it was voice and text, and
[4:45] Speaker 2: then it was image and some video and eventually what
[4:49] Speaker 2: was it for G five G was full Internet, right right.
[4:52] Speaker 3: Yeah, that's right. So as Telcos are one of the
[4:58] Speaker 3: big CAPEX investors in making that transition, and we're thinking
[5:04] Speaker 3: about how we can do the content delivery in the
[5:07] Speaker 3: most personal personalized content delivery was one of the challenges
[5:12] Speaker 3: that requires artificial intelligence and like a data data driven
[5:18] Speaker 3: delivery system. So I thought that was an interesting challenge
[5:21] Speaker 3: to take on. So I moved to SKA Telecom to
[5:25] Speaker 3: lead that effort, and.
[5:26] Speaker 2: Then you end up at NCSoft where you're president and
[5:30] Speaker 2: chief strategy officer. I'm curious what those experiences taught you,
[5:36] Speaker 2: not just about corporate governance and culture, but just these
[5:42] Speaker 2: big institutions that tend to have legacy technology. You know,
[5:46] Speaker 2: there tends to be some group that really wants to
[5:49] Speaker 2: move forward rapidly and adapt all the latest greatest tech
[5:53] Speaker 2: and then another group that hey, this is expensive, what's
[5:56] Speaker 2: the what's the ROI in this? How did you find
[5:59] Speaker 2: yourself navigating a big telecom like sk or a small
[6:05] Speaker 2: or more nimble gaming company like NCSoft.
[6:09] Speaker 3: Yeah, I mean that's a really great question, and I
[6:11] Speaker 3: think it's learned to be persistent and resilient and patient
[6:17] Speaker 3: in both places. I was criticized for, like ask suggesting
[6:22] Speaker 3: something that was not the norm at the time. So,
[6:25] Speaker 3: for example, when I was an NCSoft, one of the
[6:28] Speaker 3: things that I it was very obvious to me was
[6:31] Speaker 3: it was full of data in gaming, the businesses and
[6:34] Speaker 3: like all offered in a distised form. You have transaction data,
[6:39] Speaker 3: you have a behavior data of the gamers and everything.
[6:41] Speaker 3: So it was possible to do a lot of things
[6:44] Speaker 3: on the data driven way, which is very kind of
[6:48] Speaker 3: not today it's it's it's a lot of the companies
[6:51] Speaker 3: are doing it, But back then it was it was
[6:55] Speaker 3: not very common to have understanding in both gaming business
[6:59] Speaker 3: and as well as kind of AI and kind of
[7:02] Speaker 3: data driven business business process modeling. So when I suggested
[7:07] Speaker 3: things like, oh, like it's let's do a small thing
[7:11] Speaker 3: like like charm prediction, because you can you can see
[7:13] Speaker 3: the customer player behavior within the game and see how
[7:17] Speaker 3: much they're engaged, and you can predict if that player
[7:20] Speaker 3: is about to turn out or continue with a with
[7:23] Speaker 3: a game, and some kind of interventions could help them
[7:27] Speaker 3: stay engaged with a game. So that was the one
[7:30] Speaker 3: application areas that I didn't identify it which could be
[7:33] Speaker 3: very straightforward, but then I was told, like there is
[7:36] Speaker 3: a strong pushback from the developers and even the business people.
[7:40] Speaker 3: They said, oh, you're saying it because you don't understand
[7:42] Speaker 3: a gaming business. You're you're you're saying you're a kind
[7:45] Speaker 3: of a you're not a heavy gamer in or whatever, but.
[7:48] Speaker 2: You understand, hey, because this as much to acquire a
[7:52] Speaker 2: client or a gamer, and if we see this behavior,
[7:56] Speaker 2: a five percentage of those folks are tapping out, what
[7:59] Speaker 2: can we do to keep in and paying monthly fees?
[8:01] Speaker 3: Right right? Exactly. Yeah, So even with a very clear
[8:04] Speaker 3: data and the case presented, it was not an easy
[8:10] Speaker 3: task to have get everyone's buy in. But I think
[8:13] Speaker 3: it gradually. Just the reason I kind of mentioned that
[8:17] Speaker 3: tangible example was a small, very tangible area that we
[8:20] Speaker 3: can apply to technology and once you show the success,
[8:23] Speaker 3: I think there is a gradually one by one we're
[8:25] Speaker 3: able to adopt integrate that into our business process to
[8:30] Speaker 3: end up having a large AI lab that does like
[8:34] Speaker 3: all of those things in a more centralized way.
[8:37] Speaker 2: So what I'm hearing from you is very systems oriented framework,
[8:40] Speaker 2: both for gaming and telecom. I know the big mobile
[8:45] Speaker 2: companies in the US are constantly fighting their own churn rate.
[8:50] Speaker 2: So having a top down systems approach sounds like you
[8:53] Speaker 2: could be really proactive in terms of maintaining clients. You
[9:00] Speaker 2: would think there's buy in from everybody, but it sounds
[9:02] Speaker 2: like there's a little salesmanship involved to get everybody behind
[9:08] Speaker 2: that that approach.
[9:09] Speaker 3: Right, yeah, right, yeah.
[9:11] Speaker 2: So let's talk a little bit about what's going on
[9:16] Speaker 2: in the world of AI. I've heard you discuss various
[9:20] Speaker 2: things that are just short term hype. How do you
[9:23] Speaker 2: figure out when you're evaluating an AI system, either for
[9:29] Speaker 2: an investment or just to use the technology in a company,
[9:33] Speaker 2: how do you figure out what's valuable and what's just hype?
[9:37] Speaker 2: What are you looking at?
[9:39] Speaker 3: I mean, I think we talk a lot about hype
[9:41] Speaker 3: cycle and kind of bubble being built up in this
[9:45] Speaker 3: in this kind of AI era, but I think it's
[9:47] Speaker 3: not unheard of them in every platform shift, there was
[9:54] Speaker 3: overcapacity built, not just in AI infrastructure, but it happened
[9:59] Speaker 3: with inter like fiber optics.
[10:02] Speaker 2: Railroad, pelgram, wherever you go.
[10:04] Speaker 3: So there's always a kind of excess capacity that's built,
[10:08] Speaker 3: and I think that's when people what people are pointing
[10:11] Speaker 3: to is that is that area that there is some
[10:13] Speaker 3: kind of bubble built up. But on the other hand,
[10:17] Speaker 3: if you talk about application of the technology, if you
[10:20] Speaker 3: find the application and real business problems that you can
[10:25] Speaker 3: apply this technology to solve, to be more efficient or
[10:30] Speaker 3: bring out some insights that humans were not able to
[10:33] Speaker 3: do it, And I think there is a great area
[10:35] Speaker 3: to apply the technology, and I think there are so
[10:38] Speaker 3: many of them out there. So that's why we are
[10:41] Speaker 3: so excited about the development technology and the prospect of
[10:46] Speaker 3: it going forward.
[10:47] Speaker 2: So I've heard you discuss various priorities, whether it's a
[10:51] Speaker 2: corporate entity pursuing upgrading their AI infrastructure or you know,
[10:59] Speaker 2: just tot AI native startup. You talk about durability, defensibility,
[11:05] Speaker 2: real world impact. Explain what those three things mean.
[11:10] Speaker 3: So in making in kind of making that adoption of
[11:17] Speaker 3: the technology, there are there are two ways to think
[11:19] Speaker 3: about it. One is adopting the technology without really changing
[11:25] Speaker 3: the current work process, right, So you can, for example,
[11:29] Speaker 3: there are a lot of talk about co pilot or
[11:31] Speaker 3: like augmenting what we do make it faster like a search,
[11:35] Speaker 3: and if those things are necessarily changing our current established workflow,
[11:40] Speaker 3: but you are fully embracing what the technology can do
[11:43] Speaker 3: to make you more productive and efficient. So that's the
[11:46] Speaker 3: kind of one way of applying it, and I think
[11:49] Speaker 3: there will be some amount of the ry that will
[11:52] Speaker 3: be realized from such approaches. And the other is complete
[11:56] Speaker 3: redesign of the workflow. And I think that's a that's
[11:59] Speaker 3: a that's kind of we're a very early stage of
[12:03] Speaker 3: like kind of witnessing that, but I think that will
[12:06] Speaker 3: be a more interesting area to look out for and
[12:10] Speaker 3: could be more tremendous transformation and the value created from
[12:14] Speaker 3: such effort.
[12:15] Speaker 2: So tell us what you did at NCSoft, because a
[12:18] Speaker 2: lot of the work you put in there was about
[12:21] Speaker 2: transforming them to use AI. Was it, Hey, we're just
[12:25] Speaker 2: going to make all our developers and gamers and everybody
[12:29] Speaker 2: else a little more efficient, a little more productive or
[12:31] Speaker 2: did this require a clean sheet rethink of everything that
[12:36] Speaker 2: the company was doing.
[12:37] Speaker 3: Yeah, I mean I think it was like fifteen years ago,
[12:41] Speaker 3: and I think it's back then, I think technology was
[12:43] Speaker 3: not ready to fully redesign the game development work workflow.
[12:48] Speaker 3: But I think back then it was more of augmenting
[12:50] Speaker 3: the existing process. So for example, like we did things
[12:54] Speaker 3: like the marketing and Trump prediction and more efficiently we
[12:58] Speaker 3: had NLP that's design signed for Gamer, specialized for Gamer language.
[13:03] Speaker 3: Like we had augmenting, the animation tool that helps animators
[13:09] Speaker 3: to animate not just by pedal creatures, but like four
[13:13] 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
[13:20] Speaker 3: more focused on augmenting existing processes back then. But I
[13:23] Speaker 3: think the technology has advanced and matured today that I
[13:28] Speaker 3: think that there are more opportunities to kind of completely
[13:33] Speaker 3: redesign and come up with a new type of AI
[13:35] Speaker 3: native companies. So I see like an AI native entertainment
[13:39] Speaker 3: firms that we're thinking about what do you mean by
[13:42] Speaker 3: new type of entertainment? New type of engagement that's different
[13:45] Speaker 3: from polishing and like making higher fidelity graphics and games,
[13:51] Speaker 3: but like a completely new form of entertainment using fully
[13:54] Speaker 3: embracing the technology that we have today.
[13:56] Speaker 2: So I keep reading that Claude is writing its own
[14:00] Speaker 2: code and updating its own code. If you were at
[14:04] Speaker 2: a gaming shop today, I'm assuming, do you replace coders?
[14:11] Speaker 2: Do you have copilot work with coders? It was a
[14:14] Speaker 2: Wall Street Journal article last week. I think it was
[14:16] Speaker 2: Wall Street Journal. It could have been wired about coders
[14:20] Speaker 2: in Silicon Valley are just kind of sitting around watching
[14:24] Speaker 2: Claude rewrite their code. What is going on in the
[14:28] Speaker 2: world of software development now that Claude is capable of
[14:33] Speaker 2: updating itself.
[14:34] Speaker 3: Yeah, I think it's a really fascinating I think a
[14:36] Speaker 3: lot of the coding is done using tools like a Claude,
[14:41] Speaker 3: and it certainly makes it more efficient and like productive,
[14:46] Speaker 3: which means that we need a lot less people in
[14:49] 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
[14:57] Speaker 3: just kind of I think there are a certain area
[15:00] Speaker 3: area is that AI coders can do better, But there
[15:03] Speaker 3: are other areas that these more kind of heavy hand,
[15:07] 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
[15:15] Speaker 3: work and how it kind of is going to be
[15:19] Speaker 3: implemented in providing them kind of engaging experience as for gamers.
[15:26] Speaker 2: So my bias is that the humans are very creative
[15:30] 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
[15:40] Speaker 2: and some of the interesting novel gaming. I don't know
[15:45] Speaker 2: what to call it. I guess it's a narrative storyline.
[15:48] Speaker 2: Is that what people going to focus on, and just
[15:51] Speaker 2: the blocking and tackling, just the daily grind of putting
[15:54] Speaker 2: code into place we're going to let ai use. Is
[15:58] Speaker 2: that a today thing or is that a next you know,
[16:00] Speaker 2: is that going to change over the next couple of
[16:02] Speaker 2: decades or years.
[16:05] Speaker 3: I think that's a really good question. I think it's
[16:07] 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.
[16:17] 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
[16:26] 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
[16:46] 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.
[17:55] 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.
[20:33] 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] Speaker 2: You can find those at iTunes, podcasts, Spotify, YouTube, Bloomberg,
[51:55] Speaker 2: wherever you find your favorite podcasts. I would be remiss
[51:59] Speaker 2: if I didn't thank the Craft team that helps us
[52:01] Speaker 2: put these conversations together each week. Alexis Noriega is my
[52:06] Speaker 2: video producer. Anna Luke is my podcast producer. Jean Russo
[52:11] Speaker 2: is my head of research. I'm Barry Rittolts. You've been
[52:14] Speaker 2: listening to Masters and Business on Bloomberg Radio.

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