Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Master's in
Speaker 1: Business with Barry Ridholds on Bloomberg Radio.
Speaker 2: This week on the podcast, another extra special guest. Tony
Speaker 2: Kim is Managing director at Blackrock, where he heads the
Speaker 2: Fundamental Equity Technology Group, helping to oversee all of the
Speaker 2: active technology investments Blackrock makes. In addition to being a
Speaker 2: portfolio manager and running a number of mutual funds and ETFs.
Speaker 2: He is just a world class technology investor who understands
Speaker 2: the sector like few other people do. Not only has
Speaker 2: he put up a very impressive track record, his entire
Speaker 2: approach to the ecosystem of technology, covering everything from robotics
Speaker 2: to AI, to software to semiconduct is really quite fascinating.
Speaker 2: If you're at all interested in technology in AI in
Speaker 2: the process of thinking about tech investing, then you're going
Speaker 2: to find this conversation to be absolutely fascinating. With no
Speaker 2: further ado my discussion with black Rocks, Tony.
Speaker 1: Kim, thank you Berry, pleasure to be.
Speaker 2: Here, pleasure to have you. So let's start out with
Speaker 2: your background bachelor's in Industrial engineering from University of Illinois
Speaker 2: and then an NBA from Columbia. Were there career plans.
Speaker 1: Career plans. Yeah, first of all, thanks for having me
Speaker 1: your show titled Masters in Business. I have no Master
Speaker 1: in Business.
Speaker 2: Well you have an MBA, so you automatically qualify. Yes,
Speaker 2: for sure, that's a master's right.
Speaker 1: Yeah, that's true, that's true. Yeah, the origins of the career.
Speaker 1: You know, I grew up in the Midwest, the first
Speaker 1: phase of my life and growing up in the eighties
Speaker 1: in Illinois, you know, as a I'm from Korea actually,
Speaker 1: but so the natural I was a stem kid, and
Speaker 1: that that kind of propelled me into the engineering side.
Speaker 1: But I always had other interests outside of that. But
Speaker 1: the reason I went to Champagne we were all from
Speaker 1: state of Illinois, and my siblings and I all went
Speaker 1: to school in the state of Illinois, and and I
Speaker 1: gravitated initially to engineering and that's kind of that that
Speaker 1: that got into that, and then eventually I ended up
Speaker 1: in New York and then transitioned into financial.
Speaker 2: Well we're going to talk about that transition in a minute,
Speaker 2: but before we get there, you really begin your career
Speaker 2: as an engineer at Rockwell Automation. Yeah, what did you
Speaker 2: do there?
Speaker 1: This is a first job, right, first job? First real
Speaker 1: job out of school. It really it was the first
Speaker 1: entree into a company, not only a company a this
Speaker 1: was an automation company. It's often known for works with
Speaker 1: many industries, but helping automate. We're help. I was working
Speaker 1: on projects to automate manufacturing. Uh. They had these things
Speaker 1: called plc's, which are basically industrial computers with sensors, with drives,
Speaker 1: drive systems, motor control, robotics and all of these things,
Speaker 1: and then you package them together and you work with
Speaker 1: many different kinds of manufacturing companies in the early days
Speaker 1: of automating manufacturing processes across many industries. So that was
Speaker 1: my first entree in seeing the diversity of of the
Speaker 1: manufacturing base in this country. I was particularly I was
Speaker 1: in I was working on the East Coast, and you know,
Speaker 1: any everything from like pharmaceutical to automotive to to what
Speaker 1: a what a distribution network looked like, what tier one,
Speaker 1: tier two kind of systems integrators were with the technology
Speaker 1: of audio mating manufacturing. And so we're working on different
Speaker 1: projects and see the across a lot of industries. But
Speaker 1: I realized I didn't want to, you know, I had
Speaker 1: other I had other ambitions, and so this is what
Speaker 1: led me to going to graduate school.
Speaker 2: So let's let's talk about some of those other ambitions.
Speaker 2: You end up doing investment banking in New York in
Speaker 2: the mid nineties. What was the transition from being an
Speaker 2: engineer slash operator to an investor? What was that like?
Speaker 1: Well, when I was at when I went to Columbia,
Speaker 1: you know, I did the engineer. I worked at an
Speaker 1: engineering company, and I thought I wanted something a higher level,
Speaker 1: more strategic in nature. I actually thought I wanted to
Speaker 1: I wanted to try to get into consulting. That's a classical,
Speaker 1: classical role for MBA. None of the consultants would wanted
Speaker 1: to hire me. But the somehow the investment banking side
Speaker 1: found me or I found them, and it was an
Speaker 1: engineering here's a guy from engineering with engineering background. And
Speaker 1: you know at the time, those are the early days
Speaker 1: of pre dot com and it was a new emerging industry,
Speaker 1: and so I think they saw that linkage between some
Speaker 1: technical expertise with finance maybe working that with that industry.
Speaker 1: So that was But the the finance is what would
Speaker 1: pull me in on the investment banking more so than
Speaker 1: the consulting because of that angle.
Speaker 2: I think, and your timing was perfect in the every nineties,
Speaker 2: great time to be doing I banking and technology. Tell
Speaker 2: us about some of the transactions you saw late nineties
Speaker 2: early two thousands. What sort of deals were you working on?
Speaker 1: Yeah, just that transition, you know. I was originally hired
Speaker 1: by sgu Orber, which was a British investment bank. It
Speaker 1: got acquired and then after.
Speaker 2: The that became Warburg Pinkus that.
Speaker 1: Became SBC Warburg and then UBS bot in the UBS
Speaker 1: Warburg and then the Warburg name went away. But I
Speaker 1: was there right at the time when Warburg was acquired,
Speaker 1: and then that transition, I joined Merrill Lynch and then
Speaker 1: Merrill Lynch that go West young Man, right, Okay, So.
Speaker 2: I remember Merrill Lynch during the nineteen nineties was absolutely
Speaker 2: a powerhouse, or at least became a powerhouse towards the
Speaker 2: back half of that decade.
Speaker 1: Yeah, yeah, So it was very much a new thing
Speaker 1: for them in the West coast, and so I went
Speaker 1: and I still recalled to this day. There were several
Speaker 1: of us that were the origins of the m and
Speaker 1: a group on the West Coast from Merrill Lynch. In fact,
Speaker 1: three of those people twenty some years later we're back
Speaker 1: at joined at Blackrock, and I can tell you the
Speaker 1: story of that.
Speaker 2: Sure, let's hear that.
Speaker 1: Oh okay, yeah, there were there were There are three
Speaker 1: of us that were vps and directors at the M
Speaker 1: and a.
Speaker 2: Group was feel free to drop names.
Speaker 1: A guy named Draga Raschkeovic who is now vice chairman
Speaker 1: of JP Morgan runs the tech M and a this
Speaker 1: guy Michael Leitner, and then myself and then we worked
Speaker 1: for this guy named Rob Stewart, and then Mark Schaeffer
Speaker 1: above him led the group, but Mike Michael at Tenebau.
Speaker 1: Blackrock later acquired them and he was one of the
Speaker 1: partners at Tennemo and then recently Blackrock bought g I P.
Speaker 1: And then Rob is one of the partners at g
Speaker 1: I P. So three of the four of us, Rob, myself,
Speaker 1: Michael all ended up at Blackrock and some fans.
Speaker 2: Let's get the band back together.
Speaker 1: Drago did not Dragon still is that Jimmy Morgan right now? So? So,
Speaker 1: but those were the original days, and then you know
Speaker 1: the transactions. You know, this was pre dot com and
Speaker 1: you know the Internet was just getting going.
Speaker 2: Are you talking early nineties.
Speaker 1: Uh, mid midnighties, mid late mid to late nineties.
Speaker 2: Like I remember being on a training desk in ninety
Speaker 2: six when the Netscape and I was not allowed to
Speaker 2: trade it. When the Netscape IPO happened, that was really
Speaker 2: what kicked off a giant explosion. Were you there around
Speaker 2: that time?
Speaker 1: Yes, in that time, and these were the deals when
Speaker 1: when Cisco was going crazy and there were you know,
Speaker 1: there's so many transactions and networking, there was the optical
Speaker 1: communications boom, some of the original software and Internet assets,
Speaker 1: and so I did transactions in this especially a lot
Speaker 1: in the networking telecom. I remember working on one or
Speaker 1: two software deals and I did that for a while,
Speaker 1: and then then I really I decided to leave investment baking,
Speaker 1: which I learned a tremendous amount, especially the you know, putting,
Speaker 1: you know, the strategic nature of looking at industries and companies,
Speaker 1: and of course all the financial acumen, the rigor of
Speaker 1: of doing very intensive financial analysis. But you're always working
Speaker 1: into the behest of a client right working on it
Speaker 1: was transactional related and and this is when I decided
Speaker 1: to go and take a take a career path change
Speaker 1: to the investment site.
Speaker 2: So tell us what that transition was like, what is
Speaker 2: it like going from transactional M and A on the
Speaker 2: West coast to no, I just want to find companies
Speaker 2: public and private and invest capital in them.
Speaker 1: Yeah, I think that's that was the transition. The the
Speaker 1: financial financial analysis is the same effectively, maybe it's even
Speaker 1: more intensive on the on the on the M and
Speaker 1: A side, because you're doing much more detailed work. The
Speaker 1: way you look at industries and companies are relatively similar.
Speaker 1: It's that on the transactional side, you work on projects
Speaker 1: for a short duration of time and then you move
Speaker 1: on and move on and move on, and hopefully over
Speaker 1: time you persist, you have persistence, and you learn more
Speaker 1: about about that industry and the domain. When you go
Speaker 1: to the investment side. I started as an analyst, I
Speaker 1: wasn't you know, And here you are looking at wider
Speaker 1: array of companies. You're doing financial analysis, but not as
Speaker 1: detailed as you were working on one deal, one transaction
Speaker 1: for months at a time and then but you yet
Speaker 1: you have persistence because you're able to look at sectors
Speaker 1: and industries and companies for a longer period of time consistently,
Speaker 1: and so you build deeper domain knowledge. And and so
Speaker 1: that was one. The second is that you're no longer
Speaker 1: working for a client. You you you are working to
Speaker 1: find the best you know, investments and put your own
Speaker 1: capital at risk. Right, And so that was a change
Speaker 1: of the mindset of how to assess because you're you're
Speaker 1: not working really you're not just servicing a client here,
Speaker 1: You're putting your own capital at risk. And and you know,
Speaker 1: that was the That was the first big change of
Speaker 1: just assessing how that works, and then and then going
Speaker 1: from and then and then learning many many, many domains.
Speaker 1: And then that was the working with many different kinds
Speaker 1: of investors, different kinds of investment philosophies. I must have
Speaker 1: worked for thirty forty partpillar managers across four four or
Speaker 1: five investment firms, and that's that was, Like, I guess
Speaker 1: my second era here was to learn the skills of investing.
Speaker 2: Huh, we're going to spend more time on what you've
Speaker 2: learned in a little bit. Yeah, you said something I
Speaker 2: have to explore a little bit. Sure, it was more
Speaker 2: in depth, more intensive on the M and A side
Speaker 2: than the investing side. I'm curious as to why the
Speaker 2: two ideas that immediately pop into mind. You're covering a
Speaker 2: whole lot more companies on the investment side, but one
Speaker 2: can help but imagine on the M and A side. Hey,
Speaker 2: it's all in. You're taking the whole thing as an investor.
Speaker 2: If you buy something and you have second thoughts, well
Speaker 2: you sell a few million shares and you're done. You
Speaker 2: could walk away with maybe a little worse for the
Speaker 2: wear and tear. But when you buy an entire company, Hey,
Speaker 2: that's really hard to unwine, that, isn't it.
Speaker 1: Yeah, that's right, you know, and you're buying the whole thing,
Speaker 1: or you're representing, or you're selling the whole thing, or
Speaker 1: you're selling pieces of it, and you're working on one
Speaker 1: company and another company, bee two companies at a time,
Speaker 1: and you want to get every number right, every comma,
Speaker 1: every nuts and bolts to the as many as much
Speaker 1: detail as you can. So the precision and the accuracy
Speaker 1: and the information fidelity is much higher because that's what
Speaker 1: you're just working on that one company, that one transaction,
Speaker 1: versus like you said, you're looking at hundreds of companies
Speaker 1: and you can make a decision with the push of
Speaker 1: a button and sell or buy, And so the time
Speaker 1: spent on that analysis will invariably be less than the
Speaker 1: time spent on this one definitive transaction.
Speaker 2: Huh really really interesting. So you've been in black Rock
Speaker 2: since twenty thirteen. Obviously passive has been a huge success
Speaker 2: for Blackrock. You're on the active side. Is there any
Speaker 2: crossover do you get pulled into any discussions from you know,
Speaker 2: any of the big black rock ETF sector funds passive indexes?
Speaker 1: So the passive industry, passive part of Blackrock is separate
Speaker 1: to the active part. I guess what would be one
Speaker 1: trend is that we are also launching many active ETFs,
Speaker 1: which is the container in which most of passive funds
Speaker 1: are traded at. And then there's like passive decisions, you know,
Speaker 1: you know, a lot of the passive index thing is
Speaker 1: now an active decision. I guess you could say, if
Speaker 1: that's a day it always has been, it always has been, right, Yes.
Speaker 2: It's it's hey, we're gonna make it market cap index.
Speaker 2: That's an active decision. We're gonna we're gonna cap Apple
Speaker 2: and Vidia Microsoft at right, there's lots of active decisions.
Speaker 2: People don't realize there's quite a bit of active in
Speaker 2: their passes.
Speaker 1: Yeah, so now we're joining that that party as well.
Speaker 1: We have now active ets. We launched two recently, one
Speaker 1: on the AI site. So where we fail that dynamism,
Speaker 1: especially an industry that is in a rapid change like
Speaker 1: an AI, I think you need a lot of adaptation
Speaker 1: flexibility because things are changing so rapidly.
Speaker 2: So I want to stay with that. We're going to
Speaker 2: talk about the multiple ETFs you actively manage, but generally speaking,
Speaker 2: after passive captured more than half of the mutual funds
Speaker 2: and ETF assets, there has since been an explosion of
Speaker 2: active ETFs as well as mutual funds. Some are thematic,
Speaker 2: some are sector based, but they all have in common
Speaker 2: that it's not relying on a passive index. What are
Speaker 2: your thoughts on the future of active management in the
Speaker 2: ETF space.
Speaker 1: Well, I think the future of active management, you know,
Speaker 1: as you correctly pointed out, I think there are generic
Speaker 1: sections of the market where it is the broad market
Speaker 1: exposure SMP. Those I think continue to be under pressure
Speaker 1: as it moves to to those passive indices. But you
Speaker 1: said something very interesting there. You know, the industry is specialized,
Speaker 1: you know, sectors, thematics in the container of an active ETF.
Speaker 1: I think that is more representative maybe where the future
Speaker 1: of active industry is going where one can express a
Speaker 1: differentiated view, and invariably that is a function of specialization,
Speaker 1: I think, and of course I'm biased in that because
Speaker 1: I am focused on a specialized area, which is the
Speaker 1: technology area, and then within the technology are there are
Speaker 1: many further subspecializations, and I think those that have broader
Speaker 1: depth of domain knowledge hopefully that is the advantage, and
Speaker 1: that that gets expressed in an active fund, an ETF
Speaker 1: or a mutual fund or whatever. And you know, as
Speaker 1: I as, I've been in this technology industry for a
Speaker 1: long time. You know, twenty years ago, tech was twenty
Speaker 1: percent of the SMP, it's over forty and it's probably
Speaker 1: going higher as as now we're entering the AI era,
Speaker 1: and so generalists, I think are at information asymmetry disadvantage
Speaker 1: to those that have domain specificity. And if you have
Speaker 1: better information, better knowledge, hopefully that leads to better decision making,
Speaker 1: which is, you know, which will hopefully sustain the active management.
Speaker 2: You know, I'm so glad you said that you think
Speaker 2: the technology sector of the S and P five hundred
Speaker 2: is going higher. Whenever people say to me, aren't you
Speaker 2: concerned that tech is twenty nine percent of the s
Speaker 2: and P five hundred or whatever the number happens to be.
Speaker 2: My answer is always the magnificent seven are responsible for
Speaker 2: something like two and a half trillion dollars in revenue
Speaker 2: and five hundred billion dollars in profits. I'm shocked it's
Speaker 2: only twenty nine percent. Why isn't it half of the
Speaker 2: S and P five hundred. This is what's driving the
Speaker 2: economy in the market. Doesn't it deserve a rich evaluation.
Speaker 2: I'm curious as to your thoughts on.
Speaker 1: That one hundred percent? Agree? Okay, I agree. You know,
Speaker 1: the multiple in aggregate has not changed dramatically, but it
Speaker 1: has driven by free cash flow and the forty percent
Speaker 1: I quoting is a combination of comm services which they
Speaker 1: carved out, which is really a tech company with classic
Speaker 1: tech that's over forty percent. And when you look at
Speaker 1: the contribution of free cash flow right, which is the
Speaker 1: ultimate profit metrics it's followed, it is forty percent of
Speaker 1: the free cash flow right. You know the other thing
Speaker 1: about tech, I don't think people realize it has represented
Speaker 1: the highest growth. It actually has the highest margin. It
Speaker 1: is the highest free profitable margin. People think it's unprofitable.
Speaker 1: It's like the ninety percent of technive profit. This is
Speaker 1: the highest profit margin and the highest free cash flow growth.
Speaker 1: And that's what's even the market cap appreciation, that is
Speaker 1: the that is not not well understood.
Speaker 2: Fair to say, this is not the late nineties dot
Speaker 2: com no, you know, whimsical ideas with hardly any revenue
Speaker 2: and no profits. These companies are printing money and are
Speaker 2: wildly profitable.
Speaker 1: Yeah, and in fact, I would even make another distinct,
Speaker 1: you know, the MAC seven. The most profitable sector in
Speaker 1: all the smp any is the semiconductor industry. They even
Speaker 1: have higher margins now than the software industry, and the
Speaker 1: software industry is amongst the highest. Right, so tech in general,
Speaker 1: if you say software and semis are two thirds of
Speaker 1: all of tech, right, they have the highest margins in
Speaker 1: the world.
Speaker 2: Huh.
Speaker 1: So they have the most profitable companies with the most growth,
Speaker 1: which generates the most free cash flow, which generates the returns,
Speaker 1: which generates the forty percent of the market cap, which
Speaker 1: is and most of those are max of.
Speaker 2: It doesn't sound like a bad.
Speaker 1: Placed place to keep your And now we have AI
Speaker 1: and it probably goes higher. It's going to go higher.
Speaker 2: Huh. Fascinating. So we were talking a little bit about
Speaker 2: what makes technology so interesting. Share a little bit of
Speaker 2: your perspective. How do you go about identifying technologies that
Speaker 2: are going to drive future growth and as we've seen
Speaker 2: reshape the entire economy.
Speaker 1: You know, I guess I would say first, I'm a deconstructionist.
Speaker 1: I like to deconstruct problems, deconstruct any kind of situation,
Speaker 1: deconstruct sectors and industries. So I like to break things down.
Speaker 1: And then even before breaking them down, and this kind
Speaker 1: of goes to my childhood, I always had a fascination love.
Speaker 2: Of maps, maps, maps that's interesting.
Speaker 1: Cartography, ancient maps, and so I would I'd like to
Speaker 1: map everything out, and so like the ancient mariners would say,
Speaker 1: all the oceans, you'd want a map of where you're
Speaker 1: navigating to. And so I start with that. I'd like
Speaker 1: to break things down. I break technology down into five
Speaker 1: or six major sub sectors, and then we just continually
Speaker 1: deconstruct and break those down. And so once you start
Speaker 1: breaking these things down, you then create a map of
Speaker 1: the whole landscape, the semiconductor and lancecape, internet escape, the
Speaker 1: software landscape, et cetera. And continually break things down and
Speaker 1: so then they are digestible pieces, and then within those pieces,
Speaker 1: then you interrogate all of the technologies that are going.
Speaker 1: And so now you have this this giant, giant map
Speaker 1: of all of technology, all reconfigured and mapped out, and
Speaker 1: then you go into detail. And then this way you start,
Speaker 1: it's kind of like a battlefield commander looking at a
Speaker 1: giant war map and you see hot spots. This is hot,
Speaker 1: this is cold, this is hot, this is cold. And
Speaker 1: then you have systematized a way of looking at all
Speaker 1: of those different categories and technologies and subsectors, and you
Speaker 1: know all the companies that are there, you know the
Speaker 1: competitors there, and then you're observing what's hot and what's not.
Speaker 1: And so then so that's the current, that's the initial framework,
Speaker 1: and so then you you start to see trends that
Speaker 1: are that are happening and you think you see other
Speaker 1: trends that are that are declining.
Speaker 2: So what's so intriguing about that is we tend to
Speaker 2: think of fundamental research CFP type research as very balance
Speaker 2: sheet driven. What you're describing something that's much more holistic
Speaker 2: and comprehensive. You're you're really looking at the whole echo
Speaker 2: system of technology to see what is moving and use
Speaker 2: the magic word systematize. How do you systematize that? Is
Speaker 2: it just identifying what is on a mathematical basis popping
Speaker 2: its head up.
Speaker 1: Yeah, I think if we use AI as a great
Speaker 1: framework as a test, as a case study. So if
Speaker 1: I were to frame technology industry as we have this
Speaker 1: hardware industry, and inside the hardware industry there are many
Speaker 1: categories like smartphones and robotics and servers and things, and
Speaker 1: then there's a semiconductor industry. There's different kinds of chips, accelerator, chips, memory, chips, foundry, lodge, analog.
Speaker 1: And then let's say the software industry, there's security and applications, infrastructure,
Speaker 1: et cetera. Once you have mapped all of these things
Speaker 1: out and you know where all the companies or all
Speaker 1: the bodies are buried, and you know who's competing with
Speaker 1: whom and who's working on what. Along comes AI. AI
Speaker 1: starts with Chat GPT in GPT three point five in
Speaker 1: the end of twenty twenty two, early twenty twenty three,
Speaker 1: and it shows up as an application at Chat application. Well,
Speaker 1: the first thing you when I saw that, I said, Wow,
Speaker 1: this is going to change the world.
Speaker 2: And that was your initial response to the first demonstration,
Speaker 2: you sort of chat gbtwo.
Speaker 1: That and having a meeting with Jensen Huang in January
Speaker 1: twenty twenty three. Those two things kind of triggered it.
Speaker 1: Then once you see that, then you say, okay, how's
Speaker 1: this going to cast k through? You know, it's kind
Speaker 1: of like in biology there's a thing called I what
Speaker 1: I call it trophic cascada, an ecological ecosystem, And then
Speaker 1: you say, AI is the trigger. The first thing that
Speaker 1: you see it. It's the first representation is well, you
Speaker 1: got to build these models, and to build the models,
Speaker 1: you need these chips, and so then you go well,
Speaker 1: then you interrogate, well you need these kinds of GPUs
Speaker 1: and memory and things. Then you say, well then you
Speaker 1: need to well those are connected to the packaging systems,
Speaker 1: and those packaging systems are connected then to foundries, and
Speaker 1: then these foundaries are connected to the wayfer output, which
Speaker 1: you need the equipment, and then you start to build
Speaker 1: a chain of this is what's needed to build this part,
Speaker 1: and then those chips get stonwn in servers and servers
Speaker 1: need this whole eco supply chain, and then those servers
Speaker 1: get then deployed in clouds, right and these clouds then
Speaker 1: need Oh, by the way, these things generate a lot
Speaker 1: of electricity, and that's spawned the whole power energy movement.
Speaker 1: And then you but then you know what the power
Speaker 1: transmission and grid and technical thermal equipment that needs to
Speaker 1: power and cool these cloud data centers, and so you
Speaker 1: have built that supply chain down. And then and then
Speaker 1: after the AI is built, you bring the AI into
Speaker 1: into the into business at Bloomberg and Blackrock, and you
Speaker 1: bring those into software and then you embed that in
Speaker 1: applications and then oh, by the way, that same AI
Speaker 1: that's being we'll throw that into the self driving car
Speaker 1: and robots. And so once you see that whole chain
Speaker 1: and how that gets diffused, and then you have interrogator,
Speaker 1: you've already built these maps effectively of every single one
Speaker 1: of these little ecosystems and supply chains, and then you
Speaker 1: see how diffusion works, and then then you say, well,
Speaker 1: is it worth investing in these companies or not? And
Speaker 1: that's when then you get into the financial announce Really interesting.
Speaker 2: So I'm hearing infrastructure, which is everything from power to
Speaker 2: cloud to database to intelligence which is the modeling, and
Speaker 2: then software tools, applications, solutions. So This isn't you know.
Speaker 2: I think people tend to think of oh Ai, that's Nvidia.
Speaker 2: But what you're really saying is this is dozens of
Speaker 2: not hundreds of companies working across a whole ecosystem.
Speaker 1: That's exactly right now in the public stock market. The
Speaker 1: first two years the manifestation of what I just describe,
Speaker 1: but what you just eloquently described gets expressed in the
Speaker 1: Mac seven. You know, if I were to, let's recompile
Speaker 1: that as a as a nine layer cake. Okay. At
Speaker 1: the bottom of this of this of this cake is
Speaker 1: the power and the ender G and then that feeds
Speaker 1: these servers and chips, and then those servers and chips
Speaker 1: get live in a in a data center cloud. That
Speaker 1: whole bottom layer, those three layers is what I call infrastructure. Okay,
Speaker 1: So that's why you're seeing most of the MAX seven
Speaker 1: are here.
Speaker 2: So that's Google and Amazon and Microsoft and.
Speaker 1: Now Tesla is building AII cloud. And then above that layer,
Speaker 1: let's call it uh, that's the models and the data.
Speaker 1: So this is where you also have more maximven, Microsoft, Google,
Speaker 1: Open Ai, these some of the private companies and now
Speaker 1: x Ai. And you know there are six or six
Speaker 1: of these companies building these foundation models, and then the
Speaker 1: data you're feeding the data. And then you have all
Speaker 1: these data companies that have let's say legal data, healthcare data,
Speaker 1: insurance data, and then some of them are proprietary data,
Speaker 1: which are health being trained these models. Right.
Speaker 2: So we've seen a couple of stories about the Wall
Speaker 2: Street Journal and Reuters leasing their entire corpus of all
Speaker 2: their content to various AM models to work.
Speaker 1: On correct and you know, companies like Reddit have done
Speaker 1: a deal like that Wall Street Journal. There's some lawsuits.
Speaker 2: Even New York Times, well they haven't in some instances
Speaker 2: seem to have borrowed stuff that was you know, you
Speaker 2: your ninety nine dollars a year subscription to the Washington
Speaker 2: Post doesn't entitle you arguably to scrape all that data.
Speaker 2: But hey, they're cutting checks and cutting deals, and I
Speaker 2: think everybody just wants their piece of the pie.
Speaker 1: That's right. And then there are some companies you mentioned
Speaker 1: Thompson Reuters, which was you know, they have they run
Speaker 1: one of the one of they have one of their
Speaker 1: biggest legal data sets, you know, and they control that
Speaker 1: legal data and so then they're putting AI on top
Speaker 1: of that. So that's that that's it ellgents and the
Speaker 1: data layer, and then above that layer you have the applications,
Speaker 1: the tools and data infrastructure, and then the services the
Speaker 1: human it labor to implement and to the age.
Speaker 2: Give us some give us some names. I have a
Speaker 2: couple of things on my phone.
Speaker 1: What do you like?
Speaker 2: Oh, on the app side, Yeah, I mean I'm using Perplexity.
Speaker 1: Perplexity.
Speaker 2: It's so clean and so simple.
Speaker 1: I love chat GIPT.
Speaker 2: They're slightly differently different, right, just the output, but they're
Speaker 2: still and I'm finding far fewer hallucinations than than I
Speaker 2: used to. Yes, Like I had Bill Dudley from the
Speaker 2: New York fed in who was born in you know,
Speaker 2: the late nineteen fifties, and chat GBT mentioned he happened
Speaker 2: to be a linebacker for the Detroit Lions in nineteen
Speaker 2: fifty two. It took it away, and there was a
Speaker 2: guy named Bill Dudley who was It took it a
Speaker 2: while for it to figure out, and like, after a
Speaker 2: certain period that eventually got clean. Wait, if you're born
Speaker 2: in fifty seven, you're probably not a pro football player
Speaker 2: in fifty five. But it took it definitely took months, yes,
Speaker 2: for it to kind of somehow recognize that.
Speaker 1: Yeah, and that's on the consumer side, and there'll be
Speaker 1: a lot more consumer apps coming, you know. You know,
Speaker 1: companies like Apple have this Apple intelligence right if anything
Speaker 1: in there, absolutely locked in on your private seed. But
Speaker 1: they're gonna know you the best, and so there will
Speaker 1: be AI assistants coming.
Speaker 2: I hope it'll be better than Siri, which was a
Speaker 2: huge disappointment for sure. But I would trust an Apple agent.
Speaker 2: You would exactly to be able to say, hey, make
Speaker 2: dinner reservations for Friday at this restaurant. Here's my calendar,
Speaker 2: and invite Bob Smith and Mary and hopefully it can manage.
Speaker 1: That absolutely and even more things even more difficult. Then
Speaker 1: let's say that like, oh, I need to help them,
Speaker 1: I need to do my taxes. I want my taxes
Speaker 1: help or I need.
Speaker 2: So I'm skeptical on really complex things. And at the
Speaker 2: same time, I just read yesterday the latest comparison of
Speaker 2: AI diagnostics versus doctors. AI just moved ahead. They moved
Speaker 2: ahead on things like X rays and MRIs a while ago. Correct,
Speaker 2: but now on here's twenty data points diagnose this illness.
Speaker 2: It just moved ahead of the accuracy rate of human
Speaker 2: day you.
Speaker 1: Said exactly, the complexity of the tasks will only go
Speaker 1: higher in terms of what they will be capable to do.
Speaker 1: So and these ais are following these what we call
Speaker 1: the scaling laws of scaling intelligence. But the things that
Speaker 1: they will be capable of, it's not just booking a restaurant.
Speaker 1: It'll be doing very complex tasks. And so we are
Speaker 1: just at the very, very very beginning of that.
Speaker 2: Huh, that's really fascinating. So given the mapping you do
Speaker 2: of the whole ecosystem and then the dive into the
Speaker 2: financial background, what strategies the end do you then use
Speaker 2: in saying, Okay, I understand the whole ecosystem, I understand
Speaker 2: the various balance sheets of these companies. How do you
Speaker 2: then pick which stock you want to own?
Speaker 1: Ah? So I have a certain small you know, rules,
Speaker 1: I guess if you could call it that, that I've
Speaker 1: I've or observations that I've made over many years, especially
Speaker 1: in tech, right because this is a very dynamic industry.
Speaker 1: One of those is like, there's a power law. What
Speaker 1: I believe in power laws, And it seems like every
Speaker 1: industry I've ever looked at, there's number one and number
Speaker 1: two and that maybe in number three, so.
Speaker 2: Very fat head, and then a long yeah, minor.
Speaker 1: Let's just say fifty market chair number one, twenty five,
Speaker 1: number two, and then cats and dogs, right, winner takes
Speaker 1: all go everywhere, and it doesn't matter if you're selling
Speaker 1: frozen pizza to search advertising. Okay, these power laws and
Speaker 1: then because but the thing is that you could have
Speaker 1: power laws that apply to hundreds of categories, right, doesn't
Speaker 1: have to be all encompassing in one. And so when
Speaker 1: I look at tech and that those all those different categories,
Speaker 1: I firmly believe in these power law concepts that you
Speaker 1: want to be betting on number one or number two,
Speaker 1: especially number one, not even number two. You want number
Speaker 1: one ideally, and so are you. And so in many
Speaker 1: cases they're already existing players, okay. And so if they
Speaker 1: are already existing players and then their their hegemony is
Speaker 1: not being challenged, that's kind of an easy answer. You
Speaker 1: keep riding the wave. And that's why people are always
Speaker 1: complaining about Max seven.
Speaker 2: You anticipated where I was going to go next. Yeah,
Speaker 2: what you're essentially saying is Max seven is they're focusing
Speaker 2: on the number seven and while ignoring the magnificent side.
Speaker 2: You want to be in the number one stock everywhere,
Speaker 2: which is going to naturally force the crowd investors to
Speaker 2: the top five, ten, fifteen companies.
Speaker 1: That's exactly what's been happening. The strong get stronger unless
Speaker 1: unless there are signs of weakness, right there.
Speaker 2: Is it competition, is it missteps by management? Is it
Speaker 2: some new disruptive technology that thrusts the winners aside? What
Speaker 2: do you look for to say, hey, XYZ has been
Speaker 2: killing it for five ten years, but their run is over.
Speaker 1: That's exactly right. Usually, usually these companies do not get disruptive,
Speaker 1: but on occasion they do. I think the most obvious
Speaker 1: one recently was the ascendency of Nvidia versus Intel for
Speaker 1: thirty years Intel read and legion and and then there
Speaker 1: was a transition. There are several several reasons, but there
Speaker 1: was a transition too to accelerate computing from CPUs and
Speaker 1: and then they've lost leadership on foundry to T S
Speaker 1: m C and then mobile and they didn't they didn't
Speaker 1: engage in mobile. And so there are times there are
Speaker 1: times where companies, you know, different different transitions, like if
Speaker 1: Microsoft did not pivot to the cloud from Windows right,
Speaker 1: and the government you know, went after them on Windows,
Speaker 1: but they were they were litigating yesterday's war, right, Microsoft
Speaker 1: found Azure and then and then history was rewritten.
Speaker 2: And what do you think of the job Saudia and
Speaker 2: the Dalla has been that, you know, people.
Speaker 1: Forget that's got to be one of the great great
Speaker 1: great ceo uh and and and what he has mastered
Speaker 1: in the history of business.
Speaker 2: Microsoft was dead money for a decade. That sounds ridiculous
Speaker 2: to say. I know, people don't remember there not that
Speaker 2: Bohmer was a terrible CEO, but he was a founder
Speaker 2: and maybe just wasn't nimble enough to see the next generation.
Speaker 2: He was, you know, like many founders, they're stuck in
Speaker 2: you know Microsoft one point oh, yes, and Nadella is
Speaker 2: I don't know, maybe he's three point oh or four
Speaker 2: point oh.
Speaker 1: But yeah, definitely he's gotta it's gotta be one of
Speaker 1: the greatest unbelieved business turnarounds in history. That doesn't get
Speaker 1: that much enough recognition.
Speaker 2: I I totally totally agree.
Speaker 1: So they had this power law concept. Going back to
Speaker 1: your idea, The other one is you need a second act.
Speaker 1: You know, you need multiple acts. If you even look
Speaker 1: at these great companies, right, you know, Microsoft, for example,
Speaker 1: you had the Windows and then you had a second
Speaker 1: act which is Azure right, and Azure it's been driving
Speaker 1: the company, right. Even Apple found the iPhone after Mac right.
Speaker 1: And so you need companies that have the Amazon. I
Speaker 1: don't even know how many acts they've had so many
Speaker 1: different acts, right, And so the great established companies can
Speaker 1: continually add multiple new businesses. Not only what you're currently doing.
Speaker 1: You got to anticipate the next So these power laws,
Speaker 1: do you have, you know, multiple acts, because then that
Speaker 1: helps you have duration that you can endure and then
Speaker 1: are you differentiated enough? But then there is a whole
Speaker 1: new class of companies, right, So there you have the
Speaker 1: max seven, these power law companies. But there's always history
Speaker 1: for tech has always given you the opportunity for the
Speaker 1: new companies, the new companies to come. And so it's
Speaker 1: really the combination of let's continue to ride the power
Speaker 1: laws of the established companies and then let's find those
Speaker 1: new companies that can rise and become the new challenger.
Speaker 1: So it's that those two those are the two components
Speaker 1: of a technology absolutely fault.
Speaker 2: Before we get into the funds, I really want to
Speaker 2: just touch base on two really interesting things you said
Speaker 2: earlier one is just generally on the valuation question with
Speaker 2: technology and similarly the market concentration of the Magnificent seven.
Speaker 2: Share your thoughts on that.
Speaker 1: Yeah, I think valuation right, if I were to broadly say,
Speaker 1: is at a fair level. Now there's this dispersion in
Speaker 1: that you mentioned the Mac seven and the crowding and
Speaker 1: these giant winners. They have valuations that are higher than
Speaker 1: the rest of tech. The rest of tech has not,
Speaker 1: for the most part, recovered from the depression that we had,
Speaker 1: the recession we had in twenty twenty two. They went,
Speaker 1: they were way exaggerated in twenty one. You crashed in
Speaker 1: twenty two, and there's been not that much of a recovery.
Speaker 1: So a large part of tech is still at depressed levels.
Speaker 1: I would say we're back to pre you know, twenty
Speaker 1: eighteen seventeen levels, except the Max seven and a few
Speaker 1: companies like that that have that are at higher levels,
Speaker 1: but their performance have been better.
Speaker 2: Right, And you know, it's funny, we still have over
Speaker 2: a month ago this year, this could be the first
Speaker 2: year the S and P five hundred beats the Nazaq
Speaker 2: one hundred in a long time. I'm trying to remember
Speaker 2: the last time we saw that.
Speaker 1: Yeah, because a large part of the of the nastach,
Speaker 1: especially non Mac seven, they've not done well. You know,
Speaker 1: you large parts of software, large parts of semiconductors. Even
Speaker 1: if you're not in the AI class, you know you've
Speaker 1: been left behind.
Speaker 2: Interesting, So I want to talk about something that you
Speaker 2: do with your team. Every year, you conduct a tour
Speaker 2: of Silicon Valley. You meet with leaders of both public
Speaker 2: and private technology companies, often twenty five thirty different companies
Speaker 2: and their senior management. Tell us a little bit about
Speaker 2: what that experience is, Like, what do you learn? Does
Speaker 2: it actually help you with your investing process?
Speaker 1: Yeah? I think you're referring to our annual every summer
Speaker 1: we do a bus tour. Effectively we bring thirty Blackrock investors. Now,
Speaker 1: that said, we do, you know, two thousand meetings a
Speaker 1: year with companies on my team. Wow, I personally do
Speaker 1: almost a thousand meetings with companies. Now, this is a
Speaker 1: special event because it pulls together seven, eight, nine, ten
Speaker 1: different teams at black Rock, thirty plus execs and investors.
Speaker 1: And then we get on a bus and we go
Speaker 1: visit the top managements and CEOs both public and private companies.
Speaker 1: Every year. This has been I've been running this now
Speaker 1: eleven years.
Speaker 2: Wow.
Speaker 1: And what that does is that you know, you're on site.
Speaker 1: You know, it's a little it's a little less formal.
Speaker 1: The companies feel more comfortable because they're they're hosting you,
Speaker 1: and it's and it's really more of a strategic discussions
Speaker 1: than relitigating the quarter.
Speaker 2: Right, So it is and much longer term.
Speaker 1: Than yeah yeah, yeah yeah. And then you know, it's
Speaker 1: always a great barometer of like what what what were
Speaker 1: the topics of the tour in twenty fourteen versus twenty
Speaker 1: twenty four and you could really see an evolutionary of
Speaker 1: what was topical every year, and it's so it's a
Speaker 1: great way. It's also great for the people because many times,
Speaker 1: even you know, within a firm like Black Cruct, any
Speaker 1: of the teams don't get that much time to be
Speaker 1: with each other. So it's both for representing a unified
Speaker 1: front to the company and then also within within the
Speaker 1: interpersonal relationships that are strengthened. And then it's a really
Speaker 1: a great barometer of what are the key topics. And
Speaker 1: then if you looked at the last two years of
Speaker 1: the bus tour, there's only one topic AI.
Speaker 2: Yeah, so let's go before the previous two years. Give
Speaker 2: us some examples of ideas that were surfaced via this
Speaker 2: bus tour.
Speaker 1: So I'll give you some specific example. I remember distinctly
Speaker 1: there was one about a m d uh huh, when
Speaker 1: a MD had just announced its new chiplet based you know,
Speaker 1: Jim Keller was still working there, and it was one
Speaker 1: of the famed chip designers, and they had redesigned the
Speaker 1: processor and the CPU and that Zen architecture was the
Speaker 1: basis in which ten years later they've gained all that
Speaker 1: market share from Intel. But that was that day, and
Speaker 1: I remember because a MD was on its.
Speaker 2: Back perennially, always a laggard, always short of capital, always like, hey,
Speaker 2: these guys are going to be here in five years.
Speaker 1: But they made that seminal bet to really change that
Speaker 1: chip architecture and that and then another one I remember
Speaker 1: distinctly when there was lots of questions around Tesla, right,
Speaker 1: can they get the Model three? There they were, they were,
Speaker 1: They had warehouse, you know, not even a warehouse, a
Speaker 1: tent to make remember that, and everyone was saying twenty four,
Speaker 1: it had a tent to make the Model three. And
Speaker 1: I think that kind of unlocked. That's like, well, we're
Speaker 1: about to We're about to turn, We're about to make it.
Speaker 1: This production is about to scale. And that was another
Speaker 1: seminal moment. So you have these these events like that
Speaker 1: that come through.
Speaker 2: Let me ask you relative to Tesla an echosystem question.
Speaker 2: So for the longest time, Tesla had the market all
Speaker 2: to itself. Recently I saw a chart that showed for
Speaker 2: the first time, Tesla's market share drop below fifty percent,
Speaker 2: not because their sales have fallen, but because there are
Speaker 2: so many other players in the EV space. I can't
Speaker 2: help but give either credit or blame to Jeff Bezos,
Speaker 2: who so totally destroyed sector after sector after sector that
Speaker 2: when Musk came along, the automobile industry said, hey, we
Speaker 2: saw what Amazon did, We better, you know, get our
Speaker 2: act together pretty quickly. Any truth to that urban legend, I.
Speaker 1: Would say, in EV just pure EV cars, Tesla's share
Speaker 1: and its ascendency the entire market is especially in the US,
Speaker 1: especially the West, not China, it's definitely slowed, if not stalled.
Speaker 2: Okay, arguably I had the CEO of Lucid in here
Speaker 2: who made a very aggressive claim that whether it was
Speaker 2: battery technology motors range software. Tesla was a leader, and
Speaker 2: Lucid as as leapfrog them. You could, you can, we
Speaker 2: could debate that would but at least but it's a
Speaker 2: credible whether it's true or not, it's a credible claim
Speaker 2: which would not have been remotely credible five years ago,
Speaker 2: even three years ago.
Speaker 1: I would say to that. And I don't want to
Speaker 1: comment on that specific company, but you know companies like that,
Speaker 1: they're selling one hundred thousand dollars car, right, Tesla selling
Speaker 1: it forty thousand dollars car the fifty thousand dollars and
Speaker 1: up market is very different. Which is which is most vs? Right?
Speaker 1: You know, if you remember you go in the past,
Speaker 1: the greatest, the best selling single was like the Toto Corolla,
Speaker 1: you know, like a couple million a year, and you
Speaker 1: look at Tesla's Model three and Y and they're also
Speaker 1: in that range. So basically, if you're in that kind
Speaker 1: of category, you get to a certain market level, a
Speaker 1: saturation level. And I think that in the West and
Speaker 1: then you know, with the more reticence to adopt EV
Speaker 1: and still in the United States, you kind of have
Speaker 1: a certain ceiling you need. And this is why there's
Speaker 1: so much discussion about Tesla either having a lower cost
Speaker 1: robotex or lower cost car to get at the market
Speaker 1: sub fifty thousand dollars where you have you know that
Speaker 1: unlocks some market three times bigger. It's like a thirty
Speaker 1: thousand dollars car or twenty five thousand dollars car. But
Speaker 1: I think Tesla's main pivot really and even Elon would
Speaker 1: will tell you it's not about the car. The car
Speaker 1: is a mere means to deliver autonomy, right. And it's
Speaker 1: a robotics company, right, It's and and and autonomy is
Speaker 1: to meet big onlock, not not selling the car itself.
Speaker 2: That'll be interesting. We've been waiting autonomy for a while.
Speaker 2: One can't help but wonder how much easier it would
Speaker 2: be if if build into the roads and other vehicles
Speaker 2: where some form of our device that allows other cars
Speaker 2: to know where here's where the exit is, here's where
Speaker 2: the lanes are, here's where other cars are, like, there
Speaker 2: could be an infrastructure build out that makes that.
Speaker 1: Have you brought it? When's the last time you were
Speaker 1: in La or this year? This year? Okay, did you
Speaker 1: see Waymo's running around?
Speaker 2: I did not.
Speaker 1: I did not, So weymo is now operating in Los Angeles,
Speaker 1: and they're everywhere in San Francisco, Phoenix, and the futures here.
Speaker 2: It's just it.
Speaker 1: Is, it is, it's within grasps. Finally, it's it's always
Speaker 1: been three years in the future, but it really is now.
Speaker 2: I think so. So now let's let's bring this conversation
Speaker 2: full circle back to the funds you run. Let's talk
Speaker 2: about b I b AI, which is the I shares
Speaker 2: AI Innovation and Technology Active ETF. Tell us a little
Speaker 2: bit about that. That that's a fairly concentrated portfolio, isn't it.
Speaker 1: That's right, this is we just launched this. This is
Speaker 1: our first fora first we have two ETFs. Now we're
Speaker 1: jumping on that that ETF bandwagon will.
Speaker 2: Yeah, I think that that might work out a black Yeah,
Speaker 2: that's right here, I hear.
Speaker 1: But this this one is you know, I think, you know,
Speaker 1: hopefully we look back, uh, this is the second year
Speaker 1: of AI as we would as I would say, and
Speaker 1: I think this is going to be a decade long,
Speaker 1: if not longer, trend, and we are trying to express
Speaker 1: in a concentrated way thirty plus companies in an ETF
Speaker 1: that represents this whole stack of AI.
Speaker 2: From Nvidia down to the small the.
Speaker 1: Way up to the apps, from the compute to the
Speaker 1: apps and everything in between. And I do know one thing.
Speaker 1: So we want a concentrated exposure to the builders of AI,
Speaker 1: companies building the key elements of AI. And I do
Speaker 1: know one thing it will be. It's going to change dramatically.
Speaker 1: What we think is the companies that today might not
Speaker 1: be and so we need I feel like, especially when
Speaker 1: there's high rate of change in the early days of
Speaker 1: an industry like this, we need dynamic adaptation. We need
Speaker 1: to be flexibly an adaptive and so to lock yourself
Speaker 1: into a fixed passive structure versus a dynamically changing structure.
Speaker 1: That's really the goal of this ETF.
Speaker 2: Let's talk about I Shares Technology Opportunities Active ETF or
Speaker 2: t e K broader portfolio fifty to seventy global tech companies.
Speaker 2: Tell us what that focus is.
Speaker 1: That is basically the ETF version of our mutual fund.
Speaker 1: And so that includes tech companies, not only ETF, not
Speaker 1: only AI companies, but broad tech globally larger companies. But
Speaker 1: you know, there's lots of tech companies that don't really
Speaker 1: that don't really have that much to do with AI
Speaker 1: building AI, and so you're going to get the whole
Speaker 1: totality of tech that in that.
Speaker 2: So you said something before that has stayed with me
Speaker 2: about looking at the entire map of the ecosystem and
Speaker 2: watching what becomes hot and what fades. Technological change today
Speaker 2: is just so rapid. It changes at light speed. How
Speaker 2: do you keep up? How do you stay aligned with
Speaker 2: the industry dynamics as they evolve in real time? It
Speaker 2: seems like it's not even quarter to quarter anymore, it's
Speaker 2: minute to minute.
Speaker 1: Maybe not minute to minute, but you're you're absolutely right
Speaker 1: in AI. So there are different time scales according to the
Speaker 1: different industry. So let's say in AI, you're right, it
Speaker 1: might literally be minute to minute day to day. Okay.
Speaker 1: On the smartphone, you know, things are more staid, they're
Speaker 1: slower paced, and so you have a spectrum of rates
Speaker 1: of change. That's number one. So number two, how do
Speaker 1: we keep keep up? I mean, you know, I've I
Speaker 1: read a lot, and not only read. You have to
Speaker 1: stay attuned to all this new multimedia. There's so many
Speaker 1: experts and podcasts like yours, and and scientists and and
Speaker 1: then we do like I do personally a thousand company
Speaker 1: meetings a year. That's amazing.
Speaker 2: So that's for a day. You're working fifty weeks a year.
Speaker 1: Yes, I mean yes, I do many, many, many mini
Speaker 1: meetings a week. Huh so, and so then you assimilate
Speaker 1: all this information and then you are all I'm always
Speaker 1: doing the calculus. Who's winning, who's losing, who's winning, who's losing,
Speaker 1: what's changing, what's not.
Speaker 2: So how do you balance having a long term perspective
Speaker 2: for a technology like AI with you run a fund,
Speaker 2: you run a couple of funds. Yeah, you get judged
Speaker 2: every quarter. There's a very short term and Wall Street
Speaker 2: is notorious for being too short term focused. How do
Speaker 2: you manage the tradeoff between hey, this is going to
Speaker 2: be a dominant technology over the next five years to
Speaker 2: uh oh it's September thirtieth and we know what happens
Speaker 2: starting in October. How do you manage that trade off?
Speaker 1: That is the central question because we are being challenged
Speaker 1: all the time. You know, I feel you get some
Speaker 1: latitude if you have already a historical track record. So
Speaker 1: for example, twenty twenty two was just brutal hell on
Speaker 1: Earth for tech.
Speaker 2: It was you know, not only was it hell on Earth.
Speaker 2: For tech, it was the first year in over forty
Speaker 2: years where both stocks and bonds were down double digits,
Speaker 2: like once every half century. And then the only saving
Speaker 2: grace was twenty twenty one was so spectacular that it
Speaker 2: felt like, all right, we're giving back some profits. But
Speaker 2: it's not, you know, it didn't feel like it was
Speaker 2: seven eight o nine, which was.
Speaker 1: Twenty twenty two was worse than was worse than two
Speaker 1: thousand and eight.
Speaker 2: For technology tech, Oh yeah, for sure. Really that's a
Speaker 2: big statement.
Speaker 1: Because in two thousand and nine it was a universal collepse,
Speaker 1: that's correct. It centered mostly you know, real estate. Tech
Speaker 1: went down, of course, but it didn't go down more.
Speaker 1: In twenty twenty two, it was predominantly a tech collapse.
Speaker 2: But it wasn't like the dot com implosion where the
Speaker 2: nasty one hundred fell eighty plus percent.
Speaker 1: That's right, it wasn't.
Speaker 2: It wasn't, but it was still no fun. You were down, Yeah,
Speaker 2: it was down thirty plus percent, lost a third of
Speaker 2: its value. That's a big hit.
Speaker 1: But in my in my in my career, twenty twenty
Speaker 1: two was the worst year. And so do you have
Speaker 1: the latitude and the confidence and support by by investors
Speaker 1: and management to allow you to continue, you know, and
Speaker 1: and you know, and then obvious the last couple of
Speaker 1: years has been good, right and so but do you
Speaker 1: does everybody get that avail that opportunity to and that
Speaker 1: goes to the short term long term, but I try
Speaker 1: not to focus on the short term. And you know,
Speaker 1: we're trying to make systematic bets to the best of
Speaker 1: our ability with you know, especially an active manager. You
Speaker 1: know it is you need to show because we're we
Speaker 1: hold generally fewer companies, and you need you need a
Speaker 1: couple of years to show that those longer duration bets
Speaker 1: start to manifest. And so if I was always chasing
Speaker 1: the quarter, you would you know, you're you're now you're
Speaker 1: trying to be You're not a momentum trade, you would
Speaker 1: yeah or yeah, exactly we And that's really kind of
Speaker 1: that at the end, we're saying our decisions that are
Speaker 1: born out of all of this domain and expertise and
Speaker 1: all of this analytical rigor, and then we express that
Speaker 1: for a multi year basis, and then that ultimately comes through.
Speaker 1: And if we were to continually shift by the wind
Speaker 1: every quarter, you kind of lose your soul effectively of
Speaker 1: what you stand for, and so we try not to
Speaker 1: do that. Obviously, twenty twenty two we had to make
Speaker 1: a lot of adjustments, but other than that, we kind
Speaker 1: of stick to that same framework.
Speaker 2: H really fascinating. All right, so I only have you
Speaker 2: for another few minutes. Let's jump to our favorite questions.
Speaker 2: Okay that we ask all of our guests, starting with
Speaker 2: what's keeping you entertained these days? What are you listening
Speaker 2: to watching, streaming, et cetera.
Speaker 1: Okay, I don't get the chance to watch that much
Speaker 1: TV and streaming, but streaming shows, the ones I've recently
Speaker 1: seen I seen. I really like Showgun New one, the
Speaker 1: new One, the remake from the from the eighties, or
Speaker 1: three Body Problem I enjoyed.
Speaker 2: I love that. I couldn't get through the book, but
Speaker 2: the show was great.
Speaker 1: Yeah. And then but I watch a lot more. I'm
Speaker 1: a history guy, so I love Epic History on YouTube.
Speaker 1: It is absolutely fantastic Epic History Epic History TV. Yeah,
Speaker 1: it's fantastic. I watch a lot of science stuff like
Speaker 1: World Science Festival of Columbia. Professor here Brian Green. Oh sure, yeah,
Speaker 1: I also like chess. I watched like chess.
Speaker 2: You watch chess.
Speaker 1: Yes, I love watching chess so like Chess, Dog is
Speaker 1: just a great show, especially the old old matches of
Speaker 1: the of the great the great players like Bobby Fisher
Speaker 1: and Paul Morphy and things. And the podcast. I think
Speaker 1: the best podcast for me is The Ancients.
Speaker 2: The Ancients Ancient.
Speaker 1: This is an ancient civilizations in ancient history. So those
Speaker 1: are what Yeah, that's what kind of occupies me. I
Speaker 1: don't do as much business shows and buses this pods.
Speaker 1: I'll listened to yours a few times and a few others,
Speaker 1: but I'm more about you know, I'm in finance all
Speaker 1: day long. I don't really need more finance, so I
Speaker 1: go for my love of history. It's probably that I.
Speaker 2: Have the same issue. It's like I don't want to
Speaker 2: hear a guest I'm going to interview one another show
Speaker 2: I want to I don't want to repeat questions or
Speaker 2: steal questions. I want to bring a fresh approach, and
Speaker 2: when you're immersed in it all day, you just don't
Speaker 2: want to go that way. Next question, Yeah, who were
Speaker 2: your early mentors who helped to shape your career?
Speaker 1: The you know mentor would imbue a personal one on
Speaker 1: one like tutor and tutoring and things. I didn't have
Speaker 1: too many of those. I would say my earliest mentors
Speaker 1: I go to high school. That's of my formative years
Speaker 1: in Illinois. My English teacher who was also my debate coach,
Speaker 1: my history teacher, and my chemistry teacher. I look back
Speaker 1: and they really helped form who I am today. And
Speaker 1: then in the professional world, I would say, I go
Speaker 1: to and this is like black Rock. When I and
Speaker 1: I joined, it was Tom Callen who hired me. And
Speaker 1: Tom said, not so much as a mentor, but he said,
Speaker 1: here are the keys, and you express your creativity and
Speaker 1: build the business. And he gave me that latitude. And
Speaker 1: so I give credit to Tom Callen. But I didn't
Speaker 1: have too many people mentoring me of doing this. It
Speaker 1: was more most of my mentors are dead. I have
Speaker 1: people that I have influenced me, like like Napoleon and
Speaker 1: Frank Lloyd Wright and and and Beethoven and others.
Speaker 2: So you grew up in Illinois. Did you do any
Speaker 2: of the Frank Lloyd Wright tours? Oh?
Speaker 1: I did, all right.
Speaker 2: So we spent every Thanksgiving and we'll met and so
Speaker 2: I've done that whole run. And I have to assume
Speaker 2: you've been to.
Speaker 1: Falling Waters, right, I've been Falling.
Speaker 2: Water, so I I twenty oh really that's on my list.
Speaker 2: In twenty seventeen, I bought a car in Indianapolis, flew
Speaker 2: out testrovit, signed the papers, drove home, and halfway home
Speaker 2: was Falling Waters. And we were there the first day
Speaker 2: it was open, and I want to say it was
Speaker 2: early March and it was like a light coaching. Oh yeah,
Speaker 2: we did the whole tour. It's absolutely astonishing, not just
Speaker 2: because how delightful the building is, but never before and
Speaker 2: probably never since, will a house be so ideally suited
Speaker 2: to its surroundings.
Speaker 1: It's just absolutely Yeah.
Speaker 2: It's always interesting when you see, oh you could see
Speaker 2: the thought that went into every curve, every line, every detail.
Speaker 2: It's really it's really amazing.
Speaker 1: The genesis of that, my interest in architecture. Yeah, I
Speaker 1: read The fountain Head. You read the book.
Speaker 2: I slogged through it in college and basically gave up
Speaker 2: on her because of that book you gave But like that,
Speaker 2: it's really such a painful book.
Speaker 1: It is, yeah, but it spawned there's some ideas in
Speaker 1: it that are interesting. The idea, especially the architecture that
Speaker 1: really triggered, oh, architecture.
Speaker 2: But so since you mentioned the Fountain Head, let's talk
Speaker 2: about books. What are some of your favorites? What are
Speaker 2: you reading right now?
Speaker 1: Okay, there are certain books that are influential to me.
Speaker 1: I was grew up in just people on the show,
Speaker 1: they don't I grew up before the Internet.
Speaker 2: I don't think we're that far up.
Speaker 1: And and I was a nerd. I was a total nerd.
Speaker 2: Same and so the.
Speaker 1: Lord of the Rings and I knew you were going
Speaker 1: to go there. How did you do it?
Speaker 2: Because that was the I reread The Hobbit and The
Speaker 2: Lord of the Rings every summer throughout my teen year.
Speaker 1: Oh my god.
Speaker 2: And someone just told me that the character actor who
Speaker 2: played Smigele in the movie actually narrates the book on
Speaker 2: the audible version. And people have told me it's not
Speaker 2: like listening to a book on tape.
Speaker 1: It's like a.
Speaker 2: Full radio play that he had his voice. That's right,
Speaker 2: it's supposed to be fantastic.
Speaker 1: Yeah, I even go, Yeah, I loved it. Uh, And
Speaker 1: then I went even. I went really deep the Silmarillion
Speaker 1: and the twenty thousand year prehistory to the Lord of
Speaker 1: the Rings. I went that, how far afield.
Speaker 2: Did you go in sci fi? Heinland? Philip K. Dick,
Speaker 2: Pride of Strong recommends Pride of Sok just fascinating book.
Speaker 2: Give us one or two more books and then we'll.
Speaker 1: Currently I'm reading, I read a lot of history books.
Speaker 1: I'm reading three books I browse. I read a lot parallel,
Speaker 1: and I tend to not to finish it all. But
Speaker 1: I'm reading right now Campaigns of Napoleon by David Chandler.
Speaker 1: I reading The Fall of Carthage by Adrian Goldsworthy and SPQR.
Speaker 1: Mary Beard. And I just bought my sixty Memorable Games
Speaker 1: by Bobby Fischer. I just wanted to go read.
Speaker 2: All did you read? I forgot who the author was,
Speaker 2: but there's a great Youngis Khan biography. Oh yes, really interesting.
Speaker 2: I could see the book. Yes, But I have one other.
Speaker 2: I have a book recommendation.
Speaker 1: Okay, you tell me, you tell me, And it's.
Speaker 2: Called How to Invent Everything, A Survival Guide to the
Speaker 2: Stranded Time Traveler. And it's just a history of technology,
Speaker 2: but they use the watch McCall. The cheat is they're
Speaker 2: using the guide for time travel as Hey, if you
Speaker 2: ever get stuck in ancient history, here are the tools
Speaker 2: you can build, and here's how you should do. And
Speaker 2: it's just just a history of technology ten thousand years
Speaker 2: ago to today, absolutely fast, ten thousand years ago, right,
Speaker 2: going back to the invention of class.
Speaker 1: I have I like to collect some of those ancient artifacts.
Speaker 2: Oh, that would be that sounds like fun. All right,
Speaker 2: so I only have you for two minutes. You can
Speaker 2: get to my last two yes, last questions, like that's
Speaker 2: the problem with sci fi geeks?
Speaker 1: Yes, okay, I didn't know you're sci fi gee.
Speaker 2: Oh absolutely. What sort of advice would you give to
Speaker 2: a recent college grad interested in a career in technology investing.
Speaker 1: Not so much technology, let's say investing in general. I
Speaker 1: think you've got to be a great thinker. It's not
Speaker 1: so much the finance. Finance can be taught easy. It's
Speaker 1: about thinking, and it is about a flexibility to have
Speaker 1: a to be reason and plan and think at a
Speaker 1: you know, in a kind of a holistic and a
Speaker 1: flexible manner. Because AI is going to do so many
Speaker 1: of the tasks and and and they will often know
Speaker 1: more than you about any specific donain So you need
Speaker 1: to be above that in a way, almost like an
Speaker 1: architect would.
Speaker 2: It makes makes a lot of sense and our final question, yes,
Speaker 2: what do you know about the world of technology today?
Speaker 2: You wish you knew back in the mid nineties when
Speaker 2: you were really starting out.
Speaker 1: You know, if I knew what how this would unfold
Speaker 1: in the Silicon Valley, has it, I would have just
Speaker 1: gone straight to Silicon Valley of the company. Maybe maybe
Speaker 1: instead of being on the investment side. Huh. I don't know.
Speaker 1: It is a it's a double edged question because I
Speaker 1: like the I like the dynamic exposure to many companies,
Speaker 1: but like.
Speaker 2: Plus, the path you've taken is so fascinating.
Speaker 1: I'll say another point for the young people.
Speaker 2: Uh huh.
Speaker 1: Always bet on the future, not on the current past.
Speaker 1: Bet on the future.
Speaker 2: What a great way to wrap this up, Tony, thank
Speaker 2: you for being so generous with your time. We have
Speaker 2: been speaking with Tony Kim, managing director at Blackrock, where
Speaker 2: he heads the Fundamental Equity Technology group. Blackrock manages about
Speaker 2: eleven trillion dollars in assets. If you enjoy this conversation, well,
Speaker 2: be sure and check out any of the five hundred
Speaker 2: previous discussions we've had over the past ten years. You
Speaker 2: can find those at iTunes, Spotify, YouTube, Bloomberg, wherever you
Speaker 2: find your favorite podcast, and be sure and check out
Speaker 2: my new podcast, At the Money, short conversations with experts
Speaker 2: about topics affecting your money, earning it, spending it, and
Speaker 2: most of all, investing it. At the Money wherever you
Speaker 2: find your favorite podcast and in the Masters in Business
Speaker 2: feed I would be remiss if I did not thank
Speaker 2: the pract team that helps with these conversations together each week.
Speaker 2: My audio engineer is Meredith Frank, My producer is Anna Luke.
Speaker 2: Sean Russo is my researcher. Sage Bauman is the head
Speaker 2: of Podcasts at Bloomberg. I'm Barry Ridolts. You've been listening
Speaker 2: to Masters in Business on Bloomberg Radio.