From Technology in Focus to Finance with BlackRock's Tony Kim

Barry Ritholtz speaks with Tony Kim, Managing Director and Head of the Fundamental Equities’ Global Technology Team at BlackRock. Prior to joining BlackRock in 2013, Tony held key roles at institutions like Artisan Partners, Neuberger Berman, and Merrill Lynch. He is also a member of the Advisory Board for Columbia Business School’s Digital Future Initiative. On this episode, Barry and Tony discuss the success of passive investing at BlackRock, the general tech investing landscape, and what it takes to build a career that combines a passion for technology with finance.

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Episode Transcript

Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, radio news. This is Master's in
Business with Barry Ridholds on Bloomberg Radio.

Speaker 2 (00:16):
This week on the podcast, another extra special guest. Tony
Kim is Managing director at Blackrock, where he heads the
Fundamental Equity Technology Group, helping to oversee all of the
active technology investments Blackrock makes. In addition to being a
portfolio manager and running a number of mutual funds and ETFs.

(00:37):
He is just a world class technology investor who understands
the sector like few other people do. Not only has
he put up a very impressive track record, his entire
approach to the ecosystem of technology, covering everything from robotics

(00:57):
to AI, to software to semiconduct is really quite fascinating.
If you're at all interested in technology in AI in
the process of thinking about tech investing, then you're going
to find this conversation to be absolutely fascinating. With no
further ado my discussion with black Rocks, Tony.

Speaker 1 (01:20):
Kim, thank you Berry, pleasure to be.

Speaker 2 (01:22):
Here, pleasure to have you. So let's start out with
your background bachelor's in Industrial engineering from University of Illinois
and then an NBA from Columbia. Were there career plans.

Speaker 1 (01:33):
Career plans. Yeah, first of all, thanks for having me
your show titled Masters in Business. I have no Master
in Business.

Speaker 2 (01:42):
Well you have an MBA, so you automatically qualify. Yes,
for sure, that's a master's right.

Speaker 1 (01:47):
Yeah, that's true, that's true. Yeah, the origins of the career.
You know, I grew up in the Midwest, the first
phase of my life and growing up in the eighties
in Illinois, you know, as a I'm from Korea actually,
but so the natural I was a stem kid, and

(02:11):
that that kind of propelled me into the engineering side.
But I always had other interests outside of that. But
the reason I went to Champagne we were all from
state of Illinois, and my siblings and I all went
to school in the state of Illinois, and and I
gravitated initially to engineering and that's kind of that that
that got into that, and then eventually I ended up

(02:33):
in New York and then transitioned into financial.

Speaker 2 (02:36):
Well we're going to talk about that transition in a minute,
but before we get there, you really begin your career
as an engineer at Rockwell Automation. Yeah, what did you
do there?

Speaker 1 (02:46):
This is a first job, right, first job? First real
job out of school. It really it was the first
entree into a company, not only a company a this
was an automation company. It's often known for works with
many industries, but helping automate. We're help. I was working
on projects to automate manufacturing. Uh. They had these things

(03:10):
called plc's, which are basically industrial computers with sensors, with drives,
drive systems, motor control, robotics and all of these things,
and then you package them together and you work with
many different kinds of manufacturing companies in the early days
of automating manufacturing processes across many industries. So that was

(03:32):
my first entree in seeing the diversity of of the
manufacturing base in this country. I was particularly I was
in I was working on the East Coast, and you know,
any everything from like pharmaceutical to automotive to to what
a what a distribution network looked like, what tier one,

(03:53):
tier two kind of systems integrators were with the technology
of audio mating manufacturing. And so we're working on different
projects and see the across a lot of industries. But
I realized I didn't want to, you know, I had
other I had other ambitions, and so this is what

(04:14):
led me to going to graduate school.

Speaker 2 (04:16):
So let's let's talk about some of those other ambitions.
You end up doing investment banking in New York in
the mid nineties. What was the transition from being an
engineer slash operator to an investor? What was that like?

Speaker 1 (04:32):
Well, when I was at when I went to Columbia,
you know, I did the engineer. I worked at an
engineering company, and I thought I wanted something a higher level,
more strategic in nature. I actually thought I wanted to
I wanted to try to get into consulting. That's a classical,

(04:53):
classical role for MBA. None of the consultants would wanted
to hire me. But the somehow the investment banking side
found me or I found them, and it was an
engineering here's a guy from engineering with engineering background. And
you know at the time, those are the early days

(05:13):
of pre dot com and it was a new emerging industry,
and so I think they saw that linkage between some
technical expertise with finance maybe working that with that industry.
So that was But the the finance is what would
pull me in on the investment banking more so than

(05:34):
the consulting because of that angle.

Speaker 2 (05:36):
I think, and your timing was perfect in the every nineties,
great time to be doing I banking and technology. Tell
us about some of the transactions you saw late nineties
early two thousands. What sort of deals were you working on?

Speaker 1 (05:51):
Yeah, just that transition, you know. I was originally hired
by sgu Orber, which was a British investment bank. It
got acquired and then after.

Speaker 2 (05:59):
The that became Warburg Pinkus that.

Speaker 1 (06:02):
Became SBC Warburg and then UBS bot in the UBS
Warburg and then the Warburg name went away. But I
was there right at the time when Warburg was acquired,
and then that transition, I joined Merrill Lynch and then
Merrill Lynch that go West young Man, right, Okay, So.

Speaker 2 (06:24):
I remember Merrill Lynch during the nineteen nineties was absolutely
a powerhouse, or at least became a powerhouse towards the
back half of that decade.

Speaker 1 (06:34):
Yeah, yeah, So it was very much a new thing
for them in the West coast, and so I went
and I still recalled to this day. There were several
of us that were the origins of the m and
a group on the West Coast from Merrill Lynch. In fact,

(06:56):
three of those people twenty some years later we're back
at joined at Blackrock, and I can tell you the
story of that.

Speaker 2 (07:03):
Sure, let's hear that.

Speaker 1 (07:04):
Oh okay, yeah, there were there were There are three
of us that were vps and directors at the M
and a.

Speaker 2 (07:10):
Group was feel free to drop names.

Speaker 1 (07:12):
A guy named Draga Raschkeovic who is now vice chairman
of JP Morgan runs the tech M and a this
guy Michael Leitner, and then myself and then we worked
for this guy named Rob Stewart, and then Mark Schaeffer
above him led the group, but Mike Michael at Tenebau.
Blackrock later acquired them and he was one of the

(07:33):
partners at Tennemo and then recently Blackrock bought g I P.
And then Rob is one of the partners at g
I P. So three of the four of us, Rob, myself,
Michael all ended up at Blackrock and some fans.

Speaker 2 (07:49):
Let's get the band back together.

Speaker 1 (07:52):
Drago did not Dragon still is that Jimmy Morgan right now? So? So,
but those were the original days, and then you know
the transactions. You know, this was pre dot com and
you know the Internet was just getting going.

Speaker 2 (08:05):
Are you talking early nineties.

Speaker 1 (08:08):
Uh, mid midnighties, mid late mid to late nineties.

Speaker 2 (08:11):
Like I remember being on a training desk in ninety
six when the Netscape and I was not allowed to
trade it. When the Netscape IPO happened, that was really
what kicked off a giant explosion. Were you there around
that time?

Speaker 1 (08:27):
Yes, in that time, and these were the deals when
when Cisco was going crazy and there were you know,
there's so many transactions and networking, there was the optical
communications boom, some of the original software and Internet assets,
and so I did transactions in this especially a lot
in the networking telecom. I remember working on one or

(08:49):
two software deals and I did that for a while,
and then then I really I decided to leave investment baking,
which I learned a tremendous amount, especially the you know, putting,
you know, the strategic nature of looking at industries and companies,
and of course all the financial acumen, the rigor of

(09:12):
of doing very intensive financial analysis. But you're always working
into the behest of a client right working on it
was transactional related and and this is when I decided
to go and take a take a career path change
to the investment site.

Speaker 2 (09:30):
So tell us what that transition was like, what is
it like going from transactional M and A on the
West coast to no, I just want to find companies
public and private and invest capital in them.

Speaker 1 (09:44):
Yeah, I think that's that was the transition. The the
financial financial analysis is the same effectively, maybe it's even
more intensive on the on the on the M and
A side, because you're doing much more detailed work. The
way you look at industries and companies are relatively similar.

(10:05):
It's that on the transactional side, you work on projects
for a short duration of time and then you move
on and move on and move on, and hopefully over
time you persist, you have persistence, and you learn more
about about that industry and the domain. When you go
to the investment side. I started as an analyst, I

(10:26):
wasn't you know, And here you are looking at wider
array of companies. You're doing financial analysis, but not as
detailed as you were working on one deal, one transaction
for months at a time and then but you yet
you have persistence because you're able to look at sectors

(10:48):
and industries and companies for a longer period of time consistently,
and so you build deeper domain knowledge. And and so
that was one. The second is that you're no longer
working for a client. You you you are working to
find the best you know, investments and put your own
capital at risk. Right, And so that was a change

(11:13):
of the mindset of how to assess because you're you're
not working really you're not just servicing a client here,
You're putting your own capital at risk. And and you know,
that was the That was the first big change of
just assessing how that works, and then and then going

(11:34):
from and then and then learning many many, many domains.
And then that was the working with many different kinds
of investors, different kinds of investment philosophies. I must have
worked for thirty forty partpillar managers across four four or
five investment firms, and that's that was, Like, I guess

(11:55):
my second era here was to learn the skills of investing.

Speaker 2 (12:01):
Huh, we're going to spend more time on what you've
learned in a little bit. Yeah, you said something I
have to explore a little bit. Sure, it was more
in depth, more intensive on the M and A side
than the investing side. I'm curious as to why the

(12:21):
two ideas that immediately pop into mind. You're covering a
whole lot more companies on the investment side, but one
can help but imagine on the M and A side. Hey,
it's all in. You're taking the whole thing as an investor.
If you buy something and you have second thoughts, well
you sell a few million shares and you're done. You

(12:41):
could walk away with maybe a little worse for the
wear and tear. But when you buy an entire company, Hey,
that's really hard to unwine, that, isn't it.

Speaker 1 (12:50):
Yeah, that's right, you know, and you're buying the whole thing,
or you're representing, or you're selling the whole thing, or
you're selling pieces of it, and you're working on one
company and another company, bee two companies at a time,
and you want to get every number right, every comma,

(13:11):
every nuts and bolts to the as many as much
detail as you can. So the precision and the accuracy
and the information fidelity is much higher because that's what
you're just working on that one company, that one transaction,
versus like you said, you're looking at hundreds of companies

(13:33):
and you can make a decision with the push of
a button and sell or buy, And so the time
spent on that analysis will invariably be less than the
time spent on this one definitive transaction.

Speaker 2 (13:52):
Huh really really interesting. So you've been in black Rock
since twenty thirteen. Obviously passive has been a huge success
for Blackrock. You're on the active side. Is there any
crossover do you get pulled into any discussions from you know,
any of the big black rock ETF sector funds passive indexes?

Speaker 1 (14:17):
So the passive industry, passive part of Blackrock is separate
to the active part. I guess what would be one
trend is that we are also launching many active ETFs,
which is the container in which most of passive funds
are traded at. And then there's like passive decisions, you know,

(14:40):
you know, a lot of the passive index thing is
now an active decision. I guess you could say, if
that's a day it always has been, it always has been, right, Yes.

Speaker 2 (14:49):
It's it's hey, we're gonna make it market cap index.
That's an active decision. We're gonna we're gonna cap Apple
and Vidia Microsoft at right, there's lots of active decisions.
People don't realize there's quite a bit of active in
their passes.

Speaker 1 (15:03):
Yeah, so now we're joining that that party as well.
We have now active ets. We launched two recently, one
on the AI site. So where we fail that dynamism,
especially an industry that is in a rapid change like
an AI, I think you need a lot of adaptation

(15:24):
flexibility because things are changing so rapidly.

Speaker 2 (15:27):
So I want to stay with that. We're going to
talk about the multiple ETFs you actively manage, but generally speaking,
after passive captured more than half of the mutual funds
and ETF assets, there has since been an explosion of
active ETFs as well as mutual funds. Some are thematic,

(15:47):
some are sector based, but they all have in common
that it's not relying on a passive index. What are
your thoughts on the future of active management in the
ETF space.

Speaker 1 (16:02):
Well, I think the future of active management, you know,
as you correctly pointed out, I think there are generic
sections of the market where it is the broad market
exposure SMP. Those I think continue to be under pressure
as it moves to to those passive indices. But you

(16:24):
said something very interesting there. You know, the industry is specialized,
you know, sectors, thematics in the container of an active ETF.
I think that is more representative maybe where the future
of active industry is going where one can express a
differentiated view, and invariably that is a function of specialization,

(16:51):
I think, and of course I'm biased in that because
I am focused on a specialized area, which is the
technology area, and then within the technology are there are
many further subspecializations, and I think those that have broader
depth of domain knowledge hopefully that is the advantage, and

(17:15):
that that gets expressed in an active fund, an ETF
or a mutual fund or whatever. And you know, as
I as, I've been in this technology industry for a
long time. You know, twenty years ago, tech was twenty
percent of the SMP, it's over forty and it's probably
going higher as as now we're entering the AI era,

(17:36):
and so generalists, I think are at information asymmetry disadvantage
to those that have domain specificity. And if you have
better information, better knowledge, hopefully that leads to better decision making,
which is, you know, which will hopefully sustain the active management.

Speaker 2 (17:55):
You know, I'm so glad you said that you think
the technology sector of the S and P five hundred
is going higher. Whenever people say to me, aren't you
concerned that tech is twenty nine percent of the s
and P five hundred or whatever the number happens to be.
My answer is always the magnificent seven are responsible for

(18:16):
something like two and a half trillion dollars in revenue
and five hundred billion dollars in profits. I'm shocked it's
only twenty nine percent. Why isn't it half of the
S and P five hundred. This is what's driving the
economy in the market. Doesn't it deserve a rich evaluation.
I'm curious as to your thoughts on.

Speaker 1 (18:33):
That one hundred percent? Agree? Okay, I agree. You know,
the multiple in aggregate has not changed dramatically, but it
has driven by free cash flow and the forty percent
I quoting is a combination of comm services which they
carved out, which is really a tech company with classic

(18:57):
tech that's over forty percent. And when you look at
the contribution of free cash flow right, which is the
ultimate profit metrics it's followed, it is forty percent of
the free cash flow right. You know the other thing
about tech, I don't think people realize it has represented
the highest growth. It actually has the highest margin. It

(19:19):
is the highest free profitable margin. People think it's unprofitable.
It's like the ninety percent of technive profit. This is
the highest profit margin and the highest free cash flow growth.
And that's what's even the market cap appreciation, that is
the that is not not well understood.

Speaker 2 (19:38):
Fair to say, this is not the late nineties dot
com no, you know, whimsical ideas with hardly any revenue
and no profits. These companies are printing money and are
wildly profitable.

Speaker 1 (19:52):
Yeah, and in fact, I would even make another distinct,
you know, the MAC seven. The most profitable sector in
all the smp any is the semiconductor industry. They even
have higher margins now than the software industry, and the
software industry is amongst the highest. Right, so tech in general,

(20:12):
if you say software and semis are two thirds of
all of tech, right, they have the highest margins in
the world.

Speaker 2 (20:20):
Huh.

Speaker 1 (20:21):
So they have the most profitable companies with the most growth,
which generates the most free cash flow, which generates the returns,
which generates the forty percent of the market cap, which
is and most of those are max of.

Speaker 2 (20:31):
It doesn't sound like a bad.

Speaker 1 (20:33):
Placed place to keep your And now we have AI
and it probably goes higher. It's going to go higher.

Speaker 2 (20:39):
Huh. Fascinating. So we were talking a little bit about
what makes technology so interesting. Share a little bit of
your perspective. How do you go about identifying technologies that
are going to drive future growth and as we've seen
reshape the entire economy.

Speaker 1 (20:59):
You know, I guess I would say first, I'm a deconstructionist.
I like to deconstruct problems, deconstruct any kind of situation,
deconstruct sectors and industries. So I like to break things down.
And then even before breaking them down, and this kind
of goes to my childhood, I always had a fascination love.

Speaker 2 (21:18):
Of maps, maps, maps that's interesting.

Speaker 1 (21:22):
Cartography, ancient maps, and so I would I'd like to
map everything out, and so like the ancient mariners would say,
all the oceans, you'd want a map of where you're
navigating to. And so I start with that. I'd like
to break things down. I break technology down into five
or six major sub sectors, and then we just continually

(21:46):
deconstruct and break those down. And so once you start
breaking these things down, you then create a map of
the whole landscape, the semiconductor and lancecape, internet escape, the
software landscape, et cetera. And continually break things down and
so then they are digestible pieces, and then within those pieces,

(22:09):
then you interrogate all of the technologies that are going.
And so now you have this this giant, giant map
of all of technology, all reconfigured and mapped out, and
then you go into detail. And then this way you start,
it's kind of like a battlefield commander looking at a
giant war map and you see hot spots. This is hot,
this is cold, this is hot, this is cold. And

(22:32):
then you have systematized a way of looking at all
of those different categories and technologies and subsectors, and you
know all the companies that are there, you know the
competitors there, and then you're observing what's hot and what's not.
And so then so that's the current, that's the initial framework,
and so then you you start to see trends that

(22:54):
are that are happening and you think you see other
trends that are that are declining.

Speaker 2 (22:58):
So what's so intriguing about that is we tend to
think of fundamental research CFP type research as very balance
sheet driven. What you're describing something that's much more holistic
and comprehensive. You're you're really looking at the whole echo
system of technology to see what is moving and use

(23:21):
the magic word systematize. How do you systematize that? Is
it just identifying what is on a mathematical basis popping
its head up.

Speaker 1 (23:33):
Yeah, I think if we use AI as a great
framework as a test, as a case study. So if
I were to frame technology industry as we have this
hardware industry, and inside the hardware industry there are many
categories like smartphones and robotics and servers and things, and
then there's a semiconductor industry. There's different kinds of chips, accelerator, chips, memory, chips, foundry, lodge, analog.

(24:01):
And then let's say the software industry, there's security and applications, infrastructure,
et cetera. Once you have mapped all of these things
out and you know where all the companies or all
the bodies are buried, and you know who's competing with
whom and who's working on what. Along comes AI. AI

(24:22):
starts with Chat GPT in GPT three point five in
the end of twenty twenty two, early twenty twenty three,
and it shows up as an application at Chat application. Well,
the first thing you when I saw that, I said, Wow,
this is going to change the world.

Speaker 2 (24:42):
And that was your initial response to the first demonstration,
you sort of chat gbtwo.

Speaker 1 (24:48):
That and having a meeting with Jensen Huang in January
twenty twenty three. Those two things kind of triggered it.
Then once you see that, then you say, okay, how's
this going to cast k through? You know, it's kind
of like in biology there's a thing called I what
I call it trophic cascada, an ecological ecosystem, And then

(25:08):
you say, AI is the trigger. The first thing that
you see it. It's the first representation is well, you
got to build these models, and to build the models,
you need these chips, and so then you go well,
then you interrogate, well you need these kinds of GPUs
and memory and things. Then you say, well then you

(25:29):
need to well those are connected to the packaging systems,
and those packaging systems are connected then to foundries, and
then these foundaries are connected to the wayfer output, which
you need the equipment, and then you start to build
a chain of this is what's needed to build this part,
and then those chips get stonwn in servers and servers

(25:49):
need this whole eco supply chain, and then those servers
get then deployed in clouds, right and these clouds then
need Oh, by the way, these things generate a lot
of electricity, and that's spawned the whole power energy movement.
And then you but then you know what the power
transmission and grid and technical thermal equipment that needs to

(26:10):
power and cool these cloud data centers, and so you
have built that supply chain down. And then and then
after the AI is built, you bring the AI into
into the into business at Bloomberg and Blackrock, and you
bring those into software and then you embed that in
applications and then oh, by the way, that same AI
that's being we'll throw that into the self driving car

(26:33):
and robots. And so once you see that whole chain
and how that gets diffused, and then you have interrogator,
you've already built these maps effectively of every single one
of these little ecosystems and supply chains, and then you
see how diffusion works, and then then you say, well,

(26:55):
is it worth investing in these companies or not? And
that's when then you get into the financial announce Really interesting.

Speaker 2 (27:01):
So I'm hearing infrastructure, which is everything from power to
cloud to database to intelligence which is the modeling, and
then software tools, applications, solutions. So This isn't you know.
I think people tend to think of oh Ai, that's Nvidia.
But what you're really saying is this is dozens of

(27:24):
not hundreds of companies working across a whole ecosystem.

Speaker 1 (27:28):
That's exactly right now in the public stock market. The
first two years the manifestation of what I just describe,
but what you just eloquently described gets expressed in the
Mac seven. You know, if I were to, let's recompile
that as a as a nine layer cake. Okay. At

(27:55):
the bottom of this of this of this cake is
the power and the ender G and then that feeds
these servers and chips, and then those servers and chips
get live in a in a data center cloud. That
whole bottom layer, those three layers is what I call infrastructure. Okay,
So that's why you're seeing most of the MAX seven

(28:17):
are here.

Speaker 2 (28:18):
So that's Google and Amazon and Microsoft and.

Speaker 1 (28:23):
Now Tesla is building AII cloud. And then above that layer,
let's call it uh, that's the models and the data.
So this is where you also have more maximven, Microsoft, Google,
Open Ai, these some of the private companies and now
x Ai. And you know there are six or six

(28:45):
of these companies building these foundation models, and then the
data you're feeding the data. And then you have all
these data companies that have let's say legal data, healthcare data,
insurance data, and then some of them are proprietary data,
which are health being trained these models. Right.

Speaker 2 (29:01):
So we've seen a couple of stories about the Wall
Street Journal and Reuters leasing their entire corpus of all
their content to various AM models to work.

Speaker 1 (29:13):
On correct and you know, companies like Reddit have done
a deal like that Wall Street Journal. There's some lawsuits.

Speaker 2 (29:19):
Even New York Times, well they haven't in some instances
seem to have borrowed stuff that was you know, you
your ninety nine dollars a year subscription to the Washington
Post doesn't entitle you arguably to scrape all that data.
But hey, they're cutting checks and cutting deals, and I
think everybody just wants their piece of the pie.

Speaker 1 (29:40):
That's right. And then there are some companies you mentioned
Thompson Reuters, which was you know, they have they run
one of the one of they have one of their
biggest legal data sets, you know, and they control that
legal data and so then they're putting AI on top
of that. So that's that that's it ellgents and the

(30:00):
data layer, and then above that layer you have the applications,
the tools and data infrastructure, and then the services the
human it labor to implement and to the age.

Speaker 2 (30:12):
Give us some give us some names. I have a
couple of things on my phone.

Speaker 1 (30:15):
What do you like?

Speaker 2 (30:17):
Oh, on the app side, Yeah, I mean I'm using Perplexity.

Speaker 1 (30:20):
Perplexity.

Speaker 2 (30:21):
It's so clean and so simple.

Speaker 1 (30:23):
I love chat GIPT.

Speaker 2 (30:27):
They're slightly differently different, right, just the output, but they're
still and I'm finding far fewer hallucinations than than I
used to. Yes, Like I had Bill Dudley from the
New York fed in who was born in you know,
the late nineteen fifties, and chat GBT mentioned he happened
to be a linebacker for the Detroit Lions in nineteen

(30:49):
fifty two. It took it away, and there was a
guy named Bill Dudley who was It took it a
while for it to figure out, and like, after a
certain period that eventually got clean. Wait, if you're born
in fifty seven, you're probably not a pro football player
in fifty five. But it took it definitely took months, yes,
for it to kind of somehow recognize that.

Speaker 1 (31:12):
Yeah, and that's on the consumer side, and there'll be
a lot more consumer apps coming, you know. You know,
companies like Apple have this Apple intelligence right if anything
in there, absolutely locked in on your private seed. But
they're gonna know you the best, and so there will
be AI assistants coming.

Speaker 2 (31:29):
I hope it'll be better than Siri, which was a
huge disappointment for sure. But I would trust an Apple agent.
You would exactly to be able to say, hey, make
dinner reservations for Friday at this restaurant. Here's my calendar,
and invite Bob Smith and Mary and hopefully it can manage.

Speaker 1 (31:44):
That absolutely and even more things even more difficult. Then
let's say that like, oh, I need to help them,
I need to do my taxes. I want my taxes
help or I need.

Speaker 2 (31:56):
So I'm skeptical on really complex things. And at the
same time, I just read yesterday the latest comparison of
AI diagnostics versus doctors. AI just moved ahead. They moved
ahead on things like X rays and MRIs a while ago. Correct,
but now on here's twenty data points diagnose this illness.

(32:17):
It just moved ahead of the accuracy rate of human
day you.

Speaker 1 (32:23):
Said exactly, the complexity of the tasks will only go
higher in terms of what they will be capable to do.
So and these ais are following these what we call
the scaling laws of scaling intelligence. But the things that
they will be capable of, it's not just booking a restaurant.

(32:44):
It'll be doing very complex tasks. And so we are
just at the very, very very beginning of that.

Speaker 2 (32:50):
Huh, that's really fascinating. So given the mapping you do
of the whole ecosystem and then the dive into the
financial background, what strategies the end do you then use
in saying, Okay, I understand the whole ecosystem, I understand
the various balance sheets of these companies. How do you

(33:12):
then pick which stock you want to own?

Speaker 1 (33:14):
Ah? So I have a certain small you know, rules,
I guess if you could call it that, that I've
I've or observations that I've made over many years, especially
in tech, right because this is a very dynamic industry.
One of those is like, there's a power law. What

(33:36):
I believe in power laws, And it seems like every
industry I've ever looked at, there's number one and number
two and that maybe in number three, so.

Speaker 2 (33:46):
Very fat head, and then a long yeah, minor.

Speaker 1 (33:49):
Let's just say fifty market chair number one, twenty five,
number two, and then cats and dogs, right, winner takes
all go everywhere, and it doesn't matter if you're selling
frozen pizza to search advertising. Okay, these power laws and
then because but the thing is that you could have
power laws that apply to hundreds of categories, right, doesn't

(34:15):
have to be all encompassing in one. And so when
I look at tech and that those all those different categories,
I firmly believe in these power law concepts that you
want to be betting on number one or number two,
especially number one, not even number two. You want number
one ideally, and so are you. And so in many

(34:36):
cases they're already existing players, okay. And so if they
are already existing players and then their their hegemony is
not being challenged, that's kind of an easy answer. You
keep riding the wave. And that's why people are always
complaining about Max seven.

Speaker 2 (34:51):
You anticipated where I was going to go next. Yeah,
what you're essentially saying is Max seven is they're focusing
on the number seven and while ignoring the magnificent side.
You want to be in the number one stock everywhere,
which is going to naturally force the crowd investors to
the top five, ten, fifteen companies.

Speaker 1 (35:13):
That's exactly what's been happening. The strong get stronger unless
unless there are signs of weakness, right there.

Speaker 2 (35:22):
Is it competition, is it missteps by management? Is it
some new disruptive technology that thrusts the winners aside? What
do you look for to say, hey, XYZ has been
killing it for five ten years, but their run is over.

Speaker 1 (35:40):
That's exactly right. Usually, usually these companies do not get disruptive,
but on occasion they do. I think the most obvious
one recently was the ascendency of Nvidia versus Intel for
thirty years Intel read and legion and and then there

(36:02):
was a transition. There are several several reasons, but there
was a transition too to accelerate computing from CPUs and
and then they've lost leadership on foundry to T S
m C and then mobile and they didn't they didn't
engage in mobile. And so there are times there are
times where companies, you know, different different transitions, like if

(36:25):
Microsoft did not pivot to the cloud from Windows right,
and the government you know, went after them on Windows,
but they were they were litigating yesterday's war, right, Microsoft
found Azure and then and then history was rewritten.

Speaker 2 (36:42):
And what do you think of the job Saudia and
the Dalla has been that, you know, people.

Speaker 1 (36:47):
Forget that's got to be one of the great great
great ceo uh and and and what he has mastered
in the history of business.

Speaker 2 (36:55):
Microsoft was dead money for a decade. That sounds ridiculous
to say. I know, people don't remember there not that
Bohmer was a terrible CEO, but he was a founder
and maybe just wasn't nimble enough to see the next generation.
He was, you know, like many founders, they're stuck in
you know Microsoft one point oh, yes, and Nadella is

(37:18):
I don't know, maybe he's three point oh or four
point oh.

Speaker 1 (37:20):
But yeah, definitely he's gotta it's gotta be one of
the greatest unbelieved business turnarounds in history. That doesn't get
that much enough recognition.

Speaker 2 (37:29):
I I totally totally agree.

Speaker 1 (37:32):
So they had this power law concept. Going back to
your idea, The other one is you need a second act.
You know, you need multiple acts. If you even look
at these great companies, right, you know, Microsoft, for example,
you had the Windows and then you had a second
act which is Azure right, and Azure it's been driving
the company, right. Even Apple found the iPhone after Mac right.

(37:56):
And so you need companies that have the Amazon. I
don't even know how many acts they've had so many
different acts, right, And so the great established companies can
continually add multiple new businesses. Not only what you're currently doing.
You got to anticipate the next So these power laws,

(38:16):
do you have, you know, multiple acts, because then that
helps you have duration that you can endure and then
are you differentiated enough? But then there is a whole
new class of companies, right, So there you have the
max seven, these power law companies. But there's always history
for tech has always given you the opportunity for the

(38:37):
new companies, the new companies to come. And so it's
really the combination of let's continue to ride the power
laws of the established companies and then let's find those
new companies that can rise and become the new challenger.
So it's that those two those are the two components
of a technology absolutely fault.

Speaker 2 (39:01):
Before we get into the funds, I really want to
just touch base on two really interesting things you said
earlier one is just generally on the valuation question with
technology and similarly the market concentration of the Magnificent seven.
Share your thoughts on that.

Speaker 1 (39:23):
Yeah, I think valuation right, if I were to broadly say,
is at a fair level. Now there's this dispersion in
that you mentioned the Mac seven and the crowding and
these giant winners. They have valuations that are higher than

(39:43):
the rest of tech. The rest of tech has not,
for the most part, recovered from the depression that we had,
the recession we had in twenty twenty two. They went,
they were way exaggerated in twenty one. You crashed in
twenty two, and there's been not that much of a recovery.

(40:05):
So a large part of tech is still at depressed levels.
I would say we're back to pre you know, twenty
eighteen seventeen levels, except the Max seven and a few
companies like that that have that are at higher levels,
but their performance have been better.

Speaker 2 (40:24):
Right, And you know, it's funny, we still have over
a month ago this year, this could be the first
year the S and P five hundred beats the Nazaq
one hundred in a long time. I'm trying to remember
the last time we saw that.

Speaker 1 (40:39):
Yeah, because a large part of the of the nastach,
especially non Mac seven, they've not done well. You know,
you large parts of software, large parts of semiconductors. Even
if you're not in the AI class, you know you've
been left behind.

Speaker 2 (41:00):
Interesting, So I want to talk about something that you
do with your team. Every year, you conduct a tour
of Silicon Valley. You meet with leaders of both public
and private technology companies, often twenty five thirty different companies
and their senior management. Tell us a little bit about

(41:20):
what that experience is, Like, what do you learn? Does
it actually help you with your investing process?

Speaker 1 (41:27):
Yeah? I think you're referring to our annual every summer
we do a bus tour. Effectively we bring thirty Blackrock investors. Now,
that said, we do, you know, two thousand meetings a
year with companies on my team. Wow, I personally do
almost a thousand meetings with companies. Now, this is a

(41:47):
special event because it pulls together seven, eight, nine, ten
different teams at black Rock, thirty plus execs and investors.
And then we get on a bus and we go
visit the top managements and CEOs both public and private companies.
Every year. This has been I've been running this now

(42:08):
eleven years.

Speaker 2 (42:09):
Wow.

Speaker 1 (42:10):
And what that does is that you know, you're on site.
You know, it's a little it's a little less formal.
The companies feel more comfortable because they're they're hosting you,
and it's and it's really more of a strategic discussions
than relitigating the quarter.

Speaker 2 (42:29):
Right, So it is and much longer term.

Speaker 1 (42:33):
Than yeah yeah, yeah yeah. And then you know, it's
always a great barometer of like what what what were
the topics of the tour in twenty fourteen versus twenty
twenty four and you could really see an evolutionary of
what was topical every year, and it's so it's a

(42:53):
great way. It's also great for the people because many times,
even you know, within a firm like Black Cruct, any
of the teams don't get that much time to be
with each other. So it's both for representing a unified
front to the company and then also within within the
interpersonal relationships that are strengthened. And then it's a really

(43:16):
a great barometer of what are the key topics. And
then if you looked at the last two years of
the bus tour, there's only one topic AI.

Speaker 2 (43:26):
Yeah, so let's go before the previous two years. Give
us some examples of ideas that were surfaced via this
bus tour.

Speaker 1 (43:35):
So I'll give you some specific example. I remember distinctly
there was one about a m d uh huh, when
a MD had just announced its new chiplet based you know,
Jim Keller was still working there, and it was one
of the famed chip designers, and they had redesigned the

(43:57):
processor and the CPU and that Zen architecture was the
basis in which ten years later they've gained all that
market share from Intel. But that was that day, and
I remember because a MD was on its.

Speaker 2 (44:13):
Back perennially, always a laggard, always short of capital, always like, hey,
these guys are going to be here in five years.

Speaker 1 (44:21):
But they made that seminal bet to really change that
chip architecture and that and then another one I remember
distinctly when there was lots of questions around Tesla, right,
can they get the Model three? There they were, they were,
They had warehouse, you know, not even a warehouse, a
tent to make remember that, and everyone was saying twenty four,

(44:45):
it had a tent to make the Model three. And
I think that kind of unlocked. That's like, well, we're
about to We're about to turn, We're about to make it.
This production is about to scale. And that was another
seminal moment. So you have these these events like that
that come through.

Speaker 2 (45:00):
Let me ask you relative to Tesla an echosystem question.
So for the longest time, Tesla had the market all
to itself. Recently I saw a chart that showed for
the first time, Tesla's market share drop below fifty percent,
not because their sales have fallen, but because there are
so many other players in the EV space. I can't

(45:25):
help but give either credit or blame to Jeff Bezos,
who so totally destroyed sector after sector after sector that
when Musk came along, the automobile industry said, hey, we
saw what Amazon did, We better, you know, get our
act together pretty quickly. Any truth to that urban legend, I.

Speaker 1 (45:47):
Would say, in EV just pure EV cars, Tesla's share
and its ascendency the entire market is especially in the US,
especially the West, not China, it's definitely slowed, if not stalled.

Speaker 2 (46:04):
Okay, arguably I had the CEO of Lucid in here
who made a very aggressive claim that whether it was
battery technology motors range software. Tesla was a leader, and
Lucid as as leapfrog them. You could, you can, we
could debate that would but at least but it's a

(46:24):
credible whether it's true or not, it's a credible claim
which would not have been remotely credible five years ago,
even three years ago.

Speaker 1 (46:32):
I would say to that. And I don't want to
comment on that specific company, but you know companies like that,
they're selling one hundred thousand dollars car, right, Tesla selling
it forty thousand dollars car the fifty thousand dollars and
up market is very different. Which is which is most vs? Right?

(46:56):
You know, if you remember you go in the past,
the greatest, the best selling single was like the Toto Corolla,
you know, like a couple million a year, and you
look at Tesla's Model three and Y and they're also
in that range. So basically, if you're in that kind
of category, you get to a certain market level, a

(47:17):
saturation level. And I think that in the West and
then you know, with the more reticence to adopt EV
and still in the United States, you kind of have
a certain ceiling you need. And this is why there's
so much discussion about Tesla either having a lower cost
robotex or lower cost car to get at the market

(47:39):
sub fifty thousand dollars where you have you know that
unlocks some market three times bigger. It's like a thirty
thousand dollars car or twenty five thousand dollars car. But
I think Tesla's main pivot really and even Elon would
will tell you it's not about the car. The car
is a mere means to deliver autonomy, right. And it's

(48:01):
a robotics company, right, It's and and and autonomy is
to meet big onlock, not not selling the car itself.

Speaker 2 (48:09):
That'll be interesting. We've been waiting autonomy for a while.
One can't help but wonder how much easier it would
be if if build into the roads and other vehicles
where some form of our device that allows other cars
to know where here's where the exit is, here's where

(48:32):
the lanes are, here's where other cars are, like, there
could be an infrastructure build out that makes that.

Speaker 1 (48:38):
Have you brought it? When's the last time you were
in La or this year? This year? Okay, did you
see Waymo's running around?

Speaker 2 (48:44):
I did not.

Speaker 1 (48:45):
I did not, So weymo is now operating in Los Angeles,
and they're everywhere in San Francisco, Phoenix, and the futures here.

Speaker 2 (48:55):
It's just it.

Speaker 1 (48:57):
Is, it is, it's within grasps. Finally, it's it's always
been three years in the future, but it really is now.

Speaker 2 (49:02):
I think so. So now let's let's bring this conversation
full circle back to the funds you run. Let's talk
about b I b AI, which is the I shares
AI Innovation and Technology Active ETF. Tell us a little
bit about that. That that's a fairly concentrated portfolio, isn't it.

Speaker 1 (49:21):
That's right, this is we just launched this. This is
our first fora first we have two ETFs. Now we're
jumping on that that ETF bandwagon will.

Speaker 2 (49:33):
Yeah, I think that that might work out a black Yeah,
that's right here, I hear.

Speaker 1 (49:38):
But this this one is you know, I think, you know,
hopefully we look back, uh, this is the second year
of AI as we would as I would say, and
I think this is going to be a decade long,
if not longer, trend, and we are trying to express
in a concentrated way thirty plus companies in an ETF

(50:02):
that represents this whole stack of AI.

Speaker 2 (50:05):
From Nvidia down to the small the.

Speaker 1 (50:07):
Way up to the apps, from the compute to the
apps and everything in between. And I do know one thing.
So we want a concentrated exposure to the builders of AI,
companies building the key elements of AI. And I do
know one thing it will be. It's going to change dramatically.

(50:30):
What we think is the companies that today might not
be and so we need I feel like, especially when
there's high rate of change in the early days of
an industry like this, we need dynamic adaptation. We need
to be flexibly an adaptive and so to lock yourself
into a fixed passive structure versus a dynamically changing structure.

(50:53):
That's really the goal of this ETF.

Speaker 2 (50:55):
Let's talk about I Shares Technology Opportunities Active ETF or
t e K broader portfolio fifty to seventy global tech companies.
Tell us what that focus is.

Speaker 1 (51:06):
That is basically the ETF version of our mutual fund.
And so that includes tech companies, not only ETF, not
only AI companies, but broad tech globally larger companies. But
you know, there's lots of tech companies that don't really
that don't really have that much to do with AI

(51:27):
building AI, and so you're going to get the whole
totality of tech that in that.

Speaker 2 (51:33):
So you said something before that has stayed with me
about looking at the entire map of the ecosystem and
watching what becomes hot and what fades. Technological change today
is just so rapid. It changes at light speed. How
do you keep up? How do you stay aligned with

(51:55):
the industry dynamics as they evolve in real time? It
seems like it's not even quarter to quarter anymore, it's
minute to minute.

Speaker 1 (52:04):
Maybe not minute to minute, but you're you're absolutely right
in AI. So there are different time scales according to the
different industry. So let's say in AI, you're right, it
might literally be minute to minute day to day. Okay.
On the smartphone, you know, things are more staid, they're
slower paced, and so you have a spectrum of rates

(52:30):
of change. That's number one. So number two, how do
we keep keep up? I mean, you know, I've I
read a lot, and not only read. You have to
stay attuned to all this new multimedia. There's so many
experts and podcasts like yours, and and scientists and and

(52:53):
then we do like I do personally a thousand company
meetings a year. That's amazing.

Speaker 2 (52:57):
So that's for a day. You're working fifty weeks a year.

Speaker 1 (53:02):
Yes, I mean yes, I do many, many, many mini
meetings a week. Huh so, and so then you assimilate
all this information and then you are all I'm always
doing the calculus. Who's winning, who's losing, who's winning, who's losing,
what's changing, what's not.

Speaker 2 (53:23):
So how do you balance having a long term perspective
for a technology like AI with you run a fund,
you run a couple of funds. Yeah, you get judged
every quarter. There's a very short term and Wall Street
is notorious for being too short term focused. How do
you manage the tradeoff between hey, this is going to

(53:46):
be a dominant technology over the next five years to
uh oh it's September thirtieth and we know what happens
starting in October. How do you manage that trade off?

Speaker 1 (53:57):
That is the central question because we are being challenged
all the time. You know, I feel you get some
latitude if you have already a historical track record. So
for example, twenty twenty two was just brutal hell on
Earth for tech.

Speaker 2 (54:17):
It was you know, not only was it hell on Earth.
For tech, it was the first year in over forty
years where both stocks and bonds were down double digits,
like once every half century. And then the only saving
grace was twenty twenty one was so spectacular that it
felt like, all right, we're giving back some profits. But

(54:38):
it's not, you know, it didn't feel like it was
seven eight o nine, which was.

Speaker 1 (54:43):
Twenty twenty two was worse than was worse than two
thousand and eight.

Speaker 2 (54:49):
For technology tech, Oh yeah, for sure. Really that's a
big statement.

Speaker 1 (54:53):
Because in two thousand and nine it was a universal collepse,
that's correct. It centered mostly you know, real estate. Tech
went down, of course, but it didn't go down more.
In twenty twenty two, it was predominantly a tech collapse.

Speaker 2 (55:12):
But it wasn't like the dot com implosion where the
nasty one hundred fell eighty plus percent.

Speaker 1 (55:17):
That's right, it wasn't.

Speaker 2 (55:18):
It wasn't, but it was still no fun. You were down, Yeah,
it was down thirty plus percent, lost a third of
its value. That's a big hit.

Speaker 1 (55:26):
But in my in my in my career, twenty twenty
two was the worst year. And so do you have
the latitude and the confidence and support by by investors
and management to allow you to continue, you know, and
and you know, and then obvious the last couple of

(55:49):
years has been good, right and so but do you
does everybody get that avail that opportunity to and that
goes to the short term long term, but I try
not to focus on the short term. And you know,
we're trying to make systematic bets to the best of

(56:09):
our ability with you know, especially an active manager. You
know it is you need to show because we're we
hold generally fewer companies, and you need you need a
couple of years to show that those longer duration bets

(56:30):
start to manifest. And so if I was always chasing
the quarter, you would you know, you're you're now you're
trying to be You're not a momentum trade, you would
yeah or yeah, exactly we And that's really kind of
that at the end, we're saying our decisions that are

(56:50):
born out of all of this domain and expertise and
all of this analytical rigor, and then we express that
for a multi year basis, and then that ultimately comes through.
And if we were to continually shift by the wind
every quarter, you kind of lose your soul effectively of
what you stand for, and so we try not to

(57:11):
do that. Obviously, twenty twenty two we had to make
a lot of adjustments, but other than that, we kind
of stick to that same framework.

Speaker 2 (57:17):
H really fascinating. All right, so I only have you
for another few minutes. Let's jump to our favorite questions.
Okay that we ask all of our guests, starting with
what's keeping you entertained these days? What are you listening
to watching, streaming, et cetera.

Speaker 1 (57:34):
Okay, I don't get the chance to watch that much
TV and streaming, but streaming shows, the ones I've recently
seen I seen. I really like Showgun New one, the
new One, the remake from the from the eighties, or
three Body Problem I enjoyed.

Speaker 2 (57:55):
I love that. I couldn't get through the book, but
the show was great.

Speaker 1 (57:58):
Yeah. And then but I watch a lot more. I'm
a history guy, so I love Epic History on YouTube.
It is absolutely fantastic Epic History Epic History TV. Yeah,
it's fantastic. I watch a lot of science stuff like

(58:18):
World Science Festival of Columbia. Professor here Brian Green. Oh sure, yeah,
I also like chess. I watched like chess.

Speaker 2 (58:28):
You watch chess.

Speaker 1 (58:29):
Yes, I love watching chess so like Chess, Dog is
just a great show, especially the old old matches of
the of the great the great players like Bobby Fisher
and Paul Morphy and things. And the podcast. I think
the best podcast for me is The Ancients.

Speaker 2 (58:46):
The Ancients Ancient.

Speaker 1 (58:48):
This is an ancient civilizations in ancient history. So those
are what Yeah, that's what kind of occupies me. I
don't do as much business shows and buses this pods.
I'll listened to yours a few times and a few others,
but I'm more about you know, I'm in finance all
day long. I don't really need more finance, so I

(59:13):
go for my love of history. It's probably that I.

Speaker 2 (59:17):
Have the same issue. It's like I don't want to
hear a guest I'm going to interview one another show
I want to I don't want to repeat questions or
steal questions. I want to bring a fresh approach, and
when you're immersed in it all day, you just don't
want to go that way. Next question, Yeah, who were
your early mentors who helped to shape your career?

Speaker 1 (59:39):
The you know mentor would imbue a personal one on
one like tutor and tutoring and things. I didn't have
too many of those. I would say my earliest mentors
I go to high school. That's of my formative years
in Illinois. My English teacher who was also my debate coach,

(01:00:02):
my history teacher, and my chemistry teacher. I look back
and they really helped form who I am today. And
then in the professional world, I would say, I go
to and this is like black Rock. When I and
I joined, it was Tom Callen who hired me. And
Tom said, not so much as a mentor, but he said,

(01:00:24):
here are the keys, and you express your creativity and
build the business. And he gave me that latitude. And
so I give credit to Tom Callen. But I didn't
have too many people mentoring me of doing this. It
was more most of my mentors are dead. I have

(01:00:44):
people that I have influenced me, like like Napoleon and
Frank Lloyd Wright and and and Beethoven and others.

Speaker 2 (01:00:54):
So you grew up in Illinois. Did you do any
of the Frank Lloyd Wright tours? Oh?

Speaker 1 (01:01:00):
I did, all right.

Speaker 2 (01:01:00):
So we spent every Thanksgiving and we'll met and so
I've done that whole run. And I have to assume
you've been to.

Speaker 1 (01:01:07):
Falling Waters, right, I've been Falling.

Speaker 2 (01:01:09):
Water, so I I twenty oh really that's on my list.
In twenty seventeen, I bought a car in Indianapolis, flew
out testrovit, signed the papers, drove home, and halfway home
was Falling Waters. And we were there the first day
it was open, and I want to say it was

(01:01:29):
early March and it was like a light coaching. Oh yeah,
we did the whole tour. It's absolutely astonishing, not just
because how delightful the building is, but never before and
probably never since, will a house be so ideally suited
to its surroundings.

Speaker 1 (01:01:49):
It's just absolutely Yeah.

Speaker 2 (01:01:51):
It's always interesting when you see, oh you could see
the thought that went into every curve, every line, every detail.
It's really it's really amazing.

Speaker 1 (01:02:01):
The genesis of that, my interest in architecture. Yeah, I
read The fountain Head. You read the book.

Speaker 2 (01:02:11):
I slogged through it in college and basically gave up
on her because of that book you gave But like that,
it's really such a painful book.

Speaker 1 (01:02:20):
It is, yeah, but it spawned there's some ideas in
it that are interesting. The idea, especially the architecture that
really triggered, oh, architecture.

Speaker 2 (01:02:30):
But so since you mentioned the Fountain Head, let's talk
about books. What are some of your favorites? What are
you reading right now?

Speaker 1 (01:02:37):
Okay, there are certain books that are influential to me.
I was grew up in just people on the show,
they don't I grew up before the Internet.

Speaker 2 (01:02:51):
I don't think we're that far up.

Speaker 1 (01:02:52):
And and I was a nerd. I was a total nerd.

Speaker 2 (01:02:56):
Same and so the.

Speaker 1 (01:02:58):
Lord of the Rings and I knew you were going
to go there. How did you do it?

Speaker 2 (01:03:01):
Because that was the I reread The Hobbit and The
Lord of the Rings every summer throughout my teen year.

Speaker 1 (01:03:06):
Oh my god.

Speaker 2 (01:03:07):
And someone just told me that the character actor who
played Smigele in the movie actually narrates the book on
the audible version. And people have told me it's not
like listening to a book on tape.

Speaker 1 (01:03:23):
It's like a.

Speaker 2 (01:03:24):
Full radio play that he had his voice. That's right,
it's supposed to be fantastic.

Speaker 1 (01:03:31):
Yeah, I even go, Yeah, I loved it. Uh, And
then I went even. I went really deep the Silmarillion
and the twenty thousand year prehistory to the Lord of
the Rings. I went that, how far afield.

Speaker 2 (01:03:42):
Did you go in sci fi? Heinland? Philip K. Dick,
Pride of Strong recommends Pride of Sok just fascinating book.
Give us one or two more books and then we'll.

Speaker 1 (01:03:59):
Currently I'm reading, I read a lot of history books.
I'm reading three books I browse. I read a lot parallel,
and I tend to not to finish it all. But
I'm reading right now Campaigns of Napoleon by David Chandler.
I reading The Fall of Carthage by Adrian Goldsworthy and SPQR.
Mary Beard. And I just bought my sixty Memorable Games

(01:04:21):
by Bobby Fischer. I just wanted to go read.

Speaker 2 (01:04:23):
All did you read? I forgot who the author was,
but there's a great Youngis Khan biography. Oh yes, really interesting.
I could see the book. Yes, But I have one other.
I have a book recommendation.

Speaker 1 (01:04:36):
Okay, you tell me, you tell me, And it's.

Speaker 2 (01:04:38):
Called How to Invent Everything, A Survival Guide to the
Stranded Time Traveler. And it's just a history of technology,
but they use the watch McCall. The cheat is they're
using the guide for time travel as Hey, if you
ever get stuck in ancient history, here are the tools
you can build, and here's how you should do. And

(01:05:00):
it's just just a history of technology ten thousand years
ago to today, absolutely fast, ten thousand years ago, right,
going back to the invention of class.

Speaker 1 (01:05:09):
I have I like to collect some of those ancient artifacts.

Speaker 2 (01:05:12):
Oh, that would be that sounds like fun. All right,
so I only have you for two minutes. You can
get to my last two yes, last questions, like that's
the problem with sci fi geeks?

Speaker 1 (01:05:20):
Yes, okay, I didn't know you're sci fi gee.

Speaker 2 (01:05:22):
Oh absolutely. What sort of advice would you give to
a recent college grad interested in a career in technology investing.

Speaker 1 (01:05:30):
Not so much technology, let's say investing in general. I
think you've got to be a great thinker. It's not
so much the finance. Finance can be taught easy. It's
about thinking, and it is about a flexibility to have

(01:05:51):
a to be reason and plan and think at a
you know, in a kind of a holistic and a
flexible manner. Because AI is going to do so many
of the tasks and and and they will often know
more than you about any specific donain So you need

(01:06:13):
to be above that in a way, almost like an
architect would.

Speaker 2 (01:06:20):
It makes makes a lot of sense and our final question, yes,
what do you know about the world of technology today?
You wish you knew back in the mid nineties when
you were really starting out.

Speaker 1 (01:06:31):
You know, if I knew what how this would unfold
in the Silicon Valley, has it, I would have just
gone straight to Silicon Valley of the company. Maybe maybe
instead of being on the investment side. Huh. I don't know.
It is a it's a double edged question because I
like the I like the dynamic exposure to many companies,

(01:06:55):
but like.

Speaker 2 (01:06:56):
Plus, the path you've taken is so fascinating.

Speaker 1 (01:06:59):
I'll say another point for the young people.

Speaker 2 (01:07:02):
Uh huh.

Speaker 1 (01:07:03):
Always bet on the future, not on the current past.
Bet on the future.

Speaker 2 (01:07:07):
What a great way to wrap this up, Tony, thank
you for being so generous with your time. We have
been speaking with Tony Kim, managing director at Blackrock, where
he heads the Fundamental Equity Technology group. Blackrock manages about
eleven trillion dollars in assets. If you enjoy this conversation, well,

(01:07:28):
be sure and check out any of the five hundred
previous discussions we've had over the past ten years. You
can find those at iTunes, Spotify, YouTube, Bloomberg, wherever you
find your favorite podcast, and be sure and check out
my new podcast, At the Money, short conversations with experts
about topics affecting your money, earning it, spending it, and

(01:07:50):
most of all, investing it. At the Money wherever you
find your favorite podcast and in the Masters in Business
feed I would be remiss if I did not thank
the pract team that helps with these conversations together each week.
My audio engineer is Meredith Frank, My producer is Anna Luke.
Sean Russo is my researcher. Sage Bauman is the head
of Podcasts at Bloomberg. I'm Barry Ridolts. You've been listening

(01:08:14):
to Masters in Business on Bloomberg Radio.