From Technology in Focus to Finance with Tony Kim
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That's BloombergLive.com slash invest. Bloomberg Audio Studios. Podcasts, radio, news. This is Masters in Business with Barry Ritholtz on Bloomberg Radio.

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.

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

technology, covering everything from robotics to AI to software to semiconductors 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 BlackRock's

Tony Kim. Thank you, Barry. Pleasure to be 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 MBA from Columbia. What were the career plans? Career plans. Yeah. First of all, thanks for having me. Your show title, Masters in Business. I have no master in business. Well, you have an MBA, so you automatically qualify. Yes, for sure. That's a master's, right? Yeah, that's true. That's true.

Yeah, the origins of the career. I grew up in the Midwest. It's the first phase of my life. And growing up in the '80s in Illinois, I'm from Korea actually. So the natural, I was a STEM kid and that propelled me into the engineering side.

I always had other interests outside of that, but the reason I went to Champaign, we were all from the state of Illinois, and my siblings and I all went to school in the state of Illinois, and I gravitated initially to engineering. And that got into that.

And then eventually I ended up in New York and then transitioned into finance. 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. What did you do there? This is the first job, right? First job, first real job out of school.

It really was the first entree into a company. Not only a company, this was an automation company that's often known for works with many industries, but helping automate. I was working on projects to automate manufacturing. They had these things called PLCs, 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 my first entree in seeing the diversity of manufacturing

of the manufacturing base in this country. I was particularly, I was working on the east coast and everything from pharmaceutical to automotive to what a distribution network looked like, what tier one, tier two kind of systems integrators were with the technology of automated manufacturing. And so we work on different projects and see

across a lot of industries. But I realized I didn't want to, you know, I had other ambitions. And so this is what led me to going to graduate school. So let's talk about some of those other ambitions. You end up doing investment banking in New York in the mid-90s. Yes. What was the transition from being an engineer slash operator to an investor? What was that like?

Well, when I went to Columbia, 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 try to get into consulting. That's a classical role for an MBA. None of the consultants would have wanted to hire me, but 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 the early days of pre pre.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 finance is what pulled me in on the investment banking more so than the consulting because of that angle, I think. And your timing was perfect. The 1990s, great time to be doing iBanking and technology. Tell us about some of the transactions you saw late 90s, early 2000s. What sort of deals were you working on? Yeah, just that transition. I was originally hired by S.G. Orberg, which is a British firm.

investment bank and it got acquired. And then after the- That became Warburg Pincus? That became SBC Warburg and then UBS bought SBC and then UBS Warburg and then the Warburg name went away. But I was there right at the time when Warburg was acquired. And that transition-

joined Merrill Lynch. And then Merrill Lynch said, go West, young man. Right. Okay. So I remember Merrill Lynch during the 1990s was absolutely a powerhouse, or at least became a powerhouse towards the back half of that decade. Yeah. Yeah. So it was very much a new thing for them in the West Coast. And so I went, and I still recall to this day, there were several of us that

or the origins of the M&A group on the West Coast for Merrill Lynch. In fact, three of those people, 20-some years later, were back joined at BlackRock. And I can tell you the story of that. Sure, let's hear that. Oh, okay. Yeah, there were...

There were three of us that were VPs and directors at the M&A group. Feel free to drop names. A guy named Draga Rachkovic, who is now vice chairman of J.P. Morgan, runs the tech M&A. This guy, Michael Leitner.

and then myself, and then we worked with this guy named Rob Stewart, and then Mark Schaefer above led the group. But Mike, Michael at Tenenbaum, BlackRock later acquired them. And he was one of the partners at Tenenbaum. And then recently BlackRock bought GIP. And then Rob is one of the partners at GIP. So three of the four of us, Rob, myself, Mike,

Michael, all ended up at Black Rock and some fans. Let's get the band back together and see if we can... Drago did not. Drago still is at J.P. Morgan right now. But those were the original days. And then the transactions, this was...

pre.com and you know the internet was just getting going are you talking early 90s uh mid mid 90s mid late mid to late 90s like i remember being on a trading desk in 96 when the netscape and i was not allowed to trade it when the netscape ipo happened yeah that was really what kicked off a giant explosion were you there around that time

Yes, in that time. And these were the deals when Cisco was going crazy. And there were so many transactions and networking. There was the optical communications boom, some of the original software internet assets. And so I did transactions in this, especially a lot in the networking, telecom. I remember working on one or two software deals.

And I did that for a while. And then I decided to leave investment banking, where I learned a tremendous amount, especially the strategic nature of looking at industries and companies, and of course all of the financial acumen, the rigor of doing very intensive financial analysis. But you're always working at the behest of a client, right? You're working on those transactional related issues.

And this is when I decided to go and take a career path change to the investment side. So tell us what that transition was like. What is it like going from transactional M&A on the West Coast to, no, I just want to find companies, public and private, and invest capital in them? Yeah, I think that was the transition. The financial...

Financial analysis is the same, effectively. Maybe it's even more intensive on the M&A side because you're doing much more detailed work. The way you look at industries and companies are relatively similar. 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 have persistence and you learn more about that industry and that domain. When you go to the investment side, I started as an analyst. And here you are looking at a 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. But yet you have persistence because you're able to look at sectors and industries and companies for a longer period of time consistently. And so you build deeper domain knowledge. And so that was one. The second is that you're no longer working for a client. You are working

to find the best investments and put your own capital at risk. And so that was a change of the mindset of how to assess because you're not working really, you're not just servicing a client. Here you're putting your own capital at risk. And that

that was the first big change of just assessing how that works. And then going from, 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 with 30, 40 portfolio managers across four or five investment firms. And that was like, I guess, my second era here was to

learn the skills of investing. We're going to spend more time on what you've learned in a little bit. You said something I have to explore a little bit. It was more in-depth, more intensive on the

M&A side than the investing side. I'm curious as to why the two ideas that immediately pop into mind, you're covering a whole lot more companies on the investment side, but one can't help but imagine on the M&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 could walk away with maybe a little worse for the wear and tear. But when you buy an entire company, hey, it's really hard to unwind that, isn't it? 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, maybe two companies at a time. And you want to get every number right, every comma, every nuts and bolts to 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 and you can make a decision with the push of a button, sell or buy. And so the time spent

on that analysis will invariably be less than the time spent on this one definitive transaction. Really interesting.

So you've been in BlackRock since 2013. 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 any of the big BlackRock ETF sector funds, passive indexes? 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 the passive funds are traded at. And then there's like passive decisions

A lot of the passive index thing is now an active decision, I guess you could say. Hey, it always has been. It always has been. Right? Yes, that's right. It's, hey, we're going to make it market cap index. That's an active decision. We're going to cap Apple, NVIDIA, Microsoft at X percent. That's an active decision. Right? There's lots of active decisions. People don't realize there's quite a bit of active in their passive. Yeah. So now we're joining that line.

that party as well. We have now active ETS. We launched two recently, one on the AI side. So where we feel that dynamism, especially in an industry that is in rapid change, like in AI,

I think you need a lot of adaptation, flexibility, because things are changing so rapidly. 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, 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? Well, I think the future of active management, as you correctly pointed out, I think there are generic sections of the market where it is the broad market exposure, S&P. Those, I think, continue to be under pressure as it moves to

to those passive indices. But you said something very interesting there. The industry is specialized, 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, I think.

And of course, I'm biased in that because I am focused on a specialized area, which is the technology area. And within the technology area, there are many further sub-specializations. And I think those that have broader depth of domain knowledge, hopefully that is the advantage. And that gets expressed in an active fund, an ETF or a mutual fund or whatever.

As I've been in this technology industry for a long time, 20 years ago, tech was 20% of the S&P. It's over 40, and it's probably going higher as now we're entering the AI era.

Generalists, I think, are at an 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 will hopefully sustain the active management industry. You know, I'm so glad you said that you think the technology sector of the S&P 500 is going higher. Whenever people say to me, aren't you concerned that technology

tech is 29% of the S&P 500 or whatever the number happens to be? My answer is always the Magnificent Seven are responsible for something like $2.5 trillion in revenue and $500 billion in profits. I'm shocked it's only 29%. Why isn't it half of the S&P 500? This is what's driving the economy and the market. Doesn't it deserve a richer valuation? I'm curious as to your thoughts on that.

100% agree. Okay. I 100% agree. The multiple in aggregate has not changed dramatically, but it has driven by free cash flow. And the 40% I'm quoting is a combination of comm services, which they carved out, which is really tech companies, with classic tech. That's over 40%. And

When you look at the contribution of free cash flow, which is the ultimate profit metrics, it's followed. It is 40% of the free cash flow. The other thing about tech, I don't think people realize, it has represented the highest growth. It actually has the highest margin. It has the highest profitable margin. People think it's unprofitable. But 90-some percent of tech have profitable. And the highest profit margin and the highest free cash flow growth. And that's what's driven...

the market cap appreciation. That is not well understood. Fair to say, this is not the late 90s dot com, whimsical ideas with hardly any revenue and no profits. These companies are printing money and are wildly profitable. Yeah. And in fact, I would even make another distinction. The Mag 7, the most profitable sector...

in all the S&P, 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, if you say software and semis are two thirds of all of tech, they have the highest margins in the world. 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 40% of the market cap.

which is, and most of those are Mac 7. Doesn't sound like a bad place. Doesn't sound like a bad place. To keep your- And now we have AI and it probably goes higher. It's going to go higher. Fascinating. 89% of business leaders say AI is a top priority, according to research by Boston Consulting Group. But with AI tools popping up everywhere, how do you separate the helpful from the hype?

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How do you go about identifying technologies that are going to drive future growth and, as we've seen, reshape the entire economy? 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, this kind of goes to my childhood. I always had a fascination and love of maps.

- Maps? - Maps. - Huh, that's interesting. - Cartography, ancient maps. So I like to map everything out. And so like the ancient mariners would sail the oceans, you'd want a map of where you're navigating to. And so I start with that. I like to break things down. I break technology down into five or six major sub-sectors, and then we just continually 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 landscape, the internet landscape, the software landscape, et cetera, and continually break things down. And so then they are digestible pieces. And then within those pieces, then you interrogate all of the technologies that are going. And so now you have this giant, giant map of all of technology, all interoperable.

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 and 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

And so then, so that's the current, that's the initial framework. And so then you start to see trends that are happening and you see other trends that are declining. So what's so intriguing about that is we tend to think of fundamental trends

CFP type research as very balance sheet driven. What you're describing is something that's much more holistic and comprehensive. You're really looking at the whole echo system of technology to see what is moving and use the magic word systematize. How do you systematize that?

Is it just identifying what is on a mathematical basis popping its head up? 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 the semiconductor industry, there's

different kinds of chips, accelerator chips, memory chips, foundry, logic, analog. And then let's say the software industry, there's security and applications, infrastructure, et cetera. And 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 starts with ChatGPT and GPT 3.5.

in the end of 2022, early 2023, and it shows up as an application, a chat application. Well, the first thing you, when I saw that, I said, wow, this is going to change the world. And- That was your initial response to the first demonstration you saw of ChatGVT? That and having a meeting with

Jensen Huang in January 2023. Those two things kind of triggered it. Then once you see that, then you say, "Okay, how is this going to cascade through?" It's kind of like in biology, there's a thing called what I call a trophic cascade, an ecological ecosystem. And then you say AI is the trigger. The first thing you see, 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 need to, well, those are connected to the packaging systems. And those packaging systems are connected then to foundries. And these foundries are connected to the wafer 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 thrown in servers and servers need this whole supply chain. And then those servers get then deployed in clouds. And these clouds then need, oh, by the way, these things generate a lot of electricity. And that spawned the whole power energy movement. But then you know what the power transmission and grid and technical thermal equipment that needs to

power and cool these cloud data centers. And so you have built that supply chain down. And then after the AI is built, you bring the AI into business at Bloomberg and BlackRock, and you bring those into a 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 and robots. And so once you see that whole chain,

and how that gets diffused. And then you have interrogate, 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 you say, well, is it worth investing in these companies or not? And that's when then you get into the financial analysis. Really interesting. So I'm hearing

infrastructure, which is everything from power to cloud to database to intelligence, which is the modeling. That's right. 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, if not hundreds of companies working across a whole ecosystem. That's exactly right. Now,

In the public stock market, the first two years, the manifestation of what I just described, what you just eloquently described, gets expressed in the MAG-7. Let's recompile that as a nine-layer cake. At the bottom of this cake is the power and the energy. And then that feeds...

these servers and chips, and then those servers and chips get live in a, 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 mag seven are here. So that's Google and Amazon and Microsoft to say the very least. And now Tesla's building AI cloud centers. Right. And, um, 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 Macs, Microsoft, Google, OpenAI, some of the private companies, and now XAI. And there are six 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 helping train these models. - 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 AI models to work on. - Correct. And companies like Reddit have done a deal like that. Wall Street Journal, there's some lawsuits even, New York Times.

Well, they have in some instances seemed to have borrowed stuff that was- Yes. Yes. Your $99 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. That's right. And then there are some companies, you mentioned Thomson Reuters, which is-

they have they run one of the one of they have one of the 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 that intelligence and the 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

Give us some names. I have a couple of things on my phone. What do you like? Oh, on the app side. Yeah. I mean, I'm using Perplexity. I use Perplexity. It's so clean and so simple. I love Perplexity. I love ChatGPT.

They're slightly different. Slightly different. Right? Just the output. But they're still... And I'm finding far fewer hallucinations than I used to. Yes. Like I had Bill Dudley from the New York Fed in who was born in the late 1950s. And ChatGBT mentioned he happened to be a linebacker for the Detroit Lions in 1952. It took it a while. Then there was a guy named Bill Dudley who was... It took it a while for it to figure out...

Right.

But it definitely took months for it to kind of somehow recognize that. Yeah, and that's on the consumer side. And there'll be a lot more consumer apps coming. Companies like Apple have this Apple intelligence, right? And they're absolutely locked in on your privacy. But they're going to know you the best.

And so there will be AI assistance coming. I hope it'll be better than Siri, which was a huge disappointment. For sure, 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 that. Absolutely. And even more things, even more difficult than, let's say, that. Like, oh, I need to help them. I need to do my taxes.

I want my taxes held. 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 20 data points diagnosis illness, it just...

moved ahead of the accuracy rate of human doctors. You said exactly. The complexity of the tasks will only go higher in terms of what they will be capable to do. And these AIs are following 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. It'll be doing very complex tasks.

And so we are just at the very, very, very beginning of that. That's really fascinating. So given the mapping you do of the whole ecosystem and then the dive into the financial background, what strategies do you then use in saying, okay, I understand the whole ecosystem. I understand the various balance sheets of these companies. How do you then pick which stock you want to own? Yeah.

So I have a certain small rules, I guess if you could call it that, or observations that I've made over many years, especially in tech, right? Because this is a very dynamic industry. One of those is there's a power law.

But I believe in power laws. And it seems like every industry I've ever looked at, there's number one, a number two, and then maybe a number three. So very fat head and then long, minor tail. Yeah, let's just say 50% market share number one, 25% number two, and then cats and dogs. Right. Winner takes all. Yeah, winner takes most. It's true everywhere. And it doesn't matter if you're selling frozen pizza to search advertising. These power laws are true everywhere.

And then because, but the thing is that you could have power laws that apply to hundreds of categories, right? It doesn't have to be all encompassing in one. And so when I look at tech and all those different categories, I firmly believe in these power law concept that you want to be betting on number one or number two, especially number one, not even number two. You want number one, ideally. Right.

And so are you... So in many cases, they're already existing players. Okay. And so if they are already existing players and then 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 Mag7. You anticipated where I was going to go next. What you're essentially saying is Mag7 is...

They're focusing on the number seven 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, 10, 15 companies. That's exactly what's been happening. The strong gets stronger. Yeah.

Unless there are signs of weakness, right? 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, 10 years, but their run is over? 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 ascendancy of NVIDIA versus Intel. For 30 years, Intel ran Legion, and then there was a transition. There are several reasons, but there was a transition to Intel.

to accelerate computing from CPUs and then they've lost leadership on Foundry to TSMC. - And then mobile, they lost leadership on that. - They didn't engage in mobile. There are times where companies, different transitions, like if Microsoft did not pivot to the cloud from Windows, and the government went after them on Windows,

But they were litigating yesterday's war, right? Microsoft found Azure and then history was rewritten.

Oh, and management. What do you think of the job Sadia Nadella has been? You know, people forget. That's got to be one of the great CEO and what he has mastered in the history of business. Microsoft was dead money for a decade. I know that sounds ridiculous to say. I know, people don't remember that. Not that Ballmer was a terrible CEO, but he was a founder and maybe,

just wasn't nimble enough to see the next generation he he was you know like many founders they're stuck in you know microsoft 1.0 yes and nadela is i don't know maybe he's 3.0 or 4.0 but yeah definitely he's got it's got to be one of the greatest unbelievable business turnarounds in history that doesn't get that much enough recognition i i i totally totally agree uh

So they have this power law concept. Going back to your idea, the other one is you need a second act. You need multiple acts. If you even look at these great companies, right? Microsoft, for example, you had the Windows, and then you had a second act, which is Azure. Right. And Azure has been driving the company, right? Even Apple, right?

found the iPhone after Mac, right? And so you need companies that have, and then Amazon, I don't even know how many acts they've had. They have so many different acts. 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, do you have 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 Mag7, these power law companies. But there's always room. History for tech has always given you the opportunity for the 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 up.

and become the new challenger. So it's that, those two, those are the two components of a technology fund. Absolutely fascinating. 89% of business leaders say AI is a top priority according to research by Boston Consulting Group. But with AI tools popping up everywhere, how do you separate the helpful from the hype?

The right choice is crucial, which is why teams at Fortune 500 companies use Grammarly. With over 15 years of experience building responsible, secure AI, Grammarly isn't just another AI communication assistant. It's how companies like yours increase productivity while keeping data protected and private. Designed to fit the needs of business, Grammarly is backed by a user-first privacy policy and industry-leading security credentials.

This means you won't have to worry about the safety of your company information. Grammarly also emphasizes responsible AI so your company can avoid harmful bias. See why 70,000 teams and 30 million people trust Grammarly at grammarly.com slash enterprise. Grammarly, enterprise-ready AI.

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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. Yeah.

I think valuation, if I were to broadly say, is at a fair level. Now, there's dispersion in that. You mentioned the MAG-7 and the crowding and these giant winners. They have valuations that are higher than the rest of tech. The rest of tech has not, for the most part, recovered from the recession we had in 2022.

they were way exaggerated in 21. It crashed in 22. And there's been not that much of a recovery. So a large part of tech is still at depressed levels. I would say we're back to pre-2018, 17 levels, except the Mac 7 and a few companies like that that are at higher levels. But their performance have been better. Right. And, you know, it's funny.

we still have over a month to go this year. This could be the first year the S&P 500 beats the NASDAQ 100 in a long time. I'm trying to remember the last time we saw that. Yeah, because a large part of the NASDAQ, especially non-MAG7, they've not done well. You know, large parts of software, large parts of semiconductors even. If you're not in the AI class...

you know, you've been left behind. Really 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 25, 30 different companies and their senior management. Tell us a little bit about what that experience is like. What do you learn? Does it actually help you with your investing process?

Yeah, I think you're referring to our annual, every summer we do a bus tour, effectively. We bring 30 BlackRock investors. Now, that said, we do 2,000 meetings a year with companies on my team. Wow. I personally do almost 1,000 meetings with companies. Now, this is a special event because it pulls together seven, eight, nine, 10 different teams at BlackRock, 30-plus execs and investors involved.

And then we get on a bus and we go visit the top managements and CEOs, both public and private companies. Every year, I've been running this now 11 years. And what that does is you're on site. It's a little less formal. The companies feel more comfortable because they're hosting you. And it's really more about strategic discussions than re-litigating the quarter process.

Much longer term than the usual discussion. It's always a great barometer of what were the topics of the tour in 2014 versus 2024. You can really see an evolutionary of what was topical every year. So it's a great way. It's also great for...

the people because many times even within a firm like BlackRock, 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 the interpersonal relationships that are strengthened. And then it's really 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. Yeah. So let's go before the previous two years. Give us some examples of ideas that were surfaced via this bus tour. So I'll give you some specific examples. Sure. I remember distinctly there was one about AMD.

When AMD had just announced its new chiplet-based, Jim Keller was still working there and he was one of the famed chip designers. And they had redesigned the processor and the CPU. And that Zen architecture was the basis in which 10 years later, they've gained all that market share from Intel. But that was that day. And I remember because AMD was on its back. Uh-huh.

Perennially, always a laggard, always short of capital, always like, hey, are these guys going to be here in five years? But they made that seminal bet to really change that chip architecture. And then another one I remember distinctly when there was lots of questions around Tesla. Right now,

can they get the Model 3? They had not even a warehouse, a tent to make. Remember that? And everyone was saying you're losing. 24 hours a day. They had a tent to make the Model 3. And I think that kind of unlocked. That's like, well, 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 events like that that come through. Let me ask you,

Relative to Tesla, an ecosystem 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 dropped below 50%, not because their sales have fallen, but because there are so many other players in the EV space. I can't help but give either credit or blame to Jeff Bezos for

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 get our act together pretty quickly. Any truth to that urban legend? I would say in EV, just pure EV cars, Tesla's

share and its ascendancy, the entire market, especially in the US, especially in the West, not China,

It's definitely slowed, if not stalled. Okay. Right. 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 has leapfrogged them. We could debate that. But at least, but it's a 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.

- I would say to that, and I don't want to comment on that specific company, but companies like that, they're selling a $100,000 car. Tesla's selling a $40,000 car. The $50,000 and up market-- - Is very different. - Which is most EVs. - Right.

If you go in the past, the best selling single car was like the Toyota Corolla, like a couple million a year. And you look at Tesla's Model 3 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 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 robot taxi or lower cost car to get at the market sub $50,000. Where you have, you know, that unlocks a market three times bigger. It's like a $30,000 car or a $25,000 car. But I think Tesla's main problem

Pivot, really, and even Elon would tell you, it's not about the car. The car is a mere means to deliver autonomy. And it's a robotics company, right? And autonomy is the big unlock, not selling the car itself. 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...

built into the roads and other vehicles were some form of

RF device that allows other cars to know where here's where the exit is. Here's where the lanes are. Here's where other cars are. Like there could be an infrastructure build out that makes that. Have you, when's the last time you were in LA or this year? This year. Okay. Did you see Waymo's running around? I did not. I did not. So Waymo is now operating in Los Angeles and they're everywhere in San Francisco, Phoenix. And, um,

The future is here. It's just not evenly distributed. It's within grasp, finally. It's always been three years in the future, but it really is now, I think. So now let's bring this conversation full circle back to the funds you run. Let's talk about BAI, which is the iShares AI Innovation and Technology Active ETF. Tell us a little bit about that. That's a fairly concentrated portfolio, isn't it? That's right. We just launched this.

This is our first foray. We have two ETFs now. We're jumping on that ETF bandwagon, if you will. Yeah, I think that might work out for BlackRock. Yeah, it's right here. But this one is, you know, I think, you know, hopefully we look back. This is the second year of AI, as I would say. And I think this is going to be a decade long, if not longer, transition.

And we are trying to express in a concentrated way 30 plus companies in an ETF that represents this whole stack of AI. From NVIDIA down to the small stuff. All the 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. What we think is the companies of 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 and adaptive.

And so to lock yourself into a fixed passive structure versus a dynamically changing structure, that's really the goal of this ETF. Let's talk about iShares Technology Opportunities Active ETF, or TEK, broader portfolio, 50 to 70 global tech companies. Tell us what that focus is. That is basically the ETF approach.

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 there's lots of tech companies that don't really have that much to do with AI, building AI.

And so you're going to get the whole totality of tech in that. 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...

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. Maybe not minute to minute, but you're absolutely right. In AI, so there are different time scales according to different industries. So let's say in AI, you're right. It might literally be minute to minute, day to day. Okay. On the smartphone, it's

Things are more staid. They're slower paced. And so you have a spectrum of rates of change. That's number one. So number two, how do we keep up? I mean, 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 scientists. And then we do like...

I do personally 1,000 company meetings a year. That's amazing. That's four a day if you're working 50 weeks a year. Yes. I mean, yes. I do many, many, many, many meetings a week. And so then you assimilate all this information. And then I'm always doing the calculus. Who's winning? Who's losing? Who's winning? Who's losing? What's changing? What's not?

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, you get judged every quarter. That'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 be a dominant technology over the next five years to, uh-oh, it's September 30th and we know what happens starting in October. How do you manage that tradeoff?

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, 2022 was just...

Brutal. Hell on earth for tech. It was, you know, not only was it hell on earth for tech, it was the first year in over 40 years where both stocks and bonds were down double digits. Yeah. Like once every half century. And then the only saving grace was 2021 was so spectacular.

that it felt like, all right, we're giving back some profits, but it's not, you know, it didn't feel like it was 07, 08, 09, which was completely- 2022 was worse than 2008, 9. For technology. For tech, oh yeah, for sure. Really? That's a big statement. Because in 2009-

It was a universal collapse. That's correct. Centered mostly in, you know, banks, finance, real estate. Tech went down, of course, but it didn't go down more. In 2022, it was predominantly a tech collapse. But it wasn't like the dot-com implosion where the NASDAQ 100 fell 80 plus percent. That's right. It wasn't. It wasn't.

But it was still no fun. You were down, it was down 30 plus percent. Yeah. Lost a third of its value. That's a big hit. But in my, in my, in my career, 2022 was the worst year. Huh. 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 obviously the last couple of years have been good. Right. And so,

But 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 our ability with, you know, especially an active manager. You know, it is interesting.

you need to show, because we hold generally fewer companies, and you need a couple of years to show that those longer duration bets start to manifest. And so if I was always chasing the quarter, now you're trying to be

You're not a momentum trader. Yeah, exactly. And that's really kind of at the end. We're saying our decisions that are 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 do that. Obviously in 2022, we had to make a lot of adjustments. But other than that, we kind of stick to the same framework. Really fascinating. 89% of business leaders say AI is a top priority according to research by Boston Consulting Group. But with AI tools popping up everywhere, how do you separate the helpful from the hype?

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Join Bloomberg in Atlanta or via live stream on February 11th for The Future Investor, Finding the Opportunities. This 2025 event series will examine how companies are investing in their businesses to create efficiencies, innovate their products and services, and improve the customer experience. This series is proudly sponsored by Invesco QQQ. Register at BloombergLive.com slash Future Investor Atlanta.

All right, so I only have you for another few minutes. Let's jump to our favorite questions 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? Okay, I don't get the chance to watch that much TV and streaming, but streaming shows, the ones I've recently seen, I've seen...

I really like Shogun. Oh, really? The new one? The new one, the remake from the 80s or...

three body problem. I, I enjoyed, I love that. I couldn't get through the book, but the show was great. Yeah. And, um, then, uh, but I, I'd watch a lot more. I'm a history guy. So, uh, I, I love epic history on YouTube. It's absolutely fantastic. Um, epic history, epic history TV. Yeah, that's fantastic. Um, I, I, uh,

watch a lot of science stuff, like World Science Festival of Columbia, Professor here, Brian Green. Oh, sure.

- He's a prior guest, he's great. - I also like chess, I watch chess. - You watch chess? - Yes, I love watching chess. So like Chess Dog is a great show. Especially the old matches of the great players like Bobby Fischer and Paul Morphy and things. And the podcast, I think the best podcast for me is The Ancients. - The Ancients, I'm gonna check that out. - This is on ancient civilizations and ancient history.

So, those are what, yeah, that's what kind of occupies me. I don't do as much business shows or business pods. I listen 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.

I go for my love of history is probably the... I have the same issue. It's like, I don't want to hear a guest I'm going to interview on another show. 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. Who were your early mentors who helped to shape your career?

The mentor would imbue a personal one-on-one, like tutoring and things. I didn't have too many of those.

I would say my earliest mentors, I go to high school. Those were my formative years in Illinois. My English teacher, who was also my debate coach, 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 BlackRock, when I joined, it was Tom Callen who hired me. And Tom said, not so much as a mentor, but he said, here are the keys. And you express your creativity and build the business. And he gave me that latitude. 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 now.

I have people that have influenced me like Napoleon and Frank Lloyd Wright and Beethoven and others. So you grew up in Illinois. Did you do any of the Frank Lloyd Wright tours? Oh, yeah. I did all that. So we spent every Thanksgiving in Wilmette, and so I've done that whole run. And I have to assume you've been to Falling Waters, right? I've not been to Falling Waters. So I...

Taliesin, I meant. Oh, really? That's on my list. In 2017, I bought a car in Indianapolis, flew out, test drove it, signed the papers, drove home, and halfway home was Falling Waters. We were there the first day it was open in, I want to say it was...

early March and there was like a light coat of snow. And you went inside as well? 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

be so ideally suited to its surroundings. It's just... Absolutely, yes. 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 amazing. The genesis of that, my interest in architecture, I read The Fountainhead.

You read that book, Ayn Rand? I slogged through it in college and basically gave up on her because of that book. Oh, you gave up. It's such a painful book to read. Yeah, but it spawned. There's some ideas in it that are interesting. The idea, especially the architecture, that really triggered, oh, architecture. Right. So since you mentioned The Fountainhead, let's talk about books. What are some of your favorites? What are you reading right now?

Okay, there are certain books that are influential to me. I grew up in... People on this show, I grew up before the internet. As did I. As you did. I don't think we're that far apart in age. Yeah, yeah.

And I was a nerd. I was a total nerd. Same. And so The Lord of the Rings. I knew you were going to go there. How did you know that? Because I reread The Hobbit and The Lord of the Rings every summer throughout my teen years. Oh, my God. And someone just told me that the character actor who played Smigel 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. It's like a full radio play that he does voices. That's right. He it's supposed to be fantastic. Yeah. I even, yeah, I loved it. Uh,

And then I went even, I went really deep. The Silmarillion and the 20,000 year prehistory to The Lord of the Rings. I went that. How far afield did you go in sci-fi? Heinlein, Philip K. Dick. Heinlein, Philip K. Dick. CJ Scherer. Not only CJ Scherer, but Heinlein. Pride of Shannur. Strong recommend. Pride of Shannur? Pride of Shannur. Shannur, Shannur. I don't know.

Just a fascinating book. Give us one or two more books and then we'll get to our last two books. Currently, I'm reading a lot of history books. 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'm reading The Fall of Carthage by Adrian Goldsworthy and SPQR, Mary Beard.

And I just bought my 60 memorable games by Bobby Fischer. I just wanted to go read all those. Did you read, I forgot who the author was, but there's a great Genghis Khan biography. Oh, yes. It's really interesting. I could see the book cover. Yes, I would like to buy that. But I have one other, I have a book recommendation for you that you're going to love. Okay, you tell me. And it's 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 – whatchamacallit – the cheetahs. 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 it. And it's just a history of technology story.

10,000 years ago to today. Absolutely fascinating. 10,000 years ago. Right. Going back to the invention of glass, the invention. I like to collect some of those ancient artifacts. Oh, that sounds like fun. All right. So I only have you for two minutes. Let's get to my last two questions. Yes, last two questions. Like that's the problem with sci-fi geeks. Yes. Okay. I didn't know you were a sci-fi geek. Oh, absolutely. What sort of advice would you give to a recent college grad interested in a career in technology investing?

Not so much technology, but 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 be reason and plan and think at a...

in a kind of a holistic and a flexible manner because AI is going to do so many of the tasks and they will often know more than you about any specific domain. So you need to be above that in a way, almost like an architect would. Makes a lot of sense. And our final question, what do you know about the world of technology today? You wish you knew back in the mid-90s when you were really starting out.

If I knew how this would unfold in the Silicon Valley, I would have just gone straight to Silicon Valley, the company, maybe, instead of being on the investment side. I don't know. It's a double-edged question because I like the dynamic exposure to many companies. Plus the path you've taken is so fascinating. Yeah.

I would say another point for the young people, always bet on the future, not on the current past. Bet on the future. 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 $11 trillion.

in assets. If you enjoy this conversation, well, be sure and check out any of the 500 previous discussions we've had over the past 10 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 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 crack 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 Ritholtz. You've been listening to Masters in Business on Bloomberg Radio.

Join Bloomberg in Atlanta or via live stream on February 11th for The Future Investor, Finding the Opportunities. This 2025 event series will examine how companies are investing in their businesses to create efficiencies, innovate their products and services, and improve the customer experience. This series is proudly sponsored by Invesco QQQ. Register at BloombergLive.com slash Future Investor Atlanta.