Tech And AI Investing Trends: A Stock Picker’s Take

Episode Description

AI is experiencing a transformative moment, powering the phenomenal run in public markets, but the investment opportunities certainly transcend that small group of names. So where are the most compelling opportunities and how can AI investment not only build wealth, but contribute to a more efficient future?

Tony Kim, portfolio manager from BlackRock’s Fundamental Equities team, joins Oscar to explore the evolving conversation around AI among industry leaders, rebut AI skepticism and examine the investment potential of quantum computing.

Transcript

Oscar Pulido: Welcome to The Bid, where we break down what’s happening in the markets and explore the forces changing the economy and finance. I’m Oscar Pulido.

AI is experiencing a transformative moment, powering the phenomenal run in public markets led by companies like Nvidia (NVDA), but the investment opportunities certainly transcend that small group of names. So where are the most compelling opportunities? How can AI investment not only build wealth, but contribute to a more efficient future?

Tony Kim is a portfolio manager from BlackRock’s Fundamental Equities team and is at the forefront of technology and AI investing. Tony will help us explore the evolving conversation around AI among industry leaders, his response to AI skepticism and the investment potential of quantum computing. We’ll also discuss how Tony’s passion for technology and history relate to one another.

Tony, thank you so much for joining us on The Bid.

Tony Kim: Thanks for having me. It’s a pleasure to be here.

Oscar Pulido: Tony, earlier this summer you hosted your 11th annual tech tour where you and 36 other BlackRock colleagues took a bus more than 300 miles over five days, to meet with leaders of over nearly 30 technology companies in San Francisco and Silicon Valley. I have to say that sounds a pretty fun trip. not surprisingly, AI was a topic that, you talked about a lot. this is a space and a topic that has been changing quickly over the past year though, so I’m curious, how has the conversation evolved over that past year?

Tony Kim: Yeah, as you mentioned, this is the 11th year we have done this. The first nine years there was some talk of AI, but generally very little, very company specific. Last year, and this year, AI has dominated, the conversation. In fact, it was a topic of discussion in every single meeting.

What also is emblematic of, especially this year is, as you mentioned, the rapid change of AI and how AI has basically taken over, the entirety of Silicon Valley. There’s been a huge pivot, and this has dominated the strategies of every single company that we visited on this tour and basically across the entirety of tech.

What’s changed is in the last 12 months is that intensity has come even clearer into focus and the strategies are becoming more apparent more definitive. The commitment and focus is higher than it was even last year, which was like really the first year we really saw AI come into its own.

Oscar Pulido: It’s fascinating to me that in the first nine years of your tech tour, AI was barely a mention, or you said it wasn’t a focus. But now the last two years, it’s really the only topic of discussion.

Tony Kim: Yeah, it is really the only topic of the discussion because in the prior nine years, AI was more a tool something in the background. Operationally a few companies were using it. It is now, at the forefront of every company, and it’s really changing the foundations of, the software industry, the semiconductor industry. It’s cascading to the power and energy industry. it’s also changing just the very product and services that all tech companies are building to. That’s the sea change, and it’s been remarkable how that’s changed in 24 months.

Oscar Pulido: So Tony, it turns out we were able to join you on this tour, and as you were, meeting with different, industry leaders and company leaders, we actually were able to get some, commentary from them. So first we will hear from Arsalan Tavakoli-Shiraji, co-founder of Databricks, who has been an AI believer since this company was founded 10 years ago. He also is struck by the recent pace of change.

Arsalan Tavakoli Shiraji: The pace of change has been incredible, right? If you talk about, let’s say a year ago, 18 months ago, nobody really was even talking about AI. And now all we talk about is, what are GPUs going to be used for? What are all the different systems? How do I harness AI? It’s been a while since I’ve seen something that has so much excitement from industry, yet still is so nascent that it’s in the research phase.

Oscar Pulido: So Tony, clearly in public markets, AI has been powering the phenomenal run, in stock markets, particularly companies like Nvidia and a handful of other mega cap stocks. But the investment opportunities certainly transcend that small group of names. So, you’re a tech investor, where are you finding the most compelling investment opportunities?

Tony Kim: On one hand, one dimension we should think about AI is, there’s a stack of products and services.

And at the bottom of the stack, there is the chips and the infrastructure, the cloud infrastructure. And a lot of the investments, especially last year and this year, have been going to build that foundation. Basically, a rebuilding of the internet, of a new computing infrastructure, which is, AI. There is then another layer, let’s call it the Intelligence layer, which is the data and the models themselves, the foundation models. Those are being built and are increasing in capability. And then on top of that, there are software infrastructure and software applications and then services and solutions that combine all of this with the AI intelligence. That is now also starting to be put together of new applications that are leveraging AI.

So, you have these three layers: this infrastructure layer, this intelligence layer, and then this application layer. And the investments you start from the bottom, and you move up to the top. And in 2023 and 2024, a lot of the investment and a lot of the stock price reaction has been at this bottom layer of the stack. However, it takes time for us to move up the stack and, as we progress into year three, year four, year five, we will continue to start seeing opportunities of companies in that intelligence layer and of course finally in the application layer, which has not been as beneficiary of this first wave of AI, which we saw at the bottom layer of the stack and infrastructure.

As investors, we are looking across all of these layers of the stack The market will evolve over time, but we are seeing, at least in 2023 and 2024 for sure, a huge focus and emphasis, of building this foundation of the AI infrastructure.

Oscar Pulido: Tony, you talked about the tech stack, but maybe tell us a little bit more about the end markets and the end users that benefit from that AI spend?

Tony Kim: I’d say the first end market is around these big cloud AI computing companies, building this infrastructure and all those companies that are associated with that, that sets the foundation. That infrastructure spend then gets leveraged into, let’s say, the first end market will be consumer. And it just so happens that many of these big infrastructure companies have big consumer businesses: search, social, e-commerce, shopping. And I think you’ll start to see AI come into the consumer market and this is a market of what I would call personal assistance.

The second big end market will be around businesses, enterprises that will then, again, leverage this infrastructure spending and bring AI into companies.

The third is the end market for the real world; cars, airplanes, the military, robots, et cetera. The instantiation of AI into the physical world. These three additional end markets, again, I would say we’re in very early stages of adoption, first inning or less in many cases. But they all leverage the same infrastructure that is being invested right now at these big foundational models and foundational compute layer. And then that gets amortized and leveraged across all of these, ultimate end markets for consumers, businesses in the real world.

Oscar Pulido: Tony, when it comes to CapEx spending – or capital expenditures – essentially what corporations are spending on that new computing infrastructure, I think that’s the term that you used, Google (GOOG, GOOGL) has said that the risk of under investing is far greater than the risk of over-investing. A lot of the big tech companies have committed to massive amounts of capital expenditures towards AI, yet it may still not be enough as Hock Tan, President and CEO of Broadcom (AVGO) shared.

Hock Tan: The amount of money that is involved, we haven’t even begun to quantify. And one could imagine the level of spending required both on computing engines, on software models, on infrastructure and power in particular, could possibly be larger than what we all are thinking of at this point. And that’s why I say we are probably underestimating the amount of dollars in CapEx, in investment, we would need to make in order to reach that goal, that aspirational goal of what you call AGI convergence in artificial intelligence.

Oscar Pulido: Tony, are you worried at all that the capital expenditures on AI might not deliver the return on investment that people think it will?

Tony Kim: In one singular answer? No. However, Wall Street and investors are obviously asking that question now about ROI of AI and the issue is the two- and 10-year question. Maybe in the next two years, we are overestimating the impact of AI, but in the 10 years we might be underestimating the impact of AI. I would generally agree with that – if we are trying to match investment dollars in and profit out in the near term, that is a mismatch.

Clearly, companies are spending more than the dollars that they’re getting out right now, the two-year problem. But in the 10-year duration the potential, benefits and returns that we can get are maybe we’re underestimating that. I would generally say I would agree with that statement. You can’t match this spending with the revenue and returns linearly, one for one. But, as an answer to your question, I’m not really concerned about that. Your comment about Google and the risk of under investing, I would also agree with that.

The big three hyperscalers, Amazon AWS (AMZN), Microsoft Azure (MSFT), and Google. And all three have very, very large cloud computing businesses that they’ve built over the last 15 years. That has been the engine of growth for many of those companies. But those clouds businesses represent the cloud of the pre-AI era – the SaaS revolution, the cloud computing era of moving compute from customers premises- on-prem -to the cloud. This has been a tremendous tailwind that’s driven these companies for the last decade or more. AI has come and we have to rebuild a completely new computing infrastructure. AI then will be instantiated in all these new application end markets.

So, if you are one of these big three companies and if you do not invest, and you so happen to pause or slow down and your competitors continue, you run the risk of falling behind. And if one of your competitors also, builds an AI capability, a technology breakthrough that that leapfrogs you because you’re not investing that these are existential potential risks to the current business as currently constructed in the prior era. And so, in a way, it is not only the potential long-term benefits from AI in terms of the returns that come with that, in my opinion, there are certain existential questions if you do not continue to invest, you run the risk of falling behind, which then impacts your current core business.

So that, again, goes to this two and ten year- are you only trying to optimize for the near-term profit, or are you ensuring your position in the long-term future?

And just one more thing about the CapEx, it is a lot of money. I did an exercise, I was adding up the top 10 spenders just this year, it’s roughly $270bn of CapEx, of which the top four is $230bn of CapEx plus or minus. So, there is a lot of spending going into this year, but when you look at the balance sheets and cash flow and profitability of these companies, they can afford it. It doesn’t seem excessive to me. The other thing about the spending is it’s a lot of money, but it’s also the moat – this capital that is required to build these most advanced AIs for these companies is also the moat.

And so, this very nature of the CapEx intensity it’s also a feature, it’s also the moat, the defensibility. That all goes in hand with this long term strategic and existential risk. But it creates to me bigger, longer enduring moats and duration.

Oscar Pulido: We heard similar excitement from Rodrigo Liang, co-founder and CEO of Samba Nova.

Rodrigo Liang: You look at all these innovations that are happening across the board, whether that’s accuracy, whether that’s multimodality, whether that’s performance and speed. Wow, that’s efficiency, right? You see this innovation across all of these different ways that the models are operating, and I think you’re going to only see it accelerate, It’s a tremendous time for innovation. It’s tremendous time for technologists and we’re really excited to be in the middle of it.

Oscar Pulido: And Tony just hearing you talk, you obviously have a very long-term lens on the benefits of AI. You talked about that 10-year window. It makes sense now, why in a recent article in The Atlantic, you were dubbed an AI optimist. it’s clear just from the comments that you’re making that, that think that’s a fair, label to attach to you. What would you say then to the AI skeptics, or those that are questioning its viability?

Tony Kim: In terms of the AI skeptics, I think this goes back to this two in 10-year discussion. From what I see, many of the skeptics are wanting this perfectly matched investment with return right now today. You’re not going to get it; it’s just not matched. And then that would shift the discussion to then, do you believe in this, the longer-term returns and benefits?

And, I think I would say one of those is the strategic and existential because you can’t just assume that the current status quo will be sustained. The second is then what are the long-term benefits that could come, and the returns that could come with AI. And here it does require some leap of faith, some imagination, some creativity of thinking of what are all the possible outcomes and changes that AI can have to business and to society and to productivity.

I do believe it is the means to an end that the investment justifies the potential return. And these are difficult to counteract the skeptics right now because we just don’t know when and what those will be and what magnitude

Oscar Pulido: There are of course, a number of companies who are innovating by supporting the AI revolution, not by developing large language models, but instead things like quantum computing to assist with faster AI computations. And we heard from Fariba Dinesh, she’s COO of PsiQuantum, a company building the world’s first useful quantum computer, and asked her about the potential for quantum computing.

Fariba Danesh: I think the most opportunity for quantum computing to contribute to humanity is, climate and drug development. Because chemistry is quite complex and chemical problems are not something we can simulate today, and computing has contributed to that very little over the years. So, with quantum computing, there’s enough compute power where you can actually simulate these very complex mechanisms that happen with bond energies, et cetera, et cetera. Quantum computing is uniquely good for quantum type mechanisms, which of course chemistry is all about that.

Oscar Pulido: And so, Tony, speaking of quantum computing- which I know is a theme that you’ve been an early supporter of- what are the investment opportunities in this space? It feels like it’s something that’s been getting less attention than straight AI focused companies.

Tony Kim: Absolutely. Quantum computing represents a next generation of computing. The last 50 years we’ve been, and we currently are still, in the classical computing era. And I would say these next five years is going to be absolutely incredible in classical computing, driven by AI and what Nvidia, is spearheading and building these clusters of AI computing power, and this is all classical computing. And we are barreling toward AGI and these super nodes with this unimaginable computing power. But they’re all classical, what we call, the binary, classical computer,

However, parallel to this, it’s been a long while coming and we are now at the precipice. The dawn of, let’s call it the, a parallel, it’s not replacing classical computing, but it sits adjacent to it, a quantum computer, which, functions very differently to a classical computer. And I always say it’s more mimicking nature. You look at the real world and nature. And it’s driven by quantum mechanics and to harness that capability, we can build computers of unimaginable computational capability to run very specific kinds of problems that classical computers cannot solve. Problems such as advanced simulations, optimizations, security encryption, factoring numbers and these problems, classical computers cannot solve, and we are within the next five years at the precipice of breaking through a utility scale quantum computing.

So, if you just fast forward, let’s say to 2030, on one hand, on the classical computing side, we will have probably computers and AI supercomputer nodes that could approach a million GPUs per node creating and enabling the building of the most advanced AI models humanity’s ever seen. Parallel to that, we could have a breakthrough of utility scale super quantum computing, and through a company, let’s say, like PsiQuantum, would sit parallel to this AI supercomputer, classical computer and solve unimaginable problems and also create and help generate unimaginable data to also help train the AI supercomputer.

So, what is coming, I think in the next five years, they call it the end of the century, we could have, exponential scale up in terms of computing power, both classical AI as well as quantum. And that is what’s exciting. And if you could have one company that breaks through, you could have an open AI-like moment for the quantum computing industry.

Oscar Pulido: Tony, perhaps one final, question as you’re talking about the future of what AI could bring, it reminds me that you’re not only a prominent, technology investor, but that you also have a passion for history. So, tell us a little bit about why these two passions intersect and relate to each other.

Tony Kim: Yeah, I love history, it might not seem obvious. I have an engineering background, but my true passion has been history. I also look at historical figures either be it Napoleon or Caesar, and Alexander the Great and their strategies. Also, I look at the history of math, physics and computer science, quantum mechanics, the history of encryption and the computer with the enigma machine trying to crack the Enigma machine. All of these kinds of past historical events, historical breakthroughs, they’re very formative in how I also look at the future, and the technology. And actually, I quite live in analog world. even though I am living and working in the most advanced technology, I’m more of an analog person.

Oscar Pulido: Well, something tells me somebody’s going to be reading about you in a history book one day, Tony, you were at the forefront of the AI revolution and helping people see what was coming. So, thank you for sharing your insights and thank you for doing it here on The Bid.

Tony Kim: Thank you very much.

Oscar Pulido: If you’ve enjoyed this episode, check out my conversation with Will Sue on AI and the energy grid solving for AI’s power needs where we discuss how investors should be considering their allocations to account for AI’s growing energy demand.

Sources

Google Investor call, July 2024 per Sundar Pichai;

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Editor’s Note: The summary bullets for this article were chosen by Seeking Alpha editors.