Investing for the AI Boom: Masters in Business with Glen Kacher

Barry speaks with Glen Kacher, Managing Director and CIO of Light Street Capital. They discuss his tenure at Integral Capital Partners, as well as his start at Tiger Management under founder Julian Robertson. They discuss being a hedge fund surrounded by venture capital in Silicon Valley, as well as learning to embrace the speed of tech. They also discuss the polarization of data centers and what AI will look like five years from now. See omnystudio.com/listener https://omnystudio.com/listener for privacy information.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

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• 1:53Barry Ritholtz?

  Podcasts, radio, news. This week on the podcast, my extra special guest is Glenn Kacher. He is the founder and chief investment officer at Light Street Capital. He's got really a fascinating background and a great track record. He worked at Julian Robertson's Tiger Management, eventually ended up at Roger McNamee's Integral Capital Partners. He's put together really a fascinating focus and track record, one of the few hedge funds located right in the middle of Silicon Valley, focused on AI and technology. I found this conversation to be absolutely fascinating, and I think you will also.

• 2:37Barry Ritholtz?

  With no further ado, my conversation with Light Street Capital's Glenn Kacher.

• 2:54Barry Ritholtz?

  Glenn Kacher, welcome to Bloomberg.

• 2:56Speaker 05

  Thank you.

• 2:57Barry Ritholtz?

  Before we get into Light Street, let's talk a little bit about your background. You graduate from University of Virginia School of Commerce with a bachelor's in commerce, and eventually get an MBA from Stanford. Was investing always the career plan?

• 3:14Speaker 05

  It was. I started really looking into that industry. I read a book by Peter Lynch while I was in college, One Up on Wall Street. And, or Beating the Street, it could have been the first book, actually. And I was just caught by this idea of the search for great companies, great ideas, and the way he told the story of finding these companies and researching them is really a journey and of a detective trying to figure out what would matter in the future. And that really captivated me in my interest in becoming an investor.

• 3:53Barry Ritholtz?

  So in between UVA and getting your MBA at Stanford, you work at Julian Roberts Tiger Management. How do you get to Tiger at 22?

• 4:06Speaker 05

  Very fortunate opportunity. So one of the teachers or instructors at McIntyre School of Commerce at UVA was a former Tiger Management partner in Michael Bills. And Michael taught several finance classes there for a couple of years. He had taken some years off from Wall Street after working at Tiger and then before starting a fund-to-funds business that he's run very successfully. And he suggested that I take a look at it. I certainly knew of Tiger. Tiger was, it seemed about half of the investment staff, actually at one point or another, attended UVA.

• 4:50Speaker 05

  And so a lot of the guys there, you know, sort of knew what we were capable of as young guys coming out with finance degrees from UVA.

• 5:01Barry Ritholtz?

  And Robertson was legendary in 93. Was he still running the ship?

• 5:05Speaker 05

  Oh, yeah.

• 5:06Barry Ritholtz?

  Very much in charge?

• 5:07Speaker 05

  Very much in charge, yes. You know, I was there from 93 to 96 full-time. And then still, when I went to, sorry, went to Stanford for a year, I worked for Tiger as well. And Julian would occasionally wake me up with a 6:00 AM phone call when I was in business school.

• 5:24Barry Ritholtz?

  6:00 AM East Coast.

• 5:25Speaker 05

  No, 6:00 AM my time, 9:00 AM his time, just a half hour before the market. So he had had some discretion there. But we had some great times, you know, learning and talking through the technology industry at the time, investing in companies like Dell, Microsoft, Compaq, and Cisco were some of the.

• 5:49Barry Ritholtz?

  So really, right out of college, you're full-on technology? Did you look at other spaces?

• 5:54Speaker 05

  I worked briefly in looking at financial institutions with Rob Pitts there. And we had a great time doing that. But I was certainly more interested in technology. I had really studied that industry prior to going to New York. And so it was a better fit for me following that industry. And, you know, I think two or three months into the job, I ended up sitting two chairs away from Bill Gates at an analyst meeting, at the sort of after-the-meeting dinner. And at that point, I knew I was in the right spot.

• 6:29Barry Ritholtz?

  That's, to say the very least. So after Stanford, you end up at Roger McNamee's Integral Capital, and you stay for 13 years. And you're really less of a public markets analyst and more of a venture sort of banker. You either lead or co-lead venture investments, and the list is pretty impressive. Agile, Arcsite, Blue Nile, Epiphany, Extensity, Fortify, Interwoven, Log Me In, OpenTable, Overture, GoTo.com. What's the common thread? Is it just, hey, that's what was hot in the late 90s? Or what tied that list together?

• 7:10Speaker 05

  Well, the amazing thing about Roger was he really focused on saying, look, we can't cover every company in this industry. We were a small team, much like, you know, at Tiger, there were two or three of us looking at tech at any one time. And at Integral, even though we were tech-focused firm, but we had, you know, four or five people total. But even with that number, you can't cover the entire industry. So you have to focus in when you're investing and say, where is the change really happening most quickly? Where is it most dramatic? That disruption equals opportunity as an investor.

• 7:46Barry Ritholtz?

  That's a theme that comes up over and over in your career. Identify the disruption and get in front of it before the existing companies realize what's coming down the pike.

• 7:58Speaker 05

  It's great to be early, but not too early, right? I mean, that's also an important part of it.

• 8:03Barry Ritholtz?

  Right. I started on a desk, and early was equal to wrong, at least when you're trading public equities. Not only do you do all of these privates, where you've co-led, is this right, about 46 deals?

• 8:17Speaker 05

  Forty-six deals at Integral over 13 years.

• 8:20Barry Ritholtz?

  I read something you had said about that. And you said, you know, the takeaway from all these private venture investments is you don't buy the second or third-best company in the space. You always buy the best company you can. Give us a little details on that. What's the thinking behind it?

• 8:37Speaker 05

  Well, experience, right? I mean, you see the movie over and over again, whether it's private investment or in the public markets. That, you know, the old saying was, you know, the number-one player is going to get 2/3 of the market. Number-two player might get 20%, 25% tops. And everyone else fights for the scraps, right? And, you know, there's the ability to make higher margins and have the dominant market share is just so dramatic. And I think in technology, we've seen the power of that, you know, the ability to sort of compound that lead is definitely there.

• 9:19Speaker 05

  Now, you also see in technology that you can get disrupted, right? Incumbents are, the real innovation in these disruptive changes tend not to come from the big companies, but the smaller companies. There are exceptions to that, and, you know, we can talk through that. AI is kind of an interesting test case and the semiconductors behind AI. But there's real power into be, into compounding that lead.

• 9:45Barry Ritholtz?

  So let's talk about those moats and the winner-take-all situation. Is that primarily a technology phenomena? Is it a modern-era phenomena? Or is this companies that develop a unique moat, regardless of the space they're in, get to capture most of the market share?

• 10:04Speaker 05

  Well, I think you've seen in mature industries, whether you look back at GE and Coca-Cola, you've seen certainly there's advantages to having that dominant distribution and market share. But in technology, I think it's more a story of getting in front of your competitors and investing more, you have more dollars to invest back in the technology and to grow that lead and that compounding of advantages when, or compounding of innovation at the early part of a market's development can be incredibly powerful. And then that gives you the opportunity to put in place other kinds of moats that do kind of block your competitors from coming along.

• 10:48Speaker 05

  You know, there's a, there's a lot of discussion today around Nvidia, that a lot of people sort of assume Nvidia is going to lose their, their massive market share in AI accelerators, which is roughly 85%. And certainly I think the, the move to inference is an opportunity for competitors to change what's going on there. But I think people right now are, for instance, underestimating Nvidia's opportunity to innovate as well.

• 11:20Barry Ritholtz?

  So let's define some terms for some of the laypeople that might be listening. Compute and inference. Explain what those are. Explain how they're investable themes.

• 11:31Speaker 05

  Sure. So the, the training compute that, that, or the chips, the AI accelerator chips, and today Nvidia dominates that still with their graphics processor chips. And that, you know, those chips originally were made for gaming, for doing very rapid mathematics that have to do with calculating physics and lighting, shading in video games. It turns out that the same kind of mathematics are incredibly well positioned to do the math around AI.

• 12:15Speaker 05

  And then, so you're, you're training a model, an AI model that will be able to make judgments. And then when you're actually using that model to ask questions and, and, you know, or have it solve problems and, and actually execute those problems, that's called inferencing, right? And so inferencing can be done on a more simple chip. So people have kind of used a phrase XPU to, to, to X out the graphics and that say, this is going to be, this is the next generation of chips that can be used to actually solve the problems with those models that are built.

• 12:54Barry Ritholtz?

  Meaning the compute and the inference are going to be on the same chip?

• 12:57Speaker 05

  They can be, they can be done with the same chip, but you can have a more specialized, lower cost chip, usually an inference with more memory, for instance. And there's different approaches and software to, to execute that with a lower cost chip.

• 13:12Barry Ritholtz?

  So it sounds like our, our alphabetical evolution has been CPUs, then FPUs, GPUs, and now XPU's. What's beyond that?

• 13:22Speaker 05

  Well, I think that's why we use the term X is, you know, there's TPUs, you know, Google's version of, of their AI chip. We've got Tranium, et cetera, and others, competitors. So there's, there's, there's lots of flavors. You know, you also saw, for instance, Nvidia buy Grok, which was another approach to inference. So there will be many flavors and many opportunities and ways to innovate in, in inference to, because ultimately that will be a larger market than the training market.

• 13:57Barry Ritholtz?

  Really, really interesting. So I usually save my mentor question towards the end of our conversation, but your list of people you've worked with and worked for is just so incredible, I, I want to get it out early. In addition to Julian Robertson and Roger McNamee, there was Philip LaFont, Steve Mandel, Chip Morris, who was, I think, at Blue Ridge, Alger Viking, Lone Pine and Pala, Matrix, Kotu. That's like a murderer's row of, of modern investing names. What, what did all these legends have in common? And how were they each different?

• 14:38Speaker 05

  Well, I think the focus for, you know, we had a great team there at, at Tiger Management, and so many of us went on to start our own firms and in many of them in, sort of modeled by what we experienced at Tiger and seeing how Julian did it. I think Julian was just such an inspirational leader and, and had, was so values driven and really focused on, hey, we want to work with the best people. That doesn't just mean the people around the table with you on your investment staff. That also means the CEOs that we backed and the CFOs of those companies. We, we looked for people that we thought were of high integrity and, and if there was

• 15:23Speaker 05

  any question about the integrity of, of, of those CEOs and CFOs, we were out. We, we just weren't interested in that company. And, you know, and then, you know, Julian was, there were no shortcuts, right? It was, you got to do the work, explain to me why and how we got to the conclusion that this company is, one, positioned incredibly well and, two, it has a real opportunity. There's something fundamentally changing in their industry or in their product set that's going to change their trajectory. And then the last one was, hey, let's, let's use our power and, and success to help other people, right? And so the combination of that, of those principles was very powerful.

• 16:06Speaker 05

  We all, I think many of us wanted to see if we could do, do something similar and, and that was really powerful. And then I was lucky to go on to work with Roger and John Powell at, at Integral Capital and Chip Morris. All three of those guys came out of T. Rowe Price. And we worked with Kleiner Perkins, we were in their building. So we had an incredible, we were surrounded by some other incredible investors and that just saw things early and really invested in great entrepreneurs, people like, you know, Jeff Bezos and the founders of Google. And it was just, it just, I was lucky that I was able to see so many inspirational people and things happen early in my career and just wanted to, wanted to try to do it on my own.

• 16:48Barry Ritholtz?

  Really, really fascinating. Coming up, we continue our conversation with Glenn Katcher, founder and CIO of Light Street Capital, discussing the firm's founding and launch. I'm Barry Ritholtz, you're listening to Masters in Business on Bloomberg Radio.

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• 19:22Barry Ritholtz?

  I'm Barry Ritholtz. You're listening to Masters in Business on Bloomberg Radio. My extra special guest this week is Glenn Katcher. He is founder and chief investment officer of Light Street Capital. The firm is a technology-focused hedge fund and private investment firm located in Palo Alto, which is a good place to start. You launch in 2010. The great financial crisis is still dominating the news flow. What was the original pitch to investors?

• 19:57Speaker 05

  Sure. The original pitch was, look, we've, the game board had kind of been reset in terms of making money. Multiples were low. And we saw the emergence of kind of four things. Mobile with the smartphone really growing. At that point, it was becoming a dominant platform. Social media with, well, still, most of it was private, but we saw Facebook and emerging and Twitter and really redefining media. Cloud, the development of taking the internet technology and using it for business and the

• 20:39Speaker 05

  ability to propagate applications, you know, everywhere that the internet was available was incredibly powerful. And e-commerce, the ability to, you know, sell goods anywhere at a very low cost and, you know, with the backend that Amazon and others had built to get products delivered within a day or two to many locations in the globe. Those four things were incredibly powerful. And then ultimately, we saw things like the sharing economy coming out of that. You couldn't have had Uber and Lyft and DoorDash without having e-commerce and the mobile

• 21:19Speaker 05

  phone and the ability to get those companies distributed through the mobile universe. So there was a real emergence of these four powerful things, mobile, social, cloud, and e-commerce. And it was really redefining what we could do as consumers and business people.

• 21:36Barry Ritholtz?

  I love how you described the firm. We are the Silicon Valley home team, one of the few hedge funds living and working at the center of the technology universe in Palo Alto, 100% focused on tech opportunities. The first time I read that, I was like, that can't be right. There has to be tons of hedge funds out there, like not many hedge funds in the center of the VC universe, because all of those successful venture investments eventually go public.

• 22:08Speaker 05

  Yeah, there's a relatively small number of public market managers out there. And a good number of, you know, you've seen Philippe, what he's done at Cootu has been amazing. And Tiger Global, Chase has done incredibly well, and Whale Rock out of Boston with Alex. And so you've just seen the success of those guys. So I'm not saying it can't be done, right, by any means. But there is a real advantage to living and working in the place where the innovation is centered. And I think when we've, you know, when you see this fundamental innovation like we're

• 22:44Speaker 05

  seeing now with AI, it really draws, draws that advantage of geography back to Silicon Valley. I think there's, there's a small number of great AI entrepreneurs, and they want to be in the same community with one another. And so that's, that's a real advantage for us.

• 23:06Barry Ritholtz?

  Yeah, I kept hearing that San Francisco was over. It's dead. The city is, you know, on its last gasp. We were there in the spring, and the city is just, it's a boom town. Like, I know there's a little bit of a boom and bust, West Coast, gold rush mentality, and each new cycle of technology kind of works its way through. But it's, to anybody who steps foot, we were down by the Embarcadero. The city is just absolutely on fire. What's it like? Is this feel like the late 90s in terms of the amount of human capital, intellectual capital, and actual money sloshing through?

• 23:46Speaker 05

  That's a great question. I'd say more than mid 90s, probably. I think that the, the, we're at a point where this is very fundamental, low-level technology. We've seen something of a renaissance in the hardware industry, and that hardware innovation really matters when you're trying to scale, when you're trying to scale at the rate.

• 24:12Barry Ritholtz?

  Meaning semiconductors or everything around it, or the whole?

• 24:16Speaker 05

  Semiconductors, networking, you know, down to printed circuit boards, just the, you have to innovate at sort of every level of the stack in order to grow at a 10x, 100x rate. And the acceleration required in order to provide AI cycles at a competitive price is incredibly challenging. And, and, you know, the amount of demand that's out there is incredible. So the need to scale is back. And I think, you know, it's, it's pretty interesting, you know, what we've seen, you

• 24:55Speaker 05

  know, I think in the early 2000s, and the semiconductor industry was allowed to consolidate, and the capital was provided to do that. And you saw a company like Avago and Hock Tan, you know, really organize the industry and do some horse trading of, of properties to other, to other semiconductor firms and really rationalize that industry. And so as AI has emerged, what it's done is, it's, it's really taken advantage of the fact that there are a small number of companies that compete for a massive market.

• 25:37Speaker 05

  So AMD and Broadcom and Nvidia and TSMC, of course, in Taiwan on the backend. And then, of course, the semiconductor capital equipment companies like ASML. Those companies just have very large market share and have huge demand and huge moats and advantages.

• 26:00Barry Ritholtz?

  So let's talk about the first four companies you mentioned. Taiwan Semi, Nvidia, Broadcom, and AMD. That's about 40% of the public portion of your portfolio, or at least it was a few filings ago. I know you're not a big fan of revealing your, too much of your portfolios, but that's a fairly concentrated portfolio. Tell us the thinking behind having such a dominant emphasis on those four semiconductor companies.

• 26:31Speaker 05

  Sure. Well, it goes back to what I was saying earlier. You want to, you want to focus your capital in the place where you see the most innovation. And, and right now, that's at the, the core of accelerating computing in order to do AI. And you've, you know, right now Nvidia's got 80-plus percent market share in the network GPU market. AMD is certainly coming up in that. And as we move to Agentic AI, which is a very important innovation that's happening in AI and is really driving that next leg of growth, there's certain advantages that AMD has as being, because they also are, you know, one of the two major players in the

• 27:15Speaker 05

  CPU market and for desktops and servers. So, so there, you know, that, that explains why AMD matters a lot. And Broadcom and what they've been able, what they've done with Google with their TPU over the years is incredibly impressive and has gotten them now opportunities with OpenAI and some of the other major AI players. So that's certainly great exposure. And then TSMC makes the chips for all three of those companies. And the ability to kind of win, no matter who wins, and really have a massive oligopoly,

• 27:56Speaker 05

  monopoly almost for TSMC, we certainly want to back that company as well.

• 28:02Barry Ritholtz?

  So those four companies, plus Microsoft, you described in 2024 as the AI5. And while everybody was focused on the Mac 7, the AI5 significantly outperformed the Mac 7 that year. Is it still a concentrated holding all five? And how does that thesis hold up today?

• 28:24Speaker 05

  That's a great question. Yeah, I'd say. The company that's kind of been in and out of our portfolio, mostly out, has been Microsoft. And their early lead with OpenAI, they, in our opinion, kind of fumbled that.

• 28:40Barry Ritholtz?

  And hence, giving an opening to Anthropic?

• 28:44Speaker 05

  Yes, for sure. And so, you know, the uptake of Microsoft's AI that was, you know, somewhat powered by OpenAI really didn't work that well. And that was a real miss for them. And ultimately, they pulled back on their development and funding of their AI efforts. And I think they're now back in the game. But at the same time, what we're seeing now is, you know, they're, for instance, Microsoft is the largest security company in the world. And one of the things that we've learned is that AI is a, creates a lot of security

• 29:27Speaker 05

  vulnerabilities for businesses. So, any business, you know, is going to need to invest more aggressively in their cybersecurity defenses. And so, that will be a big benefit for Microsoft. So, that's a huge advantage for them. But I think what they've done and the repositioning that they've done on the Azure side of their business has been very impressive. They've also rationalized some of the spending that didn't, wasn't going as well in their gaming business, are sort of pulling back there. So, I think they're repositioning the company well after they sort of blinked on AI. And, you know, we're, it's back in our portfolio at this point.

• 30:09Barry Ritholtz?

  So, when we talk about Agentic and we talk about the major AI players, is this going to be a duopoly? Is this going to be Anthropic and OpenAI? Or is it going to be a little more wide open than that?

• 30:22Speaker 05

  Yeah, it's, I think, this battle's happening in real time between those two leading companies. And Google's certainly still a player with Gemini and their, their advantage in distribution with their massive success, of course, in the, in the search engine business. And they've also, now they're backing Apple's AI efforts as well. So, they have a real distribution advantage. So, I wouldn't count Google out, and they still have great technology.

• 30:55Barry Ritholtz?

  By the way, their Notebook LLM is outstanding. If you want to upload a giant, a file, a book, or anything, it's unbelievably accurate and fast. I've been really impressed with that.

• 31:09Speaker 05

  Yeah, it's, it's, you know, their ability to innovate is, you know, stunning. So, but, but the real battle that's emerging today is, is open source models that, one, are cheap, cheaper than the closed Anthropic and OpenAI models, because there's, you know, they're free. You can download them for free and run them on local hardware, or you can engage with them on, on other commodity hardware in the sky. And that, those, those open source solutions are really battling these more expensive frontier models from the two big companies.

• 31:51Speaker 05

  So, we'll, we will see, I think, the, the early signals are that, that there's a place for both of these solutions broadly defined. There's also some regulatory questions. Open, open models, you really can't regulate very well because you can install them on your own software, you can adjust them to work how you want, so that, you know, there's questions about how to make sure these are engaged safely and in the wild. But there's also not a lot of choices around, for regulators too, because those are in the wild.

• 32:26Barry Ritholtz?

  So, so I want to combine your, what you've said about Microsoft and security and open source. Is it fair to say that security-aware enterprises are going to be steering clear of open source because of the various security problems? And the duopoly of Anthropic and, and OpenAI is going to be where the big players are going to end up? If for no other reason, if there's a hack, it's a defendable decision?

• 32:57Speaker 05

  Well, there's two questions. There's using AI within your four walls and being able to provide the proper controls to make sure that it doesn't get to your, to get, get to your data that is, that is sensitive, and that it doesn't somehow leak that, or you don't, or distribute that. The second is what a bad actor can do with an open source technology out, from outside of your firm, trying to break into your firm. So, there's, those are, those are the two things that you have to, you know, account for with your cybersecurity spend. And so, there's, there's, there's lots of opportunity for, whether it's CrowdStrike

• 33:42Speaker 05

  or Palo Alto and Microsoft, as we talked about. But, but you've got to protect those. And you, you know, in addition, when it's, you're internal to your organization, understanding what the roles of the technol, what the roles are of the user of that technology, or the open source technology, and what they can access as a user, you have to make sure you, that you honor those restrictions as, you know, utilizing an agent system.

• 34:10Barry Ritholtz?

  So, we're talking a lot about public companies. Let's just look at some of the private venture investments Light Street has made over the years. And, and this is quite a list. Uber, Lyft, Slack, Pinterest, Toast, Harry's, Everlane, Box, Black Buck, EasyCater. In 2018, at the Ira Sone Conference, you presented Palo Alto Networks, far, far cheaper price than where it is today. The, at a later Sone Conference, you presented FarFetched. All of these have become giant winners.

• 34:47Barry Ritholtz?

  The, the key question I have to ask is, what does investing in VC teach you about public companies and vice versa? What do you learn about public companies that are useful when evaluating a venture opportunity?

• 35:04Speaker 05

  Sure. You know, in the venture companies that we invest in, and even the ones we don't invest in, there's real value into understanding where, what's happening in, in the industry. The, the advantage for us as an investor is that when we meet a CEO or founder of a company and trying to understand what they're, how they're solving a problem, they're starting with a blank sheet of paper. They don't have ties to some incumbent solution and incumbent set of customers that they've, they've been trying to keep happy for, you know, five, 10 years usually. So, they're able to, to be most aggressive in adopting new technology.

• 35:48Speaker 05

  And so, what we learn is, you know, that we can apply in our private investing and our public investing is what matters to them, what, what technologies are, can solve the problem with no constraints, you know, around keeping incumbent, their, their long-term customers happy. So, so that's, that's a real advantage. And I think, you know, when we, as, in 2022, 2023, as AI was really emerging as a, as a category, when we were talking to some of these early-stage firms about, okay, what's, how are you developing your AI solutions? And what, which solution, you know, which semiconductors and, and infrastructure and

• 36:31Speaker 05

  service providers are you using? That gave us a real insight into Nvidia and AMD and Broadcom as, and Marvell, as potential investments for our public side.

• 36:46Barry Ritholtz?

  Long before people were talking about it in the mainstream, you're, you're hearing this directly from these clean sheet venture startups.

• 36:54Speaker 05

  Yeah. I mean, there's, there's one great story when I was at, at Integral. Bill Joy was a partner at Kleiner Perkins for several years.

• 37:04Barry Ritholtz?

  Previously at Sun, if I remember correctly, right?

• 37:06Speaker 05

  One of the four founders, sure. And, and Bill, I can't remember the exact year, it was early 2000, early to mid 2000s. And he was talking about this, this group of engineers that he came across, I think it was at Caltech, that were utilizing the GPU to do early AI calculations. And so, this is 2005 or 6 or something like that. And, you know, we, so I always, you know, the conclusion of that team and of Bill himself, one of the great pioneers of Silicon Valley, was that GPUs would be the best chip architecture to do AI calculations. So, I always had that in the back of my mind.

• 37:49Speaker 05

  And over the years, when we would visit with Nvidia, we would ask about AI. And Jensen would talk about it, and it was a tiny, tiny product and solution or end market for them. But, and at that time, crypto mattered a heck of a lot more. But it, we, we were very fortunate in the back half of 22, crypto crashed, you know, at the time, at the same time as AI was taking off. And so, that gave us-

• 38:18Barry Ritholtz?

  It just pivoted? Was that, was that simple for them?

• 38:21Speaker 05

  Well, they, they were always working on these things, right? And, and it's really about market adoption more so than, than they're addressing it, right? And, you know, it just so happens that these things coincided. The mark, the stock market was much more focused on what was happening with crypto that drove the stock down, and not as focused on this emerging opportunity in AI. And so, as AI took off in, in the back half of 22, we were able to build a great position in Nvidia.

• 38:52Barry Ritholtz?

  So, let's talk about that, that run following 22. You guys had one of the best three-year runs of any hedge fund in recent memory. I'm, I'm looking for my exact numbers. 21 and 22, the whole market got chalacked in 22. 21 was a rough, you were down 26% in 21, down 54% in 22, and then come screaming back-

• 39:21Barry Ritholtz?

  Uh, in twenty-three, four and five, you're up forty-six percent, fifty-nine percent, and thirty-seven percent. First of all, how much are you just holding on for dear life when you see numbers like that? What's it like to live through the regular sort of drawdowns that technology goes through? Um, how, how, how much beta are you, how much volatility are you experiencing and how do you manage around that?

• 39:51Speaker 05

  Yeah, you know, it's very challenging. I mean, I think it was a very frustrating time, obviously, in, for us in twenty-one and twenty-two. We came off an incredible twenty-twenty where we, you know, played the COVID market incredibly well. We're short going into COVID emerging. Uh, it got very short the market and then had a tremendous run backing SaaS and e-commerce through that period of, of, of the world being in kind of a quarantine. And, um, you know, we, it was a difficult, uh, transition coming out of that for us. And, and so really rough time. Uh, software, uh, really got hit in

• 40:33Speaker 05

  twenty-two and over a course of a month or two. And, um, you know, had, we had to reevaluate what we were doing, you know? And, and that was tough, you know, it's a tough time. And so I think the ability to step back and say, okay, AI is emerging and these are the, uh, incredible companies that are, you know, very well positioned for it. Um, you know, I think, and they were trading at what we thought were attractive valuations. And so we've just been, you know, solving for, for looking forward over the next, you know, six, twelve, eighteen, twenty-four months, um, since then and had, had a, you know, it's been very fortunate that we've, we've been in the right place,

• 41:17Speaker 05

  uh, as AI has emerged.

• 41:19Barry Ritholtz?

  So, so let's talk a little bit about that philosophical look. And, and obviously, AI and software is a perfect example of what you've described as long the disruptor, short the incumbent. And it's not just SaaS versus AI. Um, you could be long Uber was an example I, I saw you discuss once, and short rental car companies. Walk us through those kind of, of trades philosophically.

• 41:49Speaker 05

  Yeah, well, you know, we don't necessarily do paired trades, but, um, if we think there's a, a, a well-positioned solution like Uber at a certain period of time and, and, and think that's, that's, you know, benefiting from this, this, uh, merger of, of, of e-commerce and for them and, and mobile and dominant market share, um, you know, we'll, we'll go along that. And if we see a company out there that's getting displaced or, or substituted, you know, there's, there's short opportunities. We look at them as independent opportunities, frankly. Um, so I think sometimes, uh, the market or the press around the, the stock

• 42:31Speaker 05

  market, uh, tries to simplify things into a, a, this is good, this is bad, um, you know.

• 42:37Barry Ritholtz?

  If only it was that easy, right?

• 42:39Speaker 05

  Yeah, I think, you know, I think, I think sometimes, uh, that, that leads to things getting overdone. I think software, just in the last, uh, month or two, has really had an incredible, uh, bounce back. The, I think people, the SaaS po- cop, SaaS apocalypse, if I can say it. Um, you know, that, uh, that view that software is, is doomed is sort of a, a very, a huge simplification, right? I mean, I think if you look at the history of what happens with incumbent technologies is if they're, if they solve a problem really well, they can stick around for a long time. And I think until very recently, many brokerage

• 43:24Speaker 05

  firms and banks are running, uh, mainframe solutions still, uh, because it works. And, you know, when you get a new technology, you wanna, you wanna take that new technology and you wanna apply it to do new things, um, that really gets you an advantage on, versus your competitors. You don't wanna take a new technology and say, what's the boring, uh, business process that we've automated and it really works really well that we can apply this new technology to? No one does that, right? That would be a waste of, of innovation in a lot of ways. So those core systems don't tend to get swapped out. So you get these opportunities for bounce backs. And, um, you know, that's, you know, we're

• 44:07Speaker 05

  taking advantage of, you know, the, the doom and gloom as well as, as, as the excitement about the new things. That's what we have to do.

• 44:15Barry Ritholtz?

  Really, really interesting. Coming up, we continue our conversation with Glenn Kacher, founder and chief investment officer at Light Street Capital, discussing the current environment for AI and beyond. I'm Barry Ritholtz. You're listening to Masters in Business on Bloomberg Radio.

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• 46:45Barry Ritholtz?

  I'm Barry Ritholtz. You're listening to Masters in Business on Bloomberg Radio. My extra special guest this week is Glenn Katcher, the founder and chief investment officer of Light Street Capital, a technology-focused hedge fund, uh, located right in the heart of Silicon Valley in Palo Alto. So I have so many great quotes of yours I, I want to, uh, throw by you. I'm gonna start with variant perception. We look for a mismatch in perception and reality. Timing matters, but there must be a thesis about when and how the mismatch resolves itself. Oh, so that sounds pretty easy. That's all you have

• 47:29Barry Ritholtz?

  to do. Tell us a little bit about identifying that variant perception.

• 47:33Speaker 05

  You know, I started this by talking a little bit about why I got excited to, to be an investor from the beginning. And, and, uh, part of it is being a detective, right? And going out, talking to people firsthand, uh, working with my team, uh, of investors that, that, that work at Light Street Capital every day. And we all operate in the same way, as, as Roger would say, everybody goes out for a pass. And go out, talk to the people that, that matter, talk to the customers, talk to the suppliers, talk to the innovators themselves. And, um, and that's, that's how we, we try to get it done and, and, and

• 48:10Speaker 05

  get the real story. I think we're in a situation today where, um, where AI is, is, you know, now being cast as sort of this evil empire that is going to, one, cost people jobs and, and two, um, you know, you know, it's crazy, evil people, overspending, and it's certain, you know, like, it's, it's, it's gonna crash and, and burn, uh, eventually. Um, and that's really not the story of AI. The story of AI is that the end users are, uh, self-selecting

• 48:50Speaker 05

  every day in their browser, or now with agent software or, or their, um, development tool to build more software. And they're saying, this is how I can get more done quickly and well with these tools. And that's what's driving the demand, that's, that, that's creating, uh, the capacity build for, of AI, uh, compute. And so we look at that and say, you know, there's, there's a, there's a mismatch in the way AI is being perceived today. And, um, that will reverse, but you have to figure out when.

• 49:27Barry Ritholtz?

  So that's a productivity story. It's an efficiency story. And obviously, it's a profitability story.

• 49:33Speaker 05

  It's a demand story.

• 49:35Barry Ritholtz?

  Which kind of raises the question, you're focused on the core AI players. What about everybody else? Forget the Mag Seven, the next 493 in the S and P 500. What does this mean to the rest of corporate America?

• 49:52Speaker 05

  Well, it I don't think you can forget the Mag Seven. But what does it mean? But we'll put that aside. Um, you know, what does it mean for the rest of corporate America? I think it's it's gotten their attention. It got their attention pretty quickly. And, uh, you know, I think if you talk to anyone on the board of directors of a public company or the CEO and top managers, they're saying, gosh, you know, we see, we hear bad AI. We need, we need to come up with a plan. Uh, we need to figure out how we're going to harness this tool and make it work for us. And so that is, um, you know, that's, that's the, the task at hand.

• 50:35Speaker 05

  I think it's still early to say, well, this company is doing a great job with AI. So we should buy their stock that, uh, you know, that's not, to me, a great, a great, uh, you know, thesis for today for investing. But, um, you know, I think that, that everyone that I talk to in corporate America is very focused on, hey, we've got to take advantage of this tool.

• 51:00Barry Ritholtz?

  You, you mentioned demand is, um, really surprising everybody. I want to say it was the second quarter, even Jensen Huang at, at, um, Nvidia was surprised, uh, for his expectations for the AI infrastructure spend from by 2030. I think he bumped from one trillion to four trillion. That's just a Forex giant set of numbers. Um, are, are we running the risk of over allocating to AI the way we did for things like fiber and go down the list of every new technology that seems to get over allocated?

• 51:42Barry Ritholtz?

  But at what point does this become, is this explosive upside demand gonna, gonna? When, when does the coyote step off the cliff and not realize he's gone a little too far?

• 51:53Speaker 05

  This is, this is the big question everyone's battling with, uh, today. And I, I think, um, you know, the, the Mag Seven, we talked, you know, mentioned a minute or two ago. Um, they have really become the key partner. I think if you look at Amazon, you look at, uh, Microsoft, Google, um, those companies are, um, partnering with Anthropic and OpenAI, um, in order to fulfill, uh, on building this compute stack and the infrastructure to run AI. And are they, the question is how far ahead of, um, demand is, uh, are, are they planning?

• 52:36Speaker 05

  And reality is they're not ahead, um, today. They're behind.

• 52:41Barry Ritholtz?

  They're trying, they're playing catch up now.

• 52:42Speaker 05

  They're playing catch up. The, uh, negative, um, you know, doomers are expecting them to over invest. But today, uh, that's just not happening. I mean, there are bottlenecks, right? There are bottleneck, real bottlenecks and it's quite a, uh, quite well discussed that have slowed down the ability to build. And, um, you've got companies that are in, in control of, uh, some of those bottlenecks, whether it's memory, uh, companies, uh, which we like as well, um, or whether it's Taiwan Semiconductor. They're actually, they can only invest so fast. Um, so today, demand is still running way ahead of supply.

• 53:24Speaker 05

  And so this doomerism that has, uh, grown up around AI, uh, in my mind is, is, is misplaced.

• 53:32Barry Ritholtz?

  Let's talk a little bit about the bottlenecks. Uh, I, I use, I use Gemini, I use Notebook, I use Chat, I use Perplexity. But really Claude Pro has become my, my favorite, uh, way to, to engage. And I've noticed just going from Opus to Fable, like an order of magnitude, faster, deeper, better. Uh, it doesn't feel, and, and these are coming along like every few weeks. It doesn't feel like there's much of a bottleneck. When you say bottleneck, what are you referring to?

• 54:06Speaker 05

  Well, I think the bottleneck drives the pricing higher, uh, than it needs to be today. Right? And so, um, no offense, but you're, you're probably not paying for your Claude, uh, traffic. Bloomberg may be paying for it.

• 54:21Barry Ritholtz?

  No, I'm paying, it's, well, my firm is paying and it's 200 a month. And then we just did a whole enterprise thing and it's, it hasn't been cra-. Like I keep hearing about people just going crazy on credits and spending a year's worth of credits in a month. We're pretty reasonable and a little aware of, of our spending. But it's not like it's a hundred thousand dollars a month. It's fairly reasonable for the output yet, right?

• 54:53Speaker 05

  I, I've been surprised. We're, we're, we, we have our own software, uh, product and, uh, uh, stack that we have developed on for 15 years that where we run our entire, uh, research process. And so we're constantly improving that. We're also doing analysis and of, um, and sentiment tracking, et cetera, of, um, sources that, that we, of, of data that we buy. And it's not, it's not cheap, um, to do that.

• 55:24Barry Ritholtz?

  Are you spending 50,000 a month, a hundred thousand a month? What, what does it look like? What is a typical hedge fund in the tech space? Not necessarily yours, but what do you think people are spending? I know I'm only scratching the surface for what I'm doing.

• 55:37Speaker 05

  For programmers, it's not uncommon to spend, uh, a hundred dollars, you know, a, a day. So, you know, it's, it can get expensive, you know, uh, and that adds up, that can add up quickly.

• 55:48Barry Ritholtz?

  Sure. 30 grand a month is not nothing.

• 55:50Speaker 05

  Yeah.

• 55:51Barry Ritholtz?

  All right. It's a

• 55:52Speaker 05

  You can spend a lot more than that, too.

• 55:53Barry Ritholtz?

  Uh, well, you know, a couple of months ago, there were stories about, wait, we had a whole budget for a year and it's gone in a, in four weeks. Is that the bottleneck, being able to service the, the super clients, the, the hyper users like that?

• 56:07Speaker 05

  Well, uh, that, that's, that, that's where this demand for the open source solutions comes in, that you're far, far cheaper, right? And so the ability to, to load it up on your own hardware and have it run and, and be able to also adjust the weightings of the model and, and, you know, train it on your own, uh, data. Those are all very powerful opportunities for, uh, for investors or, you know, just general, any kind of, uh, business. So, um, you know, being able to do more for less is certainly attractive.

• 56:42Barry Ritholtz?

  So another quote of yours, you, you were talking about the AI build out and you said, it's a 10 year cycle of demand. The bear case is that CapEx gets cut the moment returns disappoint. Tell us a little bit about why you think this demand cycle is going to go a full decade.

• 57:02Speaker 05

  Yeah. Well, I mean, I think we're, we're changing the entire stack of computing. The, the only thing that looks like this, um, that we've experienced before is the move to, uh, is the move to the internet architecture from client server. And, you know, these, these computing cycles happen about every, you know, 15 to 25 years since, you know, since the, the, the development of computing. And the way the technology works is completely different. Um, you know, in the old school of technology is a search and retrieve, uh, or create, uh, search and then retrieve model, uh, where you stored things in databases.

• 57:45Speaker 05

  And here in, uh, in, in AI world, uh, we're, the technology is essentially creating a custom solution, uh, custom to your question, custom to, um, your, uh, data every single time you, you use it. Um, it's just a much more complex and, um, and a compute intensive model. And, you know, the, the ability to have custom solutions and custom, uh, custom answers every single time you, you need data is, uh, is so much more powerful.

• 58:26Speaker 05

  Um, that, and, you know, if we follow history, these things take, you know, 10 to, to 15 years to become a quarter of the total capacity of the industry. So, uh, to say that it's going to take multiple decades is, is not much of a stretch.

• 58:41Barry Ritholtz?

  So where are we? Are we in year four or five now of a 10 to 15 year first leg?

• 58:47Speaker 05

  Yeah, we're exactly, we're kind of a third of the way through the first leg. I mean, if you look at the way technology develops, it's, it sort of goes in three cycles. You know, your big infrastructure, uh, development years take, you know, five to 10 years, let's say. Then, you know, then year six, year six through 16, let's say, uh, that's when your platform, uh, or OS really gets developed and, and, and put into place. And then the, the, uh, the applications kind of come in years, you know, 11 through 21. And, and, and, you know, applications become the dominant, uh, place where, uh, businesses invest and, uh, the innovation happens.

• 59:30Speaker 05

  So it's at least a 15 to 20 year, uh, cycle that we're looking at.

• 59:35Barry Ritholtz?

  I'm kind of fascinated by the energy demands and the build out of these giant data centers. Um, and I'm curious, what are your thoughts to the? Political pushback to where these are located. A couple of states have already banned them. Um, I never saw the politics against tech morphing this way. How do you look at that as a investment risk?

• 1:00:01Speaker 05

  It's a real risk that, you know, there, you know, any bottleneck that slows down the adoption of your technology is, is a problem, right? We're, we're investing in Nvidia or Taiwan Semiconductor saying, okay, here's what we expect. And in our view, the numbers are still significantly better than Wall Street's looking for. However, we have to, we have to bear in mind, you know, is there something, is there an obstacle that's going to get in that way today? It's, in our view, um, you know, not a, a, a big enough problem, but it's an, it's an emerging problem. And I think the way, as an industry, we have to get around this is that we have to explain

• 1:00:43Speaker 05

  the places that invest, uh, most heavily and most aggressively. Uh, you know, if you look at Northern Virginia, uh, not far from where I grew up, um, you know, that is the data center capital of the world. And that opportunity and what, what's happening, what's happened with, uh, tax receipts in those communities that, that have, that have all these large data centers and the demand for blue collar work in to, in order to build those data centers, whether it's, uh, electricians and plumbers and construction work. It's a, it's a massive, uh, you know, shot in the arm for those economies.

• 1:01:23Speaker 05

  And then the, the tax revenue is, is an ongoing, uh, ongoing, uh, payment that happens over many years. So I think it's a, it's a little bit, uh, it's sad that, that, uh, some of these communities are not as, um, positive about, uh, about the opportunities. I think they're just not well-educated by, uh, their elected officials.

• 1:01:48Barry Ritholtz?

  I, I'm not surprised that it's in Virginia or New York. I'm enormously surprised when you see pushback in places like Texas, um, which is big enough that you can stick a data center out wherever there's juice and, and nobody has to see it, hear it, be concerned about it. Um, but it, it, it keeps raising the question of cost of electricity and people seem to be concerned, we let a data center in here, our electrical costs are going to go up. Uh, how should we as a, a tech savvy nation of investors respond to that concern about electricity?

• 1:02:31Speaker 05

  Yeah, absolutely. The, the, the, the source of electricity needs to be behind the meter, right? So the, the, the firm, uh, that creates the data center, if it's in a, i- i- if there's not enough existing, uh, energy, then they have to provide the energy.

• 1:02:47Barry Ritholtz?

  So run a, run a gas line, set up your own generator and you're off the grid.

• 1:02:53Speaker 05

  And if it's closer, it, it, look, if it's close to a residential area, there's, there's actually a data center that's being contemplated in San Mateo, uh, California, not far from Palo Alto. And, um, you know, their, their solution is to put Bloom Energy, uh, servers behind, which are natural, powered with natural gas, uh, with not, almost no emissions. And, um, and they're incredibly quiet, almost no audible sound. And you can put a Bloom Energy, um, uh, fuel cell behind the, the meter. And even, even though that's the plan, um, residents have rallied against it because they've heard data centers are bad.

• 1:03:37Speaker 05

  Um, they're just not educated on what the solution is and how it will not impact their energy prices and there will be no emissions and no noise.

• 1:03:46Barry Ritholtz?

  And, and we have midterms coming up in November. Is this the sort of thing that once we get past the next group of elections, this will fade or is this really an ongoing challenge for the industry?

• 1:03:59Speaker 05

  It's an education challenge, yeah.

• 1:04:01Barry Ritholtz?

  Yeah.

• 1:04:02Speaker 05

  We've got, we've got it. And it, it, it's from local to national, right? Each project has to explain this is the, the, this is the decision we're making around procuring this energy. This is the, these are the number of jobs it's going to create. These are the tax revenues it's going to generate. Here's our existing energy, uh, situation. This can go on the grid without much of an impact or, or, you know, we're, we're, we're bringing our own energy. So it's a, it's both a local and a national solution.

• 1:04:31Barry Ritholtz?

  Huh, really, really interesting. And, and the Mag Seven keeps coming up. When we met in, um, the spring in San Francisco, you liked Amazon, Google and, and Nvidia. I don't recall what your thoughts were on Microsoft. You weren't a big fan of Meta, Tesla and Apple. How do you see the Mag Seven today? Is that, is that still fairly consistent or?

• 1:04:55Speaker 05

  That's fairly consistent, yes. You know, as I said earlier, we're, we're, we've put Microsoft back in our portfolio and, and, and so we're, uh, I'd say that they're, they're back in the good category. The challenge for, for Apple is to get their AI solutions, uh, tuned up and working well for the consumer. If you think about your mobile phone, it's a, it's in a very unique position. It, it has both your personal and your business data to the extent that, you know, you're, you're a, uh, not a small business person and, and it's, and that the security is there to separate those two things.

• 1:05:34Speaker 05

  Um, and so that device has the ability to optimize and, and recommend, uh, actions or, or, or solutions to you as a consumer that, uh, address both your business life and your personal life. And that's, that's a very unique position that Apple's in. And obviously you carry it around and it's on most of the time, if not all the time. And, uh, they have a real opportunity to bring AI solutions to, uh, to, to democratize them for, uh, consumers and, and in a very complicated and, but elegant way. And so, you know, if Apple can get things right, that, that should, uh, accelerate their

• 1:06:17Speaker 05

  opportunities or, or earnings over the next couple of years.

• 1:06:21Barry Ritholtz?

  They don't have a great history with it. Siri has been nothing less than a total embarrassment for a decade. I mean, I'm not revealing any secrets here. Everybody knows it's garbage. Um, and there was some criticism of Apple for not jumping in with both feet to become a hyperscaler and spend tens of billions of dollars. What they've done with Google has worked out great for both companies. Hey, what's a couple of billion dollars a year to Apple? And to Google, it's pure profit. Is the same sort of setup teeing up where it's a win-win for Apple to integrate Google's technology into the iPhone?

• 1:07:04Speaker 05

  Potentially, but it's execution based.

• 1:07:07Barry Ritholtz?

  Mm-hmm. Isn't that always the case?

• 1:07:09Speaker 05

  It, it is, but they're, but their strategy, this is a very consistent strategy where they are the, you know, the, they were not the, the first smartphone, right? They waited, uh, they, they, they watched what Nokia did, what, what, uh, BlackBerry did and, uh, rim BlackBerry. And then they came out with a, a more elegant solution after those guys established the market.

• 1:07:32Barry Ritholtz?

  Um, second mouse gets the cheese. Is that the, uh, the thinking there?

• 1:07:36Speaker 05

  Well, if you have a big bank account and, and, uh, users that really, uh, will wait around till you solve the problem in a better way, then it works.

• 1:07:46Barry Ritholtz?

  Last question before we get to our favorite questions. So I'm not going to ask you about 20 years out or 10 years out, but five years out, what does this technology look like? What's going to define AI for the consumer and business customer in 2031?

• 1:08:04Speaker 05

  Agents. The ability to have the technology working on problems, uh, when you're not directing it. That is incredibly powerful. It leads to users, um, consuming 5X the tokens that you would, that you would consume just, you know, directing AI, uh, as you would a search engine. And so the ability to have the, you know, your agent or agents working on your personal life and solving problems as they come into your inbox or into your messaging solutions with your family and friends.

• 1:08:46Speaker 05

  And then on the business side, the same thing, solving problems for you, solving problems with your, uh, coworkers and teammates. Um, it's incredibly, uh, powerful, this technology.

• 1:09:01Barry Ritholtz?

  To say the very least. All right, let's jump to our favorite questions that we ask all of our guests, starting with, and I already asked, but I gotta ask a little more specifically, who were the mentors who shaped your career?

• 1:09:16Speaker 05

  Well, you certainly have to look at Julian Robertson and, you know, just his, the example that he set and how to run, you know, an investment business with integrity and, you know, and intellectual honesty and principles. And so that was incredible. Roger and John at Integral Capital Partners were just great. As I got out of business school and was in my early 30s, really, you know, those key years of learning, again, how to run a firm and make great investments. And they gave me the opportunity to both

• 1:09:57Speaker 05

  succeed and fail in some of those private investments that I made. Those are going to be the key people that really shaped my career.

• 1:10:08Barry Ritholtz?

  You mentioned the two Peter Lynch books, One Up on Wall Street and Beat the Street. I know you read a lot of other research. Any other books worth mentioning these days?

• 1:10:18Speaker 05

  You know, I pulled a book off the shelf recently, Empires of Light, which tells the story of the propagation of electricity and the battle between Edison, General Electric, Tesla, Westinghouse.

• 1:10:34Barry Ritholtz?

  AC and DC.

• 1:10:35Speaker 05

  Yes. And, you know, incredible story. And I think at the end of the day, it was really interesting. And Edison really pushed that AC was dangerous. And to the point where he promoted it as the, for the electric chair, because it made, it made AC look bad.

• 1:10:56Barry Ritholtz?

  Didn't one of them electrocute an elephant to show how dangerous it was?

• 1:11:01Speaker 05

  Many different animals.

• 1:11:02Barry Ritholtz?

  Yeah.

• 1:11:02Speaker 05

  Yeah. And, and a prisoner. And it didn't go so well, actually. The first electric chair didn't work extremely well. So to scare people and say AC is bad. And you look at what's happening today with AI and people taking this incredibly powerful technology that is going to change the world and is already starting to change it and, and making it this evil empire. It's pretty fascinating. And I think the other side of that is that, you know, in the end of the day, Westinghouse won out with, you know, steady execution and industrialization of the backend. And you look at the Mag7 and what's, you know,

• 1:11:46Speaker 05

  the opportunity for Amazon and Microsoft and Google to build that backend. And AWS, this, you know, AI is an incredible opportunity for AWS.

• 1:11:58Barry Ritholtz?

  Which is already the biggest profit center for Amazon.

• 1:12:02Speaker 05

  Yes. And so, you know, which is not the, if you say Amazon, everyone thinks about e-commerce and they don't first think about AWS. But it's, AWS is the more important part of the company.

• 1:12:13Barry Ritholtz?

  Yeah, to say, to say the least. What are you streaming these days? I know you're on a plane pretty regularly. What are you listening to or watching to keep yourself entertained?

• 1:12:22Speaker 05

  Well, entertain, sure, X is entertaining. You know, all the, all the debate around our industry is pretty fascinating. Friends and Neighbors is a guilty pleasure. So, you know, that's something I'm, I'm streaming regularly.

• 1:12:39Barry Ritholtz?

  Anything Jon Hamm is, is always worth watching. Final two questions. What sort of advice would you give to a recent college grad interested in a career in either investing or technology?

• 1:12:52Speaker 05

  The number one thing that I tell younger folks is you have all the tools today to make an impact. And so if you want to get in the investment business, one, of course, start investing. But two, do your research, go online and then publish your research. Put it on X. Interact with people like you, people like me. And if you have, if you can uncover the story behind a stock and make some great recommendations, you're, you're trying out for the world in real time. And, and if you have the courage to do that and

• 1:13:35Speaker 05

  you do it well, it's a no brainer to hire that person.

• 1:13:38Barry Ritholtz?

  Our final question. What do you know about the world of investing and technology today? Might have been useful back in 1993 when you were first getting started.

• 1:13:49Speaker 05

  Yeah, I think early on and for investors coming to our market, there's this perception that things happen very fast. And no doubt, they're, they're changing rapidly. But at the same time, there's this, there's this reality that things do take time. And, you know, we talked about the emergence of the smartphone. The first smartphone-like device that came out was the Newton. And it didn't really work that well. And then General Magic had a solution that also didn't really work that well. And then Palm created the first thing that actually got some adoption, but it didn't do any email or messaging. And it

• 1:14:33Speaker 05

  certainly wasn't a phone. And then Palm created the Trio, right? And then the, the, I'd say in some ways, RIM was the real first, you know, RIM BlackBerry was the first real working smartphone. But it was somewhat clunky. And some people love that clunkiness, right? You know, and love that keyboard. But then, you know, ultimately got to, to Apple. And so while, while things happen fast, there, there, it also takes years for things to really develop. And so I think if we apply that today, AI can do some incredible things,

• 1:15:12Speaker 05

  but it's going to do way more in a few years. And there are, there are some obstacles other than the ones we mentioned to adoption, right? Data security and comfort of your coworkers and your, your superiors in terms of giving access to data to an AI agent. So it will take time in, in order to see, you know, ultimately what it can deliver. And so I think we're, we're just scratching the surface, even though, as I mentioned, there's a lot of battles between open source, for instance, and, and the closed frontier models

• 1:15:56Speaker 05

  and, and, but there's way more to go here.

• 1:15:59Barry Ritholtz?

  Glenn, thank you for being so generous with your time. This has been absolutely fascinating. We have been speaking with Glenn Kacher. He is the founder and chief investment officer of Light Street Capital. If you enjoy this conversation, check out any of the 651 previous discussions we've done over the past 12 years. You can find those at Bloomberg, iTunes, Spotify, YouTube, or wherever you get your favorite podcasts. I would be remiss if I didn't thank the crack team that helps put these conversations together each week. Elizabeth Cedrin is my video producer. Anna Luke is my podcast producer. Sean Russo is my researcher. I'm Barry Ritholtz. You've been listening to Masters in Business on Bloomberg Radio.