Animal Spirits Podcast - Talk Your Book: AI Winners & Losers

Starting point is 00:00:00 Today's Animal Spirits Talk Your Book is brought to you by Alger. Go to elger.com to learn more about ATFV. That's the Alger 35 ETF. Concentrated portfolio, ATFV, Alger.com to learn more. Welcome to Animal Spirits, a show about markets, life, and investing. Join Michael Batnik and Ben Carlson as they talk about what they're reading, writing, and watching. All opinions expressed by Michael and Ben are solely their own opinion and do not reflect the opinion of Redhol's wealth management. This podcast is for informational purposes only and should not be relied upon for any investment decisions.

Starting point is 00:00:36 Clients of Britholt's wealth management may maintain positions in the securities discussed in this podcast. Welcome to Animal Spirits with Michael and Ben. On today's show, we are joined by Dan Chung. Dan is the CEO and CIO and a portfolio manager at Alger. And what we talked about today was their concentrated portfolio, which in a concentrated market, having a concentrated portfolio has to be either really easy. easier really hard, right? Because you could do a closet index of a concentrated positions, but if you take away from one of the current concentrated positions, you're taking a huge bet.

Starting point is 00:01:11 Do you what I'm saying? I do. So back in my days of manager due diligence in the Endowment's and Foundation's days, I really liked when a portfolio manager was honest, because I feel like you don't always get honesty out of these people. Not that they're trying to be dishonest, but they're trying to put forth, they want you to trust them. They want you to assume that they know everything, correct? So I like it when a portfolio manager is willing to go, well, gee, I don't know or what if. And I liked how, as our conversation progressed, Dan talked about meta. He says, we own meta. But I don't know if they're going to be one of the losers from this whole thing.

Starting point is 00:01:46 And I like that sort of self-awareness of going, man, this is a proven company. But what if they're one of the heads in the chopping block here? I like that self-awareness and like, hey, it's possible. One of our holdings, could be a loser from AI. We don't know yet. Yeah, the market is clearly saying that meta is not going to be an AI winner. And it's very unclear whether the market is very right or very wrong. Nobody can see the future. So it's, it's, it was a, it was a, I agree. That was a highlight of the conversation. Because on the one hand, man, it's the greatest advertising platform in the world. It's really cheap. I mean, 14, 15 times earning, that's, that's a severe discount. Forget about

Starting point is 00:02:26 to itself to the market. So you'd feel like. like a donkey selling it here, but in the other hand, the market's not stupid. They know that. There's legitimate questions as to the sustainability and the growth rates that they're getting from the AI models and the spend is a whole other story. So, yeah, I enjoyed that part of it. Where, where, because another manager could be like, oh, this doesn't make sense. You're going to bet against Mark Zuckerberg. Look at his track record. Of course the market has it wrong. Who knows? Yes. I find it endlessly fascinating to think about the AI winners and losers. And watch, it's like the carnival game where you're shooting the water gun and the horses are going up and back and forth.

Starting point is 00:03:01 Good analogy. That's what it really feels like. And I think it's, as a portfolio manager, you have to at times rip your hair out of your head to be like, I can't believe the market isn't seeing this, that they should be a winner and they should be a loser or whatever it is. And I can't believe this company that we don't own anymore is doing so well. Why are, how is it not? So anyway, that part has to be entertaining and also stressful. Anyway, we had a really fun conversation with Dan about all the AI winners and losers, how they're thinking about the incumbents, the newer companies that are coming up, and more. So here's our talk with Dan Chunk from Alger.

Starting point is 00:03:36 Dan, welcome to the show. Thank you, Michael. Your resume looks almost as impressive as mine. You've been with the company for quite a while, but tell us who you are. Why are we talking to you? Okay, so I'm CEO and chief investment officer and a senior portfolio manager at Alger. I've been here since 1994 when I joined in the Alger analyst training program. In the 90s, I was known as the tech analyst and the head of tech here.

Starting point is 00:04:03 And before that, I had a career as a corporate lawyer. So you've been in this business for quite a while at one place for a long time, which speaks volumes to the company that you're at, obviously. Let's go right into the comparisons. What is different? And let's frame it this way. What is different about the technological environment and go wherever you want to go with this question versus the mid to late 90s when you were starting your career? Yeah, that's a great question because a lot of people are making comparisons, but I think the differences between the two periods are actually vital to understand.

Starting point is 00:04:40 The main comparison, of course, is simply that AI, just as in the 90s it was the Internet, is booming. and, of course, it's driven by a technological revolution. But the differences are very stark in my mind. The biggest one being actually that the current leaders in the AI investment boom are very different than the leaders in the 1990s Internet boom. And in particular, the companies today, whether it's Microsoft or Amazon or Google or meta or Oracle, or yes, Anthropic or Open AI, But in that first group, and I, of course, have to include Nvidia.

Starting point is 00:05:21 We are talking about companies with incredibly strong fundamentals, real revenues, massive profits, highly profitable companies that have been leaders, well, like Microsoft for more than 30 years, others like Amazon for 25 plus years, and Nvidia itself a leader for decades. The leaders have strong fundamentals. They are investing in what they see as the largest opportunity of their generation. which is AI. And that itself is strikingly different than the 1990s, where the leaders were often companies that were not profitable, minimal revenues. They were innovators, but they were

Starting point is 00:06:00 very small companies like Amazon when it went public that basically had a million dollars of revenue and was selling books online or Yahoo, which yes, went public with more revenues than that, but was a fledgling company not established or proven and not a leader in advertising. So it's a very different generation of leaders leading right now in AI. And I think it matters a lot, not only in the quality of what they're investing in and the confidence that investors should have that these companies, as a group, at least, are pretty mature, pretty responsible, essentially know what they're doing, versus the companies in the 1990s were highly improving, were amazing companies like Amazon,

Starting point is 00:06:44 but had to prove themselves and were doing absolutely every single. they could. And part of what they did is they threw out, you know, they threw out the, the cookbook from the 1980s and implemented their own playbooks. And yes, some of them work, but as we know, many of them failed. I think this generation leader is clearly, these are proven leaders here. As someone who enjoys following the markets, I think that this whole, watching this whole thing play out is very entertaining. I'm curious for you as a portfolio manager. Do you find trying to pick through the winners and losers of this whole AI revolution? Do you find it fun and exciting or is it really stressful for you? Like, how do you, how do you

Starting point is 00:07:16 view this type of environment? I feel like I'm incredibly fortunate as one of the few investors that I know of who was both an internet tech investor in the 90s. Again, I headed Alger's tech investing by the end of the 90s, who's still investing today and gets to see this in, you know, the AI phenomenon that we have. In addition, of course, I've got some really, really talented, very experienced portfolio managers and analysts. And so I'm very excited about the opportunity. I think it is a bigger, stronger, and actually better opportunity than the internet itself was. And it's really an exciting time to be a fundamental bottoms up investor. All right. I know you just said bottoms up. I want to get to the bottoms, but let's stay on top for a

Starting point is 00:08:05 second. I agree with you, incontrovertible, what you said earlier about the differences in these companies. Very different. But just because there are as many differences, maybe more so than similarities, I don't think that's a green light that this thing can go on forever and that there's not any risks lurking on the horizon. Surely there's no shortage of potential dangers out there. If there were one thing that you see today that has you a little bit nervous that, yes, this is transformative, yes, these companies are insanely profitable. They are pet, pedal to the metal, like all that stipulated. What is one or two? two things that you see today that does make you think, I don't like what I'm seeing here.

Starting point is 00:08:48 There's a couple things. So one of them, and it's very similar to the 90s in this regard, so let's look about fiber optics, right? Because in the 90s, that was the big thing. Laying down fiber optics, the big race. The race was ultimately justified, but there were many, many, many losers of individual companies that spent a ton of money, didn't have the management teams, didn't have the strategies, didn't have the technology, and ended up failing. With AI, first of all, I think the overall, quote, spending of this across AI, in some sense, is going to be justified, and we're already seeing it justified by the tremendous revenue growth, for example, the leading models like Open AI and Anthropic, which together are growing faster than anything we've ever seen.

Starting point is 00:09:35 So clearly that means the opportunity is big. But I think what is also equally clear is that the disrupting. that is going to occur, not just in internet companies, not just in tech companies, not just in software companies, but across many industries, I think the threat of disruption is, of course, also increasing. And there will be companies that are probably disrupted faster than we've ever seen before by basically AI competitors or competitors who adopt AI and use it more effectively than others. And so I think that's one of the biggest concerns I have. From a market perspective, what actually does concern me is sort of sometimes the lack of nuance that we're

Starting point is 00:10:17 seeing in the market or just fundamental understanding that it's natural to have 100 competitors chase the big market. And it's also natural that 30 to 40 of those will fail. A whole bunch in the middle will be okay. And you'll have maybe 10 winners at the top. Because what we're seeing in the market around the volatility is it's almost like, you know, right now there's a lot of consternation about the capital spending and in particular about open source models versus the leading models which are closed. And it's causing very kind of almost emotional knee-jerk reactions, which is making the market really volatile. And so that's, that is a dangerous sign in and of itself, right? As experienced market investors, we know, when you see fundamentals being somewhat

Starting point is 00:10:59 ignored and the market really reacting in a hypervolatile way, simply around sentiment or a news flash coming from one company. You do have to worry, like, is that a sign of, you know, excess frothiness in either direction? How do you think about risk management in a world like that? Because you're right. The whole Leopold situation at situational awareness was, hey, this guy laid out the next 10 years and he seems like he's on the right path, but expectations got pulled forward and too much risk. And even Sam Altman on a recent interview said, listen, this stuff is actually, like, the technology is there, but the adoption is slower than I would have expected because there's so much inertia. So I feel like the timing of this stuff, you can be right but be on the wrong

Starting point is 00:11:39 time horizon or right but by the wrong magnitude. So how do you even think about risk management in a situation like this where, hey, listen, fundamentally, I was right by the expectation. There's a mismatch between the expectations and the herd mentality and all these things. It's, it makes for a challenging environment, even though you could be right on the fact that this technology is going to be transformational. Absolutely. So the way we manage risk at Alger is first of all, to look at the fundamentals of the companies. We're fortunate that many of the companies that are doing really well right now are well-seasoned companies.

Starting point is 00:12:13 So not just InVidia, but most of the semiconductor companies have been around forever. Micron, Western Digital, the semiconductor equipment companies. Same thing with most of the software companies, whether they're going to be AI winners or losers, Oracle, ServiceNow, Salesforce.com. These are big established companies. So we're careful about looking at a scenario-based analysis. So what are their risks? What are their likely outcomes? And of course, maybe what are their bull case? You know, the optimistic upside for these companies. And the way we manage risk at

Starting point is 00:12:42 Alger is to consider essentially the risk reward in their stocks based on different scenarios. So you can take a bearish case of a company, think that it'll be moderate growth, but still also say it's going to be worth, you know, X and Y based on its free cash flow and revenues and a lower multiple. And you can also look at the same company and say, if it succeeds in AI, you know, increases its growth rate, margins improve, you know, it'll get a higher multiple. So we're very careful about position size in our portfolios around risk reward as we see it from the fundamentals and the price targets that they imply. The toughest part, as we alluded to in the earlier question, is with so much volatility in

Starting point is 00:13:22 the market, we're sometimes seeing these prices change really very rapidly and a little bit more rapidly than they should in the sense of the fundamentals aren't changing that quickly. and the software stocks are the best example of that. And many of them were 40, 50% down at their lows this year. Many of them now rallied 30% from those lows. Not that much of that is really based on the fundamentals. You mentioned these baskets of stocks, the AI winners, the software losers, whatever the theme of the day is.

Starting point is 00:13:51 And you see all these stocks move together. But that's short-term stuff. We know that over time, even though they move together on a day-to-day basis, if you zoom out a little bit, three months, six months, one year, three-year, the market does a good job of separating the winners from the losers. Not every day, not every week or month, but eventually the market sorts, all right, these are the companies that are doing well. These are the companies that are under pressure. And what you do at Alger, and we're talking about the Alger 35 ETF, the ticker for this is ATFV. This is not a closet index fund. You guys are really going for it.

Starting point is 00:14:27 So, for example, this data is a bit stale, but we're looking at data as of as of the end of the first, end of April, April 30th. And again, I know it's stale because we're in August, but just for the sake of conversation. Invidia, which is a large company, 7.8% of the S&P 500 at the time. You had a 14.3% waiting. So a 6.5% active share in Nvidia. Nebius, not even in the index, you guys had a 5% position in. Western Didge, a 0.2% weighting again as of the end of April 30th.

Starting point is 00:15:02 24 basis points in the S&P, you guys were at 4.8%. So the top 10 holdings as of that date were 64%. People are worried that the SEP 500 is concentrated. You guys are really leaning into it. So where does that conviction come from? Yeah, Alger 35 is a best idea across Alger portfolio. And the conviction really comes from a couple of things. One is, we've been doing this for 62 years.

Starting point is 00:15:29 I've been doing it for 30 plus. Even my portfolio managers, who are quite a bit younger than me, have been doing it for 25, you know, 20 years. We have a great team. We have a lot of experience in high growth, in dynamic change, in disruption in industries. I mean, these are actually the kinds of events where Alger really leans in and understands

Starting point is 00:15:51 that the opportunities are the greatest. So first of all, it is expert analysts and portfolio managers that have experienced in industries that go through revolutions like this one. Second, careful, detailed fundamental modeling of companies, every single one of them that you mentioned and all that we own. Detail financial models, P&Ls, cash flows, and also close contact with the management team, but also a lot of research around and outside of the company itself, of course, to understand its competitive positioning, the quality of its management, the quality of its products. And ultimately, of course, the value of its stock relative to competitors. And so it's hard work. There's a lot of good companies out there. At Alger 35, we're focusing in on what we think are the best companies with the biggest

Starting point is 00:16:33 moats, the best opportunities now, but also the best opportunities longer term. And you've mentioned some of the companies that we've identified as winning now and winning probably long term. Nebius is one we're really proud of. I mean, this company when we first invested in it was a small cap. It's now a $50 billion plus market cap. What we identified there was excellent AI data centers, even before AI data centers was sort of a fad. I mean, now it's everybody seems to be, well, actually, every state seems to be stopping AI data centers, even as everybody wants to build an AI data center.

Starting point is 00:17:05 But NABUS we identified a couple years ago, not just because of the data center capabilities, but because of their software capabilities that make them a platform for developing AI upon. And, of course, in the last years or so, it's really come true as they've won a tremendous amount of contracts for developing. on their platform. Can you explain how a company like that, it seems like in the last, I don't know, 12 to 15 months, just went absolutely vertical. How does, it almost seems like there are these companies that are being discovered late to the game.

Starting point is 00:17:35 It's not like, you know, AI's the chat GPT moment was in 2022. What is it that it seems like there's a, the catch-up period happened so quickly with some of these stocks now? Like how are they missed essentially? So with AI right now, we have like sort of a long-term investing.

Starting point is 00:17:53 It's not a plan because it's not as detailed as a plan, but it's certainly an overarching strategy of understanding the sequence in which things will happen in a buildout like this. And we understood two and a half, three years ago, that, yes, semiconductors, InVIDIA was going to lead, but the AI data center was going to be a center of focus. And so we invested in not only semiconductors that were leading it, but also the providers of data center technology,

Starting point is 00:18:18 and also, for example, even things like liquid cooling into data centers, so companies like VIRTIV, and frankly, even outside of tech, in energy stocks that we knew would be supplying electricity, companies like TALAN and GEVRnova. The identification of a company like NABUS is really something you have to be a fundamental investor. Because the first question is we had the plan. We say, okay, data centers are going to grow.

Starting point is 00:18:42 We confirmed with cloud providers that the need for data centers and that AI data centers are not like other data centers. They're going to be architected differently. Then we just did the very basic research of saying, okay, who are all the data center providers in the world? The big or small, we didn't care. We went across the whole landscape globally. Then we said, okay, which ones seem best prepared for AI data center computing?

Starting point is 00:19:03 They have the resources that have some experience. And actually, when we first saw Nibius, we were very small company, but we were like, wow, these guys are way ahead of the curve. Now, part of the reason they were undiscovered is that the company's stock trades in the Netherlands and the company is based there. And actually, they came out of a former Russian internet company called Yandex. And so they weren't on the, if you will, the U.S. radar screen. And I would say, you know, buried there in Europe was this small cap company with a lot of

Starting point is 00:19:31 AI experience and a lot of internet experience. And so we, you know, we narrowed it down to that in other lists. And then we met with the company, built our models, understood other value. There's other aspects to value in Nibius that actually we thought very interesting, which includes, they also have a very big position in a company called Click House, which is AI database for unstructured data. So videos, photos, unstructured data. And they also have actually, oddly enough, an asset in an autonomous driving technology

Starting point is 00:20:04 that was once in Russia and then got shut down in Russia after the Ukraine-Russia war. Was that Yandex? Yeah, it was a Yandex. They were all Yandex properties. So the funny thing is, As this little company became more complicated, and this is the value, I think, of fundamental analyst-driven research, we got more interested as investors. We're saying, wow, this little company has a lot of really interesting assets. And I say that as fundamental investors, because

Starting point is 00:20:30 if you are a purely quant investor, there would have been nothing to see here. I mean, low revenues, no profits. You wouldn't have probably seen that it had assets coming out of Andex that were quite interesting. You know, these, they were just, you know, shareholding positions. You know, we got more and more interested when we met with the management and their history and an incredible culture, by the way. I mean, maybe I'm going on too long about it, but we really do admire the management and the CEO here in particular.

Starting point is 00:20:57 Arcady is amazing. But these guys had to leave Russia in the middle of the night for fear of basically being seized. And they did that. The people fled, went all over the world. But they kept themselves together, a core of it, as a comfort. and they worked really hard for a long time to just stay together, be a company, build these products, and they happen to, of course, have the vision.

Starting point is 00:21:19 And that's hats off to Arcadia and his entire management team, his CTO also in particular, that they had the vision like AI data centers are going to require a different kind of platform than your typical data centers. And we want to be there. And they were, there they were. The neoclods are often cited in the circular financing bear case. when you hear this, I'm sure it drives you crazy. What is it that the bears are not understanding about these relationships and why it's not looking anything like the dot-com implosion? So I would say that in the case of some of the leading neoclodes like Coralweave and Nebius, this is not circular financing.

Starting point is 00:21:58 This is, I mean, these companies, first of all, they are building real assets. they're building the leading edge of AI data centers, right? They are building them and equipping them with, you know, Nvidia's leading edge server ships seem to be, you know, Vera Rubin is coming out now, is there already. So, I mean, that's an asset. It's a real asset that they're building. Call it an office building if you want.

Starting point is 00:22:26 The circular financing, which, again, I remember from 1999, what it looked like was VC, gives you a billion dollars and gives you a $2 billion market cap for a company that has no revenues, but you're an internet startup that has dot com and its name, right? You know, something.com. And you're, of course, trying to follow on the success of Amazon or an eBay or a Yahoo. And then what do you do? You don't have any assets. You spend of that billion, you spend $500 million on advertising, you know, on Yahoo and other services to try to do what? Get lots of subscribers and subscriptions and, quote, growth, right?

Starting point is 00:23:09 Because you sell yourself as a company going public with not much revenue, but look at all the subscribers I've signed up, right? Look at all the users, the metrics that I have from my website. But you've pumped it up by advertising. My point is the advertising, of course, is not building an asset. You spend it and it's gone. You know, I remember in 1998 and 1999, you know, unheard of internet companies buying Super Bowl hats.

Starting point is 00:23:33 That's circular advertising or circular financing that's going nowhere. So is that the top? If we see Nebius during the Super Bowl on Valentine's Day this year, by the way, will you sell your entire steak? There's the difference. I think Nevis, and here's the thing, there are going to be, I think some of these Bitcoin miners that are now pivoting to be, I'm going to be an AI data center,

Starting point is 00:23:56 some of them are going to be losers. They're too late. The anti-data center thing is going to get in their way. They were not first in line to sign up for Nvidia chips or memory. You know, they're going to have a lot of logistical problems, I think. And as you know, in any market, you know, if the value of the market is X, it doesn't get split up by market share. You know, if you have 1%, you get 1%. You have 10%.

Starting point is 00:24:22 You get 10%. No, the winner is the one who gets the biggest market share, tends to get a multiple of its market share and value, right? they get sort of outsized value. In pharmaceuticals, it's well known that, like, very typically, if you have three drugs, you know, the number one drug gets 50% of the market, the number two drug gets like 25 or 30, and then everybody else gets, you know, is fighting for the scraps. And so, you know, that number one or number two position is much more valuable. It's interesting to see how much the change has been in the last two to three years of who

Starting point is 00:24:53 those winners and losers are. And it seems like, oh, Google's out in first Google's dead, then Google's out in front. and then Microsoft's out in front, and they're lagging. Just to see these incumbents kind of have this horse race where, you know, people are declaring them dead and then know they're the leader. And how much of this can be where, because it seems like most of these companies have kind of just gone all in together. It's like they've held hands and jumped off the bridge and decided we're going to, listen,

Starting point is 00:25:18 we're going to plow through our free cash flow all together. Everyone's going to do it. If one of us is going to do it, we're all going to do it. How much room is there with this opportunity for all of these companies in the say like the Mag 7, I guess, or that, you know, the top 10 to come out, if not the clear winners, at least they're all going to survive and be okay? Or do you think that there's going to be real losers from that big group of names? So first of all, I love how you recap to Google because that's exactly right. And it's a good example of our risk reward, our scenario, because when we

Starting point is 00:25:47 saw, we've been in Google since 2006 and its IPO, know the company well, understand why people think it was at risk from AI, i.e. simplistically, oh, well, I'm going to go to chat GPT and I'll never do a search again. But this is so wrong because it completely understands who is the we. The we is billions of individual people who probably don't really care about chat GPT per se. What they do care about is that they've been using and loving Gmail and Google search for a long time. They love YouTube and they're customers. They associate themselves with this company. So Google didn't have to be you know, the first to invent anything. And we always thought that as the stock went down and down and down on the negative sentiment

Starting point is 00:26:31 that people had got it wrong, and Google's proving it right now, which is the easiest way for introduce an ordinary person to AI is you have the leading search product and then you power it with AI and you give them even better and better search results. So that's exactly what's happened with Google. More importantly, people miss that Google's investments in fundamental technologies So their own semiconductor technology, as well as in the cloud, and how to run a hyperscale or cloud environment, is totally paying off. Google Cloud is growing 100% last quarter. These are very big businesses growing super fast.

Starting point is 00:27:12 It's a confirmation that the technological excellence at Google is very, very high. And, you know, all hazard, I do think there's more question about meta. I have to say my concern about meta is a little odd in that we identified it early as, frankly, a winner from AI short term in the sense that they've been using AI to power their digital ads targeting for a while. Reels isn't on fire. The question is, how much longer can that go on? And, you know, they have only one business. Unlike Google, they've only got basically an advertising business. Right, everything else they've tried hasn't really worked very about, right?

Starting point is 00:27:52 Exactly. It's a good business. It's a great business. And we're just a little nervous about if you look five years out, will they have completely saturated us with, you know, ads and AI? They can't get worse, can it, Dan? I think as the user experience, it is getting worse. I mean, okay, so I was on recently and I hate to say it.

Starting point is 00:28:13 I look to Facebook. I know, it's an old guy thing. I do look at Instagram too. I look to Facebook. And I realized, you know what? Everything that I'm looking at in scrolling through, about 85% of it is not from my friends anymore. They're ads. Now, I did marvel that some of them are really good ads because it's like, yep, I like skiing.

Starting point is 00:28:30 It knows us very well. You know, yeah. So show me some skiing ads right now. And yes, I made the mistake, I guess, somewhere of looking for a mountain bike. And so show me some mountain bike ads. But I do think that meta has a little bit more of an existential risk than, say Google does, for example, in that, other than the advertising business, they've not been successful in any subscription-based businesses, really. And I think they're actually behind an AI,

Starting point is 00:29:01 although I know the recent Lama catch-up was impressive. But, I mean, that's where I'm a little bit worried about the spending there relative to what I see as future businesses. Google, I should note, in addition to YouTube, search, of course, and the cloud, they also have Waymo. And autonomous driving at Waymo is incredible. I mean, it's here. They need to reduce the cost of it. But I can definitely see autonomous driving as becoming a, you know, the next obvious thing for all of us within five years. I have a question on how you think about, last question, how you guys think about price relative to value?

Starting point is 00:29:41 And let's stick with meta as an example. So meta is trading at, I don't know, 15 times forward earnings, whatever. it is. And the market is obviously agreeing with your skepticism. And maybe it gets down to 12 times and it turns out to be the bargain of the century. Or maybe, maybe you at Alger and your team are thinking not about the next 12 months, but about the next five years, as you mentioned. And you might say to yourself, hey, listen, we're value investors to a certain extent. But I don't really care about what 2027 earnings are looking like because we think by 2030 they might be 4% higher, in which case, who gives a crap about what the PE looks like today.

Starting point is 00:30:20 Like, how do you sift through something like that? Yeah, so meta is a company that I have to admit it has kind of a bigger, you're betting a lot on Mark Zuckerberg here, right? You're betting that his leadership is willingness to just basically throw a ton of money at AI is going to pay off for meta the way it does for others. But as I've kind of tried to say, I think it's a little harder to see. social media being even more AI-powered and generating the kind of future opportunities

Starting point is 00:30:53 than, say, the way Google's doing it, which is providing both cloud services and AI-enhanced search. People don't go to Facebook to do, like, you know, research. God, I hope not. Yeah. Unfortunately, I think people do actually, Dan. Yeah, I will say meta, like, you know,

Starting point is 00:31:09 we do struggle a little bit with the controversy around it. It literally on social media has basically everybody, just, you know, between all of its properties, essentially has everybody. Yeah, they have what, four billion? I mean, literally, I think three or four billion users. It's crazy, yeah, between Instagram, Facebook. So wait, here's a question for you, last one from me. So how do you and your team decide, okay, we're going to hold this or no, it's time

Starting point is 00:31:30 to punt it and we're going to sell? Like, how do you guys come to that decision? Is it a team approach or does the buck stop with you? Like, how does it work? Our typical philosophy is, of course, if it's disappointing and fundamentals, I can't say that's true for meta. They've not been disappointing. If it reaches our valuation at the high end and we can't justify higher, that's definitely not true for meta.

Starting point is 00:31:50 It's cheap. So it's the third one is if we think we find a better name with a better risk reward profile, better fundamentals, you know, that would be when we end up replacing it. And we're always challenging ourselves to like, is there a better or more creative name to own? But here's the one thing. In the ad market, we have a. at times owned, for example, trade desk. And we still own Apploven, which we like. But in a concentrated portfolio like Alger 35, how many advertising-based names do we want to own? The answer is not that many.

Starting point is 00:32:28 I mean, you know, one or two maybe. And so right now, the advertising market is undergoing a tremendous change. As trade desk going to zero, this one's going to go private. I don't know anything, other than the share price was a buck 40, and now it's 13. Holy mackerel. It has proven in ad tech extremely hard to do two things. Turn around once your tech is behind and off the edge. And two, beat meta. So one of the reasons that we still own meta is really simply,

Starting point is 00:32:59 you are talking about the global leader in social media, and you're talking about a leader in advertising. We will tolerate some volatility and uncertainty around market. Zuckerberg and the strategy and does it work because, I mean, that team there is executed. No doubt. All right, Dan, this is a fun conversation. For people that want to learn more about Alger 35, the best ideas and the rest of the company, where do we send them? Send them to WWAlger.orgra.com. There you have it. Alger.com. Thanks, Dan. Okay, thank you to Dan. Remember, check out Alger.com to learn more about their Alger 35

Starting point is 00:33:32 ETF and all the other strategies that they run. Email us, Animal Spirits, at a compound news.com. Before investing, carefully consider the fund's investment objective, risks, charges, and expenses. For a prospectus and summary prospectus containing this and other information, or for the fund's most recent month-end performance data, visit www.alg-a-l-g-r.com, call 800-223-3810, or consult your financial advisor. Read the prospectus and summary prospectus carefully before investing. Distributor, Fred Alger and company LLC, listed on NYSC, RCA Incorporated, not FDIC insured, not bank guaranteed, may lose value.

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