Animal Spirits Podcast - Talk Your Book: AI Is Not a Bubble

Starting point is 00:00:00 Today's Animal Spirits Talk Your Book is brought to you by Elger. Go toeliger.com. Go to Elger.com. C.N.E.Q. That's eljure.com. Welcome to Animal Spirits, a show about markets, life, and investing. Join Michael Batnik and Ben 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 Ridholt's wealth management. This podcast is for informational purposes only and should not be relied upon for any investment decisions. Clients of Ritholds wealth management may maintain positions in the securities discussed in this podcast. Welcome to Annal Sprets with Michael and Ben. On today's show, we spoke to Dr. Ankur Crawford, portfolio manager at Alger. We had Encore on The Competent

Starting point is 00:00:48 Friends back in April and were blown away by the breadth and depth of her knowledge and her ability to talk about her space. She worked at Intel. Not only was she a portfolio manager, she was an analyst, but she... She was in the field, right? She was in the field, right? She was in the field. It's so unique and important to talk to somebody that has actual boots on the ground experience because I think a lot of the discussion that's being framed around the AI trade, the growth trade, the semi-trade, whatever, is framed through the lens of price. And I mean stock price.

Starting point is 00:01:22 What does a stock price do? And then you make judgments, narratives based on whatever your opinion is. But to talk to somebody who understands the supply chain, the bottlenecks. at such a granular level really opens your eyes as to why the prices are doing what they're doing. It's not just prices respond to the explosive earnings, which is obviously the case, but the backlog for as far as the eye can see. It's unique. It really is, it's, you know, I've never seen anything like this. I mean, stating the very obvious. We've talked in animal spirits a lot about the downside case of AI. What could go wrong? I think her case is,

Starting point is 00:02:02 No, no, no, no. People are looking at this using the past as their guide. This is different. And here's what could go right with AI. And so, I mean, she has a very bullish take, bullish outlook on everything. Right? So I think this is, I think it's important to hear all sides of this debate.

Starting point is 00:02:21 And I think it is worth, we've been saying, have an open mind that like maybe this is one of those times that's different. And so she kind of lays the case out for it. And I like, I love the discussion about the market making. making you feel right or wrong about these ideas and waiting for the market to catch up with you? Anyway, very interesting conversation. So here is our conversation with Dr. Anker-Crawford from the Alger Concentrated Equity ETF. Dr. Ankur-Croffert, welcome to the show.

Starting point is 00:02:53 Thanks for having me back, I suppose. Back-ish. Okay, so we did have you on the Compendent Friends back in April. And part of the conversation that I found so interesting was you thought you were wrong about the memory trade because the market wasn't confirming your suspicions. And these were more than suspicions. You thought it was so obvious that these were going to work. And they weren't. So you thought, hey, I must be wrong.

Starting point is 00:03:23 The market, like, right? Like, you've been doing this a long time. You're humble enough to know that if you're mentally pounding on the table, but the market's disagreeing with you. It's usually the market that's right and not you. Okay. this was the outlier in which you were so right. And April is, it was two months ago. It's two months ago. That's it. Micron was at $454 a share, give or take when we recorded. It's now at $1,0.50 to $1,080. It's up 135% since that conversation. So now what signals are we taking from the market? Gosh, you know, what I would say, I think it was in the context of, Initially, like, I had thought that I was wrong in September when I had first Micron, that I thought that microin was telling me, or that the market was telling me that I was wrong on the thought process. Look, there's been a lot of movement in the market since April.

Starting point is 00:04:19 And I would say back at the end of March, there were, you know, Nebius, I think was at 95. And Estera Labs was at 95. And now Estera's close to 400. And what has happened is that people have, I think the market is coming to the realization that some of what is happening in the AI trade has duration. We have seen, for example, for the neocloud's pricing for the neocloud per GPU hour is rising because we are short compute. And you've seen anthropics numbers shoot through the roof. I think they started at $30 billion. Now we're looking at $44 or $49 billion in AR.

Starting point is 00:05:01 When growth investors are telling you that they've never seen anything like this, I think everyone needs to take heed because this is a different era. And we can stop calling it a bubble. We can stop calling it, you know, one time. And everyone just needs to pay attention to what's going on. It does seem like the bubble talk is getting a little exhausting. It's funny. I looked.

Starting point is 00:05:25 I wrote a blog post in 2017 and people were talking about bubbles back then. It's been a long time coming. Do you think that people are just so reliant on history that like listen, every time there's been a big Kep-X boom and we've built out a big innovation like this, there's been a bubble? Is it just that people have too small of a sample size?

Starting point is 00:05:43 What do you think that people get wrong about that idea? Because anyone who uses history as a guide says, listen, this checks all the boxes. So what is it about, I guess, this that is completely different? I think it's exactly that using history as a guide. Because we have never seen, there's no historical precedent for what is happening today in terms of how fast the innovation is occurring. I mean, was it just last week that we were talking about, like the Nile and Brown tweet,

Starting point is 00:06:15 about how models will begin training themselves? And we've heard this before. And, you know, I had, I said this a couple of years ago on CNBC, I think, where I said, you know, when software begins to write software, innovation becomes exponential. And we are at an exponential innovation curve. You know, we're not used to thinking exponentially. And when innovation, it's also, this is digital innovation, right? So it's very easy to adapt and adopt it. So think about, I mean, if the innovation came in the iPhone, right, then we, we, needed to have dispersed all the hardware and we needed to make sure everyone had an iPhone.

Starting point is 00:06:59 And that penetration curve is a little bit different than a digital penetration curve, where everyone can adopt it immediately. I think that's what's happening right now where the digital penetration curve, there is no barrier to entry to adopt it and to start using it. The usefulness of the productivity of the AI tools has become incredibly clear. and therefore there is no compute because everyone wants to get their hands on intelligence. So, Ancour, you're the manager of the Alger Concentrated Equity ETF. The ticker is C&EQ.

Starting point is 00:07:38 But you've managed this portfolio in, what, a mutual fund or SMA wrapper for quite a while? It's actually an ETF, an mutual fund and an SMA wrapper. Okay. And when it's up to about two years ago as an offshore. of some of the other funds. Okay. When you just said that it reminded me of like when people promote their podcast, wherever you listen to, right, Apple, Spotify, YouTube, you can get it in any flavor that you

Starting point is 00:08:04 like, but if you want encore stocks, you can get them. You're a long-term investor. You are not, right? Like these are concentrated bets that you're making on these companies. How hard is it to ride these winners? Because you're right. We are linear thinkers. I wrote this a while ago, many a moon ago.

Starting point is 00:08:27 Anybody could do six plus six plus six plus six, plus six. But if you ask them to multiply six times six times six, I mean, your brain will melt. We just, we can't think that way. So as we're transitioning from linear to exponential growth, all right, my crown is up 136 percent, whatever. It went from 400 to 1,000. Couldn't go to 4,000. I'm being silly. But like, how do you think about the long-term prospects of a stock?

Starting point is 00:08:50 We know that it's discounting something a lot. But like the people have said, well, this is funny. Micron or micron is the largest stock in the Boston 1000 value index. Like what? Because the market is probably rightfully putting a discounted multiple on it eight times because we know we've been through these cycles before. But the question is, is this cycle of memory different? What do you say?

Starting point is 00:09:15 How do you think about this? Let's talk about this in terms of not just the memory. cycle because I think that there is something much bigger going on than just the memory. And memory is just kind of an example of what's happening. If you look across the supply chain for semiconductors, semis were kind of a forgotten child. I remember I was a semi-conductor analyst for Alger when I first started my career. And it was kind of like we were the ugly stepchildren to software because software had these like beautiful business models. Like, you know, semis were cyclical. They didn't get any pricing power. They would like beat each other up.

Starting point is 00:09:50 every year on getting sockets. And I remember at some point thinking, God, I used to, I used to work in a fab, right, in a bunny suit. Like, it's really hard to make these things. Why is it that Sundays get no respect? Wait, hold on, Ankur, can you just, just don't close over that for a second. So we're talking to somebody that prior to her career as an analyst and a portfolio manager, you literally worked inside of these buildings that you had to put a hazmat suit on. Yeah, well, it was a bunny suit. It wasn't a hazmat suit, but it was, I did. And I did my PhD work at, at Intel and, you know, had to build my own wafers there. And, and so it was just like I had this like, this appreciation for how hard it was to, to build this stuff. What happened? You know, semiconductors became kind of a GDP plus grower, plus plus grower to a GDP plus grower to basically almost a GDP grower. as a group. As that entire supply chain became a proxy for GDP, it all consolidated. So across the

Starting point is 00:10:57 supply chain, whether it's the PCB guys, whether it's the foundries, the memory guys, the semiconductors, they all, as semi-cap equipment, it all consolidated between 2010 and 2020-ish. So what happens when you basically get a consolidated market for the entire supply chain and a demand signal that feels exponential? It's really hard to bring on supply. And therefore, you have many different things that end up being fantastic, which is you get better margins, better pricing. All of a sudden, the power has shifted back to semiconductors and this entire supply chain for summies,

Starting point is 00:11:47 including the foundries, TSM, global foundries, you know, the semiconductors themselves, even like the networking equipment. Like so the entire supply chain is stretched right now. And this is just what's happening in memory, but it's happening across every other aspect of semiconductors and this AI build as well, including power. Now, power didn't consolidate, but, you know, that power is also short. We're basically short, I would say, soup to nuts, the entire. supply chain for artificial intelligence.

Starting point is 00:12:20 It is funny how the market sometimes tells you if you're right or wrong and that's kind of the ultimate scoreboard. I'm curious how many times that you've changed your mind since like the chat GPT moment back in 2022 about who the winners and losers are going to be. Because obviously there's been a ton of different narratives. Have you been pretty down the fairway on this and pretty resolute or have you changed your mind a lot on how this is going to play out? Look, I think that there's some big picture things that I haven't changed my mind on. There's a paper that we wrote in March, April of 23.

Starting point is 00:12:51 It was called AI and the declining cost to create. And that talked about how software and any digital assets are at risk and value should accrete to the hardware and semiconductor supply chain. That big picture was something that we held on to. However, the components of that are a little trickier, i.e., when should you have sold software?

Starting point is 00:13:15 We sold a lot of our software then, but there were kind of rip-roaring rallies like CRR-R-Wed from 160 to 300, right? There was a doubling because people thought it was an AI winner. There was definitively a points in time where we would question the hypothesis. However, we did stick to our guns on understanding that, you know, there are swaths of the market that you really don't want to be invested in. They could be trades, but not investments. Individually in names inside of sectors, I think what we have seen is there's been not necessarily, like TSM is something that we've owned for a very long time and have only gotten more convicted in, in part because you're, you've gone from a seven player market, you know, from 15 years ago to effectively a one and a half player market today.

Starting point is 00:14:09 maybe a two, I would say one and three quarters because Samsung and Intel right now are trying to find their sea legs. The compute shortage that everybody's talking about, is this the type of thing that Taiwan semi who actually manufactures these chips? Are they being the responsible stewards of the entire ecosystem? Or like, or can they literally also not manufacture as fast as supply, as fast as demand wants too. Let's study that supply chain as well. TSM is not the holder of all equipment, right? So they need to ask ASML to make them equipment. They need to ask Lamb Research and AMAT and KLA 10 Corps for that

Starting point is 00:14:53 equipment as well. So the equipment that goes into these buildings to actually... That's right. So if you go across the supply chain for even TSM, even if TSM says, you know what, I'm going to add 3X the capacity, which they never would do. that if they wanted to do that, the supply chain is going to limit that growth. Because even the Seneca equipment manufacturers cannot manufacture at that rate, because their supply chain cannot manufacture at that rate. And here is the beautiful thing, right? Everyone is afraid that this is a bubble.

Starting point is 00:15:29 Everyone is afraid that we're growing too fast. And what I'm telling you is that we are in fact rate limited by the supply chain, which is a really important aspect of what is happening. So we're almost capping the growth. So we can't get into bubble territory right now. We can't spend as much as much as we may want to, but that gives you duration. What if somebody would say, but I'm just playing devil's advocate, everybody knows that supply is constrained as far as the eye can see.

Starting point is 00:16:04 And therefore, we're going to bid up the prices of these stocks. anticipation of an endless runway. And of course, the impossible and possible part of this is, well, when do prices outstrip future expectations of what can realistically grow into? And how do you know that I know, again, I'm asking you a literally impossible question? So what would you even look to in anticipation of, okay, perhaps prices have outstripped what's reasonably, what these companies can deliver on the fundamentals? Now, what prices are you talking about? TSM prices? Oh, good question.

Starting point is 00:16:40 So I was thinking in my brain stock prices, but if there's like actual business prices, like wherever you want to take that? The most common question that I get asked is, oh my God,

Starting point is 00:16:52 the valuations are so high. How can you invest in AI when the valuations are so high? And my response to that is on what metric are the valuations too high? Because the first thing you need to get right

Starting point is 00:17:05 when you think about valuation, is the E. Only then can you come up with a P.E. So if the numbers keep moving up because we are in a supply chain shortage through the end of the decade, then what is the right earnings? Now, I will give you an example. There is a stock. It's called GEV. I remember looking at GEV and this was, I don't know, a year ago. There was a certain thesis around GEV. They make turbines for utilities and for CCTV, which are required for electricity, which is required for data centers. There's only three companies that make CCGT turbines. GEV is one of them.

Starting point is 00:17:53 They have about a third of the market. And their pricing has gone from like 1250 per megawatt to something like. like 2,500 inside of the last year. That's insane. Yes. And it's continuing. Like I was just looking at the numbers the other day. And this is happening across all of these AI stocks.

Starting point is 00:18:17 I mean, there are stocks that on 28 trade at a low double digit earnings multiple. Because our numbers might be quite differentiated from the street. But again, if you stop thinking linearly and thinking about the exponential, then you have to figure out what the right earnings is. Then we can talk about what the right P.E. is. But I would say this is happening across the supply chain, where the numbers are just low. Before you mentioned, like, hey, there's going to be some trades here, too, and some investments. When you creating your portfolio, which is concentrated, I think, what is it, 30 names or something,

Starting point is 00:18:52 are these all longer-term investments? Do you look to any trades in this space that you try to get too cute on? No, these are like, I don't know, you tell me the number, three, five, seven-year-hole. Like, what is your holding period when you're trying to buy these stocks? I mean, ideally, you're looking at things that you can hold for three years. So I always think about in three years, will this be a triple? Could this double in three years? Kind of that that's the mentality.

Starting point is 00:19:15 Occasionally, there might be a trade in there that it usually is on a pretty short leash. One of the things that you just said that I would totally agree with is that maybe I'm projecting, maybe I'm making this up, I don't think I am, that a lot of investors are asking. the questions as I did. I started the show with this. Like, is it too far too fast? Are the valuations too high? Blah, blah, blah. There's still, again, this is like anecdotal,

Starting point is 00:19:46 but there's still a lot more disbelief. I do think that investors continue to just be stunned by, and they're talking, they're looking at the stock. You are looking at the business. So you have a, to say that you have a better handle on what's actually happening is comical. But you also are talking to. investors and you're hearing disbelief and you're probably saying like these people have no idea. They have no idea what's happening.

Starting point is 00:20:11 Yeah. Honestly, Michael, I love the skepticism because if everyone was not a skeptic, then, you know, everyone would be on the same side as us. Right. Right. And so I love the skepticism and I love the debate because, again, it makes me question my own. Like it keeps me grounded as well and makes me question my own thesis over and over again to come back to what I'm telling you. There's nothing really that's deterring me from my viewpoint.

Starting point is 00:20:37 And look, you see it. Look, the most basic thing, I think at some point today you asked me, what do you look for? One of the things that we've been looking at is we on this company called Nebius. And Nebius is a, I don't even want to call it a NeoCloud because it's, it's progressed so much beyond that. I would say it's like the first AI hyperscaler, AI native Scalar that has been formed in this era. Their pricing for their old chips is up 30 to 40%. So that's their pricing for like hoppers. The hopper is the first generation of AI,

Starting point is 00:21:20 Nvidia AI chips. They were supposed to be going down 15, 20%. As soon as you got the next generation, as soon as Blackwells and Grace Blackwells came in, Hopper pricing were supposed to go down. Yet, pricing is up 30 to 40%. What that tells you is that there is simply not enough supply. For now.

Starting point is 00:21:42 For now. The thing that people keep coming back to is, well, let's see what ROI the buyers are going to see. And I think what they mean is the hyperscalars. So does that all rest on the shoulders of hyperscalis or are these orders is broadening out? I think what you have to do is look at the supply chain of AI. So we started the conversation talking about anthropic. Anthropics revenues are, or their ARR is approaching almost $50 billion.

Starting point is 00:22:15 Their rumor is that they're actually profitable in Q2. And if you take a look at, again, I'm just talking about the publicly available information. If the rumors that they are profitable in Q2, then this whole idea, of, oh my gosh, no one can ever make a profit is out the window because clearly the leader in the space is making a profit. I think if you take it just back to fundamentals, the hyperscale is are a bit more confusing in part because some of the CAPEX that they're spending is for their own internal means. And it's hard to deconvolve how much is being used internally versus how much is being used to lease or to rent out to other people.

Starting point is 00:22:59 I'm curious, what would cause you actual concern, though? For the people that keep just shouting from the rooftops, this is a bubble, this is a bubble, this is a bubble. They don't seem to quantify anything. They just kind of say, hey, evaluations are high and stock prices are up. What would be actually a cause for concern for you to say, all right, we've overdone it here? Okay, if I could magically wave a wand and we could spend $3 trillion in CAPX and place it in the ground, I think that would cause me to worry.

Starting point is 00:23:22 if I saw, you know, some sort of an algorithmic change of such that we could do a lot more with less, that would cause me to question. Although, you know, I think one of the one of the other misnomer's in this market is that we all remember deep seek, right? Deep Seek Monday. And the fear was, oh my gosh, that, you know, this Chinese model is doing so much and they didn't spend any CAPX. And I think what, you know, the conclusion I have come to over, you know, the last, I guess, the year since that's happened is that the business model for an open sourced model is going to be quite different than the business model for a frontier model, where the value is going to reside in different places.

Starting point is 00:24:10 So for frontier model, the value resides actually with the model holder because they are actually adding value by providing, you know, incredible intelligence. So they should hold the value. On the open source side, I think the value actually accretes to the infrastructure layer. Because the open sourced models, I believe, are all going to converge upon one another and become highly competitive. So I do actually think that there's this interesting, like, you know, also misunderstanding in the market about open models and closed models.

Starting point is 00:24:47 and this idea that, you know, the open models are going to take all the profit from the closed models. But I am watching for any of these open model suppliers can cross the chasm with something super innovative. Because, look, I would say that right now you have to be willing to survey the market all the time and change your mind. Because the innovation curves are just so fast that you can't count. anyone out. All right. So, Ancor, we've spent, we've spent this entire, the entirety of this conversation talking about the mega trend where your bread is buttered on the, on the AI infrastructures, supply-constrained soup to nuts story. But this is, there's more going on here. This is not like a replacement for SMH in your portfolio. This is, this is broader than just the

Starting point is 00:25:41 AI stuff. So this is a large-cap growth strategy. How are advisors and clients thinking about it, asking you, where does it go? What's your response to that? Look, I think that we are at a very interesting time in our own histories, such that the overall economy is going to move from a consumer-led economy into an industrial-led economy. And you're starting to see it already, where the economic growth is going to be dictated by reshoring and capital. growth. And all of that has a long tail in the broader economy, which is why, like, if you look at the portfolio, there's companies like QXO in the portfolio, which are, which is a building products company or HICO, which is an airplane parts manufacturer. So it is, I mean, I would like

Starting point is 00:26:36 to remind everyone that this is actually very much a large cap growth strategy. However, we're leaning into the biggest change factor in our economy right now, which is artificial intelligence, which touches almost every aspect of the market. So, Encore, we're in the year 2031 and we're looking back to 2026 as this incredible moment of time. With hindsight being 2020, what do you think is the one area of the AI ecosystem that investors will have wished they paid more attention to? I think power in the industrial ecosystem because the same thing that's happening, you know, across the AI supply chain is happening in power.

Starting point is 00:27:23 And that's capacity that's even harder to bring on. So if you look at the IPPs, which are the independent power producers, today they are trading at kind of low teens multiples. Which, you know, in the broader, I mean, again, you know, and that's low teens multiples. on like 27, 28 numbers. It's not like we're looking out to 2032 to justify the valuations. One thing that is very clear is that we don't have enough power for the eventual reshoring of a lot of industry and a lot of capacity back to the U.S. They are just long-term beneficiaries of this AI super cycle.

Starting point is 00:28:08 Encore, this was amazing. Thank you so much for taking the time. time to do this. For people that want to learn more about your concentrated equity strategy, takeris, CNEQ, where do they find more about the strategy? Just go on to our website, alger.com forward slash CNEQ. Perfect. Thank you so much. Thank you to Ankur. Remember, check out eljur.com. To learn more, email us Animal Spirits at the 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,

Starting point is 00:28:58 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 ARCA Incorporated. Not FDIC insured. Not bank guaranteed. May lose value.

Animal Spirits Podcast - Talk Your Book: AI Is Not a Bubble

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