Speaker 1: Welcome to Inside Active, a podcast about active managers that
Speaker 1: goes beyond sound bites and headlines and looks deeper into
Speaker 1: their processes, challenges and philosophies and security selection. I'm David Cohne,
Speaker 1: i lead mutual fund and Active Research at Bloomberg Intelligence.
Speaker 1: For the past few years, markets have been driven by
Speaker 1: a narrow set of companies benefiting from powerful structural trends,
Speaker 1: most notably AI. But as those trends become more widely recognized,
Speaker 1: the challenge for investors is no longer just identifying them.
Speaker 1: It's figuring out where the next layer of opportunity lies
Speaker 1: in what's already priced in. Today, I wanted to explore
Speaker 1: how an active manager navigates that, how you separate durable
Speaker 1: growth from how you build conviction and a concentrated portfolio,
Speaker 1: and where the market may still be underestimating change. One
Speaker 1: to me discuss this is doctor Acre Crawford, executive vice
Speaker 1: president and portfolio manager for Alger, including the Alger focused
Speaker 1: equity fund ticker alg r X and the Alger Concentrated
Speaker 1: Equity ETF ticker cn eq Encore. Thank you for joining
Speaker 1: me today.
Speaker 2: Thanks for having me.
Speaker 1: David so Alga is known for its positive dynamic change philosophy.
Speaker 1: How do you define that in practice? And you know,
Speaker 1: what does it look like in a portfolio today?
Speaker 2: Yeah, I think in order to understand what that positive
Speaker 2: dynamic change means, I you know, it's important to understand
Speaker 2: the pillars of how we get there. There's two fundamental
Speaker 2: kind of philosophies that feed into positive dynamic change. The
Speaker 2: first thing, looking for companies that are simply growing right
Speaker 2: their market disruptors. Their top line is growing at a
Speaker 2: at a rate that is impressive and significant. Generally, there's
Speaker 2: a product that is very compelling and they're market share gainers.
Speaker 2: So that's like a typical growth a company that we
Speaker 2: would we would classify as change because they are changing
Speaker 2: the market around them and challenging the current state of affairs.
Speaker 2: On the other side of the ledger, we have what
Speaker 2: we call life cycle change. And life cycle change is
Speaker 2: interesting because a lot of growth managers don't think of
Speaker 2: this as growth. It is companies that may have gone
Speaker 2: through their their their growth kind of period and have
Speaker 2: now saturated their markets and they have to decide who
Speaker 2: they are. So are they going to continue growth or
Speaker 2: are they going to you know, just milk what they
Speaker 2: have and go into kind of a harvesting phase where
Speaker 2: they have low growth. And what we're looking for is
Speaker 2: companies that are either going to take advantage of a
Speaker 2: changing market or they're going to restructure their business such
Speaker 2: that they become growth businesses again. And the benefit that
Speaker 2: you get on this side of the ledger of life
Speaker 2: cycle change is oftentimes these companies look like they're almost
Speaker 2: value companies, but we think they're just unrecognized growth and
Speaker 2: you know, you get the benefit of not only the
Speaker 2: multiple expanding, but the earnings start starting to surprise to
Speaker 2: the upside. So both of these are change factors. Whether
Speaker 2: that change is coming because the market is changing, the
Speaker 2: environment is changing, the company is changing, or the CEO
Speaker 2: is changing, right, And those change factors are often underestimated
Speaker 2: by the market, and that's that's really where their opportunity
Speaker 2: for us lies.
Speaker 1: So, I mean, when you're evaluating a company, what do
Speaker 1: you think actually separates you know, durable, compoundent growth from
Speaker 1: companies that may just be riding a hype cycle.
Speaker 2: You know, when we look at businesses, we actually look
Speaker 2: at them on a three to five year perview, and
Speaker 2: the reason we do that is because we don't want
Speaker 2: a company that has a hype cycle behind it that's
Speaker 2: a one year hype cycle. So by looking at companies
Speaker 2: over a longer period of time and understanding what they
Speaker 2: blossom into, it forces you to ask the question, is
Speaker 2: this hype or is this durable growth? So I think
Speaker 2: it's just a natural part of our process, Like we
Speaker 2: would never pay for a company that has a one
Speaker 2: year cycle, and we would never pay a high multiple.
Speaker 2: I remember when I started this business, people would be like, well,
Speaker 2: what are they growing next year? Let's put you know,
Speaker 2: whatever that growth rate is, let's put a thirty multiple
Speaker 2: on that. Like, if it's a thirty percent growth, let's
Speaker 2: put a thirty percent thirty multiple on that. It's kind
Speaker 2: of like a one peg and it would always be
Speaker 2: funnel me because I was like, well, what if the
Speaker 2: growth ghost is the next year? You know, at what
Speaker 2: point do you what point do you make that in?
Speaker 2: And that's that hype cycle. So if you think in
Speaker 2: in phrases over a three to five year period, I
Speaker 2: think it's much more powerful because you kind of separate
Speaker 2: the winners from from just the hype.
Speaker 1: So I guess if we go a little bit deeper,
Speaker 1: can you kind of walk us through your research process,
Speaker 1: you know, like from you know the start to you know,
Speaker 1: actually having high conviction. You know, what are these signals
Speaker 1: that really kind of move the company from you know, hey,
Speaker 1: this might be interesting to you, just could really be
Speaker 1: a high conviction pick for us.
Speaker 2: Yeah, I think it. You know that the process, whereas
Speaker 2: it's hard to say where exactly it starts, sometimes it
Speaker 2: is a kind of a top down point of view,
Speaker 2: in which case, like if you think about AI right,
Speaker 2: that that thinking really came from a more top down
Speaker 2: point of view. And we then identified the company needs
Speaker 2: that we're net beneficiaries, and then our team worked on
Speaker 2: understanding the nuances of each of those companies and identified
Speaker 2: where the bottlenecks or where the beneficiaries would lie. On
Speaker 2: the other hand, we identified who would get impacted negatively
Speaker 2: and position portfolios that way. But the but the research
Speaker 2: process is actually quite deep in that you know, not
Speaker 2: only do we understand and dig into the quality of
Speaker 2: the management team, but you know, the durability of the businesses,
Speaker 2: the competitive dynamic, the you know, the the kind of
Speaker 2: margin progression and the revenue progression ends up being incredibly
Speaker 2: important as we think about the durability, you know, the
Speaker 2: team like we What I would say about Alger is
Speaker 2: that we have a team that is probably outsized for
Speaker 2: the assets that we have, and in part because our
Speaker 2: research effort is so deep that you know, I think
Speaker 2: we're we're one of the biggest users of a guidepoint
Speaker 2: on on the street, and in part because we want
Speaker 2: to understandstand the fundamental dynamics that is driving the revenue growth,
Speaker 2: like what are the structural advantages that businesses have to
Speaker 2: outcompete others? You know, are they becoming a oligopoly? Are
Speaker 2: they do they have pricing power? Will the market allow
Speaker 2: them to have pricing power? Right? So, these are all
Speaker 2: the questions like what is the technology? You know, what
Speaker 2: is truly understanding the base level of that technology and
Speaker 2: what the base level of the product is key. The
Speaker 2: effort is actually kind of a very holistic effort that
Speaker 2: that we put forth in order to make decisions as
Speaker 2: to you know, where to invest.
Speaker 1: So I do want to get to the you know,
Speaker 1: pricing power just a second, but I kind of want
Speaker 1: to just have one more question. You mentioned both you know,
Speaker 1: top down themes like AI and you know, then you're
Speaker 1: combining that with bottom up stock picking. Is it one
Speaker 1: or the other that actually drives decisions or you'd say
Speaker 1: it's kind of like a combination of both.
Speaker 2: It's probably a combination of both. But what I would
Speaker 2: say is fundamentally we are stock pickers. You know, our
Speaker 2: philosophy lends us to pick great stocks, and if you
Speaker 2: look at our alpha, historically it has generally come from
Speaker 2: that stock picking versus you know, and look AI, I
Speaker 2: think is a very different theme that is so powerful
Speaker 2: that you know, it's kind of top down and bottoms up.
Speaker 2: But you know, I would say, historically we happen to
Speaker 2: be very good stock pickers, and I think that our
Speaker 2: philosophy lends itself to it because we're always looking for
Speaker 2: what's changing on the margins.
Speaker 1: So, you know, as I said, I wanted to talk
Speaker 1: a little about pricing power because c neck I'm not
Speaker 1: sure if you call it that or just as an
Speaker 1: EQ you know focus EQNQ, you know, focuses on companies
Speaker 1: you know, oligopies or you know, or companies with you know,
Speaker 1: monopolistic characteristics. If I'm saying that correctly, what are the
Speaker 1: specific traits it really signaled pricing power to you?
Speaker 2: Oh gosh, so you know, it could be it could
Speaker 2: be many things, right in but in part, when you
Speaker 2: have markets that have one to three players, that automatically
Speaker 2: tells you something about the market, right it tells you
Speaker 2: something about the margin structure. And when that market begins
Speaker 2: to grow, the net beneficiaries of that are only one
Speaker 2: to three players, and if the barriers to entry are
Speaker 2: very high, then they have pricing power. Right. So if
Speaker 2: I think through, for example, the competitive landscape, and I'll
Speaker 2: I'll make this super simple to think through. If you
Speaker 2: have a company that has an incredibly high margin but
Speaker 2: the barrier to entry is very low, it will naturally
Speaker 2: attract capital. Right. If it's if the technological mode is
Speaker 2: too low, then it will attract capital into that market
Speaker 2: and the margins will shrink to a point where it
Speaker 2: doesn't make more sense for other competitors to come into
Speaker 2: the market when the barrier to entries are high, whether
Speaker 2: it's a data mode, a technology in mote and there
Speaker 2: are only a few players, as what has happened in
Speaker 2: the semiconductor industry recently, where you know, over the last
Speaker 2: two decades, the market is consolidated because it was so
Speaker 2: difficult to kind of cross the chasm with every next node.
Speaker 2: So all of a sudden, we have these markets that
Speaker 2: are effectively duopolies with very high barriers to entry, and
Speaker 2: therefore they have pricing power. So as you go through
Speaker 2: looking at pricing power, it's imperative to understand the competitive dynamic,
Speaker 2: how that competitive dynamic is changing, and how the market
Speaker 2: is moving. So I would say, you know, in a nutshell,
Speaker 2: we're looking for businesses that you know, have high barriers
Speaker 2: to entry so that they can maintain pricing power.
Speaker 1: Yeah, I do want to ask, you know, especially if
Speaker 1: we're talking about AI tams. You know, there's thought that
Speaker 1: some of these companies are trading at pretty high premium multiples.
Speaker 1: How does valuation kind of play in your process?
Speaker 2: Yeah, so you know, I'd like to take contention with
Speaker 2: that that, like what everyone thinks that these these companies
Speaker 2: are trading at high multiples. And it was just this
Speaker 2: year that Nvidia was trading at something like a sixteen multiple,
Speaker 2: which is a sub market multiple, and even today I
Speaker 2: think it's trading in line with the market and people
Speaker 2: I think they have it's this misnomer of the stock
Speaker 2: has gone up a lot, therefore the multiple must be high.
Speaker 2: What I think has been largely missed in over the
Speaker 2: last two and a half years, is that the numbers
Speaker 2: have also come up significantly such that the multiples have
Speaker 2: actually contracted in some cases. So we look at you know,
Speaker 2: Taiwan Semiconductor for example, it trades at a mid teens multiple.
Speaker 2: You know, to me for one of the most strategic
Speaker 2: assets on this planet, that does not seem that egracious.
Speaker 2: You know, it is by far what I would call
Speaker 2: a one and a half player market with incredible margins.
Speaker 2: And you know, something ever happens to SMC we go
Speaker 2: into a global depression, yet it trades it a fit
Speaker 2: that a mid teams multiple. So I would take a
Speaker 2: little bit of issue with this like misnomer that we
Speaker 2: have these incredibly high multiples in the AI space. Now
Speaker 2: I think in some of the private markets maybe maybe
Speaker 2: that's true where the where the multiples are significantly higher
Speaker 2: and they're like revenue multiples. But that's like a different
Speaker 2: ball of wax. So, yes, valuation does play a role
Speaker 2: in how we think about growth, and you know, you
Speaker 2: always what we we are cash flow investors. We want
Speaker 2: to know that that growth will yield cash flow. That
Speaker 2: is a kind of every single model that we build
Speaker 2: or every single company that we look at is backed
Speaker 2: by a DCF or a discounted cash flow model that
Speaker 2: yields for us a price target. And it is one
Speaker 2: of the keys to our of how we get to
Speaker 2: the valuation. It's not simply PE or PEG or it
Speaker 2: is based on cash and you know, the terminal growth rates,
Speaker 2: the terminal values, like all of these things play into
Speaker 2: our thinking about the valuation. So it is imperative that
Speaker 2: whatever company we own will they may not be you know,
Speaker 2: generating a lot of cash today, but as they grow
Speaker 2: into the business that we expect them to grow into,
Speaker 2: that they really start to show us the leverage, especially
Speaker 2: on that free cash flow.
Speaker 1: Okay, and you also, you know, your portfolios are fairly
Speaker 1: ir relatively concentrated. You know, what gives you the conviction
Speaker 1: to hold say third to fifty names versus a more
Speaker 1: diversified approach.
Speaker 2: You know, I think that a having high conviction as
Speaker 2: a function of our research process. We have a team
Speaker 2: of incredible analysts that you know, that are digging up
Speaker 2: what is a differentiated viewpoint And once you can establish
Speaker 2: that that differentiated viewpoint, it's actually easy to understand who
Speaker 2: the winners are and how a stock will progress even
Speaker 2: if there's a little bit of volatility. And you know,
Speaker 2: let me give you an example of a stock that
Speaker 2: has been recently pretty volatile. It's a company called QXO.
Speaker 2: And just this morning I was having a discussion with
Speaker 2: our one of our analysts, and as we're going through
Speaker 2: the model, I was thinking, Okay, based on these numbers,
Speaker 2: we believe they'll earn x and twenty thirty and therefore
Speaker 2: this stock should more than double over the course of
Speaker 2: the next three years, right, And let's test our conviction
Speaker 2: level on that statement. And so we went through and
Speaker 2: kind of re underwrote the assumptions. And you know, they
Speaker 2: just did a new acquisition recently yesterday of Top Build,
Speaker 2: and it took the it took the market a little
Speaker 2: bit by surprise. But we want to re underwrite our assumptions,
Speaker 2: you know, stress test them and say what number do
Speaker 2: we get to. So if I look at this business
Speaker 2: over a three four year time period, what does it
Speaker 2: earn and how much do we think the market is
Speaker 2: willing to pay for that such that we compound the
Speaker 2: growth over many years. And let's hypothetically say, for example,
Speaker 2: QXO is going to earn. You know, I'll just give
Speaker 2: you kind of the street number, six billion dollars. We
Speaker 2: can then underwrite that and say, okay, well, if they're
Speaker 2: going to if there's if there ebit does going to
Speaker 2: be six billion, how much should we pay for that
Speaker 2: in three years? And what's interesting is that if you
Speaker 2: can underwrite a company that's going to double, if not
Speaker 2: more than double, then it's a matter of patience and
Speaker 2: watch execution and understanding your management team because they're at
Speaker 2: the stewards of your capital. So that's what that's what
Speaker 2: gives us the conviction to hold through periods of volatility,
Speaker 2: understanding where a business is going and having conviction in
Speaker 2: our underlying numbers over not just now, it's over a
Speaker 2: longer period of times.
Speaker 1: So you know, an extension of that, you know, if
Speaker 1: you have this conviction, how do you determine position sizes?
Speaker 1: Is there something that helps you determine what would make
Speaker 1: a smaller position versus the larger in the portfolio.
Speaker 2: Yeah, So when you have a twenty to thirty stock portfolio,
Speaker 2: like the tail end of your portfolio can't be filled
Speaker 2: with smaller positions. So every position really has to have
Speaker 2: a meaningful impact and Look, I'm as a you know,
Speaker 2: as being trained as an engineer. I like to do
Speaker 2: things like super mathematically. Right, if you have a thirty
Speaker 2: stock portfolio, you take a undred percent divided by thirty names.
Speaker 2: You know, a average position side should be three point
Speaker 2: three percent, right that that is just like the contribution
Speaker 2: of each The more conviction you have, the higher it
Speaker 2: gets above that's three point three percent. The lower conviction
Speaker 2: you have, the lower it gets on that three point
Speaker 2: three percent. And you know, there's a little bit of
Speaker 2: differentiation in the portfolio in part because the benchmark that
Speaker 2: we compete with, which is the Rustle one thousand growth,
Speaker 2: has incredibly weighty positions. So when you have nine to
Speaker 2: ten percent positions, it becomes more of an exercise on
Speaker 2: what is the active weight that I want to express
Speaker 2: in a business that is that we feel bullish about.
Speaker 2: So that's a little bit on the weighting. But and
Speaker 2: I would say that that the very top of the
Speaker 2: portfolio we have to think about the active weight contribution
Speaker 2: and for the rest of the portfolio you kind of
Speaker 2: divvy it out like I described.
Speaker 1: So, I mean, is there a you know with concentrate?
Speaker 1: You know, I always bring up you know, risk. How
Speaker 1: do you think about risk or is there risk management process?
Speaker 1: Is it kind of volatility, capital loss or something else
Speaker 1: that you know you're really keeping track of.
Speaker 2: Yeah, So it's interesting because as you run more concentrated portfolios,
Speaker 2: your risk becomes not sector risk, it becomes single name risk.
Speaker 2: And so the key for understanding the risk in your
Speaker 2: portfolio is actually understanding where each company sits and you
Speaker 2: know where, and understanding that the core of these businesses
Speaker 2: very well. Because again it's all like it's no, it's
Speaker 2: not necessarily the sector risk you're taking. It's the execution
Speaker 2: by the management of the company that you own becomes
Speaker 2: probably one of your biggest risk factors, and whether or
Speaker 2: not they can execute that's you know, it is a
Speaker 2: diversified portfolio. So what we're always trying to do is
Speaker 2: find the best companies inside of each the best companies
Speaker 2: on this planet, really a lot of which reside here
Speaker 2: here in the US. And you know, I think we
Speaker 2: have to be mindful of the volatility. I e. It
Speaker 2: can't be a full on AI type portfolio. It needs
Speaker 2: to be diversified because that is the mandate that our
Speaker 2: clients have requested of us. And so there is companies
Speaker 2: like GFL Waste, which is a waste company, but it
Speaker 2: has an interesting story behind it that we think that
Speaker 2: it can drive the position, you know to or drive
Speaker 2: the stockwatch higher in terms of value. Or Pico, which
Speaker 2: is a very unique company that has incredible pricing power
Speaker 2: that sells airplane parts. So you have to diversify a
Speaker 2: cross kind of end markets in order to create diversification
Speaker 2: and capture growth and and mitigate risk.
Speaker 1: What would typically cause you to sell stocks fundamental deterioration, valuation,
Speaker 1: or just better opportunities.
Speaker 2: It could be that we're just wrong, right, We could
Speaker 2: our thesis could be wrong. I would say one thing is,
Speaker 2: you know we are we are incredibly humble, like we
Speaker 2: don't stick to a viewpoint and say we cannot be
Speaker 2: wrong because we had this three five year view. If
Speaker 2: if something fundamentally changes, we we do we are. We
Speaker 2: have the socratic process where we're constantly asking questions and
Speaker 2: and if all of a sudden there's like thesis creep
Speaker 2: and we start noticing that there's thesis creep in the
Speaker 2: way we're viewing the company, I would say that that
Speaker 2: would be you know, a flag or a yellow flag.
Speaker 2: As to whether or not the company should be sold.
Speaker 2: Other times, it could be that the stock is appreciated
Speaker 2: much faster than we expected, so it's pulled forward the
Speaker 2: anticipated return that we expected and the risk reward is
Speaker 2: simply not the same anymore. You know, where we thought
Speaker 2: there could be one hundred and fifty percent upside over
Speaker 2: three years, all of a sudden it appreciates enough such
Speaker 2: that there's fifty percent upside over three years, which again
Speaker 2: is then not really a compelling return from them. So
Speaker 2: that would you know, that would inspire us to trim,
Speaker 2: if not sell the stock. Or there could very well
Speaker 2: be like what you mentioned last, that the opportunity set
Speaker 2: is changing, and you know, one stock might be up
Speaker 2: and the other one has gone down, and you just
Speaker 2: flip flop and to a different into something that has
Speaker 2: a better risk reward, you know. And we did this recently, well,
Speaker 2: not that recently, I guess it was a few months,
Speaker 2: four or five months ago from you know, we we
Speaker 2: owned Vertive, which is a cooling company in CNEQ sold
Speaker 2: Vertive because you know, all of a sudden, we thought
Speaker 2: the upside was still significant, but the upside in GeV
Speaker 2: was more immediate, and we we flipped into a different stock.
Speaker 2: Now both have done well, but you're counting on GeV
Speaker 2: to have just more immediate upside and and longer three
Speaker 2: or three year long upside, which which is which has happened?
Speaker 1: So then how do you handle being early versus being wrong,
Speaker 1: especially in you know, fast moving themes.
Speaker 2: Ah, that's a great question, you know. I think really
Speaker 2: understanding a business allows you to have the conviction to
Speaker 2: hold if you're early. And I'll give you an example.
Speaker 2: You know, we wrote this paper in three years ago.
Speaker 2: It's called AI and the Declining Cost to Create and
Speaker 2: it basically went through how artificial intelligence is going to
Speaker 2: recavioc in software. This was probably an effort that was
Speaker 2: a two to three month effort in researching and talking
Speaker 2: to experts in the industry, and a lot of the
Speaker 2: experts actually disagreed with this viewpoint, but it was very
Speaker 2: clear that one of the modes for software was starting
Speaker 2: to come unraveled. And once we saw it, it was
Speaker 2: all almost like you couldn't unsee it right, And that
Speaker 2: conviction allowed us to hold that thought over the last
Speaker 2: three years kind of get us out of long held
Speaker 2: beloved software positions that we had held in the portfolio.
Speaker 2: For many, many years, and it allowed us to hold
Speaker 2: our ground because we were early. The market didn't believe it,
Speaker 2: you know, a lot. We got a lot of pushback
Speaker 2: from like if we would ever just float this to
Speaker 2: to kind of industry insiders. There was a lot of
Speaker 2: a lot of pushback, but we ended up being right
Speaker 2: and you're seeing it today in the market. So we
Speaker 2: were early now, you know, to some extent, it didn't
Speaker 2: hurt us because you know, software didn't perform the way
Speaker 2: you know, semiconductors or the rest of the AI food
Speaker 2: chains performed, and where we put the capital. But really
Speaker 2: the crux of it is is truly understanding and having
Speaker 2: a well researched thesis so that you're not wrong and
Speaker 2: you know, but I will say, but also having a
Speaker 2: humility to accept that you could be wrong. You know,
Speaker 2: so I've given you obviously like one of our big successes.
Speaker 2: I'm sure I could pull out one that we've been
Speaker 2: wrong on, but but yeah, or I'll give you another
Speaker 2: example like TSMC. I would say that we were early.
Speaker 2: We started buying this when you know, when it was
Speaker 2: eighty and I remember we started buying it, and we
Speaker 2: bought it because it was trading at twelve times cash flow, right,
Speaker 2: and I mean we were sitting here thinking, my gosh,
Speaker 2: you know, how is it that the most strategic asset
Speaker 2: in the world, that is going from a three player
Speaker 2: market to a one and a half player market. And
Speaker 2: at the time, it wasn't that clearer that Intel and
Speaker 2: Samsung were going to struggle as much as they did,
Speaker 2: But that was one aspect of our bullishness because we
Speaker 2: felt that they were going to struggle. You know, there
Speaker 2: was this overhang that China was going to invade Taiwan,
Speaker 2: so you know, there was a lot of kind of
Speaker 2: like dark clouds over this company, but it fundamentally is
Speaker 2: one of the most strategic businesses. So you know, we
Speaker 2: held that point of view that even if it is
Speaker 2: a three player market, it shouldn't trade at twelve times.
Speaker 2: We held the point of view that China wouldn't be
Speaker 2: invading Taiwan, at least not at that moment in time.
Speaker 2: We watched the Taiwanese elections, we saw that it was
Speaker 2: likely not going to happen like that they were not
Speaker 2: going to be replaced with a new party, and it
Speaker 2: all gave us conviction to buy more of the stock.
Speaker 2: But that was very counter to you know, what the
Speaker 2: rest of the market was thinking.
Speaker 1: So you've been, you know, pretty vocal about AI being
Speaker 1: a generational opportunity. Where do you think we are today
Speaker 1: in that cycle? And you know, where do you think
Speaker 1: the market's still underestimating its impact?
Speaker 2: Oh gosh, David, look, I think I don't I don't
Speaker 2: know about the market. I would say that people are
Speaker 2: still very confused. You know, people are pretty still very
Speaker 2: confused about you know, what AI can do. Are we
Speaker 2: in a bubble? I just feel like we are in
Speaker 2: like such the early early innings of artificial intelligence and
Speaker 2: its capability, and as it becomes more democratized, the real
Speaker 2: power of this technological it's not even an evolution, it's
Speaker 2: a revolution, will become evident to everybody. I think that
Speaker 2: there's a lot of like concern for the market or
Speaker 2: from the from the people that you know, AI will
Speaker 2: I don't want this data center in my backyard or
Speaker 2: and in part I think it's because they don't truly
Speaker 2: understand how capable this technology can be. And if we
Speaker 2: don't build it here, someone also build it somewhere else.
Speaker 2: I think that there's just a lot of misunderstanding about
Speaker 2: artificial intelligence on a kind of human level as well
Speaker 2: as in the markets. I mean, I've heard so many
Speaker 2: people I get asked this all the time, like are
Speaker 2: we in a bubble? And I'm just like, I like
Speaker 2: sometimes look at people who ask me that, I'm like, gosh, like,
Speaker 2: go try and use these tools before before you ask
Speaker 2: that question. Because once you start to use the tools
Speaker 2: for more than an alternative to search on, you truly
Speaker 2: ask it to do things for you. I think you'll
Speaker 2: be mind blown and you'll understand how much compute we're
Speaker 2: going to use and why people are spending this kind
Speaker 2: of capital in order to support this industry. And look,
Speaker 2: I've held the belief that I think in twenty four
Speaker 2: I was pretty public about my viewpoint that capex is
Speaker 2: going to go up in twenty four, in twenty five,
Speaker 2: twenty six, twenty seven, and twenty eight. And that framing
Speaker 2: comes from the viewpoint that the amount of computational need
Speaker 2: that we will have is going to grow logarithmically like
Speaker 2: it's going to be an exponential growth, right, it is
Speaker 2: not linear. And you know, if you build a supply
Speaker 2: demand model for tokens, it's quite clear to see how
Speaker 2: this is quite feasible. And look, the only fly in
Speaker 2: that ointment is if we get algorithmic changes that allow
Speaker 2: us to do more compute or more intelligence with less
Speaker 2: compute on a large scale basis, like two three orders
Speaker 2: of magnitude, right and then, but that's a technological shift
Speaker 2: that if that's going to happen, we hopefully catch.
Speaker 1: Well, it's definitely going to be exciting to watch. Unfortunately
Speaker 1: we need to end here, but core, this is a
Speaker 1: fun discussion. Thank you so much for joining me.
Speaker 2: Oh thanks thanks for having me David.
Speaker 1: I also want to thank our listeners. If you liked
Speaker 1: the episode, please share it, subscribe, and leave a review.
Speaker 1: If you'd like to see more of our research on
Speaker 1: the terminal, go to bi fund, go for fund and
Speaker 1: Active Research until on next episode. This is David Cone
Speaker 1: with the inside Active
Speaker 2: St