Animal Spirits Podcast - Talk Your Book: Public & Private Opportunities in AI

Starting point is 00:00:00 Today's Animal Spirits Talk Your Book is brought to you by cranechairs. Go to craneshares.com to learn more about the crane shares. Artificial Intelligence and Technology ETF, ticker AGIX, that's A-G-I-X. Cranchairs.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 Ridholtz, wealth management. This podcast is for informational purposes only and should not be relied upon for any investment decisions. Clients of Ridholt's wealth management may maintain positions in the securities discussed in this podcast. Welcome to Animal Spirits from Michael and Ben. Michael, one of the things that we talk about occasionally on the podcast is how we'd like to just hit the fast forward button and see how this all plays out, right? Who are the winners, who are the losers, who has an egg on their face, who looks brilliant.

Starting point is 00:01:00 AI is no different in that. It would be fascinating to understand in five, seven, ten years what does this look like in terms of not only just AI in our lives, but from a market structure perspective, right? How different does the stock market look? Are there a ton of new winners or is it literally just the same companies? That's why I think investing in AI is so difficult. And you have these venture-backed companies, these private companies. Are they just going to get bought up by the big players or are they actually, are they, they're going to be the ones that take some of these places and push people, push the current

Starting point is 00:01:34 winners out of the way? That's right. So we get into all of that today with Jonathan Schellen. He is the chief operating officer, our crane shares. We talk about their new fund, Ajax, which invest not just in the publicly traded hyperscalers that we talk about all the time, but also some private companies that are making big waves in the industry. So here it is. Here's Jonathan. Jonathan, welcome to the show. Ben, Michael, great to be with you guys. So there's this little corner sliver of the market called AI. People have never heard of before.

Starting point is 00:02:10 Crane shares now has an ETF investing in this segment. Give us a little background down on what's going on here. Sure. It's taken us a little while to develop the ETF, Ajax, in part because a few years back, we were watching the Mag 7 and the AI space, and I thought to myself, back to party like it's 1999, right? And it's always good to be a little bit skeptical, but not cynical. So we started to explore the space. We wanted to capture the AI opportunity in a meaningful way, but felt like we needed to understand it better. So we approached our friends

Starting point is 00:02:51 at Etna Capital. We've known them for a long time. And what makes them unique is that they are AI native investors. They don't come from the buy side or the sell side. One of the partners at Etna worked at Sequoia Capital and was an early investor in a lot of these early private companies in the AI space. And his partner was an engineer at Cruise Automation, which was subsequently bought by GM. So what we envisioned to do is to bring the 10 to 20 year AI opportunity to investors and do it in an ETF. And we could talk about kind of what we learned on that journey of research to actually build it. One of the things that is different about Ajax versus the other baskets of stocks that try to get exposure to this gigantic theme is there is, there are some

Starting point is 00:03:48 private names in here. So I'm wondering how that fits into the overall thesis because there are a lot of companies that are private that are capturing a lot of value. Obviously, Open AI being the gorilla in the room, but there's others. It's not just them. So how did you think about going about both securing the shares, putting it in the wrapper, which companies and why? Talk about that part of it. Yeah. And that's what took a long time. Let me give you a little bit of rational as to why we even own them. As we look back historically, at other, you know, kind of massive revolutionary cycles, whether it was railroads or highways or even the Internet, we saw that they always followed this pattern, where you go from hardware,

Starting point is 00:04:39 these kind of key inputs, then you go to infrastructure, you know, like laying the rails, and then you finally go to applications. So one of the things that we learned when we were studying the space and trying to understand how things evolve over the next 10 to 20 years is this recognition that you need all three. You're going to need hardware, you're going to need infrastructure, and you're going to need the application companies. It turns out that inside of that infrastructure category, which for AI includes data centers and cloud computing and other segments, including the foundational models, all those foundational

Starting point is 00:05:21 models, Open AI, XAI, Anthropic, Perplexity, they're private companies. Like, you can't get them. So if you wanted to build a proper AI portfolio, you have to move beyond Mag7, you have to move beyond the NASDAQ, and you have to move beyond public securities. And so that's what took so long. We had to figure out, can we even do this? Are we allowed to invest? Yeah, what are the rules of that with each? ETFs investing in private companies because I don't know a whole lot in the background there. So you are allowed to own up to 15% exposure in illiquid securities. And so private companies qualify as illiquid securities. We're targeting around 10% because the 15% is a hard limit.

Starting point is 00:06:13 And as you know, things can change with performance and flows and whatnot. But you also have to fair value those securities. So that's the other thing. You have to build an entire infrastructure around looking at the securities, fair valuing them, and making sure that you can create a nav each day. So how do you go about that process of coming up with a fair value? So every day you have to do it, are you using proxies? Like, what are you using? Because obviously these companies aren't marked every day.

Starting point is 00:06:44 That's right. So one of the things that's pretty amazing, and I should mention, And we do own both Anthropic and X-A-I in the portfolio. We participated in Anthropics D-Round back in March, and they did an E-Round later this year. That was at 3X the valuation, just to put it in perspective, right? We invested around $60 billion. They were more recently marked at $180 billion. So your question is a really good one, because how do you reflect this movement from 60 to $180

Starting point is 00:07:14 inside the portfolio. But what's really great is that this space has grown so much that there's actually a very large secondary market. So, you know, people are trading the private shares in the secondary market, and they're fairly accessible. You know, these are firms that are worth tens, if not hundreds of billions of dollars. And you have various organizations, institutional investors,

Starting point is 00:07:42 even some of the founders, have liquidity. So there are now data sources and we rely on them that give you secondary market data with regularity. So we're able to look and see what are prices looking like in the secondary market? And that gives us a pretty good proxy. And then we do a lot of our own kind of qualitative overlays. We obviously are watching news flow, looking at filings, trying to see if there's something upcoming. And I should mention, we are on the cap table of both Anthropic and XAI, right? Sometimes people gain access to these through an SPV, a special purpose vehicle. We participated directly in Anthropics D-Round and XAI's tender offer. And that's fairly unique. And that has a lot to do

Starting point is 00:08:32 with our partnership with Aetna, also our institutional standing in the community and access to these firms. So you mentioned going beyond the NASDAQ going beyond public markets. Crane shares obviously is synonymous with investing in Chinese tech stocks. I assume that means this is a global fund. It is global. So one of the things that if you look at the composition of the fund, it is about 25% Mag 7. So we want to go beyond Mag 7. But it has about 50% of its exposure outside of the NASDAQ. And it might surprise you to know that there are a bunch of companies that we own, even U.S. companies that aren't in the NASDAQ, for example, dualingo, sales force, and so on, are

Starting point is 00:09:21 U.S. firms that actually are not, they're not in Oracle, another good example, not in the NASDAQ 100, which may surprise some people. And then, of course, we invest in firms like Nebius and SAP that are non-U.S. companies, right? So we wanted to get global exposure, but we wanted to really nail down the AI theme. And we think this is the right way to do it. So you're getting the MAG7 for sure. It's about a quarter of what we have. You're getting private company exposure up to 15%.

Starting point is 00:09:51 And you're getting a number of companies, many companies that we think are in this application space that are going to be very important as the cycle progresses that we're accessing globally. who is nebius i've never heard of that stock yeah so so nebius is a company that specializes in servers and data centers globally they're out of amsterdam um so again this kind of falls into the what i would describe in our bucket into the hardware bucket and but what's interesting is right now our portfolio is comprised of about 23% hardware 49% in infrastructure infrastructure and 30% in this application sleeve. And within that infrastructure sleeve is where we have our anthropic and XAI exposure. But the key here is that if you're going to build something that's durable over a period of 10 to 20 years, you really need to recognize that these weights could shift. I spent a lot of time in glide path investing. So you can almost think of this as a bit of a glide path that as as time progresses, you would expect less and less in hardware. more in infrastructure and application. And there are application firms that are going to emerge, that are AI-native, that don't

Starting point is 00:11:12 exist today. Right now, the companies in the application space that we invest in are like the duolingo, service nows, and the sales forces, but there are going to be brand new companies that we don't even know about that are going to pop up and that are going to be critical drivers in that space. Jonathan, you mentioned like the transition from the glide path from hardware to software and all sorts of other layers and applications in between. I'm curious to get your take or the house use take on robots. Elon was all about that. He's talked about how it's important for him to have

Starting point is 00:11:44 control of the stock so that he can control the robot army and his vision of what that's going to look like. Tesla is a top 10 holding in the portfolio and is going to be a key player in this humanoid robot, whatever space we're calling it. Where are we going? What is this? What is it's going to look like it won. So I talk about this being kind of the 10 to 20 year capture of AI. If you want to go out even further to 2050, Morgan Stanley is saying by that time, the humanoid space is going to be a $5 trillion revenue industry and that there should be about a billion robots running around. We believe that. In fact, we launched an ETF. We launched the first ever humanoid and embodied AI.

Starting point is 00:12:31 ETF. It's called COID, K-O-I-D. And it's become quite popular because we have access to a unitary robot. We parade them around New York City. We've had them, you know, walking around. We did a bell ringing with them on the NASDAQ. And it's performing very well. That, too, is kind of a global mandate. And it's going to own a lot of companies, some that you know, some that you don't. But it focuses on actuation, you know, COID, kind of the things that allow the robot to move effectively, Critical Materials, Rare Earths, AI and semi-names, and, of course, the humanoid and automation apps that will come. But that, to me, is what comes next. AI right now is what we think of as digital AI, and most of what we do in this portfolio is digital. Eventually, AI becomes physical

Starting point is 00:13:21 AI. It becomes embodied in things like robotaxis, which we already know about, but certainly humanoids, but also equipment, manufacturing, that is very much the future. So you could tell, we're very much focused on this category of investing, and we think really meaningful returns can be achieved in the space. Credits are also being 10 minutes in and not mentioning a bubble yet. But we have to obviously bring it up a little bit. It's the topic of conversation these days that everyone wants to talk about. You've seen the historical comparisons to the railroads and the fiber optics in the dot-com bubble. I think the hardest part about handicapping this current CAP-X cycle is the fact that the companies that are supplying it are the biggest best

Starting point is 00:14:08 around corporations we've ever seen. I think that's really hard when they are all at the same time investing in the same infrastructure, the same companies, they've all kind of gone in on this together to different degrees. How do you try to handicap this stuff when you see those comparisons and you say, hey, listen, we haven't seen this type of infrastructure investment. since the dot-com bubble and since the railroads, like, what do you think about the opportunity when you see these types of numbers that just seem like otherworldly? Well, and again, this is where I think it does help to see, to look at things through the private company lens. Just in the example, you know, like I said, we own Anthropic,

Starting point is 00:14:47 and when we bought it, the data that we were looking at said that Anthropics got a billion dollars of ARR, and when they did their E-round, it was $4 billion of A-R. are just in the course of a year. So I think what's different with this time around than say even the tech bubble that I referenced earlier in the late 90s when I remember living in the Bay Area and web van, I don't know if you remember web van, but web van was doing grocery delivery and they had about an $8 billion valuation after they went public. Webvan had fewer vans than United Airlines had aircraft and they were worth twice as much. So that's, you know, know, kind of the poster child for a bubble. Now, mind you, you know, I was like, look,

Starting point is 00:15:32 the really nice vans, but they're not as nice as a Boeing. So that's where I was initially really quite, quite skeptical about what was happening here bubble-wise. But a couple things I would say. One, valuations right now, if you look at forward PEs, we haven't reached kind of a blow-off top. So certainly there's room for volatility. You're going to have things move up. You're going to have things move down. That's why we think having this basket approach is important. But the other thing to note is that when you're looking at what's happening in this space, you're going to have a natural migration that are going to be winners and losers. But there is a lot of demand still. There's a lot of need to support what's happening. And we're just, we really are getting started.

Starting point is 00:16:17 You know, where we are across the AI spectrum of things is we've just gone from chatbots to some reasoning, you know, where the AI understands context, right? If you can, if you go right now and you plug in some Python code into an AI, it'll recognize that it's Python code and that you're asking it to debug it. That's, that's an acceleration from where we were even a couple of years ago where it just wanted to talk to you. And then where it's going is, is kind of what we talked about before. You're going to have agentic AI really solving, solving workflow problems, helping with automation. And that's going to require a lot of, a lot of energy and a lot of continued investment. The last thing, you know, maybe I'd mention on this, using history as a guide, is

Starting point is 00:17:03 if you go back 15 years to 2010, you had Intel, $113 billion company just came out with the core I3 processor. You had Apple, $163 billion company just released its first iPad. You had Amazon a $58 billion company 10 years after opening the marketplace to third-party sellers. So you would be wise to invest in all three of these types of companies, you know, between 58 and 163 billion. But how did they do sense? So Intel, which was the hardware piece of this, up 1.6x. It's now worth 179 billion. Apple, 3.9 trillion, up 24X, which was the infrastructure. play at the time, Amazon, the application play, up 41x to $2.4 trillion. So, you know, we believe that as long as you are cognizant of what types of companies

Starting point is 00:18:04 you own, where they are in their cycle, what role they play in the broader AI cycle and dynamically adjust, you should do okay. Inevitably, there are going to be companies that are super overvalued. but the metrics that we had in other bubbles, like I remember, you know, eyeballs and page views and all that kind of stuff, which really wasn't tied to revenue and was becoming very popular with the sell side community. We don't see as much of that yet in the AI space. You know, we're seeing tangible metrics that have to do with revenue generation and growth. So four to five percent of the fund right now is in, as we mentioned, anthropic

Starting point is 00:18:46 Anthropic and X-A-I. Is there plans to pump those numbers up and get closer to 15 percent? Yes, we have a pipeline of companies that we're looking at, really all the time, because as the fund grows, we want to make sure that we're close to that 10 percent level. But you don't need to own a lot in the private company space to have the right kind of exposure and the right level of performance. In fact, you know, we've seen that even the two companies that we've owned, the private companies that we've owned, we can actually track the performance of how they've done. We've actually built an index for this fund for the public securities.

Starting point is 00:19:29 So, you know, call it the 85 to 90 percent that's in public stocks. We track using an index. So you can actually very clearly see, even on our website, how much have the private companies contributed to performance? And they've added about 5% of returns since we launched the fund. And it's doing pretty well since it came out a little over a year ago. It's up about 47%. If you go on CNBC, the smart thing to say is that we're investing in the picks and the shovels, right? You can't not say that and not sound smart.

Starting point is 00:20:03 So what are the picks and shovel plays for the AI boom? So the picks and shovels, so you're talking about. now just like the hardware plays, right? Yeah. Yeah. I mean, look for us, it's the, a lot of the chip makers like Nvidia, SK Hynix, ASML, TSM, but what I wanted to highlight is that when you look at other ways of structuring portfolios, that's going to be a big part of what they invest in. That's, that's about 23% of our portfolio. And while it can go up a little, the center of gravity means that that section of the portfolio will probably go down and transition over to the infrastructure side, where you have the cloud flares and the palanteers and the data dogs and

Starting point is 00:20:49 the nebuses. So this goes back to what we're talking about before. These weights will dynamically shift using a lot of these great inputs that we have with our partners that are at now that focus on AI readiness and AI relevance. I'm curious. I'm really fascinated in the private side of the ETF. How volatile are the prices for those marks that you're using? Are they relatively stable or are they moving quite a bit? When we look at the secondary market prices, there tends to be a range because, you know, unlike spreads that you see in public equities, which tend to be pretty tight, the spreads in private equities can be wider. So we don't want to move the price of a private holding every single day if we're observing, you know, price movements in the secondary

Starting point is 00:21:39 market that are pretty narrow. So what we do is we, once we exceed a particular threshold, we'll move the price. And in that earlier example I used, when we bought Anthropic at, you know, kind of around $60 billion in valuation, it moved up to $180 billion, when a round is closed and when there's a new, new priced round established, we will necessarily move to that new value, right? That is a firm value. But in this example, over that period of months, we were gradually increasing the price of Anthropic because that's what we were observing in the secondary market.

Starting point is 00:22:14 People recognized that a new round was coming. There were rumors about what it would be valued at. And so by the time that this E round actually occurred, we were only about 20% of 20% away from that new price. And so think about that. This security moved 3X in value, and our fair value methodology allowed us to gradually, systematically increase the value of Anthropic to a point where just before that new round was released and announced, we were within 20% of that value, which, again, in public equities may seem like a lot, but in the private space, that's a pretty good way of ratcheting up.

Starting point is 00:22:56 So there's 56 holdings in here. Talk about what comes into the portfolio, what goes out. how are things weighted? How are they monitored? What does all that look like? Yeah. So every quarter, we go through a systematic process. As I'd mentioned, we'd built an index around this to codify how we think about looking at the AI ecosystem. And the two major scores that we produce for every single one of these potential securities, there's an AI relevant score and an AI readiness score. The easiest way to think about them is an AI relevant score says how much sensitivity is there to AI in this company, right? Is AI relevant to its revenue

Starting point is 00:23:39 generation into its strategy? And AI readiness is just a matter of depth, you know, how much penetration has AI had within that organization. So not surprisingly, a company like Nvidia, would rank very high on relevance and readiness, Microsoft would as well, partly because Microsoft does not only incorporating co-pilot and everything and a lot of what they do and offer to clients, but they also have Azure, right? So which is their cloud-based part of their business.

Starting point is 00:24:16 So we revalue these things each and every quarter. And on a quarterly basis, I would describe the changes as subtle. And the idea is to make adjustments and use the research that we have from Aetna. As I said, their process is a little bit unique because they're looking at this through a private company lens. But it's been extremely effective engaging the success of public companies in the AI space. So we've had some, you know, some of our best winners, for example, and I think I mentioned this early on, was in that application sector. some of those companies that would historically have been meaningfully underway in a MAG7

Starting point is 00:24:58 or even the NASDAQ 100. So I think that's where we had a lot of value within this portfolio. How often is their turnover? Are there new companies coming into this index all the time? How does that look? Yeah, I mean, we're looking at a really broad universe. So there are 300 to 400 names that are in these 12 related industry. So you can have companies coming in and out.

Starting point is 00:25:21 But again, you wouldn't expect that to happen very often. I think that you also have a $2 billion minimum. So we want to make sure that we're excluding kind of the smallest companies if they're too, too new. And this is a really interesting thing. People when they think about private companies, they necessarily think that they're somehow smaller. That's not the case.

Starting point is 00:25:44 If you took the five largest private companies globally, they would fall within the NASDAQ 25. So it's a huge opportunity cost not to invest in private firms, in my opinion. When we were doing this research, we were shocked. Like XAI, if it was public, would be the 19th largest company in the NASDAQ. Anthropic would be the 22nd largest. So not having access to these private firms means you're really giving up a meaningful part of the universe. And that's why we felt so strongly of figuring this out and bringing this to the market. If you had the opportunity to invest in OpenAI or and or perplexity, would you do so? Or is it like, listen, we are, our bets are with XAI and Anthropic? No, we are, I mean, I could say that there are a number of companies

Starting point is 00:26:37 on our list, and those are on the list for sure. There are many. But to your point, OpenAI actually has a higher valuation than XAI and Anthropic. Maybe combined. Yeah, yeah. And then perplexity is a bit smaller than some of these others, but they play a very important role as well in what they're doing. So these are firms that we're doing research on. But as I'd mentioned, what we try to do is to get on the cap table of these companies. So there's a timing element. To be on the cap table of a company, you need to participate in their round. It's either a... How hard is it to get on these cap tables? Wait, hang on, to that point, so when you say to be on the cat table, you mean you want to own, like, you want to get primary shares? Yes. And we do. So this is really important. When the, our exposure to XAI and Anthropic are our shares, um, that we participated in a round, right? We participated in the D run. No, I mean, I should be careful. So with XAI, we, we, it was a tender offer. So it was buying from existing investors. But, but you're not, you're not buying an SPV within an SPV. No. Okay. Okay. Oh, interesting. No. And this is, so we're the first ETF that I'm aware of that has direct shares of private companies. And again, this goes back to our relationship. We're not anti-SPV, but we're going to have a pecking order. Our pecking order is to be participating in these rounds when the company's offering them to be on the cap table because it gives you just a higher standard of price and economics. But at the same time, if we're, we're, we're, uh, We're very keen on the SPV opportunities, and we have a great network there and can access

Starting point is 00:28:22 private companies through SPVs. In fact, I should mention, outside of this ETF, we've actually launched with both MSCI and S&P private company indexes, so top 10 indexes of pre-venture or pre-IPO venture companies, where we would actually construct private funds entirely of private companies. So we're very focused on growing in this space and providing these opportunities to our investors. Where we draw the line with AI, like, for example, like Starlink, surely they're leveraging AI in some capacity. I'm sure they are. Would that potentially meet the criteria?

Starting point is 00:29:04 It may, it may. But, you know, they're, how relevant is AI to what they're doing, right? I think that their relevant score may not be as high. high as something like, you know, like why did we buy? So in that kind of Elon Musk ecosystem, why did we buy XAI? Why does XAI stand out? It stands out because it's got the highest intelligence score amongst the, you know, GROC's got the highest intelligence score amongst all the various LLMs. And it's given you data from, you know, some of the rest of his ecosystem, including Teslas.

Starting point is 00:29:44 I don't know if Starlink would fall into that category, at least not yet. Now, maybe they do something that ties them more closely in or makes them more AI dependent or relevant, but I don't think that's the case right now. How does a company like Duolingo pass your screens? I'm curious on that one. Yeah, I mean, so Duolingo's business, as you know, is, I mean, I think heavily, they're a heavy AI user. So I think their ability to grow and continue to expand their business model and revenue is very much tied to using AI successfully and automating what they do.

Starting point is 00:30:21 So I think that's why that some of the names that we have in here may be counterintuitive. You would also say like Adobe, when I think of Adobe, I think like PDFs, but many from or even Salesforce, you would say, well, Salesforce is just CRM. Like, why is that in there? Well, Salesforce just launched something called agent force. So they're going to use agentic AI and roll that out and try to increase penetration amongst their clients, right? So if you're a Salesforce user, you're going to be approached by Salesforce and having them say, use our agents, use our agents across your business, expand beyond just what you do in CRM

Starting point is 00:30:57 and try to integrate workflows across your entire company. And we're being approached. I mean, you are too, I'm sure, as an asset manager. we're being approached by AI firms all the time asking us to somehow stitch together all the things that we do across our organization. So if we came back to you in five to ten years, does this portfolio look completely different, you think? Or do you think that a lot of these big players are still there at the end of the cycle? Yeah, I think it's a good question. I think the major differences you're going to see is that our application sleeve, which is now about

Starting point is 00:31:32 30% is going to be significantly larger. It's going to be the largest segment of what we invest in, much like infrastructure is now. So I think it's going to be north of 50%. I also think you're going to see a lot of the newer private companies that we invest in are not going to be just an infrastructure, which is where we are now in the phase, right? Why are we invested in private companies and infrastructure? Because those are the ones that are closest to going public. They're the ones that are going to add the most value we think to our investors. I think you're going to see a lot of private companies get picked up in that application segment. So companies that may not even exist today. And that's what I'm pretty excited about as well, that we'll have the ability to

Starting point is 00:32:13 start diversifying our private fund exposure as the fund grows and evolves to include these new firms. Because we really do believe that there's a kind of a life cycle to how this is going to play out over the next 10 to 20 years. Jonathan, last question from me. So the private companies being in the portfolios is a new thing. If there are opportunities to exit, let's just say at a silly markup, 5X, whatever it is, while there's still demand for a set for on the secondary market, would you consider doing that? And or, or I should say, are these being held until a public offering, which, you know, with these giant companies could be, who knows how far away? Yeah, we have that flexibility. So in other words, there are two ways that we would envision

Starting point is 00:33:01 exiting. One is, you know, and I think the preferred route is for these companies to go public, and we are a beneficiary of what that means. But another approach is, you know, kind of having, if the company has a tender offer, we can participate in a tender offer and sell our shares. So either or, and I think we'd have to be judicious about which way we go, but I think the preference, when we buy these are our desire is to hold them until the companies go public. And we think many of the ones that we bought, Ken, it's not likely, you know, given the size of these companies that they'll be bought out. You know, we know that there are a lot of companies that are owned by PE, but we're trying to buy companies that are large, have deep liquid secondary markets.

Starting point is 00:33:47 You know, and that's the other thing. If a company gets meaningfully large and all of a sudden our private fund portfolio is above the 15th percent, we would want to trim back. So we would want to leverage that secondary market and take some of those gains and reduce that exposure. All right, Jonathan, we're really to send people to learn more about the fund. Sure, crane shares.com backslash agics. And because you asked, I would also say craneshares.com backslash coyd to learn more about our humanoid and embodied AI strategy as well. Awesome. Thank you, Jonathan.

Starting point is 00:34:24 You got it. Thanks, guys. Okay, thank you to Jonathan. We'll check out crane shares.com. more about the fund and all their other fund structures, email us, animal spirits to the compound news.com.

Animal Spirits Podcast - Talk Your Book: Public & Private Opportunities in AI

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