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- [00:18]
A
Today's show is brought to you by Betterment Advisor Solutions. Every RIA knows the tension. You don't want to turn people away. You don't want to require high minimums. And you want to help clients who are just getting started. Because that's where the long term relationships begin. But here's the truth. Those simple accounts, they take a lot of work. Account opening, trading, rebalancing. Before long, your staff and back office are underwater and trying to stay afloat. That's why RIAs are turning to Betterment Advisor Solutions. It's the platform built for segmenting your book and streamlining those smaller and simpler accounts. The onboarding experience is automated and paperless. The portfolio management is streamlined and tax efficient. The client experience is consistent and exceptional. Explore what segmentation can do for your firm today. Lower your operational lift, but keep your standard of service high. All with Betterment Advisor Solutions, your biggest regret will be not doing it sooner. Learn more@betterment.com Betterment Advisors Ladies and gentlemen, welcome to Live from the Compound. Humanoid robots are no longer science fiction. They're on factory floors right now. And the numbers suggest the next few years are when this goes. From early adopters to everywhere. Global shipments of humanoid and quadruped robots grew 250% last year to nearly 53,000 units. Goldman Sachs projects more than 250,000 humanoid robots shipped by 2030 and a total addressable market of 38 billion by 2035, a number they have just revised up sixfold. One investor saw all of this coming earlier than almost anyone else, bet his own money on it when the entire VC world told him not to, and then launched a publicly traded fund on the NASDAQ in May to let retail investors in on the trade. My guest is Andrew Kang. He is the CEO and co founder of Robo strategy Ticker Bot on nasdaq. A veteran crypto investor who made some of the earliest bets in defi and then walked away from the whole thing to go all in on physical AI. Welcome to the show, Andrew. So happy to have you.
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B
Hey, Josh, thanks for having me.
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A
How's that for a build up? Pretty good.
- [02:41]
B
Yeah. Excellent.
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A
All right. All right. Now I understand you also battled Ant man in the quantum realm, or was that a different Kang?
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B
Believe that was a different one. There's also a different Kang from MicroStrategy itself. Familiar.
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A
All right, in 2017, let me set this up. In 2017, I wrote a blog post, just own the damn robots. And it sort of went like mini viral in the financial blogosphere, which is A thing that used to exist. But I was explaining the relatively recent, at that time, NASDAQ explosion in terms of people realizing that these companies were on the verge of automating the entire economy and that investors worried about the future should just get long tech. And after a decade in which the NASDAQ 100 is up about 500% since then, I'd say it was one of my better calls. You've taken that a step further. You have personally and professionally gone all in on robots. Tell us about the origin of your decision to want to do that.
- [03:50]
B
Yeah, so the origin of my decision was around two or three years ago. A friend of mine showed me this company, Figure AI, and I took a look at the video, and they were having robots walking around in a lab looking like humans, just like you see in the sci fi movies. And it was like, well, before you would have thought that was kind of crazy. But now it was in the context of ChatGPT having launched, I think, a little bit less than a year ago. And it just kind of made sense that, okay, these things can probably actually start working now. No way is a pipe dream. But, you know, the reason why we didn't have it work was because intelligence was always the gaining factor. And I think it was kind of a little bit more clear that intelligence development of it was really going to accelerate and that you could potentially solve general intelligence for robotics in a really reasonable amount of time. Not 50 years, not 100 years, but something more like three to five to seven years. And so that made a really compelling time.
- [04:47]
A
So Figure AI had, I guess, prototypes of robots, but this sort of predates the rise of generative AI. It's before ChatGPT or right around the same time. And for you, that's the thing that unlocks it, where you say, okay, I now think this is workable and investable.
- [05:06]
B
Yeah, it was late 2023, like January 2024 or so. And so it was a little bit after ChatGPT came out.
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A
Okay, okay, you've told this story elsewhere. You talked to a lot of other VCs, you went to your whole network and you were talking about figure and robotics. And you say almost everybody told you not to invest, but then you put in a million bucks anyway, then you raise that stake to 19 million. Walk us through that period of time. What do you think you saw that the rest of them didn't? And are you very happy to have not listened to that advice, given the rise of robots as an investment theme, know, within a couple of years later?
- [05:54]
B
Yeah, so just kind of like looking at the company figure and trying to understand the total market opportunity of was. It was, it was a new framework that you had to kind of have kind of had to develop because we never had humanoids before. And so there was an established market for this that you could look at completely new. And, and so, like, the way we kind of thought about it was, well, humanoids are essentially productizing, you know, physical labor in the same way that LLMs productize knowledge work, you know, digital intelligence. And so, you know, if a robot can do anything that a human can do, and it's working 24 7, 365, it never has to sleep, it never gets tired, never takes breaks or complains or quits the job. Right.
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A
Like, no health insurance.
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B
Pretty good.
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A
No 401k match. Right?
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B
Yeah. And like, then, so then your, your market size is essentially the entire physical labor market, which is something like $50 trillion. I know that's a really nebulous number. It's just kind of like a really big thing. And so it's how much perspective. 50 trillion.
- [06:59]
A
50 trillion is the annual value of physical labor in our economy.
- [07:05]
B
Right. It's all the people. Yeah, I mean, that are working, you know, factory jobs or, you know, working in retail environments. But it's also, but it doesn't include all the labor gaps that we have and all the economic value that could be provided by, you know, all the jobs that exist but just can't be filled as well. And so the market could potentially be larger if we start bringing robots to space, having them in other environments where it just doesn't make sense economically for them to, you know, have people doing those jobs today.
- [07:37]
A
You are different than a lot of people, myself included. I always think, like, yeah, robots 50 years from now, or a lot of people would say 20 years from now, but you're like a three to five years from now person. And I think that's where you stand out from other people. I think conceptually we all understand there have been robots in factories for a long time. The big difference now is that they're humanoid robots. They almost. They don't just act as a coworker. They sort of. There's a verisimilitude with a real actual coworker. But you don't think that takes 20 or 50 years. You think that's like, right this minute. What makes you confident that that will be the case? And where do you think our audience will look around and see robots next to them the soonest?
- [08:25]
B
Yeah, look, I think in 2020, I probably would have been on the same page and thought that this was something that was more of a moonshot and, you know, wasn't sure if this would be achieved in our lifetime. But when GPT came out, I think it was pretty apparent that the slope of technological process was changing quite dramatically and things would be getting better much, much faster. And so we saw that jump from GPT 3 to GPT 5.5, 5.6. Right. In the last three to four years. And that was a huge jump. I mean, these machine intelligences are doing things that are sometimes things that we can't even do ourselves. The intelligence levels have just skyrocketed. And so I think you can just easily extrapolate to that similar path of development happening for physical AI as well for the intelligence of robots.
- [09:19]
A
You have a lot of contacts in the space and you've seen a lot more than the average person who's listening or watching us right now. I think speaking as the voice of the average person, everyone's been sent the YouTube video of the dog with no head, which is very disconcerting. Everybody remembers when Elon Musk brought one of his humanoid robots to the Kardashian mansion to, I guess, serve drinks at a party. And then the thing that they say is, like, all right, the dog looks like a toy. And the Elon Musk stunt with the robot, there was actually a person controlling the robot behind the scenes. I still feel that people don't really believe that this exists or that they're gonna run into one of these. So just to double down on my original question, where would you tell regular people that they're gonna come into contact with these humanoids first?
- [10:18]
B
Yeah, I mean, in regular contact, I would say it's probably a few years out from now, but I think you're going to see it more so on the Internet or if you live in specific places like Silicon Valley, a lot sooner. Right. I don't know if you saw the figure. AI live stream was around one or two months ago that went pretty viral where they had a humanoid robot doing logistics tasks, sorting packages, flipping them over like the same way a human would. And it went out, went on for eight days straight. And I think that was like a little bit of a mini chatgpt moment where people sort of realized, this is real. It wasn't controlled by a human. And. Right. It didn't need to. It wasn't some clip that was chosen out of a hundred clips or 100 takes. Right. And that was the one that was posted on The Internet, but. Right. It was working autonomously for a long time.
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A
And wait, the robot was sort. I've seen that clip, but I watched 30 seconds of it. I didn't watch eight days of it, but the robot spent over a week at that task, I guess.
- [11:14]
B
Yeah, they had a few. They had a few robots changing shifts because each robot, after, you know, I don't know, eight, 10 hours, they had to go and charge their batteries, and there was another robot that came and
- [11:25]
A
swapped over to say they had to go call their wives or pick up their kids at karate or something. But. All right, so they have to swap the batteries. But all things, all things being equal, that's what we're going to see in that package sorting role, for example, in like, a factory setting or a warehouse setting.
- [11:42]
B
Yeah, package sorting machine, tending packaging items. I mean, all sorts of things. It's, it's, it's kind of hard to kind of list off everything that a robot could do in these factories, because it's just, you know, almost everything a human can do, but also more. Right. Because some tasks are just too dangerous or they require too much intensity or strain from a human. That's where a robot can do a really great job.
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A
You've done the math on this publicly. You said a robot doing the work of three humans at roughly $2 an hour versus 35 to $40 for a US worker. At that math, the economic incentive for adoption becomes almost impossible to ignore. So I guess the only real holdup is how fast can you manufacture robots and how quickly can you convince business leaders to insert these machines in their work environments? What else really is there that would hold this up?
- [12:45]
B
Yeah, I would say intelligence. Sorry. I mean, I would say the manufacturing is the main bottleneck. The intelligence is going to get there in the next one or two years. If you kind of take a look inside the research labs or some of these headquarters of human robotics companies. It's, it's kind of magical in terms of, like, what they, what they're able to do. But, you know, we can only produce so many robots per year right now. And to produce, say, a factory that can manufacture a million or 10 million robots per year, that'll take, you know, a little bit of time to get going. So that'll be the model, but we're going to solve it in the next, I would say, three, four years.
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A
So we're going to get into some of the investments that you're making today. But just conceptually, is it likely that Tesla will be, at least in the early Stages of this. The first company who actually has the wherewithal to manufacture humanoid robots at some sort of scale. Do they look like they're in the pole position from a manufacturing standpoint?
- [13:44]
B
100%. I think they're working on a 10 million robot per year facility right now, which would be the, the biggest one by far. Most companies are producing on the scale of thousands to tens of thousands of robots per year today. So it's a gigantic leap.
- [14:01]
A
Andrew, you've been very honest about what you think comes next for workers, maybe more so than a lot of other people building in this space and a lot of thought leaders in Silicon Valley. You think that or you've said AI and robotics will eventually replace both physical and cognitive labor, and that perhaps universal basic income, or ubi, becomes a necessity. Most executives in the space, again, they're not saying that out loud, I would imagine. Maybe they're saying it over drinks with their colleagues, but you seem to lead with it. So talk about why that component of it is really important for us to be honest about.
- [14:46]
B
Yeah, well, I mean, you can't fight technology. Anyone that's tried to fight it in the past, they've always lost. And so I think you got to start planning ahead of time for when that reality hits and people are displaced by this technology. And, you know, we can't do it two years, three years in the future because people might be out of jobs at that point. So we need to start working on a plan now for when that moment does come. Because when it comes, it's going to happen real fast and you don't want to react late. And, you know, people could be in a lot of trouble if you are reacting late.
- [15:18]
A
The techno optimists seem to think that there's going to be a boom in jobs we never could have conceived of before happening in the wake of this robotics revolution. And I don't know if that means robot repair. I'm not 1000% sure what what that means, but I guess there are a lot of people working in jobs today that we couldn't have imagined 20 years ago, like social media manager. So talk a little bit about, I guess, why you're hopeful that we're not talking about UBI being the way everyone gets paid, maybe just a subset of workers who are the first among the displaced while they try to figure out what they're going to do next. Or is it more bleak than that?
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B
Yeah, I mean, I'm sure there's going to be some jobs that people will move into that people don't want robots doing service related jobs where you want a human touch, for example. And you know, maybe that gives a higher level of service if you have a human doing that for you as opposed to a robot. For example, in China they have the food delivery robots in a lot of the hotels, but they don't have them in the five star hotels, the best hotels. Right. Because it kind of adds a little bit of like a less premium service. But at the same time, like, what if you get androids, right. What if you have robots that are almost indistinguishable from humans and provide even a better level of service then? Well, that's maybe pretty tough to deal with. I think the argument goes like this for the, maybe the. Some of the technology people, which is we've always found like new jobs for people, but the reason why we found new jobs is because we found jobs to do that required more planning or like con, like complex cognitive thinking in some way and intelligence. AI is not going to stop. It's going to be able to think in all the ways that humans can. And so I don't see that being a good extrapolation to the future. And yeah, I'll just leave it at that. Robots.
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A
So you think these previous technological waves where within a couple of years somebody that used to be a blacksmith or somebody that used to manage a horse farm, then we get the automobile, Those people maybe become automobile mechanics. That analogy may not hold true this time because of the thinking that AI is capable of doing. And that's the thing that prior waves of technological advance just they didn't have as a feature.
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B
That's a great way to look at it because you mentioned robot repair mechanic. Why couldn't a robot do that? You're going to have robots building robots.
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A
Stop. You're taking all the good robot repair jobs. Stop. All right, look, it's a serious subject. We're laughing about it. But would you say, on the spectrum of optimism versus pessimism about what this is going to mean for the average person, would you say you're leaning more toward pessimism or are you just neutral? Because it doesn't sound like you're in the 8, 9, 10 level of the optimists who say this is going to be incredible because think of all the new industries we're going to create. It doesn't sound like you're on that side of the spectrum of thought on this.
- [18:34]
B
Well, I think if we get to figure out the AI safety, AI alignment piece, then there could be some pretty good outcomes for humanity. Elon talks about buttons for everybody because labor is just going to be so cheap and we're going to be able to do so much as society, and if we write the right frameworks for letting that benefit all the economic value, benefit people of all classes, then I think we could have a great outcome. But we got to get that right.
- [19:03]
A
I agree. What would you do if you had the power to enact some sort of plan or program at a national level? What would you do today? Or what would you start talking about today so that people are asking the right questions and looking for the right answers to those questions?
- [19:21]
B
I think there needs to be more research done in studies, and I think there's been some already around ubi and what happens to society once you start, you know, giving out essentially, like government support, paychecks to. To everyone? You know, there are some societies that have done it in, in Europe, and it's worked out well for them. But, you know, there have been some implementations that haven't worked out so well. But it's also, you don't really have a choice because if there are no jobs for people, then what else are you going to be able to do? You know, Sam Altman, I think, talks about universal basic intelligence, but I'm not sure that's a little bit harder to translate because I'm not sure anyone will just be able to turn intelligence into food and, you know, housing for themselves as well. So you probably got to provide that for a lot of people.
- [20:10]
A
So one of the models that I guess would be deemed successful is in the Nordic countries where they've taken the oil wealth of the nation and they've created sort of this prosperity fund that manages that oil wealth, and every citizen effectively gets a dividend from that. And it's sort of how they've been able to make it so that they don't have one or two really rich people who have captured all of that oil wealth. And everybody else in the country just looks at it. It's like, that must be nice for them. So it's sort of an example. I mean, it goes into, like, socialism and areas that you and I aren't gonna go into today. But do you think that might be some sort of a model where the government is involved in robot investments and is able to capture some of that shared prosperity and make sure that it's being sort of universally applied? Or is that more problematic than it is a solution?
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B
It seems like the government's kind of going that direction already. Right. They've invested in semiconductor companies in the Us like Intel, they provided financing for the Rare Earth's processing companies. And I think it's pretty clear that robotics is next to. They've, you know, Latinx been on TV over and over saying about how important robotics is for the country. And, you know, we've been a little bit behind on it compared to other countries in terms of incentivizing the domestic industry. But now it is a major priority for the government. And you're seeing that with the conversations that are going on with some of the bills that are going through Congress and the Senate right now. And so, yeah, I absolutely think that, you know, having government investment in the industry is, is, is important.
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A
I want to talk about the structure of what you built because this is where it gets really interesting for our audience. You've got a vehicle which you'll describe to us that went public on NASDAQ in May. So it still has that new fund smell. The ticker is bot bot and it's a closed end fund as opposed to an ETF or a venture capital fund. It's something a little bit different. Can you explain what robostrategy actually is, why you structured it this way?
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B
Yeah, Robo Strategy is essentially a publicly listed venture capital company that is exclusively focused on investing in leading robotics companies and predominantly private robotics companies. And really the concept is we're really bullish on the industry. We think it's going to grow 100 fold, a thousand fold. We're going to bring humanoids right to the market. We're going to invent all these new applications that can be done by robots. But all that exciting innovation is happening in the private sector. And you saw this with the AI
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A
labs, the private markets away from this. A lot of it's not on the stock market. So you're giving people away to own stakes in the private companies that you identify as being worth investing in.
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B
That's right. Yep, exactly.
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A
Okay. The microstrategy comparison is something that you've leaned into publicly. The idea is that if I have any of this wrong, just correct me. You issue shares at a premium to nav. You use the proceeds to buy more equity in robotics companies. And it sort of sounds like the flywheel that Michael Saylor first proposed when he began to use MicroStrategy as a way to do that with Bitcoin. Strategy's NAV is a live Bitcoin price, effectively, I think he owns, was it 850,000 bitcoin or something like that? And so the price of the security is a function of where is the Price of Bitcoin and how many bitcoins does strategy own? So it's easy to understand by people, and then it'll trade at a premium or a discount to that amount of bitcoins. Your private company valuations are estimated quarterly, and that's what gives investors a fundamental view into what bot could or should be worth at any given time. Do I have that right?
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B
Yeah, we're actually going to probably start updating it monthly on our website. I think there's a lot of nuance in understanding nav because it's very different from the NAV of a fund that holds publicly traded assets, where those assets are pretty much mark to market every second or every minute for something like Bitcoin for us, right. These private assets are marked at the last round valuation or sometimes at a discount. And so what that doesn't take into account is all the changes in the company, right, between rounds. And like a public company, that valuation or the growth of the company is being reflected pretty much every single day, every, every second.
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A
Right.
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B
That's not reflected in the Navy. And so. Right. But if there's a positive element or a negative development, it's not reflected until the next round. And that could be six months out, a year out, two years out. And that's part of the reason why you might see differences from the company, right? Robo strategy trading at a premium or at a discount nav to kind of reflect some of some of that development that might occur between rounds. And there's so, and, and, and I think you, you should also understand that private markets and public markets value assets differently because there's. There are two, mark, there are two different markets and they have a different subset of market participants. And you see this happen all the time. More private companies, when they go public, some of them might be valued more highly when they go public because there are more buyers, there's more demand in the public markets than there are the private markets, right? Which is really a small subset of the total investors in the entire world, where the public markets are the subset of almost every investor in the world. And you see this in some public companies, where their whole strategy is based on rolling up private companies into their balance sheet companies like Transdig or Constellation Software, where the public companies, you know, the public markets mark them at something like a 15 to 40x earnings multiple. And their whole strategy is buying companies in the private markets that are valued at maybe 3 to 8x that do very similar things. And so they can spend 100 million. And as soon as that's on their balance sheet now it's 400 million. Right. They've created 300 million.
- [26:51]
A
It's an arbitrage. They do that in my industry. The larger registered investment advisory firms have sort of like an enterprise multiple. And so when they go and buy a mom and pop ria, that's immediately like. It immediately adds to the value of the enterprise at like 3 to 4x. Just by virtue of this is now no longer a standalone business doing 7 million in revenue. We're adding this 7 million in revenue to us and therefore the multiple on that revenue is higher. Because our multiple is higher. This is a very common thing. So you're doing that in a market where there's less price discovery, there are less investors total. It's like in an enclave primarily in Silicon Valley or in Asia. And as a result there's some sort of, I don't want to call it alchemy, but there's some sort of arbitrage where once these companies become part of your fund, all of a sudden there could be an uptick in what they're worth.
- [27:53]
B
Yeah, in private equity world, they call it multiples arbitrage. There's a bunch of terms for it and we're just applying it to venture capital, which is, I think the first time people have done it in the public equity markets.
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A
Okay, could you update the value of the private companies you're invested in based on shares changing hands amongst private shareholders? For example, you invest in a robotics company and an employee manages to sell some of his or her stock to a venture capital fund or through one of these platforms and then the value is different from the last round. Are you able as the manager of the fund to take that into account and how you value these startups, or is that an area where you don't want to go, you'll just wait for the next financing round to write the value up or down?
- [28:45]
B
Yeah, right now it's a small component of our valuation framework. Could be a larger component over time. What I would also note is that the secondary markets for venture are pretty funny in that they don't act like the public secondary markets. They also anchor to the most recent rounds because people say, hey, look, they just did this round six months ago, money changed hands. Yeah, right. And then it comes, right. Like whenever there's a new round that happens that's a little bit of alpha. Actually, you know, I don't, I don't think that the markets are entirely correctly priced A lot, a lot of the times in the secondary markets, well, it's hard.
- [29:23]
A
Like take, take for example anthropic. So let's say they do around and you know they're raising at a valuation of. This is like years ago they raised at a $50 billion valuation and then news comes out like three weeks later that they got this massive contract with the Pentagon. Obviously the company's worth more, but there's no ticker and no one's trading it. So the private market knows it's worth more, but until there's a new transaction, hard to say exactly how much more. And that's a really big difference between public market investments and private.
- [30:01]
B
There's a lot of transactions in the secondary market, but the thing is that there's no like they're not publicly reported. And so there's a lot of non transparency or opaqueness in terms of where these things should actually be priced and what people are buying and selling them at.
- [30:16]
A
Okay, so you're being very honest and open with your investors in the bot fund. Hey, these valuations are going to change rapidly. We hope they'll change positively, but it'll be sudden and we won't know for sure. And I feel like I read through some of your stuff. You're just saying this is very different than public market investments and you should act accordingly.
- [30:44]
B
Yeah. It's interesting navigating this nav framework because it's know of course we try to be conservative on it because you know, we don't want to be overestimating our, our, our marks and the secondary markets can be intransparent and maybe a little bit slow at the same time. Right. Like we want to be able to provide accurate values and I guess the public market is kind of doing that in a, in a way by trading these things at, at a, at a premium. I hope it's something that becomes more transparent over time. But the nav framework was just never made for this world where the valuations move so fast. Right. It was. Most of the close end funds in the past have been private credit funds where the change.
- [31:25]
A
Or they'll own municipal bonds or they'll own. Right. Okay. Your three largest positions are figure AI Apptronic and Dyna Robotics. According to what I read, each represents a quarter of the fund's net assets. It's a pretty concentrated bet. It seems like you want to own a lot of the best and not just sprinkle in 100 different startups for the sake of saying you're diversified. Of course what comes along with that is increased risk if something goes wrong with one of them. Tell us about those companies and what people need to know. Just like as far as why you chose those specific investments.
- [32:10]
B
Yeah. So one thing I would note is that the percentage allocations are going to change pretty significantly over time. The reason why they might be a little bit more concentrated was because when we started the fund around a year ago, there wasn't as many exciting companies in the space that were more mature than they are today. And that's changed quite a bit because the field is moving so fast. There's so much more talent going into space and companies are maturing quarter by quarter. And you know, in terms of the companies that we've chosen, you know, we focus on companies that have just have the biggest power law, potential impact companies that have, you know, tackling the biggest markets in the world and still even that multi billion dollar valuations have potential 100x upside. Right. We want to basically find the anthropics or the open AIs of the robotics world. And we also want to be selective because imagine if you invested in maybe a lower valuation like AI company that you felt, because you felt anthropic or OpenAI was too expensive and you were trying to catch up to them. I mean you would have probably not done too well because most of them, right, they just kind of got out competed by these larger companies that had more talent, more resources and just were better, better leadership and, and so that's kind of our approach where we just want to bet on the best and leading companies in this space because they're in is so much more upside available. You don't need to be picky and there's a lot of alpha and being able to differentiate between, you know, the winners and the losers because there are going to be a lot of failures in the robotics space.
- [33:42]
A
Okay, so what's the elevator pitch on, on figure AI?
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B
I mean they're, I would think about them as like the apple for humanoids.
- [33:51]
A
They have, they have the best product.
- [33:53]
B
Yeah. It's not just you know, their chops and manufacturing AI and hardware, which I believe they're all top of the line for, but it's also the experience that they've been able to show with a robot with you know, the videos that they've created. And you know, you walk into the figure office, it feels like you're walking into the future. There's you know, hundreds of robots walking around doing household tasks or doing tasks in like a logistics environment. And you know, it's like designed in a way where it's like this is a premium product If I have people in my home as a, that's something I would show off. I want to, I wouldn't want to show off like a dinky, you know, $5,000 robot that is, you know, like breaking, you know, every six months or
- [34:30]
A
what are they going to sell the first, the first model that's for sale to the public? What are they going to sell that for?
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B
I think that's tbd.
- [34:37]
A
Okay, but we're thinking it's six figures or not necessarily it.
- [34:43]
B
They might have a model that goes that high. I think they're probably going to try to make it more affordable. And I think the leasing, the leasing robot type of business model is going to be popular as well that a lot of these companies are exploring. But that's more so to industry. Right. Opposed for the home.
- [35:01]
A
What's Apptronic?
- [35:04]
B
They were one of the earliest humanoid companies. They've been around for nine, 10 years and they have what I consider some of the original innovators in actuator development. Actuators are basically the motors and the, in the joints of the humanoid that basically allow them to move around. And you know, that's one of the most important components of a humanoid or any robot in general. And they partner.
- [35:27]
A
That's a bet on a supplier to the robot companies there.
- [35:30]
B
So they make their own humanoids now. Before they were a consulting service and they had actually produced the prototypes from for one of the very well known humanoid companies today. But then they decided that, hey look, we're going to develop our own humanoids now. And so they're developing their own hardware. They partnered with JBL to do the manufacturing. They partnered with Google DeepMind to develop the AI.
- [35:49]
A
Okay, and lastly, Dyna Robotics, what's the bet there?
- [35:54]
B
So Dyna is a really unique case where a company like figure they're developing both the AI and they're also developing the hardware. Unlike I guess Eptronic is that they're doing it kind of entirely vertically within the company itself. But their robot doesn't have legs. You know, they're creating robots that are completely stationary. They're just two arms or they're on a wheel base. And I think that's a really big market as well because not every single robot needs to move around to have legs. And those add a lot of cost to the robot. Right. Most tasks in a factory you're just kind of stationary, using the same job over and over and over again. It's repetitive and right. For a lot of environments as well. You don't need to go up and down stairs or go across tough terrain. You just need to be able to move around the same floor.
- [36:39]
A
Yeah, depending on what its job is. Not every job requires mobility on foot.
- [36:48]
B
Yeah, exactly. That's what they're working on.
- [36:51]
A
Okay, last question. You just announced a $36.5 million private share issuance two days ago. Is this. I guess it's not. I want to ask you if it's dilutive, but I'm not sure if that's the right terminology because it's a closed end fund. And ostensibly you said you're deploying it like you're going to be making an investment with that money. So it's additive even to the existing shareholders of the fund. But I guess, how should a shareholder in BOT think about this share issuance and future share issuances as you find new opportunities that you want to invest in, you're going to need capital to do it. I think everyone understands that.
- [37:35]
B
Yeah. So we've announced three pipe fundraises over the course of the past three weeks, totaling close to around 100 million. Those were all done with institutional investors that we believe are very long term oriented, not selling them into the public market. And they were all done at multiples to the publicly stated NAV. I believe around 3 to 4x.
- [38:02]
A
And so these people believe in what you're. So these people believe in what you're building so much that they're paying a very high premium over the actual NAV that you're now reporting. So that's a sign of a lot of confidence.
- [38:15]
B
It was close to the market price of each day that we had the pipes. Yes.
- [38:21]
A
Okay.
- [38:22]
B
Of course, like we're not, you know, as the largest shareholders in the company, the management team is not going to want to do dilution or issue shares if we don't believe it's massively accretive. Right. The value that we're getting from doing the issuance itself at a, at a multiple, plus the value of the investments that we're making and what we hope to generate from the returns has to outweigh the cost of dilution. So substantially personal decision.
- [38:48]
A
Okay, so if you're a shareholder in BOT and you see an issuance, your attitude should not be, oh, I guess this dilutes the amount of exposure I thought I had to figure AI. The way that you should actually think about it is, okay, they must have identified some opportunities and they want to go after it, and that'll be more investment in this portfolio that I'm invested in. That would be the way you want people to do that.
- [39:16]
B
We're increasing the exposure to the companies that people see and want in the portfolio. In the same way MicroStrategy did that for Bitcoin. Right. They increased their bitcoin per share. That's one of the key metrics. They look, look at something between 5 to 10x from when they first started accumulating it in 2020. And so, you know, hypothetically, if we had one figure share per robo strategy share, we hope to increase that by multiples in the future as much as we can so people can actually have more exposure on a person.
- [39:48]
A
That's awesome. So somebody that's thinking about investing in robotics and they believe, as I do and as you do, that this is happening and it's something that you can actually benefit from if you place your bets right. There are lots of publicly traded robotics ETFs. And now what you have listed is something completely different because you're able to invest in pre public robotics companies that have great products and ultimately at some point hopefully will themselves go public.
- [40:22]
B
That's correct, yeah. And you know, these private companies stay private longer and longer. SpaceX IPOed at 2 trillion. Anthropic OpenAI not going public until at least a trillion. And that trend is going to keep going for these private companies because there's just so much capital going into these markets and it's a long process to go public. It was not difficult. You have to deal with public board and all these other things. And if they have the ability to stay private, most companies are going to choose to do so.
- [40:48]
A
All right, Andrew, I really appreciate your time today. Let me just cover both of our asses. Nothing that you hear on this show is ever an endorsement or a recommendation to buy or sell any securities. Of course, do your own research, use your own judgment. If you want to read more about bot and read the risk factors and read about the company holdings. Andrew, what would be the best place for people to go?
- [41:13]
B
Yeah, RoboSurgery Co or on X? RoboStrategy.
- [41:17]
A
Okay. RoboStrategy Co or follow robo strategy. RoboStrategy on X. Andrew, thanks so much for coming by. Can we come to you in the future as we see more robots and want to talk more?
- [41:28]
B
Yeah, we'll bring a robot to the studio next time. Josh, thanks for having me.
- [41:31]
A
I love, I love it. Nice to see you. Thanks so much for your time. Thank you guys for watching and listening.
- [41:35]
B
Take care.
- [41:51]
A
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