Is Robotics The Next Megabubble?

0:00 Welcome to a great episode of Azex. We're super happy to present Andrew Kang, the founder of Robo Strategy, here to talk to you about all of the incredible things that are happening in the robotics industry and the launch of his new product. This is potentially a $10 trillion industry according to Andrew and I do happen to agree with that. And in this episode, we talk about all of the things that you need to know about this next potential mega bubble.

0:28 So, make sure if you like the episode, you click like, you click subscribe, you tune in because we live stream on Wednesdays and Fridays talking about everything that you need to know with regards to the market. And we consistently are dropping new guest podcasts about industries that you're going to want to hear about because in this crazy world, there are a lot of things that are happening and there's one way to stay on top of it. It's to tune in to a 1000X. If you have any questions at the end of the episode, go to our ThousandX terminal, which is a new product that we launched. It is a basically think about it as a trader buddy in your pocket. It will answer any questions about anything related to the markets. It's at 1,000x.mmoney. Go check it out. And thank you for tuning in.

1:17 [music] >> [music] >> Andrew, thank you for joining the ThousandX podcast today. We are super psyched to have you. You're working on some really interesting things. Uh, welcome. >> Thanks for having me, Ali. >> This is fun. I know we've we've known each other we've known each other for a bit, but we've known each other from the world of crypto, and now you're known as the Robo King. the moniker that people are giving you online.

1:51 >> I I haven't heard of that one, but that's fun. >> I've I've seen that around. You've gone super super super deep into the world of robotics, and this is a world that I don't think a lot of our listeners or a lot of people have really paid super close attention to. It's getting it's getting hot right now. And I wanted to start by asking you really, you started off in crypto. you started off as an investor and then you get into robotics.

2:19 How did that take place? Maybe walk me through your entry into investing and your evolution from crypto investor into robotics investor. >> So I would say my professional entry into into investing was probably around the 2018 uh time period. Um went really heavy into crypto when the markets uh were dying. um and I would say had a little bit of a sunun uh being early in sectors like DeFi that weren't really established at the time but eventually took off you know brought on five or six other people to help manage the portfolio and and start what is known as mechanism capital and you know we we never took outside capital and our primary focus was investing and uh you know trading the crypto markets and having you know acqu act active venture capital investing as well. We never really ventured too much outside of the crypto space until I would say 2023 because that's where we felt our expertise and area of competency was.

3:30 And but in 20 late 2023, early 2024, a friend told me about the company uh Figure AI. Uh and you know, I watched a video of the founder Brett and you know, about why he believed humanoids were going to be the future and what they were building with the company, and it it just made sense. Humanoids were always the sci-fi dream, right? You'd see it in every sci-fi movie, uh but you didn't have it in real life. And I think the concept has been around for at least a hundred years like where people have imagined machines that are shaped like humans and can traverse the world and manipulate the world like we can. But it was just there were too many technological barriers. And if you think about it, the barrier was always intelligence. I think the hardware design it's difficult. Yes. But it it was solvable. And uh but to to make a robot understand the world in the same way that we do and to be able to interact with it uh in you know infinite amount of different circumstances and environments and different objects that that that requires basically you know very high level of physical AI and with chat GPT coming out in 2022 I think it was clear to the world that we were going to have essentially digital AGI within a reasonable amount of time and you could extrapolate to that extrapolate that to say we're going to have physical AGI as well. From that perspective to me I think it was clear that hey look there there's this inflection point that is going to occur really soon where robotics I would say like development or humanoid development was looking like this and now it's going to be like this in terms of you know what what these machines are actually capable of. the best time to invest in my opinion is is at these inflection points because not everyone realizes that the pace of development is going to change. Uh the expectations for development are going to change and the market is going to you know reach that future state a lot sooner than everyone would think and the market's not always pricing it that way. And so it kind of reminded me of crypto in 2014 and 2015 from that perspective in the in the sense that the I think some early adopters were starting to understand this is going to be really big. there was a lot more resources going in to build the industry and it was really the perfect time to to jump in because it's not just that things were under a price but the field was really kind of complex and not well understood and that's exciting to me as an investor is to be able to tackle something that is there's no like framework for evaluating it like there is for say like SAS companies right like that's really established and you you have to figure out the best way to evaluate it yourself. And if you can do that, you have tremendous edge over all the other investors in the industry.

6:26 And I felt like we did that in in in crypto and DeFi back in, you know, 2019. And this was kind of very similar in the sense that it was so interdisciplinary. There were so many different kind of complex topics evolved in in robotics. You know, it's going to be a challenge to kind of learn about all of them and evaluate h how important each of the different I would say factors are in robotics development and in in building a company in the space and we felt like we could really differentiate ourselves and you know establish a foothold as you know one of the top robotics investors in the world right you know the timing is important >> that that that makes total sense but I I want to I want to dig in here because I think this is something that's really important especially for investors in general eneral and people that are looking at how how do I how do I even begin to navigate this world? You're in crypto, you're in DeFi. There's so many different industries that you could have gone into, right? You could have looked at space, you could have looked at AI, you could have you could have looked at robotics. There are probably some red herrings out there in industries that you could have gone down that didn't didn't pan out. I mean, like what what really drew you specifically because I think a lot of the things that you said could be said about space as well, but it's like were you watching like iRoot?

7:37 Like was there an inspiration moment where you're like, "Oh, like robot. Have you always been interested in in this?" I mean, how did you actually end up here? And maybe talk me through the process of that. >> Yeah, I wouldn't say like I was a super sci-fi nerd, but I'd always appreciated some of the movies. It it you know, I think space while it wasn't as hot as it is right now, it still SpaceX I think was starting to get proven already and it was at you know, a significant valuation and there was interest in the space. I mean, if you look at the total market cap of all robotics companies, private robotics companies at the time, man, it it probably was like $20 billion.

8:15 Right now, it's probably around 100 150, maybe pushing $200 billion. And XRP is is what is it's close to hundred billion. Poke the total market cap of Pokemon trading cards is around $50 billion. And so I think that puts into perspective really like how early we are in this industry that is, you know, I think it's going to be tens of trillions of dollars. And so the industry as a whole still has 100x, you know, potentially a thousandx upside remaining. And yeah, it it just I I would say that it it seems a lot more blue field and tangible as well cuz space is cool to look at. But I'm, you know, I don't think most people are going to ride a rocket ship. Maybe they will in 20 years, but robots are going to permeate everyday life and it it's going to happen, I think, a lot a lot sooner.

9:08 >> Yeah. I mean, what do you what do what do you think about that? Like what is let's let's say the world's 2035 or whatever year you think the the robots the robots are coming. But what what types of things are these humanoid robots doing? I mean, what how are they how are they contributing to to to this world? How might you and I interact with them? >> They man, they're they're going to do everything that humans are going to do in in the real world. So, they could be your uh you know, personal assistant. I think right now it's like pretty expensive to have a personal assistant, but if you can have a humanoid robot that costs say $20,000 for an economy one or $50,000 for a premium one, that is pretty costefficient. It especially if you know you're doing that as a onetime cost and maybe pay a little bit on an annual basis, but that can add a tremendous amount of value to people's lives. in in America, right? A good personal assistant could cost, you know, 40 50,000 a year for I would say like maybe like the lower end of the range.

10:09 And I've seen executive assistants go up to 200,000 400,000 all-in compensation. Uh but not just that, but you know, like you can have robots taking care of your your parents. That'd be amazing to have. Uh you can have robots working in factories. You can have robots driving cars. You can have Rob, even though we'll have autonomous cars, you know, like we're still going to have manual cars as well. Uh you can have robots working at hotels, at restaurants, uh and you can have them go on on the moon as well, go to space, right? And be in environments where it's difficult to have humans operated.

10:46 >> The the the first robot astronaut is like uh we're really we're really hitting in sci-fi now. I mean, this is this is crazy. I mean, what I I am I am sort of curious as to like what what are the types of things that you're seeing right now like the general state of the robotics markets. Talk to me about the top companies and what they're trying to accomplish. Uh you know what what are what what are they building? So I know you have you have investments and intronic you have investments in in figure. Uh like what what is being built right now? Is it everything that you're describing or are we starting a little bit lower? everyone. So there are companies that are building towards basically solving general purpose robotics. Um those are companies like Eptronic and Figure uh because they're focused on the humanoid form factor which is the most versatile which means they can go really anywhere a human can go and even more right to to space. Um, and then they're really exciting companies that I feel like are less hyped right now, but are going to be really giants in the future of industry because we've always had industrial arms, right? Like we've had automation, we've had machines, but the ability for them to be intelligent and not need weeks of programming and, you know, ten tens of thousands, maybe hundreds of thousands of dollars of engineering costs just to set things up. That that opens the space up for you to deploy robots and so many more applications around the world. And not everything has to be moving like a humanoid. A lot of stuff done in factories, they're stationary and so you can just have an industrial robot arm. And so, you know, standard bots, one of the key companies in our portfolio, they build mostly cobots, which are basically, I would say, smaller versions of standard industrial arms that can work safely among humans. and they build industrial arms and they also build some other types of general purpose robots. But they're they're general purpose in the same way that humanoids are. And so that is a tremendous market. And if I think there's going to be billions of humanoids, then there's probably also going to be billions of mechanical arms around the world. Uh whether they're there to make coffee or cook or to uh unpack things in a warehouse, that market is is huge. And if we, you know, think we're gonna re-industrialize America, we're going to start manufacturing a lot of stuff here that was formerly manufactured in in China, it makes sense to have a US-based industrial arm manufacturer. And there's only one uh that really exists at scale and and that's Standard Bots. Um there's a lot of companies uh and by the way, one at scale in America. Uh there are a lot in Europe and in in Asia, but it's pretty key to have one that is homegrown, vertically integrated, not reliant on, you know, China as a key component of their supply chain. So that's just one example of uh I think some of the other less hyped uh companies in the portfolio that could be getting a lot more attention in the future. Yeah, this is this is I think an an important an important point here.

14:16 It's like the the market the market seems to have expanded not just in terms of market cap but in terms of the the companies that are that are entering the space. I mean, if you go back uh when you first started, like how does how is the market I'm curious like how's the market shifted over the last two years? Are you seeing a lot more interest? Like are you seeing uh you know the your traditional VCs come in now and start to get really excited about robotics or is this still a a niche area that like are these companies raising easily now or is it or is it still hard for them?

14:48 Uh I would say that interest has really started to inflct the last three four months or so. Uh and the reason why it started to in inflect was because there there was this huge rewriting in software right there was like this huge wakeup call earlier this year that software businesses some of them were not as durable as we thought they were and the prospects for future software businesses um that are venture fundable right like that the perception of that changed significantly and so VCs whose you know the VC industry like software pores I would say like a majority of their investment interest and a lot of them had this existential moment where they were say they were like hey look if we can't invest as much into software where else are we going to invest obviously you know they were already looking into AI but robotics and physical AI started to become more of an apparent next stage for the venture capital industry you and people started to understand how big this market could be. There were a lot of concerns previously around, you know, capex costs, competition with China, um the ability for us to manufacture in America and just overall you know it it what VCs like to be a little bit hopping on trends and you know that trend wasn't established yet and and so that that changed right in the last few months and so we're seeing some uptake uptick in interest but I don't think it's anywhere near where it's going to what what it could be as in the amount of interest we have in AI companies right now like that that's the equivalent I think of what it will be in the next one or two years you're seeing that start to trickle into you know well basically every tier one VC and I would say like tier 2 VC is looking at the robotic space right now and some of that is like turning into term sheets at you know multiples higher valuation than these companies were raising at in, you know, just a few months ago. Um, but I think I think that's that's it's really going to accelerate.

17:01 >> That's that's exciting. Do you think do you think part of it's going to have to do with the actual capabilities of robots improving? I mean, I know at least from from my perspective, some of my interest has been the I think it was Figure that started live streaming the robots working and when I when I saw the humanoid robots actually doing things and you see videos out of China of like humanoid robots dancing and it it it just seems like the world is catching up to the fact that these things are actually happening. And I'm kind of curious like do do you think that like what have you seen cuz I'm sure you visited the factories.

17:37 I'm sure you've gone behind the scenes. Is is there stuff that you've seen that's like blown your mind yet? Like are we are we close? Like are there are these humanoid robots going to like are we going to see sports leagues with them? I mean what like what what have you seen that you find crazy with these robots? >> Yeah, I think we're we're pretty much at the GBT3 level of robotics in terms of intelligence right now. I I just think that it it doesn't it's not as striking or not as obvious to people because for GBT3 level of like um intelligence for you know LLMs it was wrong half the time and that's not impressive for a robot right for it to like pick up a cup like only accurately half the time and but it it means like we're getting really really close uh to to solving general purpose robotics. What what I what I would say is like some of the frontier models, what's really impressive about them is that they're generalizing a lot more. That that is kind of like the hallmark of like what you want to see AI models that actually work is that they can face environments that they've never seen before, right? Like you put it into a completely new home or factory that it's never been trained on and it can operate that in in the same way as if it was in the factory or home that it had training data on. uh or it's able to interact with new environments, right?

18:54 Like it's able to pick up a new package that it had never seen before. And I think one one of the I would say key capabilities of the AI models of the last few years was this concept of in context learning. The fact that you could say something to an LLM, right? And it would understand that context and then be able to give you an answer and then you would be able to have a conversation with it, right? as opposed to it forgetting every single time. That is right. We we're starting to get that in the physical AI models as well. And so I can show it an example of a simple task, right? Like put this uh uh item into a box. It's able to do that. That's that that's a really simple task. It's called pick pick and place. Uh we we can do that, but now it's starting to expand to more complex long horizon tasks as well. So meant you know tasks that might occur in factories like hey look put these items into a box package it uh and then take that box and then put it over there and and so the more complex these tasks get the more it can start to basically replicate um you know what humans are doing in in the real world.

20:11 Not only that there the the the more recent models are starting to show that they have the ability to memorize things internally or innately. Uh there is an example shown by ROA AI where uh they played the the shell game. So they had three cups they put a ball under one of the cups and they shuffle it around and they asked the robot to pick which cup the ball was under and who was able to pick that up. Um so a a lot of these kind of I would say capabilities or characteristics you you can call them emergent right as you scale up data as you scale up compute um these models are capable of more and more things that allow the robot to now function uh more like a human would be able to and and unlike a traditional robot which is very pre-programmed to just do one thing if any small thing changes right like I move this cup from here to here. It just doesn't work anymore. And so we're we're getting really close I think to the chat or the GPT5 of robotics. There are if we think about you know the time from 3 to five that was two years right I think it's going to be way less than two years. I think it's going to be something like a year and the the reason is because there were a lot of learnings from a research perspective going from three to five. It wasn't just scaling compute. It was learning about how do I best do RLHF? Uh how do I best structure mid-training? How do how do I find the best mix for pre-training data, right?

21:50 And how do I create infrastructure to annotate my data more effectively and efficiently? And so all these learnings, a lot of them h have been learned so far, right? We figured out a lot of these things and now we don't have to replicate all of them again. we can we can apply those to those physical AI models to compress that that timeline. And so robotics, I think AGI is is is is going to happen a lot sooner than people think.

22:19 >> So So are the I'm curious about the the edge that the these robotics companies have because you've talked a lot about the the intelligence models like are is is it possible that you know your your your your clouds and your your chachi of the world, right? If if they if we achieve AGI on on that front, then we can just hook them up to basically any old hardware. And so in that case, like where where does the edge where where does where does the edge remain in the for the robotics companies or or are they building like very specific models and you think it's going to be very difficult to translate them?

22:50 >> Yeah. You can't just like hook up claw into a robot and have it work. >> Yeah. So the the difference between LLMs or or or VLMs um and robot foundation models are that robots need to understand the physical world around them. And so you know traditional you know like opus right their understanding of the world is based on text. Imagine like you just had like a blind person that like could only like hear things and you know suddenly you gave them vision and they they had never moved around like they were a blind person that were like like had no limbs.

23:32 >> I mean this sounds this sounds like a really sad person >> and then like imagine you you gave them limbs [snorts] and then you gave them sight and then you told them to interact with the real world, right? Like it's it it wouldn't work, you know? they maybe they could be able to to figure out after a lot of a lot of you know like trial and error but it's not going to work out of the box like that and and that that I I make that analogy to kind of just like help you try to understand the difference between these LMS which only understand the world via text and robot foundation models which need to understand that needs to understand feeling right like I need to be able to understand hey look if I look at this I I I know if how much pressure I need to apply to keep it held and not drop, right? Um but just purely looking at it, I guess like you know some vision language models can understand that it's being held but they can't understand how much pressure I'm applying. And and so that is I think uh that's a human experience that also needs to be translated into robot models. And there's this kind of like this this semantic or this kind of like further semantic understanding that robots need to understand. Um if I just say like uh hey put this take take this cup and then put it on the drawer over there. It's it's not very obvious for an LLM. Uh like which drawer am I talking about? What do I mean? Put it on top. Right? And if I say say like I'm like carrying like a glass of water, I need to understand that like I don't carry it like this cuz the water can fall out, right? And so I need to understand physics as well. I need to understand the fact that if I interact with an object too hard, if I hit something, it might damage me, it might damage the object. And so that kind of understanding is not imbued in something like Claude. It it it that needs to be imbued into you know what robot models are you know what people are working towards for robot models today. For example, like if I'm picking up a bottle, how do I know if I should pick it up with one hands or or two hands, right? Like, but the bottle gets big enough, I need I need two hands, but like at what size? Like, does that make sense? And like we there's a lot of that intuition in in robotics research, they call that prior or affordances, right?

26:00 That we take for granted as as humans. And some of that we're born with and and some of that we learn as we grow up that robot models also need to learn. Uh, and they need to be able to learn by themselves as well because there could be new situations that we put in them into that, you know, we haven't even thought about that they need to be able to adapt to like humans can. Um, that's kind of like the next level of of of robot learning.

26:23 >> It really seems like you've done I mean you've done clearly like a ton of work to un to understand this field. And I think a lot of our listeners right now the these these are people that are thinking how do I like how do I allocate my money? How do I invest? How do I spend my time? uh most of our listeners are are investors or traders uh and and they're in the markets and I think you've done maybe one of the most impressive jobs of coming up to speed on a new industry that I've seen in a very long time and I'm curious as to like your approach to understanding robotics.

26:59 I mean once you decided, hey, I'm going to go invest in this thing. How did you even get up to speed? Are you getting on the phone? Are you calling people? Getting on the phone with them? Are you reading books? I mean, you can't really read a book on this kind of stuff. Or maybe you can, but I'm like, what was your process for becoming what did you know, now you're one of the world's experts on on this industry? You you've you've invested in a ton of different companies and and you're very close to the ground. And basically, how how how did you how did you get to the place where you can just talk to me for 27 minutes so far about robotics?

27:32 >> It was like pure obsession, right? Like for the past two years, it was like the only thing that I've thought about from day to night. uh you know, weekends, etc. There's just no days off. The only t time I take off is I, you know, will surf a few days a week, you know, work out a little bit. >> Well, I mean, I assume you'll be able to socialize with the robots at some point. That's part of it.

27:51 >> Yeah. I I I I I just talk to Claude. That's just that's my primary uh point of contact with another being. Um [laughter] which is really helpful by the way to answer your question like in terms of understanding some of these concepts. Yeah. like there's a lot of experts that you know like we've become friends with you know founders really great researchers but I don't I don't want to bother them all the time um and so but like man like if you go through a paper right like there's it can seem really daunting because there's so many technical concepts but now it's just so much easier because I don't need to read a textbook I just tell it what I don't understand explain this to me explain this concept to me um like what are like you know how is this application how's this experiment done like why is this model architecture architected in in the way it is like what are the trade-offs with other model architectures and it's just like I think a key part of investing is honing in and focusing on like what you don't know and identifying those kind of like unknown unknowns and filling that that gap and it's easy to be like hey I don't know something uh forget it um or focusing on what you do know. But I think it's really important to become the best investor that like you you you know you have vision everywhere and um you know I can try to figure that out as best as I can. I think I've done a decent job over the last two years but then nothing replaces decades of experience as well. And so that's why we talked to other experts in the field and why we've built a team at Robo Strategy that has robotics experience across a lot of different domains. Um, and so, you know, for example, Scott Walter on our team, he's had 40 years of robotics experience.

29:40 That's more experience than some teams that we've talked to have. Um, you know, he's built two companies and sold both of them in the space, the last one to CUKA, which is very large robotics company. And, you know, he's had clients across aerospace, across um, consumer goods, across a lot of the areas in the physical world um, that robotics are going to be applied to. and he understands, you know, like the pitfalls and the things that we should be paying the most attention to. That is like a key part of investing as well is like, man, there are thousands of variables that you could look at which are important and and and which are not and how do you weight the importance of each? Um, it's like you you you have to create this mental model over time which is not simple and there's no textbook formula for it, right? It's just you do it through um experience and and and debate and going down really deep rabbit holes of thinking well you know if this happens well what what are the outcomes for the company and doing that across like a thousand different I guess like lines mental exercises if we're if I were to zoom out a little bit more like investing at the end of the day I think to like from a first principles approach comes just comes back to how do I analyze the riskreward of something which sounds really simple but like you know two different people can come up with like widely drastic estimations of risk and reward for a specific investment or specific trade, right?

31:18 Someone can think there's a 99% chance of something being successful. And someone can think there's a 1% chance. And someone can think, hey, look, the risk is, I don't know, I lose all of my money. Someone can think like 50% of the time I lose all my money. Someone can think, hey, look, I lose 20% of my money um you know, a tenth of the time and then 50% of my money uh a quarter of the time. And so, I mean, you have to think in probabilities, right? And to think in probabilities, you have to understand all the different scenarios that can play out. And to understand all the different scenarios, you need really deep industry experience and just like thought that's put in uh into what what can happen. Uh and then to do but to do that, you have to also understand it's it's kind of like this meta thing.

32:08 You have to understand your own understanding of the space, right? because I if I overestimate my understanding of the space, then maybe I won't dig in it enough and I and I will have a wrong estimate of what the real riskreward of this investment is. >> How do how do you check yourself on that? I mean, if you like making sure you're not you're not overestimating. What what's your what's your approach to that? I mean, do you are you surrounding yourself like with with people that are arguing with you? I mean, like what's your what's your process there? We're we're but our culture in as a firm is just like very truth seeking like very reality seeking like we try not to be dogmatic. We can get very high conviction about certain investments but only because like we've thought it through so so deeply and talked to so many experts and done our due diligence.

32:55 How do you not overestimate yourself? I I think it's like maybe having like a little bit less of of an ego. I mean we we all have egos. I I I definitely have you know ego. I I think just prior prioritizing truth gathering I would say helps with that and also just like constantly trying to understand what can I be missing what perspective am I not seeing where can I be wrong and like if you've maybe like validated like five different avenues of like where you could be wrong and it turns out hey I'm not wrong uh maybe the market's wrong uh then like that for example That's I think that's what happened with with figure AI. Uh okay then then I can feel like a little bit more comfortable about my understanding of investment and where it's going to go. But that is really important. I think like maybe a lot of investors o overestimate their knowledge of the field. So you just have to be really really obsessive and turning over every single stone that you can.

33:57 >> That makes sense. And I think you know you your process obviously led you to a really great spot. You were very successful in crypto. Now you're now you're uh venturing into new ground in robotics. I want to talk a little bit about how you actually are supposed to invest. So I mean we basically talked for 30 minutes about what the opportunity is. The opportunity is clearly clearly massive. And now the question that's probably on everybody's mind is how do I actually invest in robotics?

34:26 All these companies, all these companies are private. Uh, and you seem to have come up with some solution to this. You launched a private, you launched a public company called Robo Strategy, uh, which now trades on on the on the NASDAQ that basically rolled up your investments that you had privately uh, into a publicly owned vehicle so that so that people could buy it. And I want you to talk if you could a little bit about how you decided to do that because most people I think would just want to basically hold I mean why why why are you letting other people buy your portfolio out now if you think this thing is going to the tr trillions you know like what what was like how how did this all come about?

35:09 >> I think it's going to be really hard for people to make their own decisions in investing in the best robotics companies. um it's going to be near impossible I think to do it to the same level of excellence that we're doing it at because we have a team of robotics experts and this is all we do day in day out. Um not just from experience point of view but also the network that we've built in the space to be able to diligence everything from you know talent internally to supply chain. You know are these companies really ordering as much as they say they're going to order? Do they have those relationships?

35:47 You know, because you know, founders, a lot of them are great at giving pitches, but maybe not all of the claims can be validated all of the time. And uh you know, maybe someone looks really great on paper. You know, they have PhD from so- and so university, but like uh from like in operating with within a company, maybe they're not the best person for that. uh and it won't turn translate, you know, like there could be, you know, hundreds of hours that go into diligencing a a large investment. Uh and that doesn't even include kind of like the cumulative cumulative experience that has kind of taken place. And you know, like we're going to be able to talk to customers that uh people aren't going to be able to talk to to see, hey, look, are these robots really is performing as well as the company claims? Is it are you really going to be buying a lot more robots in the in the future? That that's why we built the firm is because I couldn't do it alone, right? No, nobody can do this alone. And that will result in better decisions being made on investment choices and uh you know sizing of the investments.

36:58 There there's a lot of what is it? I think people that are trying to cha chase some some of the hype a little bit and you know we hear about some of the investments that are being made and it feels like people are trying to play catchup a little bit right and they're trying to find hey look I want the next figure AI but it it just they don't they haven't seen or maybe like thought too deeply about all the ways that it can also not work because robotics is a really hard industry and even though there's going to be a lot of winners there I mean there are going to be some really big winners uh still undecided how much breath there are there's going to be like how many there's going to be a lot of failures right there's going to be just in in venture investing and startups in general there's going to be very very high failure rate and so going back to your question why why why did I decide to start robot strategy instead of continuing to invest privately is because you know I started talking about these robotics investments on axe and I I probably got over a thousand DMs and replies people asking had we get exposure to space and what companies should we be buying, right? And in the in the public markets, it's really just Tesla, maybe like one or two other companies. And Tesla's two trillion market cap, I think it's going to do great, but all the exciting stuff and I think there's going to be trillions of dollars of value creation happening in the private markets and just most people won't be able to get access to that.

38:25 SpaceX, Anthropic, Open AI, they're going to a trillion dollars plus before they're going public. And look, my primary goal is winning. It's not like I'm an altruistic person. I, you know, like my primary goal is I want to give everyone access. I think that's a really nice that's a really nice kind of like um maybe factor in terms of like what we're building. Um and it's important right for making robot strategy work is because the unique value that we provide is that in the public markets if you want exposure to this growth that's going to happen in the robotics industry from maybe like hundred billion dollars to tens of trillions of dollars there's no other way to get it. And for us, we always focused on early stage investing at mechanism capital because that's where we felt there was the most asymmetry and if we took more additional capital, it would dilute our returns.

39:19 You saw with open AI and anthropic that now the power law can really apply and we believe it's going to apply for robotics as well. I mean, I think the economies of of scale is a really significant factor because if you don't have scale, it's going to cost you what, like 500,000 a million to produce a robot just from a bomb perspective, right? Not just from like the R&D perspective. Uh whereas if you have scale, you can produce it 90% cheaper.

39:44 understanding all of that that scale is important and power laws are going to apply like we're going to be able to put tens of billions of dollars to work in the entropic of robotics because there's going to be a multi- trillion dollar winner and it's going to be very high risk adjusted return and be previously you look at growth stage investments you know you're targeting maybe 20 25% right >> and now I think it's reasonable belief like even if something to a billion dollar valuation multiply by a billion dollar valuation. I can target 100% year-over-year with maybe like this the what I would consider a very similar amount of risk.

40:26 It might not be the same. It might not be the same underrated risk from a different investor that doesn't understand the industry as well, but from somebody that understands how this might play out in all the competitive factors and whatever, like I I can get a very high amount of comfort with some of these later stage companies that maybe they're not selling billions of dollars of robots yet, but I have a strong belief that they will in in in the future and they're going to be able to scale that to very very high numbers.

40:58 Uh, and and so like how do I get there, right? I mean, we could do it in in private markets, but it's like we tried really hard, maybe we can get to a few billion dollars, right, within a year. And but that's not really interesting. Like if we're we want to do this and we've built the best investment team in robotics so far, I want to do this at tens of billions of dollars of scale. Um, I I think the market opportunity for an investment fund like this is actually in the hundreds of billions at least for now, maybe more in the future. And the public capital markets, Elon says, right? Like it's 100 times bigger than the private capital markets. And just traditionally VC has never been done like this before, you know, and there's a variety of reasons for why, but I think the time is is ripe now to essentially invent an entirely new type of venture capital model that benefits both public market investors and also the fund managers as well that can scale in a new way. Yeah, I want to I want to also there there are two there are two things that I want to make sure that we hit on and number one is you name this thing robo strategy and it seems to be an illusion to micro strategy in a way and there there are a lot of these SPVS out there that have been trying to go public and and you just buy a piece and they have high fees but you're doing something different right with the structure and what specifically is different about your structure that you think is going to be accreative it's you're you're uh You're you're running in some ways the Micro Strategy playbook, taking the good and leaving out the bad, right?

42:34 >> I think our Micro Strategy was definitely I would say an inspiration for our model, but they were actually not too different from some of the other similar models that have existed. They basically took like the private equity model, right? The private equity, the public company rollout model, and then applied it to Bitcoin. How that works by the way um is you have a lot of these big companies in every sector. One example is Transdime. Another example is constellation software where they focus on say you know for transdime it's aerospace supplies. uh for constellation software it's you know software and in public markets they trade at 15 to 40x multiples and for smaller private companies that are in the same sector they might trade at 3 to 8x multiples right because different markets price the same ass they can price the same asset differently because you have a different set of market participants and so what they do is they their whole strategy for growth is predicated on M&A I buy this private company right maybe I spend 100 million once it's on my books, it rerates immediately to 400 million.

43:42 And so it is immediately accretive and you know if I have a reasonable enough cost of capital, I can just kind of do this on repeat over and over and over again instead of right like relying on maybe organic growth within my existing companies because I feel like that is maybe like a little bit of a harder lever to play to play growth in. Um and so that's that's kind of what Micro Strategy did, right? Um and I guess the the difference was for Micro Strategy is that there there was a big access issue and so people bought there's a huge demand for it the stock because people wanted exposure to Bitcoin and they couldn't get it in the public capital markets right people have restrict even though you can buy on Coinbase a lot of funds institutions investors they have restrictions and they can't access it um and so they buy Micro Strategy for exposure uh and then even after the ETF came out I I thought the premium would collapse, right? But it it still stayed really strong for a while and they were able to issue billions of dollars of more equity because man that turns out that capital base that has these restrictions is really really large, right? These RAS and Diamonds, pension funds, etc. If we think about access as really the primary demand driver, that issue is multiplied to thousandx for private robotics investments, private venture investments in in general, right? really only, you know, this select group of venture capitalists and sometimes their networks that invest in these SPVS that can get into these deals. And I think for robotics, it could be even more constrained if we're really successful because, you know, maybe like we'll be the primary financeier of a lot of these rounds. And not only that, but Bitcoin we think about as like the TAM for micro strategy, right? The TAM for robotics is going to be multiples. I would say an order of magnitude larger. The Bitcoin market cap right now is is below 1.5 trillion. Amazon's larger than that.

45:40 Nvidia, Apple, Google, they're all larger than that. You know, AI is going to be as well. I don't I think it's very fair to say robotics can be as well. And so, not only is do we have a better selling point um because of really like there's no other avenues for the public markets to get exposure, but we have a larger market as well. And so I I think we could be larger than micro Azure at their peak market cap was around 100 billion. I I'm reaching for something that's more like SoftBank scale uh in the in the hundreds of billions.

46:10 >> You you you you heard it here first. Andrew Kang is going to build Soft Bank part two but bigger. I mean that's that's >> essentially a close-end fund, right? >> Yeah. I mean it's true. It's true. I mean and so but in in order to do that you're going to need to expand past robotics at some point >> or do you don't I don't think so. Why? Well, I mean, >> you you you you think that you can capture like a size of basically I mean, let's say let's say the the robotics market goes to 10 trillion. Like, how much of that market do you think you'll be able to capture?

46:40 >> Well, 10 10 trillion is like what, like 7x the current Bitcoin market cap? >> Yeah. >> And so, Micro Strategy market cap times seven, right? Like that's already in the hundreds of billions. It's >> true. >> Um, and that's without like the increased access, right? like there's so many avenues for people to buy buy Bitcoin. Uh and then you you asked earlier about like what what are we what concepts are we taking in? We're taking in the accretive issuance as a way to scale and to have a second engine to generate shareholder value, right? To increase our NAV per share. What we're leaving out is is the leverage part of it. Um we're not going to do um preferred shares. uh we think there's a huge amount of uh upside in our underlying investments because of how early it is in the market and how much we think that the industry will continue to expand and so if we use leverage it will be very very selective and you know we'll probably not have it on the books for very very long that I guess that's that's maybe how you would compare our our models um and I'd love to talk about the creative issuance part because I think that is maybe really underappreciated. People look at the premium, right? And they see it as something that is bad. That is I I think that's missing the picture because yes, the premium adds extra risk because if the premium goes down, right? Then it you know it compresses from say 4x to 2x that is a 50% loss in market price. It can also expand if demand increases, right?

48:22 um or if say the market is pricing in something that is not within the the NAV because uh the NAV um you know how it works is it looks at the last round valuations um and sometimes there's a discount if say we have series B shares as opposed to series C shares um but doesn't take into account hey look the you know if a company is going to do a next round very soon or there's this major milestone or a huge amount of growth that is not encompassed in NAV but you know the public markets they price these things on a more real-time basis but in terms of a creative issuance right like traditional venture fund they drive their returns based on the underlying investments if we're able to manage the the premium well we can have another engine for growth for the fund which is what we talked about earlier for this the private equity micro strategy model they they call it in their world uh multiple arbitrage, right? Private public company arbitrage, earnings arbitrage, it's the same exact concept applied to venture capital. And so say if there hypothetically if we go through a bare market and there is no markups in our portfolio um and the value of the companies from a nav or from like a mark perspective stays the same for 6 months a year if there is a premium that is held right at say 3x 5x whatever and we're issuing shares at that premium um that can increase the NAV per share.

50:05 If we do it at a discount, that would decrease the NAV per share. On the other hand, uh from a regular peri perspective, we're not allowed to do it at a discount, nor does it make sense for us to do it at a discount, nor does it make sense really for us to do it at, you know, uh 1x or a very minimal discount because we believe in the value of the portfolio, right? And as the largest shareholder myself, my incentive is to maximize shareholder value. And so we're going to be very thoughtful in terms of how we raise capital and do share issuance in a way that is maximally accreative for shareholders.

50:46 >> I think that makes sense. Also one one one point that I've always found interesting about this this discussion and then I want to talk about the specific companies as as we as we wrap up but it's that it's like as as these companies become as robo strategy becomes bigger or mic not necessarily micro strategy because Bitcoin's a large liquid market but any uh private holding vehicle that goes public that actually at some point might be setting the price for the underlying assets because these things don't are not trading 24/7 right so like if people are willing to pay 2x for your nav, maybe these companies are going to raise like a 3x in a year or two years anyway. So, it's like people are just pulling forward that price appreciation. So, it's like that might actually be the true price at that point, which is what I'm trying to also like wrap my head around.

51:32 >> It's it's possible, right? Because I think if you think about Bitcoin NAV, right? Like the way Micro Strategy looks at it, they're valuing their NAV based on a liquid asset that is trading real time 24/7. And basically it's it's a public market asset for us, right? We invest primarily in private market assets that are not trading 24/7. And if they went public, it is possible that they would trade at at a different price. They could trade lower, trade, they could trade higher.

52:01 >> As we as we as we as we uh wrap up here, I want to get like a rapid fire of all the companies in your portfolio right now, like the 30 secondond pitch for each one and why they're in why they're in your portfolio. Okay. Yeah. So, a figure AI, I think, is the Tesla of this, sorry, not the Tesla, the Apple of this generation. I mean, like we, if you just look at their videos and the robot that they design, I think it's really clear that they have tastes and style that I haven't seen from any other like robotics company out there. Uh, definitely not the the the Chinese ones.

52:36 not not to dunk on them per se, but you know, like those look like pretty industrial cookie cutter, but I think like what's beautiful about Apple is they made a product like so thoughtfully um w with like design and and user experience in mind to a level that nobody else was doing. And it's like a beautiful experience having an Apple that that was was kind of like what they focused on. I think Figure has a very similar type of DNA and you can see it in the cotton that they put out. And if I have something in my home, like I want it to be awesome, right? And I want it to be perfect and I want like and people are going to be maybe I'm inviting people in my home. I want to be proud of that. And like having like an iPhone, right, at some point was a little bit like a status symbol. And I think you're gonna have little that same thing happen with robotics as well.

53:28 Um, and you know, obviously I think they're going to be [snorts] able to execute on on that vision. They have the technical chops to do so. You know, I think they're I would say like the next best maybe like a year or two behind figure playing in the private markets for humanoids. Um, they were one of the earliest innovators of humanoids that are out there. They built the prototypes for some of the biggest humanoid companies that we know today. and they have a lot of experience in power design and manufacturing which some people might perceive as simple but you know Elon has said you know manufacturing like Tesla for Tesla was 100 times harder than design for it and so that's underappreciated right because they they have a partnership with Jable um you know one of the huge large scale hardware manufacturers in America and they also have a partnership with Google DeepMind which is I would say like one of the leading AI organizations in the world and has been working on robotics for more than a decade. We have standard bots. We talked about them previously. I think that they're going to be really an industrial giant in America. I mean, they're they're going to power basically, you know, the re-industrialization of of America. Um, and they're vertically integrated, which is really important. So, I I think like that company is important to the American government and the American people for that to succeed. We have Dino Robotics.

54:57 They are one of the best robot learning researchers, robot learning research groups out there. Uh especially in the field of post training. And so they were one of the first companies [snorts] that were able to get these robot models to perform at 99.9% um success rate. Uh and that's what you need, right? To be able to deploy these in the field. It can't be breaking or not working like 5% of the time. It can't even be messing up 1% of the time.

55:23 That's too much. like you can't have a human like intervene every hour or something like that. Uh that's the the goal of these robots is that humans don't have to intervene ever. Um and they're also building their own hardware platform which is pretty differentiated as well. Dax mate. So they're taking an approach where they're kind of working towards the Unity of America. I used to be skeptical about the unitry approach because you know the the hardware wasn't it's not good enough to be used in a production setting. Um, but it was really great in the sense that for their business, they were able to sell thousands of robots last year and they will sell many more this year. And they were able to build a developer mode, right? Because it was really like the only uh commercially available humanoid that was out there that, you know, could people could buy uh, you know, really conveniently and that was at a reasonable price. And there's a lot of research labs out there and you know I guess entertainment firms that want robots. And so if we think about like what's needed in the robotics world, we need to do a lot of research. We need to do a lot of development. We need to collect a lot of data. And to do that, you can't do it on a screen. You you need actual robots to do that. And so Dexmate is the first company in in the US to have commercially sold uh humanoid robots. They they sold first wheeled version last year and you know they were selling to basically all of the major US research labs and some big companies and they're going to be launching uh you know a legged version pretty soon. Uh I think that's later this summer. And what people I think don't understand is that robots are going to be a platform in the same way that the iPhone is a platform.

57:16 People are going to be able to develop their own skills. Uh and so you can think about it as like there's this developer economy that's going to form. And that's what made smartphones so great, right? because they didn't just have all the experience from everybody at Apple, but they were able to take it from everyone that was creative and smart in the whole world and make the iPhone more useful for everybody. And that's what's going to happen with robotics as well. Like I'm going to have somebody create maybe like a skill to have my robot to be able to cook as well as Gordon Ramsay.

57:47 >> I mean, that would be that that would be pretty nice. >> To do that, you need to have your robot that's commercially available for people to to do work on, right? And not everyone's going to develop their own robots, their own hardware, and their own manufacturing. That's really hard. You need you need somebody else to do that, right? And I think that's a that that's a really great business model that is underappreciated and not many other companies are currently focusing on in America.

58:11 >> Maybe maybe maybe we need to do a part two to this podcast cuz I have like an infinite amount of questions to ask you and I feel like we we only scratched the surface. But unfortunately, that's all the time that we have for today. So Andrew, I really appreciate you coming on. This has been an incredibly enlightening conversation. I know our listeners are going to love it and uh we'll we'll be live with this soon.

58:34 [music] [music] Nothing said on the ThousandX podcast is a recommendation to buy or sell any investments or products. This podcast is forformational purposes [music] only and the views expressed by anyone on the show are solely their opinions, not financial advice or necessarily the [music] views of 1KX media. Our hosts, guests, and the 1KX team may hold positions in the company's funds or projects discussed.