Transcript: How Are Investors Navigating the Wild Frontier of Robotics Startups?

[00:00:00] Start

[00:00:00] Brannon Jones: So that's exactly what we see happening for deep tech over the next 20 years. It's such an exciting time, in my opinion, for deep tech, because the rules are still unwritten for deep tech. So if you and I were making PayPal in the 90s.

[00:00:14] Audrow Nash: It’d be so much easier now.

[00:00:17] Brannon Jones: It'd be deep tech back then. Right? We need a full team, we need scientists, we need researchers.

[00:00:23] AlleyCorp Overview

[00:00:23] Audrow Nash: So now we are recording.

[00:00:24] Brannon Jones: Alright. Well, thanks so much for having me. My name is Brannon Jones. As you mentioned. I'm an investor at AlleyCorp on our deep tech team. In AlleyCorp’s early stage venture capital firm. We're headquartered in New York City. Generally were pre-seed and seed. Maybe a little bit of series A stage of companies where we will invest. But we'll come in at the at the earliest round. So you have to like to be the first check. And everybody in our company, regardless of which specific vertical they work on, has an operating background. So we really feel like we can one lean and be helpful. But to even just sympathize with the with the founders, on a personal level. So, I've been in AlleyCorp for two years now. As part of our deep tech team, we have four teams in total. So three other teams, so deep tech. We have our diversified investing team, which will handle the majority of our software investments. In kind of sector agnostic. We've got our healthcare investments and then we've got our economic infrastructure team that we are fourth team. And they focus a lot on workforce development. A little bit of food insecurity, education technology, things like that. So, yeah, that's us in a nutshell. Started as the family office of our CEO, an entrepreneur named Kevin Ryan, long time entrepreneur in the New York ecosystem. Actually, many decades, career marked by success, in the entrepreneurial sphere. Started out at DoubleClick. Sold that to Google, founded MongoDB, founded Zol business insider, jock group. It's, there's that that I'm sure I'm forgetting yet, but a lot, a lot of success. And in many ways was one of the earliest people in in tech in NYC. In some, I mean, won an award as the godfather of tech in NYC last year at the kind of this Tech Hall of Fame thing. But actually it reflects and hearkens to our name AlleyCorp. So it takes the name from back when they were coining the term Silicon Alley to be the East Coast counterpart to Silicon Valley, which was happening in the West Coast. And this was all happening a few decades ago when he was doing, he was doing Double Click, and he was trying to bring tech talent from California to New York and convince them to come here and say, hey, things are happening. It's happening now. It's exciting. It's we got this big billboard, it's Soho, and put it out and said, Welcome to Silicon Alley. And wanted to coin that term. And, and that's actually, how when the term Silicon Valley came about. But it's the roots of our name, Alec Corp. So, that we what we call the fund, because of that.

[00:03:10] Audrow Nash: Hell yeah. Awesome. So a lot to talk about there. What do you think of the New York tech scene in general? Like, I'm not too familiar with it. I'd love to hear what you think about it, how it's going. I don't know. How is it in general?

[00:03:26] DeepTech

[00:03:26] Brannon Jones: Yeah. New York tech scene. I mean, I was going to say pleasantly surprised, but I shouldn't even be surprised. I would just say pleased. It is growing. It is growing in terms of people is growing in terms of productivity. We are adding jobs. So the tech scene is actually growing very fast in New York. And, and according to some measurements, like one of the faster growing ecosystems, I always think about the New York and East Coast tech scene from the deep tech lens standpoint, of course, because that's where I invested. Maybe I should also pause and say what I actually think deep tech is. Sure, because people always ask me that. But, broadly speaking, it's kind of science based innovations. And we think of it we what we call deep for us is robotics and aerospace type startups, advanced manufacturing. And then finally, a little bit of energy energy transition. And we really picked those areas because again, we have operator background. Those are the areas where we have experience. So my background was as mechanical and aerospace engineer, as a roboticist. Then I was at SpaceX. I worked in both the Falcon program, which is our legacy program, watching him landing rockets. And I worked in their R&D program, Raptor as well. It was building robotic factories to build the first versions of, of Raptor, which is the primary engine for their Starship vehicle, which at a minimum is going to dramatically expand rideshare access to space for people who want to send satellites up there, but eventually will also be the vehicle that takes humanity to, Mars and beyond. So, that was a lot of fun. Then from there went ran my own startup, both a hardware startup and an AI software startup, and then business school and then after that, Alec caught.

[00:05:22] Audrow Nash: What was your hardware startup?

[00:05:24] Brannon Jones: So if you was in the fitness space. And so we were making you were using thermoelectric to make ice packs, and, the CTO had come up with, novel way to rapidly cool. That was it, fan based. So you'll see, like Theragun or Hyperice that got these fan based cooling systems that you could wrap around a needs like embedded into a knee wrap, but we had a thermoelectric way that could get much colder, much more able to control, and so you could go ahead and set your whole routine 20 minutes normal, 20 minutes cold on and off. And you could have a raft and it could be much colder. So I was running, PCB design, for them. For about I was with them for, for about five months. It was, it was, pretty cool. A lot of fun. Yeah. Quick, quick stint. That one. Yeah. There were some other team dynamics that I think made it maybe, a place where I wasn't sure for how long to to stay around, but it was it was really fun. And a great experience.

[00:06:26] Audrow Nash: Yeah. Sometimes startup are chaotic, for sure. Okay, so we've talked about New York. Tell me, so you've mentioned a little bit of your background. What what did you so are you a mechanical engineer by trade or what's your trade.

[00:06:40] Brannon Jones: Yeah, mechanical engineer by training mechanical and aerospace. Technically I studied that at Sweden. And basically really specialized in robotics. And so that's what I was doing there. And then that's also why it kind of made sense to be implementing robotic factories at SpaceX. And actually, speaking of Princeton, makes me want to say one more thing about your prior question with the New York ecosystem, which is that from the deep tech standpoint, yes, California has the most density in terms of deep tech startups. Boston, like deep tech per capita, is maybe number two. But New York is coming up really fast at number three. And this when originally. Right. That's the that's normal response. You're kind of a little bit a little bit surprised by that. But actually when you think about it it does tend to make a lot of sense. So of course what everyone thinks. Yes, we have a very mature capital stack here with so many funders in the ecosystem, in a very mature financial industry. Secondly, we have some of the top deep tech institutions in the world right nearby. So again, I was Princeton, new Jersey, right across the water. And you've got Yale here, you've got NYU here, you've got Columbia here. You've got Carnegie Mellon down the way. I don't know, we could kind of co-opt Penn into that space. And so you've got really a nexus of really high caliber institutions that, put out great science. So that's number two. Number three is just the pure diversity of New York, one of the most diverse cities in the country. And then, of course, it's also dense as well. So because of that, talent wants to be here. Talent is here. You can find what you're what you're looking for it. And then finally, because kind of the political capital the city has, it's an important city. It's one that sets many dreams, both culturally but also from a regulatory standpoint. So all those things kind of come to make this confluence that actually makes it makes sense for there to be tech startups. And I think there should be more deep tech startups here in New York. I think that's one of the reasons why we will continue to see more. And actually people forget New York has a really deep legacy of of deep tech, actually. So the electric grid invented by Thomas Edison here, the first industrial robots were installed in Trenton, for GM building. Building cars, Bell Labs was about semiconductors and telecom right there in person. There was lots of aviation. Some of the first flights happened on Long Island. And there's a bunch of other industrial stuff that I'm even forgetting. But New York has such a rich legacy of contributing in extremely important technologies, I think semiconductor to to the world. And so it actually makes sense to see some of this resurgence in deep tech here in New York City. And selfishly, it's one of those opportunities where you come to a major city and there's an awesome ingredients for an area and a community that actually hasn't really been cultivated or, really brought to bear in a way. So we had AlleyCorp want to be some of those people to, to, help bring up that deep tech community here, here in New York.

[00:09:53] Audrow Nash: Okay. How do you so when you say New York, do you mean like Manhattan or the surrounding areas or New York State? Because like when I think of Manhattan, I think very space constrained. And that to me doesn't necessarily scream deep tech. Like you can have a lot of the design and coding and things like this. But how are you thinking of this?

[00:10:14] AlleyCorp’s Reach

[00:10:14] Brannon Jones: Yeah, to be fair, I do think we think about it more broadly and holistically. Certainly the nexus of talent is is here close to Manhattan or in Brooklyn. But upstate New York does a lot. There's a lot of agriculture, there's a lot of shipping, there's a lot of ports, tons of transportation. A majority of it actually comes down there, through there to actually get into Manhattan. And so, new York State broadly, but even that kind of tri state area, I, as I sort of mentioned, in roped into this whole northeastern, area, really center to round and ground anchored by New York. But it could be kind of tiny, dispersed even into new Jersey. There are some more industrial areas, and we have some of our companies who find a lot of their work there, either in construction or otherwise. Manhattan itself has some pretty unique, pretty unique characteristics that could make it make sense for certain deep tech companies. But I do agree, like at the macro level, it probably would involve, some of the surrounding area. And I think that's a great thing.

[00:11:14] Audrow Nash: Yeah. Okay. Hell yeah. So at AlleyCorp, are you primarily funding New York based companies or are you guys funding companies all over the place, or how does this work?

[00:11:27] Brannon Jones: Yeah, so we are geography agnostic. We end up funding a good number of New York based companies because we're here, boots on the ground in those ecosystem, hosting events for the scientists at Columbia and NYU know them well. So they come to us first. We've got a great relationship now. But again, that's not that's not prescriptive and probably half of the investments in our deep tech portfolio are actually on the West Coast. But we've even got some that are there outside of the outside of the US. And that's and I wouldn't be too abnormal for us. I think one of the things we try to prioritize, especially early, like being an early investor or an early stage investor, is that we want to invest somewhere that we can get to want to get to because we want to go there. We want to see the tech, we want to be helpful. We want to know the team, that we want to have that relationship. Those things make the difference. In early stage far more than than in late stage. So, yeah, probably 50% of them on the West Coast. The rest are scattered or throughout the East Coast. But we've got some in Boston, we've got some here and otherwise.

[00:12:32] Audrow Nash: Okay. Hell yeah. So when you talk about making, like growing the New York ecosystem, it's like you're going to events, you're going to the universities. This kind of thing, and they talk to you first. So this is like a good way to help New York become more of a deep tech place. Is that fair or what do you think. Yeah.

[00:12:53] Brannon Jones: You know that's absolutely right. It's a good way to make deep tech more prevalent in New York. And it brings it to be top of mind because again, all the ingredients are actually here already. It's just we want to stir people to action and to give them that impetus to actually take those steps and some of that is, is training knowledge pathways, access into entrepreneurship for scientists, because it's actually pretty challenging to navigate the world of entrepreneurship. Oh, totally. If you're a PhD, post-doc industry researcher, I even think about myself as an engineer in industry and just understanding the way into entrepreneurship. Yep. It's pretty ambiguous. So some of the things that we'll do just to, to, to be practical about this is like we would even work with universities to sponsor research at a lab and say, hey, this research gets to a certain location, certain like milestone. We would spend this out, we would help start up this company. Because I guess I should say this at the beginning. AlleyCorp is also a venture studio, part of that DNA where what does it mean?

[00:14:00] Audrow Nash: I don't know what a venture studio is.

[00:14:02] Brannon Jones: Yeah, absolutely. So Venture Studio is a firm that will also start new startups from scratch. So we'll come up with the idea. Cool. Like a professional team, professionally starting new startups from scratch. And that that comes from, again, the legacy of Kevin Wright. I mentioned because he started MongoDB from scratch. He started a business, started Gill Corp., He started all these companies. And so we've got a really strong muscle in terms of how do you start a company in many very disparate industries? How do you start a company and make one that's successful? What do you look for in a founding team? How do you run it at the beginning? How do you get yourself set up? And so that is one of the things that we do pride ourselves on. So when we're talking about nuclear dating, the deep tech industry here in New York City, one of the core ways we do that is interacting with all of those great resources that I mentioned to say, hey, can we bring them together? And rallied around an idea, a technology, a team, give them the funding they need, give them the infrastructure they need, give them business plan, support them, as a firm and let those teams go in and build companies and be really successful. So in deep tech in particular, some of the ways that's looked has been through the through the universities, as I mentioned. But that I think is a is a key piece of building the, building the ecosystem, as well as drawing awareness, to, to the ecosystem. And as we continue to see winners, great companies that are built and funded in New York City and in the area, investors will begin to understand what that looks like, begin to be able to really intuitively, understand how to invest in those companies, get excited about them. And, and of course, we want to be the champions and, and biggest cheerleaders for, for that wave.

[00:15:43] Portfolio Highlights

[00:15:43] Audrow Nash: Yeah for sure. So I think let's see, we talk about a plan at the beginning. I think I want to pivot just a little bit. And what I want to do now is talk about some of the portfolio that you guys have. And then what I'd like to do from there is just ask a lot of questions about the investment climate and your perspective, on investing in robotics companies and a bunch of things around this, but, so what? Tell me about your portfolio. Tell me about the robotics companies or general deep tech companies that you have. I'd love to hear kind of the stage when you were involved, and it'd be very cool to say how you're helping them in addition to funding them. I know it's a lot, but I'd love to see how it goes. Cool. Yeah, let's do it.

[00:16:29] Brannon Jones: I want to see how it goes, too. So, we've got about 18 deep tech companies right now, and that's across robotics, aerospace, manufacturing, energy. Now, initially when we started building out this deep tech team because it's been around for about three years now, it started as purely robotics. And that made sense for a lot of reasons. The biggest reason is that, technological readiness level for robotics is the highest among pretty much any deep tech technology that you would still consider. Deep tech, where there's still a good amount of scientific research that needs to be done to bring that company or that technology to bear.

[00:17:06] Audrow Nash: So we start hanging fruit. Basically, in robotics, given the state of technology.

[00:17:11] Eyebot Kiosk

[00:17:11] Brannon Jones: That's exactly right. That's that is exactly how we felt when we came up with the conceptual agreement for our deep tech vertical. So we started in robotics. So majority of our companies are in robotics. And then, a little over a year ago, we expanded to add on the other categories that I mentioned. So I'll talk to a few, a couple maybe, or one or so in each of those different areas. But on the robotics side, one of the companies that, yeah, I mean, we're excited about all of our companies. One of the companies I'll mention is EyeBot E-Y-E-bot and the name, the eponymously named eyebot they give eye exams. It's a kiosk that can be placed in a public location that has a lot of foot traffic and a person can come up to that kiosk, stand a couple feet away and get an eye exam in 90s. It'll test all the visual acuity. It'll even give them the option to buy the prescription right there on on the, touch screen that's embedded in the kiosk. So you can go get it. Cheap price. Then you can also even buy contacts or glasses right there, too. That will get mailed, to the house or wherever you want it to. Yeah, it takes it nice.

[00:18:19] Audrow Nash: It's great.

[00:18:20] Brannon Jones: It's like a. Yeah, in a way. Anything it doesn't spit out there, it doesn't spit out the eyeglasses itself. But yeah, it is it is true to the point you're making a familiar kind of a form factor that people are used to. And what's interesting, 60% of people in the world need glasses. And, maybe even 60%.

[00:18:41] Audrow Nash: That's crazy.

[00:18:43] Brannon Jones: And 65% need vision correction. Yeah. So huge market. So many people need this. And of course, right now everybody has to go to the doctor annually or every six months, get a prescription. It's kind of a hassle that doesn't really need to exist when you think about it like just from an engineering lens, a first principles thinking. Lynch why does it need to be that way? And so these this team has come up with some really, really exciting refractory technology that sends light into your eyes. You don't have to be super close to it. It comes back extremely accurate. And they did a bunch of tests comparing the fit of the contacts and glasses to a human doctor, and it's actually better now. We still have doctors approve everything. And so, it ends up being a seamless experience for the user, but they're doing really well. And they're one that we're excited, excited to back. And so they're not so much traditional robot as you might think of many moving parts. And we do have we do have robot robots. So we're here for that too. But that's more of a hardware play. But kind of gives you a representation of something that we were excited about it and the kind of fundamental thesis behind that is really democratization of access. And that'll actually be a key theme that you see across our thesis, how we decide what we want, what we want to invest in across this, the tech verticals. But democratization, you mean. So for example. Oh, well, makes sense. I buy this democratization of access to to. Yeah, exactly. But it's it's broadening accessibility, whether that's reducing cost barriers or otherwise. And so in many ways, our investments in the space sector are really thinking about, that broadened access and the infrastructure that needs to be built to support that. So when you have something like space, dramatically reducing cost of getting to space like orders of magnitude, probably 100 x now is probably, you know, in today's dollars $100,000 per kilogram in 1984, if you're sending stuff up for a space shuttle, by the time we get to, Falcon one, maybe it's 10,000. Falcon nine is maybe 5000 Falcon hoagies, maybe 1000. So we we've already seen 100 X, and then you're talking about Starship, which is supposed to be on the order of hundreds of dollars per kilogram, maybe 100 bucks per kilogram is what they're trying to hit. Bonkers and X reduction and in in price to get to space. Like if you make anything a thousand times cheaper, people are going to start doing that thing. So that's what we think about democratization. Okay. So let's say people start doing their thing okay. What breaks in the system next? What needs to exist? What kind of what.

[00:21:25] Audrow Nash: Are the next bottlenecks I see?

[00:21:27] Brannon Jones: What are the next.

[00:21:28] Audrow Nash: Bottleneck after bottleneck to get bottleneck efficient.

[00:21:31] Brannon Jones: That's right. Yeah. People start putting things in space. Those things are going to need to get monitored. There's going to need to get maintained. They'll need to get moved around to be protected, whether that's, you know, cyber counterintelligence, those kinds of things. So it's, yeah, it just really, really helps to think about the future and help you see around corners in that way. When we think about, okay, here's the democratizing trend. Anytime we see democratization of this, and there's massive uptake, it creates new industries. Yeah. Yeah.

[00:22:03] Audrow Nash: So I guess when you democratize something, you give access to it. And that creates growth. And that's something that you as investors are interested in. Because if more people, it's like a network effect kind of thing where it gets more and more valuable, how replicate. That's a cool way to look at it. So you democratize things and that leads to growth. And that's why it might be a good investment.

[00:22:25] SaaS vs. DeepTech

[00:22:25] Brannon Jones: Cool. Yeah. And we sort of think, you know, maybe this is one of those investor type phrases, but we sort of think of it as the non-linear unlock. When you can get so many technology start within government or DoD or a niche use case, and then they commercialize and that's the non-linear unlock, and you can bring them to the masses. That's the democratizing moment. That's when you really see massive uptake. So that's kind of the sort of example that we are that we are, interested in. And you see that across, you know, semiconductors, which started, I mean, I guess, how does semiconductor started, to calculate missile trajectories for the government because they literally didn't have enough compute to make sure the missiles got where they needed to be. But now they're in every single electronics device. And that's when you think about the non-linear because the cost came down. So, things like that is what sort of trends we're trying to to back. And how do we support those changes as they're coming in. So I mean, yeah.

[00:23:25] Audrow Nash: One thing that's interesting to me is that kind of thinking is what has led to a lot of investment in software as a service models, for my perspective. But you guys are going into deep tech as well as a few other areas, but how are you thinking of this? Because the point of software as a service is like, you code it once anyone can use it. And that's why it's been a fairly sexy business model. But but so why deep tech? And how are you thinking about it kind of coexisting within this scaling framework? Oh, yeah.

[00:23:59] Brannon Jones: Absolutely. So. SaaS has been a great business model. It has shown itself to be that way. But it is probably important to remember that it didn't exist. 20 years ago, and it almost wasn't a crazy. It was an emergent business model. The rules for SaaS rule of 40, whatever asset intensity you should have, what your net dollar retention should be, what all those financial terms people you use to quantify whether or not a SaaS business is good, those didn't exist 20 years ago. And they happen from investors saying, oh, I see that the internet is changing everything. The access to software, again, democratization of people being able to build tools is changing everything. And they almost had to just believe that people were solving a real problem. And then over time, it's almost a lagging measure. We went back and you said, oh, here, the creator of this business, I want to find traits in other business similar that match that, and that's what we think. So that's exactly what we see happening for deep tech over the next 20 years. It's such an exciting time, in my opinion, for deep tech, because the rules are still unwritten. For deep tech. We see all these changes. We see improvements in both semiconductor cost and performance. We see falling hardware costs. We see aging demographic. Obviously, we see all the improvements in AI, in the hype around it. We see improvements in connectivity, in 5G, we see demand for for e-commerce and shipping and more need for those kinds of logistics and automation. And then then obviously, there's, you know, all the questions about global competitiveness, globalization, reshoring, manufacturing, revitalizing industry here, all of those kind of come together and say, okay, this is going to be an exciting time for D tech. And we really believe those are going to drive demand and make some really, really big companies. The kind of on the scale of which we haven't really seen in mass in deep tech yet. And that's kind of what makes it most exciting. Now back to SaaS. We're thinking about it still obviously great business models, but in a way, for us as deep tech investors, the investing style and strategy is changing within SaaS because it's a more known entity and also because I in many ways is leading to the commoditization of production of of software tools. Right. So if you and I were making PayPal in the 90s.

[00:26:29] Audrow Nash: Be so much easier now. Yeah.

[00:26:31] Brannon Jones: It'd be deep tech backed it. Right. We need a full TV scientist. We need researchers today. We just need a weekend. And a couple good AI agents. I mean, probably we're coding, you know, just text today, like, you know, speaking. Get it? And then it's coding for us. Yeah. And so you see that trend and what that really coding is. Yeah. What that really means is I think it's going to be potentially harder to deploy massive, massive amounts of funding into software as the costs continue to drop, which is a good thing for everybody. Did the cost drop that people are seeing productive tools? Deep tech again, is the untamed frontier still wild with the creativity of all the scientists out there in the natural world and all these incredible scientific discoveries. And so I think that we one will be able to invest many different ventures to, I think, the deep tech investors who are leading the way there will set the standard for for what it looks like to invest in deep tech. They'll set the standard, they'll set the rules, they'll they'll make up the new metrics and heuristics that the industry will adopt over the next 20 years as we continue to see winners. And that's what we that's what we want to do. That's what I want to do. That's when I'm answering your question of how I think. That's why I'm excited about. That's one of the reasons why I'm so excited, because it also can be some of the most transformative technologies, even if you I mean, I was talking about Bell Labs earlier, so they're on my mind. But even you think about all the work they did around telecommute locations back into all of that. We wouldn't have modern phones if they hadn't been working on that. And even that that scientific discovery, hard research. Just think about how much communicate has totally revolutionized.

[00:28:09] Audrow Nash: Oh, totally. Yeah. We're you're in New York. I'm in Texas. It's crazy.

[00:28:13] Brannon Jones: How true. That's right, that's right. Yeah. So deep tech companies have the ability to be the most transformative cars, phones, semiconductors, planes to really shape culture, really shape our environment. And so it's not that I see anything wrong with test businesses or like they're not exciting to me, but when I just think about impact for dollar, I get really excited about deep tech and how could could literally shape our physical infrastructure or culture or environment, those kind of things.

[00:28:46] Portal Space

[00:28:46] Audrow Nash: Oh, everything. Yeah, for sure. And I'm interested in talking about a lot of the things you mentioned, the globalization, these kinds of things. But let's keep going with your portfolio. So we have this EyeBot one that seemed really cool. You mentioned a little bit of space. I don't know if you want to talk more about that.

[00:29:02] Brannon Jones: Yeah, yeah. We've got a great new space investment. And this one we are so excited about. It's actually probably our first actual, space investment. Now, because I told you we kind of expanded into deep tech. Recently, we've been looking at the space sector, but still space is still emerging. It's still nascent, still dominated by the major players. And so we've been trying to pick our our investments pretty selectively. So this will be our first one. This one is called Portal Space and we are so excited about them. They are building a new type of thruster for satellites for in-space movement. So your satellite can navigate around. They offer 10 to 20 times as much thrust as what's now available on most satellites. If you're just if you and I were going to put a satellite up there. Okay.

[00:29:55] Audrow Nash: I don't I don't really know the state of satellite. Yeah. Satellite tech for this kind of thing. So 10 to 20 times sounds like a huge improvement to. How is it done now? How are they doing it?

[00:30:09] Brannon Jones: Yeah. So space is the space is all about conservation of momentum is the way that people move around. So you take a, pressurized can and you squeeze it and it shoots out and you fly, fly back the other way. And that is how satellite.

[00:30:26] Audrow Nash: You shoot out mass in one direction.

[00:30:28] Brannon Jones: Shoot out mass. And functionally, that's that's I mean, that's what every rocket thruster for a satellite or an engine for an actual rocket does. And that's what our Raptor engines do. They just shoot out a ton of mass, and the more you heat it up, the more mass you can shoot out without using about your fuel. So they have it's it's bonkers. It is bonkers. And you look at the efficiency and they are just like bonkers percent. Yeah. Yeah. Totally crazy. Incredible machine. So, and so what they've done is they are building a system to actually vary efficiently, use a liquid propellant and, shoot it out very fast without needing to, implement many moving parts or a lot of, energy even. And so because of that, they can do that at high flow rates. High flow rates means they're basically putting out a lot of fuel. If you put out a lot of fuel very fast, you get a lot of thrust going the other way. And they the insight actually came from an engineer, who was an engineering leader at SpaceX, for a long time, developing the Raptor engine. So the weapons I built, he designed. I didn't know him at the time. Yeah. But, super cool. Definitely always fun to connect to the space network. And that was where the core insight came from. And this actually makes me, you know, just talk about the future of DPC in terms of we're seeing some deep tech winners in the Tesla, say, and rules the space X. Oh yeah, totally in the Morpheus from those Morpheus meaning the alumni from them who leave them and start companies are bringing so much knowledge, not only technical knowledge, like from a research standpoint, but knowledge about how you actually build a company. How do you actually get a whole bunch of engineers who all think they know the right way and no one else does, and get them to productively move forward, at incredible speeds? That's what they're bringing. And that is what the startup world has, has needed, for, for deepfakes. That's one of the big catalysts changes. That's why we're so excited about portal.

[00:32:31] Audrow Nash: So, anything else to mention on this portal space?

[00:32:35] Aescape Massage Robot

[00:32:35] Brannon Jones: Yeah. I mean, I think that the reason that we like them and I guess is one piece I didn't say is they provide infrastructure for the new space economy. So when you say, okay, maybe there's 10,000 satellites in space and we think there's going to be ten times that in the next ten years, well, mobility becomes extremely important. When you think about national security, when you think about, monitoring mobility becomes extremely important. And so if they have the most mobile platform, they are providing infrastructure that everybody will need, government need, commercial need. And that's why we think it's a democratizing. It's a democratizing trend. Because even if you can commission their satellite to to go and do an operation for you, and it's, it's space, you don't have a logic up there. You can just rent time and have it go do something for you, move around your satellite, check something out. You're giving so much, you're making access to space actually tenable and affordable. So that that's one of the reasons why we're really pumped about about them. So that's one in space. So I give you a robot one, I give you a space one, I give you a one that I'd.

[00:33:41] Audrow Nash: Love more of a robot. One because eyeglasses. Yeah. I mean, my my thought on robot is as long as it senses things and acts with. I think these vending machines that do your glasses do, or like scan your eyes. Do. But, any like mobile robots, robotic arm stuff. I don't know. We got it annoys whatever else you got. You got it.

[00:34:03] Brannon Jones: All, baby. Okay, so let me tell you about the next one, so I'll give you one more. You like? This is a New York one for you. And I also think shows a great example of how robots are starting to have that nonlinear unlock by breaking into traditionally non automated sectors. This one is called Aescape It's spelled like escape. But with an A at the beginning Aescape. They are a robotic massage table. So you imagine a massage that's got two robotic arms on top with. They've got specialized ins that, allow them to actually perform the massage like a masseuse. You lay on the table, you're looking at an iPad beneath it's a flat panel, and you see basically your own body. Now you wear a special type of, athletic wear that has these micro sensors in it that the robots are trained to see. So you get your own, just like you wear your little limited gym, you wear your your.

[00:34:53] Audrow Nash: So it gets your shape because your shape is super hard to detect and stuff. So you have these markers. And so that's how you get the body texture.

[00:35:01] Brannon Jones: So exactly. That's exactly right. And then the robotic arms come and give you massage. You can then hilariously choose where you want it to be. You can adjust the pressure. You can control the music in the room, controlled lighting. And they are doing phenomenally well. They just raised an 83 million, dollar, series fee to expand the robotic massage. Wow.

[00:35:20] Audrow Nash: Very appealing. That's awesome. Yeah.

[00:35:22] Brannon Jones: They're doing great. And they're just down the street here in New York. So that's what I'm saying. They're fantastic robotics companies that are, that are emerging here on the East Coast. But, you think like New York is probably the right place for that, because they'll be able to expand with a luxury gyms, hotel chains. That's where they've seen a ton of traction. And it's an industry that is, you know, dull, dirty, dangerous. The things that people talk about, being factors where it makes sense to automate. If you talk about, like, being a massage therapist, it's actually, a lot of chance, a very high chance. An injury.

[00:35:58] Audrow Nash: Yeah. Super rare. It's hard to access emotions.

[00:36:01] Brannon Jones: Super repetitive motion.

[00:36:02] Audrow Nash: They put a lot of force for sure. They it's like they need massages because giving massages, intense kind of thing.

[00:36:11] Brannon Jones: It is hard to go get and find a massage. And so this is another kind of democratizing trend in itself. But they're doing extremely well. They've got a big team. They are moving fast. And their table works great I think two years ago.

[00:36:25] Audrow Nash: Have you done it.

[00:36:25] Brannon Jones: When I first met. Yeah, that's exactly I was going to say, because they're here, I just will pop over there. And I was so I was doing the demos and so I had the, the healthy portion of, of cash. And when I was doing it. But even back then, even two years ago, it was actually a fantastic massage. And so it's it's only better now. So, that's kind of to.

[00:36:46] Audrow Nash: Compare, like, I mean, if you go to like a really good Thai massage. Yeah. I have a hard time imagining a robot being close to as good as that, but like an average one where they're not as knowledgeable or as focused or things like this. Like, how do you think of it in terms of quality? And I'm sure that being invested in them, you want to say that's very good, but like, how do you think of the quality for everything? Oh, it's very good.

[00:37:10] Brannon Jones: Top tier. Okay. So no, I'll give you my real answer, which is that it is good, but that you would probably want to start to evaluate it. And you will value your massage slightly differently. You will you will evaluate the quality of your massage slightly differently.

[00:37:25] Audrow Nash: Yeah. Because there's quantity. You could do infinite quantity if you have access to an infinite.

[00:37:28] Brannon Jones: Quantity and you have infinite control ability. And that's what you don't have in a great time massage. They're going to do whatever, they're going to put you in a pretzel and you're going to like, oh my gosh, that's what I need right now. I feel great after. Yeah, yeah, you can tell them. But then you'd have to be speaking the whole time. This you have so much more control. You can go.

[00:37:45] Audrow Nash: Quite good on an idea. It's so funny.

[00:37:47] Brannon Jones: Yeah. So it's so it's it's high quality in the sense that you can get exactly what you need. They can provide the pressure that you need. Certainly a person will have more dexterity at the end of their. Yeah. The robot can't. So for I think the very high end type of Thai massage. Yeah. You know, there are places only a person will be able to,

[00:38:07] Audrow Nash: To. Yeah. Good for now for this guy. If for now. Yeah. For now, if you, It'd be it'd be funny to do, like, I don't know, machine learning in some way where they're doing reinforcement learning or something like this where you or supervised learning, I guess, where you can click and give it a reward at the end and then it, it hill climbs to find really good ones for you or something like that. But the space is so difficult that I think that'd be hard. Like the optimization space. But yeah, I do, I do kind.

[00:38:34] Brannon Jones: Of giving it a digital tip. Yeah, yeah yeah, yeah, exactly.

[00:38:38] Audrow Nash: That's I don't like it. Whatever. How is it? And also because you have the iPad there, you could like for every thing it's doing, you could give it feedback pretty frequently just selecting a spot. How is this last thing. That's a funny thing. So it's kind of like the way I'm imagining it is. It's like between a massage chair and a person, maybe like halfway or a little closer to the person. Or did you say.

[00:39:02] Brannon Jones: Yeah, I would say it's it's much closer to a person than a massage chair in terms of how you'll feel in the experience that you'll have. Yeah.

[00:39:09] Audrow Nash: Because you're not in the uncomfortable chair and everything too.

[00:39:12] Brannon Jones: Yeah. In those those arms have six degrees of freedom or even more. Yeah. And so really. Yeah. You can really get now does.

[00:39:20] Audrow Nash: It, does it focus primarily on your back or does it do like arms forearms, fingers like these kinds of things. Because these are I imagine it would be much harder.

[00:39:28] Brannon Jones: Yeah. So when you start talking about fingers and you need that kind of next level of dexterity, this thing is mostly here with, with no pressure nubs that are, you know, proprietary, patented, very specially designed nubs right there. They are specially affected.

[00:39:42] Audrow Nash: The technical nub. Yeah.

[00:39:44] Brannon Jones: No, they don't have fingers. So yeah, they can totally do shoulders, arms, back legs. Yeah. But if you're really talking about like getting into to small tissue in between bones and joints, that's on the future roadmap. That'll be version two.

[00:40:01] Audrow Nash: Yeah. I would love like a smaller nub that they could get, like, I don't know, in between your shoulder blades or stuff like this. Like, that'd be super nice.

[00:40:08] Brannon Jones: And they design it with, like, quick disconnects to change out the.

[00:40:11] Audrow Nash: Oh I'm.

[00:40:11] Brannon Jones: Sure. I think it's more about to the point. You originally made scale of data in totally control and you know, so I 100% those things will come down the pipeline. Now on the boat, Matt.

[00:40:23] Audrow Nash: What's so exciting about their series B, though? That's so cool because that's, so have they, they've really proven a market with that because B, you're scaling for this kind of thing. Yeah. Yeah, yeah.

[00:40:34] Brannon Jones: Generally that's, that is the big thing. They have proven that people want this and there's a few elements to it, which is one that they are solving a problem that people want massages kind of inaccessible. People have different comfort levels with massages and want more and less control done. That's what you kind of think of. The other piece is that for the customers who are actually adopting this technology, it also provides, some other second order intangible benefits, which is like, hey, more people may come to my gym if there's a massage table here.

[00:41:10] Audrow Nash: Oh yeah. So it's a wonderful gimmick too. Yeah. I mean, wonderful kids stuff like, oh, I'm going to choose the one like that one has the good exercise stuff, but this one has a robot that massages you. Yeah for sure.

[00:41:20] Brannon Jones: So even if it didn't work and it does work, it does work really well.

[00:41:23] Audrow Nash: It's a good gimmick.

[00:41:24] Brannon Jones: But even if it didn't work, it provides value to those customers by enhancing the brand, by bringing more foot traffic and some of those other things. And so that's so cool to see. That's been cool to see them go through. Okay, is a term I'm just going to throw out now called human acceptance testing instead of user acceptance testing, human acceptance testing being it needs to be accepted by humanity broadly society. It needs to fit into the ways that we already think about the world, and we already think about culture. And from that standpoint, they have nailed their human acceptance testing beyond just the user who actually wants a massage. So that's that's one of the things that leads to that kind of non-linear unlock, why they've been able to scale, why they've been able to get that traction, and of course raise a great round.

[00:42:10] Audrow Nash: I I'm sure that they did a good job with this, but I also thinking about it, I'm having a hard time imagining why it would be so difficult because I think people would just go, oh, massage chair, but better and that kind of thing. But what do they do? Well, for human acceptance testing or why is it more complex than what I think?

[00:42:30] Brannon Jones: Yeah, actually, one of the things I was talking to the CEO about this recently, but, they spent a lot of time in two phases where I think a lot of deep tech companies don't spend enough time. One of them was actually in the book, the industrial design, the physical mockups. They spent a lot on going through those, making sure that it was something that was esthetically.

[00:42:51] Audrow Nash: Pleasing and everything has to feel like a luxury experience.

[00:42:54] Brannon Jones: Right? And not a terrifying torture contraption, which we could easily write if I, if you and I on first principles, were just going to design one of these things, it might be a little bit terrifying. So they spent,

[00:43:05] Audrow Nash: We'll see you and you get a Kuka arm or some, some gigantic arm that can move cars or something like that would be crazy.

[00:43:14] Brannon Jones: That would be scary, right? So they got cobots right attached to the table, but also the way that it looks, the form factor. Yeah, they did a lot of looks like prototype. And we they were literally almost making almost making arts and crafts in sculpture to find out. Hey, what do people like, what do they want to have around. What are the ground? Oh super cool. When are they most comfortable? What are they not. That's number one. Number two is they have been brilliant with their marketing. They have been brilliant. So they tapped into lifestyle influencers. They been on social media, they've had features. And the biggest publications, they were on the New York Times Best Inventions for 2024 list. I can't get in the back of a cab without seeing the little archway in the screen in the back here, in here in New York, because they were so focused on controlling the messaging around it. And they. Yeah, that they that part of that human acceptance testing of, of getting through that social, that kind of social evaluation. So, very, very clever by the CEO. And not enough robotics companies do this, not enough to keep that 100% with you. Yeah. Yeah.

[00:44:19] Audrow Nash: Distributional distribution is key. Right. And marketing is a huge part of that. So it's really nice to hear about robotics companies doing that. Well I feel like a lot of times we nail the tech less frequently, nail the market and the tech, and then less frequently nail the distribution market and tech.

[00:44:39] Valar Atomics

[00:44:39] Brannon Jones: Yeah that's right. No, absolutely. And so that was one of the things they focus on a lot is just make sure, making sure that even in a distribution a key piece is the perception 100%. When you go out into an area that's highly dynamic and you actually want I do to interact with people. People's general mode of being is if it looks like garbage, it is garbage. In a car factory. Doesn't matter. It just needs to be functional. But out in the real world, you got to be thoughtful with those things.

[00:45:07] Audrow Nash: Very cool. Okay. I want to bring up one more startup or so.

[00:45:12] Brannon Jones: Yeah. Oh, absolutely. So this one would be, kind of probably more squirrely in our energy transition, but also leans in with manufacturing. This one is called Valar Atomics. They just came out of still.

[00:45:27] Audrow Nash: Great names for all your companies, by the way.

[00:45:29] Brannon Jones: I think so, too. I think so too. We I do think we like to pick, back teams that understand how to tell the story, understand our mission. And naming is probably so it's a piece of that. So maybe I'll go run some analytics on it after seeing how many of our best performers had great names. Anyway.

[00:45:46] Audrow Nash: All of them.

[00:45:47] Brannon Jones: But yeah, I'm sure, Valar Atomics Atomics, they just came out of stealth with the $19 million seed round, maybe a couple months ago. And they are building new reactors. Big seed. But nuclear fission.

[00:46:01] Audrow Nash: Nuclear. Yeah. Okay. So, yeah, energy is super expensive, I think. I don't know much, but, it seems to me to be the case.

[00:46:09] Brannon Jones: Yeah. So, I mean, some of the infrastructure costs can be expensive to get to get set up, but their whole idea is, they want to provide energy very cheaply, and they're doing some pretty exciting things. They're not only thinking about how do we they're not like, they're not thinking about nuclear in the same way that everybody else's. They're not trying to do create hydrogen in or go through an atrocious process. Okay.

[00:46:35] Audrow Nash: I don't know anything really about nuclear. Yeah, too. I would love the basics of it. So, like, my model is you have something that generates heat, that generates steam, that pushes a turbine, and that makes electricity. But you need something to make the heat. So you make the steam. Is that correct?

[00:46:51] Brannon Jones: That's exactly right. So that's tradition where people use nuclear force to create that heat, to create steam. Now there's a new crop of nuclear, of companies, I guess, who are trying to create basically green hydrogen. And some folks are trying to do that with nuclear. These guys, they want to create extremely high heat to create green hydrogen. They want to separate the so hot that it separates the water molecules. Then they want to take that hydrogen that's been separated out from the water, and they want to put it through another industrial process where they effectively combine it with, carbon dioxide and they use a process to separate the oxygen from the carbon dioxide, and they get the hydrogen and the carbons to bond together through a well known industrial process. So what you're spitting out at the end of this machine is actually hydrocarbons. It's methanol. It's unrefined jet fuel. Oh and so what they actually want to create is nuclear synthetic fuels green jet fuel. Green diesel green gasoline, net zero gasoline. It takes in carbon dioxide turns it back in the fuel. And it's a phenomenal idea.

[00:48:00] Audrow Nash: It's so freaking cool. Yeah.

[00:48:02] Brannon Jones: It's so energy dense. It's the most energy dense transportation. There's already a massive market. Everyone uses, hydrocarbons right now. And if you can do that in a way that's that's actually beneficial for the environment or doesn't hurt it, then your distribution check, you already know that there's a massive market for it because you think about it, the biggest, the biggest oil companies are sovereign nations. So massive, massive market, massive, massive demand if they can get this right. So they are cleverly combining a few different types of science, to get to that end goal. And at each step, even if they just create high heat that can be used for industry, to create a variety of, of raw materials. So they are yeah, they're one we're super excited about to back and they're at LA. So one of our examples of a is West Coast way.

[00:48:50] Audrow Nash: Hell yeah. Yeah. That's cool. I just the thing I understand is they're taking the normal process and they're making, byproducts more productive for this kind of thing. So you can also generate energy for that. So it's like you get two for the price of 1 or 2 for, I don't know, the price of one and a half or something like that, which is awesome. Super cool.

[00:49:10] Brannon Jones: Exactly right. Yeah. And so they can get extremely, extremely cheap prices for hydrogen, which ultimately leads to cheap prices for, hydrocarbons. So very excited about them. And we've got, a number of others we got, just list them off.

[00:49:24] Koop Technologies

[00:49:24] Audrow Nash: Yeah. Go ahead. Yeah. Koop is awesome. So I did an interview with Sergey Little. He's awesome. Yeah. He's six. Robotics infrastructure, robotics tooling such a good thing.

[00:49:35] Brannon Jones: Yes. Okay. Amen.

[00:49:38] Audrow Nash: So they do insurance just to say they're great insurance for robotics startups. They're wonderful.

[00:49:43] Brannon Jones: They're wonderful. And they are doing so well because they're betting on a growing industry. Same as we're talking about democratization. Well, if I had a doctor in access to build robots, who is insuring them because they all are going to need this liability coverage, and they have found a way to quantify and underwrite the chance very effectively. Misbehaves and doesn't do something it's supposed to do. And they insure that. And because they actually get the pricing right, they can offer very low prices, which, you know, who likes private low prices is startups because they don't have any money. So these they are quickly taking the market by offering them, hey, really good insurance at great prices that they can actually underwrite extremely low loss ratios. And so yeah, totally. They're actually super strong. And they yeah, I agree, are an insurer tech company. They're not what you would traditionally think of as a deep tech company. But for us it still fit the mandate because we talk about democratization in infrastructure. They are the rising tide that will lift all ships if they make these robots easier to get out to the wild, easier to ensure they also have a compliance product. If they make those things work well, then they pave the way for for more deep tech companies to to come through. And this is.

[00:50:56] Audrow Nash: Where it spins up that flywheel.

[00:50:58] Glacier Robotics

[00:50:58] Brannon Jones: Spins up the flywheel. Yeah. It is nice to have a, a, you know, a bigger AlleyCorp team because then I can go over to our diversified tech team. They look at insurer tech all the time, and I can say, hey, I can underwrite the quality of the robotics market. You look at a true tech all the time. Give me an expert opinion here. They quickly looked at it and we said this is a no brainer. So, Koop with a K, we really like that glacier because another one they do recycling robotics. So they would go into material recycling facilities. That process all the recycling for major urban centers. And right now people are just doing it by hand sorting, you know, white plastic and green plastic in this type from that time. And they've got a robotic algorithm which can identify the type of plastic, what it is, and then quickly send an arm to grab it, and it's got like two arms and hang down camera and it will sort them into the bins, extremely reliably, quickly, effectively, in some critical structure.

[00:51:58] Audrow Nash: I've seen a number of robotics startups in Europe that are working on this. I don't think any of them have gone anywhere. Why? Why is this hard? And why are they likely to succeed in Europe? Perspective. Yeah.

[00:52:14] Brannon Jones: Yeah. So this is hard for two reasons. Probably more than two reasons. Two reasons that I think are top of mind. One of them is that it is a legacy industry that has not seen a lot of automation. And so even when you're trying to make the business case to some of these recycling facilities, they're still trying to figure out how they quantify it, how they measure it, where the gains really are. And they're not always, the most excited to adopt robotics. So you really have to have a high ROI. It's one of the reasons why we left Glacier. Second reason why.

[00:52:47] Audrow Nash: Their ROI like ballpark.

[00:52:50] Brannon Jones: Yeah. So there are times lag will be. Yeah. Right. In terms of actual actual payback on the machine. So. Well, I don't want to butcher this, but I think they allow facilities to make their money back within. It's it's definitely less than a year. But I was going to say six months, so something something like that.

[00:53:09] Audrow Nash: Well, it's a big difference.

[00:53:12] Brannon Jones: It is a big difference between six year. Yes. But, what they also allow is for you to really scale up, scale up your operations to your recycling facility industry. And one of the things is that, that I like about them, why they, I think they're going to be successful is actually, I think, within their technology. So one of the areas where they shine the most is in their ability to actually identify, identify those materials that are coming down the conveyor to actually see what kind of plastic it is. Quickly. And it's actually a very challenging visual problem because they're not sorted well, they're stacked on top of each other. They're dirty, they're folded over, they're crushed. They don't look anything like their original form factor. So you can't even really use standard terms of AI and say, this is a can because it don't even look like you can anymore. So that is then their proprietary technology. And one of the founders spent a lot of time doing, like building vision models for meta. And that was kind of their core expertise. So they have a phenomenal team. They built tech that's better than, than anyone else, trying to do that. And so that's, that's what we're confident about that.

[00:54:20] Audrow Nash: Cool. So yeah, maybe that was the problem with a lot of the European ones is the labeling was really hard to figure out what's the right type for here and there. And maybe with like modern AI, you're able to very effectively learn which ones go where, and then it can figure out all sorts of clever distinctions that it can pick up on. When sorting.

[00:54:46] Civ Robotics

[00:54:46] Brannon Jones: Yeah, that's 100%. And then when you actually do that, now you're capturing data that the Murph that the recycling facility didn't have before, they don't actually know fully what's coming down. They don't know where it's coming from. And they're two people that care about that. One is a recycling facility. So they understand their operations too. Are the, companies who are actually creating the material that gets recycled, whether you are, beverage company or, you know, maybe you make toothpaste bottles or something like that. Now, you know what your footprint is if it's actually getting tracked. So they also add this massive digitization layer to the industry, which they'd never had before. And there's a lot of really cool traction from the market, because the excitement from, from that. So, sorry about that one. Our last one, that's maybe more on the mobile side. I mean, we we do have more or less what I'll mention here is called Civ Robotics. They are for the solar panel industry. And what they'll allow you to do is if you're going to go build a large, massive solar field, they have a rover that will go out and it will mark the areas where you need to put the where you need to put the pylon. So, just automates that portion of surveying solar fields. They've got 100 robots in the field, like, more than many companies that we see. And they're at an early stage making money. And, that's growing and growing really fast. So excited about that one, too.

[00:56:08] Investment Challenges

[00:56:08] Audrow Nash: Oh, yeah. Seems like an awesome portfolio. They seem like all good companies. Okay, so I would love to see just your thoughts on a lot of things related to robotics investment. Sure. One of the things that has been interesting to me is I've met a number of companies that I consider quite promising, but at the same time, it doesn't look like their market is large enough to justify venture capital investment. Like, it's like they'll do a they'll do a thing, they'll be profitable, but they might 10x or 50x or something like this. But it's not like knock it out of the park. Amazing. So they're getting passed over by a lot of investors. How, so what it seems to me is it'd be really nice if there was some sort of like, robotics investor with a longer time horizon or more conscious of hardware or, it's like smaller, fewer bets where the odds of the companies succeeding are higher than they typically are in venture capital, where you put a lot into a ton of startups and some are wildly successful and most die out. Do you do you kind of understand the problem that I'm trying to describe and absolutely do? How do you think of it? Because it makes it so that robotics is hard to fund. And I would really like if there was a better solution for this. What do you think?

[00:57:46] Brannon Jones: Yes, I agree, but I think this goes back to something that I was saying earlier, which is that the rules for deep tech actually still are.

[00:57:54] Audrow Nash: Being established.

[00:57:55] Brannon Jones: At the times. Yeah, they're still being established. You know, a lot of investors, I believe are getting wrong right now is that they're trying to apply the same framework from SaaS on to deep test, but it's actually very different in terms of how these companies commercialized. To your point, take a little bit more capital upfront. They can take longer timelines. But after that they actually tend to not need as much, whereas a software company needs much less at the beginning. But as it scales, then it actually needs a lot, because now you've got competition, because your technical differentiation is very challenging to maintain. And so you need to maintain this thing through distribution, through for user experience marketing. So it actually flips it on its head. Where in the venture world there's so much risk ahead when you're investing in software, even if you're solving a great problem, you know, the bulk of your spend, the bulk of your risk mitigation is actually coming down the road. Deep tech's actually a little bit in the reverse. So what it lets you do is say, hey, I know that this is solving the problem. And we try to be really, really quantified about this. It's like we call it like your value creation multiple. We really try to understand, okay, for every dollar that the robotics companies customer is going to give them, how many dollars can that customer now go get in exchange, either in savings or an increased rate of oh.

[00:59:12] Audrow Nash: Look at this in advertising, where it's like, if you're advertising brings in more than you spend, then it's free advertising and you can keep advertising. That's right. So you're saying the same kind of thing from a company perspective because it lets the company scale and thus it's a no brainer from the company's perspective. Cool.

[00:59:29] Brannon Jones: So they pay you $1 a month for your robot in $10 a month. That's great. You see a ten x multiple. You know that that person is going to try, their hardest. They're going to advocate for that. That's making a real difference for the business. Now, if you see something like that, especially at their early stage, that's easier to underwrite. And you made the point about 1050. That's not the 101,000 x. You're right. But consider that a venture capital fund is a top decile fund that is one of the best performing funds in the world. So what it means is that actually, if you can bring together ten and 50, you can have a phenomenal fund, even though it doesn't look like the traditional software fund. And I really, I really attribute that to kind of the, the capital, the late stage capital bias that happens in software, which certainly later stage tech companies need to raise money, but it's more about scaling. I think it's a little bit more understood, and it's harder to rip out a robot after you put one in than it is to switch software accounts. So that also starts to give them a little bit more staying power, a little bit less risk as they mature. What it means is that you can feel slightly more confident if you see a very high value creation, multiple, in your early stage robotics company that they are going to create some amount of value, going forward. And so even if it's a smaller market, you think, hey, we can get a very valuable company here, we can get one where we can we can make enough money for it to make sense for a major firm. That's one that's kind of one reality, to it. And why it kind of makes sense at the early stage. Also, though, well, actually, I'll stay on the small, smaller markets. What also tends to happen is a lot of these can tend to be not exactly winner take all, but have a very strong leader follower effect where you can become the best in the industry. You can become an industry standard. And I think part of that is because it's physical.

[01:01:30] Audrow Nash: I don't quite get what you mean. I'm not sure what you're linking this idea to. What do you mean the follower effect and what?

[01:01:36] Brannon Jones: Oh yeah. So here's what I'm here's what I think is that if, you are an e-commerce company and you have the option of using the same hardware software that Amazon uses, or you could just use some random on off the shelf, which when you come, you're probably going to do the Amazon one. And so all.

[01:01:54] Audrow Nash: Things equal for.

[01:01:55] Brannon Jones: Sure, all things equal for sure. And I think with robotics, because reliability is such, such a key parameter, if you see something working in the wild, you're very, very much more likely to go ahead and try to implement that yourself. And that's what I mean. The leader follower effect, the leaders in the industry tend to pull on the a lot of others. Yeah. So that's why you see like even you can even see even in classic machinery, like how many types of robot arms are there out there. Yeah. Yes. Kawa ab Senate Kuka you are. There's five right. That's it. Because they take so much of the mark. So there's much more like concentration tends to be. And they tend to have a very strong, pull market. So even if it's a smaller Tam, you can capture a lot more of that than you could with software like how many accounting softwares are there? Infinite. Yeah, I know.

[01:02:51] Audrow Nash: And how many CRMs are there and all this other. That's right. Infinite. Yeah, yeah.

[01:02:55] Brannon Jones: So that's the point that I was that's a cool point.

[01:02:57] Audrow Nash: I like that I like that concentration related point. Okay. How are you.

[01:03:04] Brannon Jones: But also deep tech companies have the biggest markets too right. Providing energy to the world is enormous. So it doesn't always have to be that way. And we do like personally like to have a mix of things that we think can like, have a big proportion of a small market and also play in a massive tent. So.

[01:03:20] Audrow Nash: Yeah. You can have some moonshots in your portfolio because if that works it'll be frickin incredible. That's right. And the other ones are very likely to be successful but may not be like I know trillion dollar companies or whatever. Yeah, I agree with you where I think, robotics has a bigger moat than most software companies like once some company makes some good UI, and has some feature and proves itself to be a good company, then you'll get a ton of competitors that all do the similar thing. And so that that very small competitive moat and so it's like that's when it's like all distribution, all the advertising as you were mentioning, whereas robotics, there's a million hard problems that a robotics company needs to solve to deploy and be reliable. And it's a much higher cost for this kind of thing for new entrants to go in to figure out all that. Again, it's almost like starting a completely different startup.

[01:04:18] Brannon Jones: Yeah, exactly. And the last piece I would say, and this is not generally that venture capitalists think, but the last piece I will say is if one of those companies does fail, there's a lot of valuable IP that's created in that process. And so the failures tend to not be quite as severe, because you can still sell it off for parts, so to speak, because there's a ton of IP generated now. Yeah. We're not playing for the downside. We're playing for the upside. But when you're just talking about what sort of an outcome do you expect? Well, we're not expecting to have 50% of our companies be zeros because we don't even think the fourth of these is zero. Even if they went out of business today, there's a lot of IP that still be able to somebody.

[01:04:55] Audrow Nash: That's cool. I haven't thought of it from an IP perspective. I think you're right there. Yeah. I mean, the software you develop, the, infrastructure you develop for manufacturing, the know how you develop, the founders you cultivate, like all of that is really valuable. So it's it's a nice, nice way to look at it, too. And you can sell off the hardware. Worst case. Yeah. Oh, hell yeah. Okay. Any other, any other things when thinking of that, those were all very good points. I really thought that was a good answer.

[01:05:27] Brannon Jones: Yeah, not so much in terms of of thinking about like the, the Tam thing. I mean I think often about like.

[01:05:34] Audrow Nash: And also addressable market just if. Yeah that's right. If people then know. So like how much could you possibly make if you had all of it for this kind of thing.

[01:05:45] Brannon Jones: That's exactly right. Yeah. How many of these things are bought at a year? How many people around the world use it? Is that a big number of people? Small number of people? And I think one thing I guess I maybe I'll, I'll say I'm curious to hear your, your thoughts and if it jives, which you're seeing and hearing from other robotics founders, but what feels different now compared to robotics investing five, ten years ago is not only the transformation in technology, but the speed at which the founders, I think some of that is because, again, we talked about the education that they got at some of those more mature deep tech companies. Some of it's because, the practice of entrepreneurship has become more quantified. Some of it is because AI tools are speed people up. But the hardware companies of today, you could even take, for example, figure robotics within a couple of years, they're, you know, in talks to, to raise around 1.5 billion around it, $39 billion gone crazy. Is it is crazy. But the speed at which that company moves is much more like how software traditionally thinks. And so you're seeing some of that come over into robotics that I think is fundamentally the biggest difference in why some of these companies are being successful. I also think it's one of the things that not enough founders are getting correct, which is just ship, ship, ship, create new iterations, try new things, test subsystems and put them in, do it in a low cost way. Just do enough to test the critical function and get it back it. And you should be really going through those iterations as fast as you can. I had a company tell us that they made over 100 different iterations of the robot in a period of like six months, and this wasn't 100 like design conceptualizations, it was a hundred physical instantiations of their robot. You know, most of those were small, small tweaks. Yeah, small tweaks, but they're doing it because they're getting it in front of it. They have a customer come to their shop and they put it in front of them, and they have them try it and they observe, and then they make a bunch of changes. They were doing things 3D printing subsystems, sticking it together with like putty and stuff, just enough so they can test the core system. And then if it worked, they'd go and do a full build out and they'd integrate it into their design. But they were going through those rifts so fast. And to my awesome about learning, that's what makes all the difference. And actually in like robotics manufacturing, the actual process of building the robot itself is so key for the quality of the robot going through the manufacturing, just to go through the manufacturing teaches you how to make it, how to make it quickly where you could trim out waste, how to get those parts to sync well together. And so you can come out with a product that's very reliable and very low cost. And then you can see, hey, where can we actually increase quality? Where do I failures tend to be? And then you can increase quality. So I think that's actually one of the reasons why for example China DJI unitary all a bunch of their other robotics initiatives are growing so quickly is because if you're in Shenzhen you go pick up the parts, within hours, you stick it in, you'll do another rest. And the more you do those revisions, the more you're actually understanding the hardware. Whereas I think there has been too much of a traditional approach of thinking about, okay, what order apart it gets here in weeks, we'll test it in weeks and then we'll make a change. And there's just no way to compete with a feedback loop that slow in. The software doesn't operate that way. There's shipping no new version all the time. They so the best robotics companies are moving much more towards that axis. And I think honestly US has certainly the advantage in terms of IP technical know how talent. But this is almost no replacement for that manufacturing speed. And so that's what I want to see from a lot of startups, is just going through those cycles as fast as possible. Yeah, pretty good outcomes.

[01:09:50] Market-Focused Startups

[01:09:50] Audrow Nash: Oh yeah. Yeah, I totally agree. And I think one of the things that I noticed with this related so I've been podcasting, with Robo Hub and then sense think act and now the Audrow Nash podcast for like 12 years or something like that. And so I've been interviewing startups this whole time. And the thing that stands out to me is companies are becoming market focused, and that makes it so that they're pragmatic and they get out there quickly and they learn versus just being happy with the technology. A lot of people, it seems like we're just building things because they enjoyed building things and they weren't going to the customers and they would move slowly to perfect it before ever putting it in front of a customer. And I feel like I've seen a very large change in the types of people that are found in companies now, in the last few years. And, I'm curious to talk about like, a thing that I've noticed. So I'm in Texas. I'm talking to a lot of the robotics community in Texas, in my opinion. And maybe this is an area for you guys to look into more. But I've met a lot of the best market focused founders here of anywhere I've been. I lived in the Bay for a while. And I'm from New England, and I was out in Michigan for a while and things like this. But it's it's an interesting thing, and I think that them being market focused leads to them being pragmatic and making choices where they can iterate quickly. They try to get the product in front of customers quick, get the customer paying early, all these things like this. But do you have any thoughts on this?

[01:11:40] Brannon Jones: I mean, yes, but let me just make sure I understand your question correctly. You're thinking about you're talking about like location, like within Texas. Are we seeing things or you're talking about in general market focus? Yeah.

[01:11:52] Audrow Nash: Or you asked how I, what I thought, was the speed thing, and I don't, I don't fully know what it is because a lot of the things you mentioned, AI, better open source software, them coming out of these great companies. So then, my, my thought is, I don't know why this is occurring, but I am seeing a different breed of founder in the last year. And then a little thing within there was, I'm seeing really good ones in Texas, which is really interesting to me. But kind of digression for this kind of thing.

[01:12:27] Brannon Jones: We too are seeing really good ones in Texas. Actually. We have companies in Texas too. Yeah, we are seeing really good ones in Texas. And it's fun to see the tech hub emerge there. What I will say is you're 100% spot on about the founders who now have a market focus. And I think there's a function of a couple of things. One of the big things is that some of the enabling technologies have made robotics more accessible, deep tech more accessible, actually building a hardware product and more accessible. What that what that means is that if you're an expert now in logistics, you can come up with a robotics idea, even if your background training is not in robotics. And that was never the case before when you had to have the researchers doing everything fully custom. So yeah, when you get that, you have a person who not only knows how to move with the culture, like the cultural speed of business and entrepreneurship, but you have someone who's got a very deep insight into what the actual problem was, which was the missing link. In the past, when you had researchers coming out say, hey, when someone want to use this great gizmo. And I was like, that's great, but I don't understand how to use it now, they know exactly not only how it should be used, but again, the human acceptance testing, how people think about using it, how it fits with their preconceived model of the world and their preconceived model of their business operation. So I think what you're saying is 100% correct. And we're actually seeing many of our CEOs, CEO of Aescape not a classical roboticist, came from the lifestyle industry, and that's why he's doing so well here. Many of our CEOs not classical roboticists, but industry experts, and they have a brilliant wizard of a CTO and engineering team, of course. But I think what you're seeing is indicative of the fact that there's more interest in it and there's more accessibility to start to build a deep tech company than it was in the past.

[01:14:17] Early Robotics Investments

[01:14:17] Audrow Nash: I think you're spot on. I think that's a is probably accessibility and making it so that people who are market focused rather than just like super amazing roboticists can start these companies. That's super cool. What are you. So one thing that I notice about a lot of investment firms, you guys included, is it's a lot of pre-seed to series A, are the ones that I think of that are primarily focusing explicitly on robotics. It gets harder when you get I mean, even like, you guys are saying your seed and pre-seed mostly some time series A, and I'm seeing that quite a bit. Why do you think that is? And do you think like first, do you agree? Second, do you do. Why do you think that is? If it's true and then, where do you imagine this going in the future? Like, will you guys have big wins and then start investing in later ones in five years? Or how do you think of the investment ecosystem and why are we mostly pre-seed and seed?

[01:15:18] Brannon Jones: Yeah, yeah, yeah. So definitely have some thoughts on that. But I think it's mainly about the newness of the emerging class, the emerging asset class of deep tech. And I think to be a good investor right now, today in robotics, you got to understand the technology. You got to understand AI, you got to understand it fundamentally. And if you're somebody who understands it fundamentally, either of, you know, engineering or operations, kind of a background or whatever sort of insight you're most useful at the early stage, you're most useful to your founders. You can provide the most kind of advice there. And that's one of the things that that we do. I mean, we provide, of course, all sort of business advice, but there's been a number of times when we've been saying, hey, here's how we have seen companies in general approaching their supply chain challenges. Here's how we've seen them approach. Okay, there's sort of initial pilot design. And then one of the things we do, which is great about having a deep tech portfolio is when when one company has a question, I just offer it to the rest of the portfolio. I had somebody say, hey, I need to build a looks like prototype. And I was just telling you Aescape did that so Well, like, you need to talk to the CEO of Aescape and they figured it out. So there are shared learnings that are beginning to be developed as well within the portfolio that, those learnings are still happening at such early stages in the company. So that's that's part of where we can be most useful. So that's from the founder perspective. Those early stage investors can be most useful in deep tech. Now actually from the investor perspective, because a lot of those investors have the core insight that I was talking about with that background experience. That's actually where we can be the best investor. If you look at an operating background, I believe that I have an edge when I'm looking at an aerospace manufacturing, robotics company and I can understand, hey, this could be used, this wouldn't be use, this would actually scale, this wouldn't. Here's what we've seen. There's less of a question of will this tech work? Does anybody want it at the later stages? And that's where you would probably have a more classically financially oriented investor underwriting that. And so that's why I think just because where the industry is the tech's changing so fast, many of the investors and us, especially, we are specialists in a specialist, makes the best decisions, has the most differentiated judgment and perspectives, and could be most useful at the early stage. Now, when we talk about where is it going to go? That will absolutely continue. People continue to specialize, but I think you'll also see, greater expansion into those later stages. I'm not totally sure. That's probably not what we're doing at AlleyCorp. Again. Our, our our advantage is being operators where early stage, that's where we like to be. That's where we're going to stay. But I think you'll see more of an emerging market, to kind of provide capital for, that, that crossing the chasm phase. I think that's going to take time. What I said at the beginning was that the rules of deep tech are still unwritten, and I think we're going to start to see companies that are doing really well in the market. And in some ways, the investing landscape will have to catch up and say, oh, this is this is the kind of thing I want to fund. One thing we do also see, though, is that. Right now, it still can make sense even for there to be series B, series C, deep tech investors. I think they can actually do really well due to what I think is a short term information gap. Right now, inefficiency in the market, which is that some asymmetry? Yeah. Which is that if we go and build a robot, there's a huge difference between that robot being 85 and 99, 90 and 99, 99, 99.99% reliable. As engineers, we would see that. We'd say, oh my goodness, this thing, it's ready to ship, it's ready for commercialization. But what may be lagging from that standpoint is the size of the commercial traction rovers. You may have many interested pilots, you may have small orders and deployments. It will take some time to get those in the field. You'll have to do some debugging. The customer will have to use it and try and interact with it. And so even though we know that these companies there, maybe they've gone from your series A, they're trying to get their series B and they've really increased the reliability. They've got deployments in the field. It's much more reliable, even though we know that's a big difference. Some of the investors right now aren't actually recognizing that has real traction because they're not trained to think that way. I don't think it would be say that way forever. But for those investors who are willing to jump in and do have the key insight are looking for the right signals. What it means is that sometimes your series AA to series B prices are not changing as much as the value of the company itself is actually changing. And so I think you can actually get cheap prices in a way if you are a savvy series B, series C investor. Right now. And so we try to maintain good relationships with those kind of people that we, we, think have a great perspective. So I actually do think there's a lot of room to win as a slightly later seed investor. And then over time, that will mature.

[01:20:36] Audrow Nash: Yeah, that's my impression, too. I think that, they're not, as you said, they're not trained to see that way. And thus it's very, very difficult to get a series B funding as a robotics startup. It can be difficult to but B is like a lot of companies die when they're reaching for their B round, or at least they're like they get unfavorable terms or they get an A like a bump up or something like this. But who are the specific I would love if you can name some of the companies that you find very good for series B, like A or B investment in robotics companies.

[01:21:17] Brannon Jones: Yeah for sure. And then there's, there's a bunch. So I want to want to shout out to my. Oh yeah. But some of the ones we like to work with a ton are like Eclipse Ventures. We really respect, the way that they, that they think about it and they do their work, and they're willing to find a winner back them, believe in them, and kind of see them through lead around f prime. They do some of the best robotics investing around.

[01:21:46] Audrow Nash: Yeah from scratch them. I had Sanjay on, a little while.

[01:21:49] Brannon Jones: Just wonderful. And they have some really well developed thoughts and some insights in probably.

[01:21:55] Audrow Nash: Do a right. I don't think they do much.

[01:21:58] Brannon Jones: They do some do they do B they actually will do some B yeah. Yeah for sure okay. That's awesome. But but probably end there. We will do things with like Google Ventures. We will do things of course, with, you know, the other names, the likes of these, the address, it's the costless. NEA has been a great partner for us, too. So, yeah, definitely. Definitely, an ecosystem that's emerging. And as interest in will biotics grows in general, we're seeing more people play there. We've. Yeah. Equities. Another great one to shout out. They're a great firm. So we see more investors kind of getting interested in and and jumping into. But yeah we definitely have we definitely have friends. We like to to send it to and talk to hell.

[01:22:52] Audrow Nash: Yeah. Awesome. Yeah. Yeah. Because that that's good to know. On a related note, I'll ask after too, but I would love to have I would love to interview some of the people from these companies to get their perspectives too. I would love a connection to any of the people from those companies. Just I know, I know a bunch of investors that are like seed pre-seed through like kind of a and it'd be nice. It'd be nice because there's so many companies that are at series A and they're really struggling finding good investors. So. Okay. Hell yeah.

[01:23:30] Brannon Jones: Chairman, there would be wonderful guest. And I would be super curious to hear what they say to you too, right? Yeah. Yeah, that that'd be super cool.

[01:23:40] Humanoids

[01:23:40] Audrow Nash: Hell, yeah. Yeah. Okay. So, so you mentioned a lot of interesting things. I'm kind of at a loss for which to go with. I would love to hear your perspective, actually. So let's do kind of rapid fire, because we're coming around to the end of the thing. I would love to. And I mean, like a few minutes on each one. I'd love to hear your perspective on humanoids.

[01:24:05] Brannon Jones: Oh, yeah. So humanoids, one of the most complex robotics challenges out there. So you think about really robotics needs to be this harmony between the software and the hardware for every individual element, and you need them to be able to understand and work together. And humanoids are adding so many axes in degrees of freedom. And then you're throwing them in highly dynamic environments. But like very unscripted and open ended. So it's a, it's it's robotics on hard mode.

[01:24:34] Audrow Nash: That's super hard mode.

[01:24:36] Brannon Jones: So we believe in the ability for people to, to build these in a platform where we will experiment. And then I right now hesitate to jump in on humans. We haven't back to a humanoid company, yet. And a lot of that is derived from what I was telling you before. But one of the key metrics we look at, which is your value creation tool, if you want to create a lot of value for your customer, it's super low, right? Right now they're expensive, they're unreliable. And,

[01:25:04] Audrow Nash: They don't do that much to.

[01:25:06] Brannon Jones: And they don't do that much. Yeah. So it's hard to create a value creation metric. So when we're trying to be principled right now, when we look at it, we said, okay, we still think vertical AI robotics platforms. I mean, they are what has been taking the majority of the, of the funding. But we think they will continue to, to do that. Yeah. In the interim now, I do expect there'll be some kind of hybrid that has more generalized capability and intelligence, but isn't quite at the full humanoid level. So maybe beyond just moving apart from A to B, you know, moved from A to B and package it and sorted that sort of things. I think it'll start on a.

[01:25:41] Audrow Nash: Mobile base with one arm for that. Yeah.

[01:25:44] Brannon Jones: Exactly. It doesn't need to be. It doesn't need to be humanoid, which right now it's still very hard to do. But I do believe that that the cost of humanoids, the challenge of humanoids will come down. I just think we're still three years out.

[01:25:57] Audrow Nash: Do you have a. Do you have any guess on the timeline? Like, is it five year? Is it one year, five years, ten years, 15 whatever. Whatever you think.

[01:26:05] Brannon Jones: You know, it's hard to predict. It's hard to predict. A year ago, I would have told you, you know, that we were probably maybe two years ago I would have told you were ten years out. But even within the last couple of years, the breakthroughs for robotics, for embodied intelligence, as they call it, which is AI for for robots have been dramatic. And you see skill, you see physical intelligence, you see efforts, in Nvidia for project group. You see World Labs, all these efforts to say, hey, how can we dramatically scale up the training, data, make the AI systems robust such that robots can learn very fast. And I guess actually, Google's RT to RTX, models where some of the progenitors of all of this and kicked it off so.

[01:26:54] Audrow Nash: So much good work came out of Google for all this. It's absolutely unbelievable.

[01:26:58] Brannon Jones: Unbelievable. And they're still doing it. And the DeepMind folks, I mean, really blown away. But I guess to say, what does it say in the last 12, 18 months, we have seen more innovation in robotics AI than we have in the last 5 or 10 years. So where's 2 to 2 years? Do I probably still do ten years out? I probably think we're probably five years out. Okay. Now, before we see, before we see a humanoid doing, something, useful.

[01:27:27] Audrow Nash: That's a pretty low bar for that. Because. Pretty funny. I think the big something useful is something useful.

[01:27:35] Brannon Jones: Something useful, but useful. I mean, I mean, creating more value than it than it cost. Yeah, yeah.

[01:27:42] Audrow Nash: Yeah, I agree, I, I'm not sure on the timeline. AI the thing that I am not convinced on is the reliability of the systems and safety of the systems, but, I'm very happy to be proven wrong. I would absolutely love to have a humanoid in the house doing stuff.

[01:27:59] Brannon Jones: But yeah.

[01:28:00] Audrow Nash: We'll see.

[01:28:00] Brannon Jones: That is absolutely the challenge. But, I mean, I think we're seeing some some parallels where reliability and safety, they really do just take time out there in the wild. And so even you saw totally email raising $6 billion. They're now deployed in Arizona, California, Texas, Georgia. Right. They are getting out there. They are collecting the data. And there's really nothing to replace that kind of a thing. So, I just think that that happens a little bit with deployments in time.

[01:28:32] Deglobalization

[01:28:32] Audrow Nash: Let's see, these next two, I wonder if we can lump them together. Oh yeah. deglobalization. So you mentioned deglobalization at some point or at least the idea of it occurring. And China. Tell me about these. Yeah.

[01:28:45] Brannon Jones: Yeah. So I mean the real forces happening right now, some, people looked at their supply chain infrastructure from during the Covid times when it was hard to get anything as well. But now, with changes in administration, changes in climate, there is more of a feeling of, hey, will America be able to keep up from a technological standpoint with other places in the world? You see that China was getting like many was getting like humanoid robotics, at least from the US. But the number of even industrial products that are fully made, sourced import in China is really increasing, in China. So, like their global share of the market for robotics is probably 50%. It probably was like only 30% five years ago even. And so, yeah, that's what I'm telling you about iteration speed in manufacturing. Now, the manufacturing and robotics are so interlinked that the better your robotics are, the better your manufacturing is, the better. You can manufacture robots at low cost and high quality. And so it really is a productive flywheel. And that's what I think. Not enough founders do. I actually think it probably worthwhile for more robotics founders to just go spend a week or two in Shenzhen and see how it's actually being built, because it it will be so, so, so mind blowing. And that's why the trips we have scheduled later this year in aliquot to go, to go, get boots on the ground. So, I think like, for example, unitary robotics, is one of the, their top robotics companies, Hangzhou. And they are really putting a lot of emphasis behind it. China, like, is putting a lot of emphasis behind them and believes in them. And in some ways, I mean, we we actually see them doing some interesting demos, dancing, doing choreography where he, even Tesla, Optimus is like not not doing stuff quite like that with, it so in some ways you're seeing, oh, they actually are starting to like something that could be more of a viable, viable humanoid. And then there are many commitments, by the administration, by private companies, they are paying to say, hey, we're going to spend $14 billion on robotics over the next ten years. So they're just really, really all in seeing that as kind of an edge. And, I think it's absolutely driving innovation forward. I think that, yeah, for something like that to happen now, we need more of these startups to, to.

[01:31:21] Audrow Nash: Compete in the US now in the US.

[01:31:22] Brannon Jones: In the US. Sorry. Now in the US, it's probably twice as expensive or more, to build a similar robot arm completely sources in the US versus there. So if you think about okay, people are trying to build redundant supply chains here, it's just going to be it's going to be more expensive. And I think we need to leverage some of the advantages that we have, some of the advantages and technology in talent. We just talked about all the great stuff coming out of DeepMind. If we are going to try to build capabilities and other folks don't have, and a lot of that needs to give us the ability to, to iterate. So those are kind of my higher level thoughts, but they right now are positioning themselves to reach extremely high levels of automation and have autonomous factories and things in it. And, yeah.

[01:32:12] Audrow Nash: Yeah. What what do you think about, the US and Mexico? Like, a lot of manufacturing could be done in Mexico.

[01:32:21] Brannon Jones: Yeah, I think it's a great idea. I, I personally yeah, I've liked it. And, I think that that near showing approach makes a lot of sense. And you can take advantages from, differences in labor costs and still the cost, but I so for me, that feels like, a great, a great path forward. And I know that some companies are working on that and building some foundries there.

[01:32:48] Hype vs. Reality in Robotics

[01:32:48] Audrow Nash: Okay. Oh, yeah. So one last thing before starting to close, do you, I would love to hear what you think. Given all of the attention on embodied AI and just all the hype around robotics at this time, what do you think is hype and what do you think is reality like, and how do you think about these two things? Because, I mean, a big part of being a successful investor is distinguishing these two things. Hype and reality. How do you think about it, and where do you think we actually are?

[01:33:27] Brannon Jones: Look, there have been transformative breakthroughs since Apple level changes. What I would posit is that the only companies that are actually benefiting right now from AI, the demos that we're seeing, that we're seeing, oh, they're so interesting. It's really just kind of picking place or, you know, and they can shove, they're saying, oh, watch this, cook a fancy meal. But the onions are all chopped, the carrots are sliced, and it's just moving. It's just pushing around the carrots in a bowl. It's just pick and place. It's just a we can do faster object identification and put a thing from here to there. And it's super important to be able to recognize an object to understand where should I pick it up? Where should I grab it. But they're not doing some of those more, more kind of intense, and dexterous and complicated, tasks right now. I mean, they couldn't unroll a Ravel of tape. Even so, it's, you know, so when you're thinking about, okay, packaging things up, most of it's still done in classic automation. It would be very hard even to, like, fold up a box. It's all kind of still just picking a place. And we're seeing these awesome models, these visual language models like, you know, Google's got their, their Gemini robotics, model that they are showing some cool breakthroughs in terms of the robot understanding its environment. But I think there needs to be a little bit more time for one hardware to catch up for dexterity. And I guess proprioception would just be the robot's inability to understand where it is in space and how to move. People are working on things like that. People are, you know, making different actuators that work more like muscle fibers, such that robots can move more like humans, which value that is. Then they can actually learn better from humans, slightly more in a transferable way. From like a recording of, a human or etc. but, yeah, right now we seem a little bit capped still. And I think we're, I'm personally kind of waiting to see, okay, who can do the next level of, of utility. If you're going to have a generalized platform, you need a little bit more generalized function then. But I think we're.

[01:35:41] Audrow Nash: Seeing that pick in place. Yeah yeah yeah. Because pick and place I mean what we've been able to do that for a long time now. We can do it. That's right. But yeah okay. And maybe looking out 3 or 5 years. What's your outlook on the robotics industry? I bet you're pretty bullish on it. But I would love to hear your perspective.

[01:36:04] Brannon Jones: Yeah I absolutely I absolutely are bullish on it. I think that we're going to see robotics enter domains where they haven't classically been the same. I think that for example, retail is going to be a big space actually. We started looking at this and thinking about this and that's what brought us to that. EyeBot investment in the first place. We were, just looking at where the labor shortages were going to be the most intense we saw retail was a big space. We looked at our deal flow like the last thousand robotics companies we had seen and we saw and mapped those onto the spaces, actually, where where labor shortages are predicted. Well, we saw was that there was a disproportionately low amount of robots that we were pitched in the retail space, despite the fact that there were going to be high labor shortages. That to us, made us think there's an opportunity for people to build here. We think that good retail solutions, robotics, retail solutions can do quite well. That's what made us, identify. EyeBot, which is, fitting a little bit into that retail model. So classically under automated areas retail, we think hospitals, agriculture in some ways, we think possibly even more domestic situations, like within offices. We're seeing some folks start to build businesses there. Yeah. It's been it's been pretty interesting. I think those would be areas where we see there's been a lot of effort around robotics and cooking. I think that's probably slightly further out. But, automation within those areas where classically there hasn't been a lot, are ripe areas, in our mind. Hell yeah.

[01:37:41] Audrow Nash: Yeah. I agree with you on a lot of the spaces. I think cooking is a long way out. And agriculture, I think like, I'm really excited about a lot of the outdoor mobile robots, like agriculture, mining, maybe like moving stuff around a construction site. There's constructions. And simple, simple things like, bot built and they're not simple, but things like framing for example. Yeah, yeah. Very exciting.

[01:38:07] Brannon Jones: Very nice. Yeah. We've looked hard at that kind of robotic housing, sector. We really want to make a bet there. We haven't yet, but we would love to. And I totally agree with you. It's it's right on the horizon.

[01:38:19] Key Takeaways

[01:38:19] Audrow Nash: Yeah. For sure. Let's see. So what do you hope people take away from this interview?

[01:38:28] Brannon Jones: So two things. One, I think that I would love for them to think of be AlleyCorp as some of the most, forward thinking robotics investors at the early stage and deep tech investors across manufacturing, aerospace, robotics. So yes, please think of us. I would love for them to sort of think of the northeast and the deep tech ecosystem. They're so into it, build in it. Yeah. Yeah, really consider it. And then I would love for more, deep tech founders to, think about how they're building quickly think about those iteration cycles. Think about how can you actually speed this up from a first principles standpoint? As well, because I think we need we need a lot of, of great winners. One, to attract talent, to attract capital, but also to bring those innovations to people who need them and create that value. So I think those are some of the, some of the big things. And I also think more robotics companies should market themselves, because it's it's great for people to see what humanity can do with this kind of technology.

[01:39:33] Audrow Nash: Totally agree. Oh yeah. Well, this has been a lot of fun. Thank you for coming on and I appreciate talking with you.

[01:39:39] Brannon Jones: Audrow, thank you so much for having me. This is great time.

[01:39:43] Audrow Nash: Alright. Bye everyone.