Inside the Startups Powering the Physical AI Revolution ($100 Trillion Opportunity)

What does your vision of the future look like in 10 years in terms of robotics? I see it as almost inevitable. We will be always in the presence of a robot. In the same way that we are currently always in the presence of like a mobile device. Right now we can hand it over to someone who's never flown a drone or never controlled a robot. And they can task a team of autonomous systems to do some really complex stuff. Is the long tail of jobs such that humanoid robots are the only solution? Like how do you filter people? What is your method to say? This is a great person to join my team. I followed a similar bias and what I experienced at Euclipto, which was brilliant and pragmatic. People are better than very, very tenured and experienced people a lot of the time. The more difficult and more ambitious the problem, the easier it is to get great talent. A really weird thing we had going on. We had all these robots out there talking to each other over the radio. Some trucker would get on and talk to them as well. In natural language or there are all, they're all talking to each other. Move to this position. Some trucker gets on there. Bloody hell, are you talking about that? I'm talking to you, fleet of robots. Sorry, I don't understand that. Come on. I'm experiencing a theory of stuff. And today I have another three amazing guests on the pod. I have Michael Irwin from Breaker. He's building robots that act like humans. Joe Harris from Alloy. He's accelerating the world's path to autonomy by helping you train your physical world AI model. And a very special guest to end us off. The first ever repeat guest on the oversubscribed podcast. Australia's fastest growing YouTuber is a ratings magnet. That's one of the reasons why he's back. Co-founder of Eucalyptus. And he's now helping Australia think bigger and start being the best at stuff again. Charlie, Gearside, welcome back. Thank you. I feel quite underqualified seeing these guys right here. Looking down on us from the young Rich List. Well, I think it's a good place to start. Like you're trying to encourage Australians to build more stuff. And we're sort of going into the frontier today. I guess you could say is one of the main things I like about Angel investing. You get to peek around the corner at what is coming. And I think Michael and Joe think Charlie you'd agree. They're building stuff that, you know, the industries are on the frontier. Maybe even building into industries that don't exist yet. The hard, I reckon these guys are doing the hardest stuff. Some of the hardest stuff in Australia right now. Maybe, you know, it's up there. Maybe it's not quantum computing. But it's pretty body hard, so very impressed already. Yeah, so we'd love to hear the bounding stories of, yeah, a break of first and alloy. And we'd love to hear your comments as well, Charlie, on why building hard things is important to Australians. Yeah, awesome. Well, on that point, I want to say that I feel like all the easy problems are solved. I hate to say it. I think there's only hard problems left. But, yeah, breaker, we, there's three co-founders. We're all working as robotics and machine learning engineers. And we were looking at the level of autonomy that was being developed by all these companies. And it just didn't really align with our view of what robots should look like in the future. And admittedly, that view is R2D2. That's what I think robots should be. So a robot that you can work with without needing any massive ground support station or understands what you want to do. It, you can trust it to actually complete a task. So, yeah, just no one was really solving that problem. And with the advances in transformer architecture, there was the, like, the key bit of technology had finally been unlocked that could actually deliver that level of autonomy. So, yeah, we started breaker and been going now for two years. And, yeah, we've kind of got the, got the first R2D2 kind of bit of tech working on some drones now, which is great. Yeah. But give us an example of that. Oh, if you can pull that up, D-Lake as well. We can see some of your tech on the screen now. So I know we went for a great tour. Thank you very much, of breaker at the Australian Technology Park. And, like, it's literally like talking to R2D2, as you said, right? Natural language to the robot and they speak back or communicate back in that. Yeah, yeah, exactly. And I think the main thing is that we, what we want to try and deliver is rather than having, like, operator command, like you have a bunch of robots and you say, all right, this robot, go to this place, look in that direction. We want you to give operator intent. So we don't want you to think about what robots you even have or what capabilities they have. We just want you to provide your intent to that team and just say, you know, I want this thing done. And the onboard agents on each of those platforms work out how to do that. They work out what resources they have, what capabilities they have, and what the best way to execute that is. And for us, what that looks like is the system is just insanely easy to use. Like, you need zero training to work with a full team of robots. So like right now, we can hand it over to someone who's, you know, never flown a drone or never controlled a robot. Can you give us an example? Like, I think one that you mentioned, you know, fly up to 100 feet, look for a white sedan in a three kilometer radius. Yeah, yeah. Like if you think of like a security task, like let's say a security officer and he's got a whole lot of drones with them, says, you know, I'm a little bit concerned about this area. Can you just go and check that nothing's happening in that area? Or, you know, can you just monitor this road and make sure that, you know, this thing doesn't happen on that road? Or, you know, if you've got another robot that you're working with and you just want something done, and yeah, you just provide that intent. So the first kind of, the first industry we're going after is actually defense. It's a very mature user of robotic platforms. And in that scenario, like these kind of commands are really relevant. Like, can you monitor this area or look for this thing? You know, I'm worried about this in this place. And that's all you have to say to it. And it looks after that task. Before we get back to the conversation, I want to tell you about the sponsor who made today possible, Vanta. As a startup founder, you're juggling multiple priorities from the expected, like finding product market fit, to the unexpected, like customer requests for SOC to ISO 27001 certification. But achieving compliance is time consuming. And time spent on it is time away from needs of the business. That's where Vanta comes in. Vanta is the all-in-one solution for startups to become compliant quickly and build a security foundation with ease. With the combination of automation and extensive partner network and a security marketplace, Vanta provides the necessary tools and expertise for startups to achieve compliance seamlessly, no matter how urgent your needs are. And at every phase of growth. Over 10,000 leading companies, just like the ones who have been on the Overseas Drive podcast, like EverLab, Relevance AI, Instant, Alloy and Atlassian, trust Vanta to automate their compliance so they can focus on growing their startup. Startup customers get $1,000 off at Vanta.com/over-subscribe. Hey Michael, I want to understand how hard this is, because I've heard the reason why we don't have a Alexa or an Apple Home version of LLMs is because it's so hard to get. The probabilistic aspect of LLMs to integrate with the deterministic aspects of objectives. How do you guys progress on that? Yeah, this is a great question. So the most difficult thing is that, especially with using machine learning for decision-making, there's always, you have a probabilistic error. So if you have it on a robot that's making thousands of decisions every minute, you have an enormous chance of incorrect decisions being made. So that's kind of breakers secret sources. The leveraging a small LLM, so an SLM, to manipulate a decision-making system. So you have a very dynamic decision-making system. But we split it into two parts. So we have what we call fast decision-making and slow decision-making. Slow decision-making is manipulating the decision-making algorithms that do the fast decision-making. So we can put great checks in, make sure it's very reliable when it does manipulate those. But the fast decisions are made algorithmically, so they're deterministic. But the expectations of your users is going to be that the tolerance level. Yeah, 99.99% right? 100%. Similar to SAS when you're like, "Oh, my uptime is four-niners." That's going to be the kind of conversation that's going to happen at these SLAs. Totally. And the way we've kind of dealt with it now is by pushing back on the user. So yeah, if I. Rayling Gracefully is the biggest challenge. And what we do right now is like, okay, if you've asked it for something, like let's say you send a drone out, it tells you about a car that you were looking for, and you ask it, what's the number plate on that car? Can't detect the number plates. The system falls back, it says, look, I can't detect that, but here's a video so that you can see it. So that's kind of how we're dealing with it right now. - No, it's not going to be honest. - Yeah, yeah, yeah, yeah, yeah. It has to be honest, I think that's the-- - It's not of this hallucination of, oh, you're exactly right, here's a made up fact. - Yes, exactly, yeah. - And it's almost like deaths, road accidents, and what, how low that's going to get with self-driving cars, right? It's like, people don't understand that the robot's ability to make a lot more decisions of what faster can counteract the fact that maybe a good chunk of them will be wrong. - Right, yeah, totally, yeah. And I mean, I think the other really difficult thing that we're doing is we want it all on the edge. So we want to put all of this decision-making onto the agents, it kind of goes with our view of what autonomy should be. Wherever you have the intelligence, you have to send the information to that place where the intelligence sits, right? Now, if you are, if your intelligence is on an open AI server in LA, you got to send all that video data, telemetry data, everything to that server in LA. And I mean, like when I think of us eventually having robots in our homes, like a figure kind of robot in our home, I'd much prefer that that happens on the edge and on the device, and you have all of that locally happening where you can kind of see it, and you know where it's happening. So privacy reasons kind of thing, or? - Yeah, privacy, I mean, in defense, the edge computing has a lot of benefits because it lets you deal with electronic warfare and a lot of low bandwidth communication, all of that kind of stuff, but jamming essentially, right? - Yeah, jamming. - You're trying to guarantee that you're gonna have a network on the Internet. - But, you know, like we are, we're starting in this industry and we plan to spread to commercial robotics as well, and it just kind of aligns on what our view of commercial robotics should be, which is, yeah, like for privacy, like you have a robot in your home, you know that that robot is your robot. - It's your robot. It's doing what you want, and it's all happening in your house. Like, yeah. - And is that save on compute cost as well? Is that like the nice little sun? - That's actually the secret agenda. (laughing) No, no, it's, I mean, it's way more difficult to do. Like the level of, I mean, the easiest, like it's so much easier to just have a massive LLM sitting on a server somewhere, the complexities of putting all of that intelligence onto the edge of actually, I've got the, well, I've got the piece of compute, like it's kind of, like that's what we're targeting at the moment. So, - That's very Steve Jobs. Like, - Yeah. (laughing) - I have a dream to start, - Just to work for the live there. - Watches. - But yeah, I mean, like we can put that little piece of compute into a lot of robots, right? Like it's tiny. So, that's kind of, like that's what we have to achieve. - And Joe, alloy, very excited to hear about this. Congratulations on the fundraising round, amazing news, amazing cap table, amazing supporters. But on the last episode of the Oversource Rob podcast, Charlie mentioned your, in his top three people, he's ever worked with, which is high praise. Not sure who the other two are. - I was, too. - That's what I said about that. - And you've got three co-founders in the previous business. (laughing) - I was gonna say, he's one of two. - He's one of two. - It's all relegated. - Well, he didn't say, I'm not top. He's not top three. - Oh, I'm top three. - Oh, I can't see. - I mean, they're running. I mean, they're running. - But me, like, super excited, to dive into alloy and have been building for almost a year now, you're very highly regarded in the Australian startup ecosystem. So, mate, please tell us more about alloy. - That's very kind. And Charlie did name his first son after me. - Sorry. - That's also high praise. - Wow. - Yeah, I just kind of get enough of this guy. - My wife is seriously concerned. (laughing) - Look, I think I've been told it's a, I've been assured it's a coincidence, but, you know, her name's a name, so. (laughing) - Yeah, so I left Eucalyptus after four years in August of last year. So, it's just gone over a year. But at that time, I just knew that it was time for me to go and start my own company, my own journey. And I didn't, I hadn't exactly locked in what that was going to be at that moment. It was quite a, I guess, a burn this ship's moment for me, to just ensure that I didn't have a safety net, 'cause Eucalyptus was, obviously, is an awesome company. And so it felt like I needed to sort of get out of that so that I would force myself to figure out what that next chapter was going to be. But I'm originally, like, people kind of, I guess, know of Eucalyptus, and they know of my work there as sort of growth and marketing a lot of the time, but originally I'm actually a electrical engineer. That's my sort of educational background. And I then worked in Alassian as a software engineer working on dev tools and the ecosystem and then growth. And that was kind of the segue. And so really, since I've been a small kid, I wanted to work sort of on robotics and space. Those were sort of two areas, I think, like a lot of little kids was really, really inspiring, but was just not the time to work on that when I was graduating. My opportunities as an electrical engineer included working at Telstra's commercial office and going to work it down at EDI, programming, like mining, like sort of microcontrollers, or working at the railway. And it just didn't excite me in that same way. And so I ended up at Alassian, which was obviously really exciting at that time, the company to go to. And so when I was leaving Eucalyptus, I sort of, a new alert, the next thing had to be sort of even more ambitious, it had to make sense that I was good leaves such an awesome opportunity at Eucalyptus to go do something even bigger. And so I got very, I guess, inspired by the re-launch reusable rocketry that was going on, and Starship and the cost of getting kilos to orbit coming down exponentially. And so it started to feel to me, analogous to the age of exploration from hundreds of years ago, where we first figured out joints.companies, were able to figure out the economics of getting a boat of things from one sort of continent to another. And it just led to this multi-hundred year sort of age of doubling the global GDP and so much opportunity. And that felt like the precipice of what we were on again, but now the economy is $100 trillion, you know, instead of 10. And so I was excited, I was getting into it, and I was like, okay, well, if we're going to space, we're going to be doing industry there. So people like Vada, people like Fleet Space, they're doing awesome work. Obviously if we're doing that, it felt that the next thing after industry, once you go and you start growing things, you need someone to go and harvest them. And so you would have settlement come after. And so all of this was to say that I felt that if we were to settle in space, we would need a food source, and that led me to indoor farming, 'cause if we're going to grow it in space, you need controlled environment agriculture. And that was around the same time if you remember in 2021 and too, a lot of fundraising for indoor ag. 24, a lot of deaths of those companies. If you're sorry to billion dollars sort of nothing to kind of keep going with, a lot of them pivoted, but relatively unsuccessful. And I was just super curious as to why. And it just kept coming back to this question of automation. You would think it's the power and the electricity, but the real killer cost was the labor. And they scaled so quickly to these giant footprints that they needed an enormous amount of labor to run the factory because the automation they were attempting to pull off was not at a level of this 99.99% that you would need to make the economically viable. And so I spent a lot of time, I spoke to dozens of founders of both these indoor farming companies and people who were working on the automation side of it. Some people who perhaps maybe had worked at one of these and gone, you know what, I'm going to go do the fruit picking arm 'cause we need it. And then maybe been unsuccessful with that after a file for years and a lot of very tough conversations with them about sort of the realistic experience of building that kind of company. But it was also the confluence of, you know, LLMs bringing the cost of this edge compute down. The LLMs themselves getting more efficient and smaller and more performant, getting multimodal. There was all of these factors happening at the same time. I felt like, you know what, this might be the moment where we actually can work on robotics for the first time in a material way. And there were plenty of great companies that have built up over the last 10 years, but you're seeing like this proliferation of new companies now. And I just realized if I wanted to do this strawberries in space that I needed to solve the robotics performance and reliability issue, which ultimately came back to the management of the data and getting value out of that data. The telemetry that we were just talking about a second ago, if it's producing many, many, many, many gigabytes of data, sending that all of it is like finding a needle in a haystack for the 1% of the matters. And for a lot of companies, there's just no reliable way to figure out which 1% and so that is the problem that LLOY has created to solve. Helping those robotics companies figure out which 1% of their data is useful and is valuable and speeding up their rate of iteration so that we can get to that abundant future faster. - Wow. And so what does that look like for the user side? So they, you have customers, they come to LLOY, they use your software or. - Yeah. - Our customer group is people who make the robots, you know, someone like a breaker, for example. And they produce a lot of multimodal data. And so they would integrate with our platform. We support sort of different kinds of deployments but that kind of gets into the weeds a bit. For them, the data would flow in. We would give them this orchestration layer. We make it all searchable with natural language, sort of like a search engine for your data. Not just for the images, 'cause when people think of robotics, they think of perception. but- A large amount of the data is also these time series, these numerical graphs of things. And that's actually almost just as important, if not more important, sometimes than the vision. Because you may have an issue with one of your actuators, one of your motors, but I won't show up in the camera. The camera looks fine. But the arm is not doing what you expect. And so for a lot of these engineering teams, the tool set is mostly around images and mostly around supporting vision. But there is not a huge amount of support for time series and for text logs and images, all as one thing. And so that's why we want to be that first robotics native data platform, data infrastructure. Because historically, there maybe just wasn't a big enough time. But the timing of this is really perfect. Yeah, that's awesome. Sounds like a hard problem to solve. Lots of fundamental machine learning, lots of fundamental mathematics. The team is a lot of data scientist, data engineering. People with PhDs and robotics, but also PFT and maths. That kind of style of team. As you know, guys, Vanta are the biggest supporter of the Australian startup ecosystem. And we have cooked up a unique event slate to finish 2025. Founder versus investor, Padel, which is the world's fastest growing sport for the fastest growing startups in November and Sydney. And we have 361 Angel Club in Sydney in November, where you can meet 100 investors and 100 founders all on one night. Then to end the year, we have the 1013 runway conference in Brisbane on the 27th of November, featuring 500 founders and investors. Simply go to oversubscribedpodcast.com/events to find out how you can apply to these events and meet the best founders and investors in Australia. So you've got the idea for the company. You've done the fundraise. I guess for both of you guys, I know Alex Cup from Palantis says the best engineers look for hard problems. So how do you spot that talent and attract these people to solve these hard problems? Going to the joys of the joys of the-- You've got eight now, right? So you've just, but you've literally just hired your latest crop of geniuses, right? That's right. Yeah. I mean, it's kind of you alluded to this before. And I imagine this is a similar experience for Michael. It's actually the more difficult and more ambitious the problem, the easier it is to get great talent. Yeah, that's true. And I was part of the decision making of like for myself, I want to do something that's ambitious and interesting. But so do the other-- the best people in the industry. That's what they were looking for. And sort of for me, I'm that sort of joining factor of being able to bring the resourcing from the funding and sort of the network to then create an environment where we can go and push the boundaries and do this really interesting work. So I put a post up on LinkedIn just expressing that this is what we're going to do with this general direction, not even the specifics. And we got well over 300 likes on that, which got in front of many tens of thousands of people. And so all the inbound came from that and then the referrals from those people. And we've gotten some really excellent hires just off that one post and we're now pretty set for now. Yeah. How do you-- like how do you filter people? I followed a similar bias in what I experienced at Euclip to switch was brilliant and pragmatic people are better than very, very tenured and experienced people. A lot of the time, especially for how changeable the startup environment is. And so I really have built a great team of both experienced people but also I really went into passionate people that they're doing side projects, they're shipping things, they're demonstrating that they are a driven person outside of just having stuck it in a job for 10 years or 15 years. Yeah. I don't think anything beats passion. Someone that's really passionate about the problem and is excited to actually solve it. Yeah. I remember when we went to a breaker, very strategic investor movie, book the meeting for 5 p.m. come to the office, meeting went for two hours. But it was the Thursday or Friday as well. And legitimately, every single person was still there at seven o'clock, like the buzz and atmosphere. It was pretty crazy. 12, 14 people in there, all coding away. You know, we've got the hardware everywhere. Yeah. It was finding passionate people like that. It's amazing. Yeah, 100%. People that just enjoy doing the work. Did you pay them a bonus for that? It makes a 200 bucks under the table. I just think that the brand is coming in. And Michael, what about values alignment? Given that you guys, you know, your wedge is defense. But I would say that your aesthetic is quite defense orientated. Yeah. Do you-- and obviously, some people on faith value, I disagree with these people, that reject defense on some ridiculous moral basis. And don't really appreciate how freedom is maintained. But have you had any troubles with hiring people that are mission aligned to defense? Or if you found that quite easy in Australia? Look, we haven't found it to be a huge issue, to be honest. I think you crane changed a lot of people's perceptions on defense companies. Like, you know, when we kind of watched in real time, like a country that looked quite similar to ours, get invaded. I think a lot of people kind of had their realization of, like, you do actually have to be able to protect yourself. And, you know, there are bad actors in the world that you have to be able to defend yourself from. So I think that changed a lot of people's perception on working in defense. And I mean, for us, like, we have-- especially if you know what, we're obviously building AI in defense, which has a whole-- like, there's a whole nother range of ethical considerations that come alongside that. So, like, for us, we have very clear company values. We make everyone aware of those company values, and we build our product against those. And we're also just very, like, very honest with people when we interview them. Like, you know, the company has to be a fit for them as much as it is a fit for us. So, yeah, just being-- this is exactly what it is. Like, if you're comfortable with this thing, you know, love to have you. And you probably find people opt in, like, dry imagine a similar thing with, like, techno optimism and, like, the oncoming robotic-- Pond and other. That's definitely a component of it. But I actually think I finished the final interview with an anti-cell, because the team is so early stage in the company's life that I want to-- I want them to buy in despite knowing all the watts and all. You know, it's like, this is going to be hard. It's going to be-- it's a period where we're going to have to work quite hard. There's going to be times where we ship something. We have to unship it, delete it, sort of way start again. Wasted work, wasted time. We have to remain humble and changeable and hear feedback from customers that we might not want to hear. And I want to tell them all that stuff up front. That it's not going to be this kind of, like, late stage tech scale up where you just kind of chill, get free launch, and clock off right away. That if there are places where they can go and do that, and they should, if that's what they're looking for. And I've had that to be rejected people from big tech because of those factors, where it's just felt like, for them, it's not the right time. It's not that they're not brilliant. I still think of very highly of them. But I just felt that at this stage in the company's life, they were just not the right fit. That's a change in the last, I guess, two years. So obviously, the Trump administration has come in, like Andrew, I know, you're a big-- Palmer Lucky fan, Charlie. I love the bloke. Yeah. I know you've got a few of these good shirts as well. I've even got one up here. Was that an actual would you, Palmer Lucky shirt? Yeah, you were. You were it. You can see your sweat stains. That's crazy. That's crazy. I've got that just for you. But I guess, yeah, how has it changed in the last year? Obviously, Andrew, you know, Trace Stevens, Palmer Lucky, raising some good capital, attracting good talent, mission-aligned people. Like, have you seen, I guess, Michael in the last two years, a bit of a shift in investor sentiment? One, 100%. Yeah. Even in the last year, to be honest, when we raised our first round, there were very few VCs that were interested in defense investing. Especially for us, where we're starting in defense. And yeah, I think those defense unicorns that came out of the US changed a lot of people's opinions about defense investing. The US is obviously incredibly bullish at the moment on investing in defense companies. And that's kind of-- I think that's sort of bled across into Australia. And there as well, which is great. And if you've got your co-founder Matt, rather than the US, who's X-Andral as well, who's a person who must help with investors? Yeah, no, for sure. So he's Matt worked at Andral before we started Breaker. And yeah, I mean, I think even the-- Andral's an awesome company. Like, they do really cool stuff. And even some of the connections that we've had from there have been really helpful. So yeah, it's been good. May, what do you love about Palmer Lucky, Charlie? To just-- I know you can use Twitter feed. He just says whatever-- like, he speaks so much truth. And when he comes back at people, he just like-- He's got a great mallet. Yeah, he's got the aesthetic downpatter. Yeah. He's about to give you zero fox, basically. But you went to-- I don't know. You followed him for a while. Yeah, it was like, he spoke back when they acquired the Australian submarine company, which name escapes me. They basically-- he was over and he spoke at the pub in the middle of the city. So I got a few closet, sort of, right-wraiting folks from you who just sort of-- who wants to come and watch Palmer Lucky speak. He said, closet, I thought you meant you were going to like raise closet for a day. Oh, no. [LAUGHTER] He was actually-- yeah, he's a great speaker. So that was good. And I guess the US, obviously, a lot of your customers there, like how did it-- like I didn't even got Matt over in. Austin, you said at the moment, what's the sort of strategic decision behind that? Yeah, I mean-- I think we realized pretty early that if we wanted to build a scale of company that we do want to build, a lot of that effort has to come out of the US. So it's an unfortunate reality of being an Australia is that if you're competing with US companies, they have access to capital and market that we just don't have here. So we need to get our foot in to have some of that. Coming for us, we'll raise our next round in the US, we'll definitely, I think most of our work will come out of the US and we'll kind of try and cling to stay as much of an Aussie company as we can while that happens. What about you, Joe, do you imagine a lawyer moving to the US one day or a split team? Yeah, I mean, we are currently working with probably the best robotics companies in Australia, so it's kind of where we started. Go through and try and collect them like the Pokemon gym badges. But they've been really instrumental in sort of the early feedback in R&D, but we will obviously hit, you know, if you're going to be a venture back company, we've raised, you know, $4.5 million, that's a substantial wicked. There's going to be expectations that come along with that of the type of scale that we can achieve. I believe very firmly that we will. That's going to require expanding out of Australia and sooner rather than later. You know, I sort of split my time. I go over to the US sort of every couple of months, typically around San Francisco, but we'll also, you know, there's plenty going on in other areas in the US as well. And so part of that is pipeline, building up relationships, just getting more established there, investors as well, like I've noticed, even as you mentioned, like this year, so I raised that round in February of this year and incorporated the company on my birthday in February. And so that's like, that's a great birthday present. Yeah. Six or six or seven months ago now. Obviously, it was like ideation phase before that, but that was when we really kicked off and earned its first full time in May. And even since then, there has been a really market shift in VC sentiment in this space. So when I did the rounds on that first, first check, like robotics broadly were still seen as a highly, highly skeptical, like why now? People have been saying it's coming for 15 years. Why is this time going to be a big deal? And that was the prevailing sentiment of a lot of venture capitalists. And at the time, it was obviously like peak, agentic LLM focus, like that's kind of what your business has to look like to be interesting. But then I'm already starting to see like these memos come out of a lot of these big funds that are talking about the enabling layer of robotics and how important that is going to be for this next wave. But you know, Nvidia's been preaching that for a very long time since February even, big shift. And now it's getting quite a lot of new inbound of like, oh, what are you guys working on? Like, can we have a chat again? You know, people who were like, oh, we don't really think this is happening now coming back and being like, what actually could we have a chat? Preempting the next round. At least wanting to get the information to decide. That's awesome. I'm sure you have a good birthday in 2026 as well. Yeah. I've been angel investing since 2017 made over 80 investments. Many of them through 1013. So 1013 is Australia's largest network of angel investors. And each month we send out a curated list of one or two deals that you can choose to join in on the journey. These are companies like EverLab and Instant that you've seen on the over subscribed podcast and other companies like Go One, Mr. Yarm and AutoGrap. If you're interested in finding out more about the world of angel investing, I'm happy to jump on a call, share some more stories and tell you about the exciting companies that we're currently looking at. We're going to 1013.vc/over-subscribed and you can book a call with me for next week and we can talk about all things start up and angel investing. What about other differences in the US? Obviously you guys are over there a lot. Not just on the defense side, but I guess the founder side. Do you guys get inspired over there? You're meeting people like Trace Stevens and Palmer Lucky. Have you been to El Segundo? Is the question? I haven't. So what is it? If no one's seen that, I would say get it up, do you like it? We'd be looking at it at Google Earth, picture, but it's basically a part of LA where I'm pretty sure it was like an industrial backbone of US manufacturing, but it's been taken over by startups basically. I'm pretty sure Andrews there. A lot of the fans in space. Defense in space. Yeah, it just looks amazing. People just driving around in pickups and they're close to the beach and just like welding shit. It feels like it would have the opportunity to almost become the shenjian of the US. Right? How that came from farmlands to industrial metropolis in like one generation. That's actually a good point. When is Australia getting a special economic zone? Is the question there? Where is it going to be? I've heard it's for bar and bar. It's a bit of a. I feel like that's already a special economic zone. Exactly. For him, you're an economic zone. Maybe wherever you put your research facility, Michael. Yeah, the Southern Highlands. Found it. Yeah. We've set up in Austin in the States, which I love Austin because it's a bit weird as well. You have self-driving cars and then Texans wearing big hats. It's just the mixing of worlds is great. The manosphere of comedians as well. Oh yeah. You know, like Theo Vaughan and Joe Rogan. It kind of like matches, you know, like the San Francisco dance, bro. Yeah, exactly. But when I bring it back to Australia, Charlie, I know you're working on a new initiative called Build Australia. Like how do we get these certain kind of zones? How do we get people like Michael and Joe, you know, keeping them here longer, getting bigger technical teams? Yeah, exactly. We like to hear about it. Yeah, it was like it originally started as a tweet. Do you mind pulling it up? It's not. Yeah, you might have to scroll back a little bit, but it's if you come up, it was basically, it was a retweet. So it wasn't even, it was stolen, Valor, basically. Toby Lucky and a bunch of Canadian. If you go back, if you go back a little bit, there it is. There it is. Yeah. So Patrick Colson tweeted, coolprojectbuildcanada.com would be cool to have this for Europe and Ireland. So I literally just retweeted that when it's your version of this Australia, who wants to get involved. And I think at like, within 24 hours, we had like 50 or 60, you like, really you like intelligent and like patriotic founders, engineers, designers in a, in a DM thread and soon a WhatsApp group of like, hey, let's actually do this. That's when it gets serious. Yeah, it gets serious. And I, yeah, I was not planning on, and Pasha, who's been on this pod is heavily involved in that as well, in this as well. And we were like, yeah, we went, he's got to start up as well in white, white comedy. And he's like, I wasn't planning on doing this, but when you get that many good people in a group, it's like, like, in a bottle. And so we're like, all right. So about three or four weeks ago, we started building a brand, a sort of like marketing arm of the ideas to popularize ambition and Australian excellence in industries like what you guys are in. And it's not going to be a think tank. I promise you. But you will be able to build by some awesome merchant just like, I don't know, it's almost like the effective acceleration movement with an Australian sort of wink. So yeah, nothing fully built yet, but what's this space really? Is there anything from build Canada that you liked or didn't like? What's the, what are you pulling from it? Yeah, well, then more, I would say they're more of a think tank. And so what I did like is that they build tools. So they have like an outcomes tracker for like politicians. If you go, do you like if you go into projects, you can see that they've done a bunch of things like, I think they've done like a tax calculator to like just encourage people to like essentially what would a enterprise, your own enterprise look like to encourage people to actually start shit. And they've got another one which is like holding politicians to account like more open data stuff. We've come up with our first, we're doing a tool to launch, which I won't spoil what it is just yet, but something in this vein that draws attention to the fact that what a people think that, you know, when the great Australian thing is when someone says, oh, we should build X here. People say that it's unviable. As you mentioned earlier, Joe, because of either energy or labor costs, therefore we shouldn't even try. And I think it's time to call bullshit on that. And yeah, we got something in that realm coming. And I feel like that's a narrative not just in Australia, but in a lot of countries at the moment, this like re industrialization, re-nationalization of supply chains, having sovereign capability, not being so dependent on the network of other nations that might have shifting ties of relationships with. Totally. Yeah, it's so bizarre to me that people like to cost things out as if the costs don't amortize over time of any new venture. And there's no additional benefits for trying. And the government's basically been unwilling to put their thumb on the scales and give us an unfair advantage where you look at career in China and where their government's literally, subsidize entire industries until they get set up. up the unwillingness of that to happen here is really frustrating and so we're trying to shine on that basically. Yeah I think Australia always seems like we're scared to pick winners. You know like we don't want to pick like an industry that we are going to back to be world leading or we you know we just don't seem to be willing to take big risks on you know big outcomes. It's unless you're psych quantum. Yeah exactly. That's really relaxing. That's what a boy said that on that. That has been good though. Like that is a good example of it. Like that is and I mean like the Australian quantum computing is like awesome now. We're actually the head of the game it's great. What's strange to me though is that like I think the pick winners thing I think is overstated because it's like oh capitalism is like delicate ecosystem. Yeah. It's I don't believe that it necessarily is but if you are going to pick winners maybe you putting money into one company is not the way to do it but look at entire industries and ways to sort of fund yeah individual ecosystems like defense like solar panel manufacturing or lithium battery manufacturing. I mean there was that article recently about the Australian battery manufacturer that like went you know went into administration weeks before a new government grant was just was coming out so I think wow yeah we're shooting ourselves in the foot when it comes to that stuff. And we're just pull up your YouTube feed here like you've done many awesome videos what what type of feedback are you getting from yeah the general public like is this where the momentum is going to start for the build Australian movement. Yeah I think the idea with the YouTube channel was basically just a share some learnings from the Euclifters journey and try and get Australians more bought in at a grassroots level that like maybe instead of buying an investment property that I would put that money into buying a business starting a business and producing some actual value and also getting rich along the way. And getting rich part seems to appeal to people and those videos have done done well like this was the first video about e-shop and sweat equity which people have responded well to a lot of people didn't really know that sweat equity is the thing. Yeah the more macro view that like this is what ownership looks like this is actually useful pathway that maybe Australian that the fortunes of Australia can change if we all start to build more stuff and you know we can leave a prosperous life. Is there one industry that you guys are going to go after first like is there one is it manufacturing like what's the what's the first thing that you guys are looking at kind of giving a bit of a boost. Yeah I think I think manufacturing is the most salient because it's so yeah it's in the dumps really and it's so visceral and evocative and can be so futuristic. Yeah yeah I think that seems pretty obvious but then you know there's energy and all that kind of stuff. It's like that whole thing around you can embargo the sales of chips and you have to throttle the AI chips that go to China but then if China is adding your entire country's energy production every year in solar they'll just have a bigger data center. Yeah. It's have more chips. It doesn't matter if they're less powerful. Exactly. Yeah you're playing the game on too small a scale I'm not seeing the picture that's coming. It's crazy to me that the one part of the energy equation that people seem to be I mean we're talking about transition we're talking about how we bring more power online but China is streaks ahead because they own the entire supply chain for like particularly around solar like you know Australia essentially invented the photo Voltaic cell. And we don't produce any of that here. We've got sand. Yeah. We've got sand. It's crazy. There's that photo. I don't know if you've seen there's a photo and it's Martin Green who invented the like he was you know worked on the first solar cell. Yeah. And there's I think there's three other guys in the photo and I think two of them from that photo went on to start the biggest solar manufacturing companies in China and like and those guys did their PhD in Australia you know and this yeah kidding. Yeah. Yeah. That's yeah. That's outrageous. But we'll have wrote we'll have robot production lines before long. It's going to be necessary right and that's going to be the forcing function. I don't view it as like he's waiting for robotics. It's going to be the driver that's bring pulls it into the market like because of the fact that we you know if we're the thing I think about a lot that kind of scares me and gives me up at night is just the current like rate of inflation and people expecting I will normalize you know come back down to 40 years come back to cyclical like what if it doesn't right like people who are growing up in the future having a worse time than the people who grew up in the past is not the world that we want to be if we're actively able to affect the future we should be building the better one. And for me it's not going to just come from you know us like tweaking the rates and fixing it that way like it's always come from technology to technology has always been the big deflationary force and that comes with consequences and externalities that we need to manage and be proactive about around job transitions and things like that but it is for me the only way that we can counter and address the like looming sort of affordability crisis for the future generations of not just this country but every country. Absolutely. Well said. I mean what does your vision of the future look like in 10 years in terms of robotics? Would love to hear both your takes. I think there's going to be a lot more robots. I think there's going to be a lot more robots that do a lot of the things that in the same way that LLAMs have kind of automated very low level tasks in industry like software engineering. Like sort of those a lot of those in turn tasks now in any software business that's now done by a senior engineer with an LLAM. I think we're going to see a similar shift like that in you know a lot of basic menial tasks will start to get done by more advanced robots that are easier to work with and you know hopefully clever and better processing data. Do you think like an optimist in every house like a specialized or generalized robots what's going to win? I have a feeling generalized robotics is going to win. I think it depends on the timeline of the question because if we're sort of being asked about 10 years I like I actually think the answer is going to be it's both in the same way that we currently have like we are the generalized robot in our home and we use a bunch of specialized robots like washing machines and dishwashers and ovens and things that do very specific deterministic tasks. But if you were to have specialized robots that perhaps need to be coordinated there may be a more generalized layer whether that's physical as a humanoid some other form factor whether it's digital as some kind of data orchestration. Is the long tail of jobs such that humanoid robots are the only solution do you think? Like for example I was thinking about climbing a ladder and replacing your roof tiles. That is such a niche job that you have to do once every couple of years potentially but having something that could do it is that sort of make that popular. I do see that because the world has been formed around human form that you know the obvious choice to initially get traction will be to be able to backwards compatible inserted in. And so I think we will see this like boom of those robots in that form factor but it may be a local optimum. Yeah. It's like backwards compatibility is a go away. Right. It's legitimately what it is. It's like we created a system and now we have a new update and the new update is the humanoid robot or a new a robot of any kind and the best form factor for it is to be humanoid so that it's backwards compatible. But that may not be like that's a cost efficiency to return equation right. How quickly can I get this into the market? How it doing productive things and making me back value but that might not be the you know they may retool the whole factory to be a much more optimized specialized robotic system. There's more like people talking about these robotic dreadnought factories right. It's like fully end to end like measured in units created per cubic meter per second. But that will come after right. It's like you'll probably side load in all of the humanoid robots and get the value and then the next competitor who comes and just drops them will rethink it from first principles. Yeah. Where do you think the end state of it is because you still want people to have jobs right. You still want people to have a purpose in life to go out and when I think the latter part is the important part is they have a purpose and meaning but we've kind of we've entangled that to be one to one mapped to a job. Yeah. And that your meaning is your work and obviously getting meaning from labor is a key part of our like fundamental DNA and our like primal survival instincts. But I think that we've been on this curve for a long time of doing physical labor then doing knowledge work and then now that's like each of those is getting kind of updated. And it's like we're probably just moving up the strategy chain. Like you end up everyone's jobs look much more like playing an RTS than they do like moving bricks. Yeah. And think about the the toil on the human body that is based on that definition of needing to go and do those say like heavy labor as a function. Like it comes with a big human cost like giving people other options I think is actually a good thing. So I'm walking down the street in Surrey Hills in 2035 turn right going to my apartment. I walk in what's it going to look like in terms of the user experience from a robotic point of view I guess. Love to hear your takes. What would be a skyscraper? It would be an underground silent. in Wentworth? - I'd love to have an optimist robot. Sign me up. - I reckon. - I hate cooking. - Something can do my cooking for me, I'll be so out. - Yeah. - I see it as almost inevitable. I don't have 10 years as the right timeline, but I think it's in the order of like 10 to 20 years. Like we will be always in the presence of a robot. - Yeah. - In the same way that we are currently always in the presence of like a mobile device. - Where does the VC space see it going? Like what is, I mean what are you guys looking at? - Well as Joe said, the VC is only think it's an attractive space in the last six months. So still got to develop out the thesis. But you know when people like Elon investing so heavily into the optimists they want to make one in every single house. Like it's pretty compelling proposition. You know a lot of the sort of funds and angels in the US to saying you know it's going to make Tesla the most valuable company in the world. Which obviously already got a very nice market cap. But yeah, yeah, you definitely wouldn't bet against him to yeah change the way we live again. - Well I think you know we've seen the bit or less than around the main driver of improved LLM performance being more compute and more data. And it doesn't necessarily have to be specialized data. It's just more. And we're exciting to run out, right? Like the online corpus of human knowledge. We've been pushing that scaling law pretty hard. And we've almost reorganized. You think about now all the conversations that we have with these LLMs is sort of creating that new knowledge that they couldn't train online. And so we've almost reorganized around the incentive of I get value when I do this. But really we're just feeding the LLM. Every person who logs into chat GBT and has a conversation with it, we're just feeding it. And I think you know similarly we originally were feeding the internet and then they used the internet and they fed it to the LLM. And now we are feeding it with these new conversations. So why you know Elon's got X and that feeds right into Groc and that gives them a huge real time corpus of information, information breaks on X and it's fed into Groc. I just see that one of the reasons that we started alloy was because the data from robots is so heavy because of the perception data. Like vision specifically, very heavy data. One gig a minute, pretty normal. That density also means it's very rich of information compared to text, which is quite sparse. And so if I think this is the reason why you see all of these labs trying to now collect both multimodal data, they want to give you a reason to give them images and videos because it's way better for training. The next frontier. And then doing physical devices like the acquisition of I/O from OpenAI so that they can get the pendant, they can start capturing the real world. But then you look at something like Tesla, it's already got like hundreds of millions of hours, if not more, of driving data, which is really just eight cameras pointed out the physical world. And then once there's an optimist in every home capturing video, it's like you start to see that that becomes a game. It's like where are you sourcing the network of data to feed the digital god that's being created? Yeah. How important is that the richness that comes from the data, like cameras or microphones in the real world? Because I suppose you could say that text, the corpus of text is about the internet. You said judgment where it is knowledge about something that reveals something, whereas those other data sources are sort of like representations of reality. Yeah. What do you think about that? Descriptive versus declarative kind of thing. Yeah. How useful is the 100 millionth hour of driving data compared to having micr-- images of them under a microscope, for example? Yeah. Well, I mean, that was kind of the big battle that's been playing out over the past few years. If you're like scale AI is, for example, curating special data sets with experts. And then I mean, do people vote with their feet? Where is he working now? I just think that Grock came out, smoked everyone on the benchmarks, and their whole thing was courses, and the giant data center, and the X data set. And they just-- out of two years, if I've been working on this for like a decade, they took the R&D from other companies, the data that they had access to, biggest compute in the world, and smoked everyone. So I do think that we have had a bias historically. It's why it's called the bitter lesson. So we've had a bias historically that we think that our specialised human knowledge is more important than just general information. And it might not be true. And that's why it will organise around just volume. And that's why it's like, if you say that we're going to be in a presence of a robot at any time, you'll be like a humanoid at home or some kind of specialised robot at home. They'll-- yourself driving cars or robot. So you'll sort of leave from your house, house you get into a car that will drive you somewhere. You'll arrive at work. You're probably interfacing with robots at work in some way, because they're probably doing a bunch of the labour. Maybe then you interface with an LLM through some other form factor. And so all of that is collecting information. So it's super, super advanced CCTV, essentially, in every place in the world. It's not a valid judgment. It's not something I want to happen necessarily. But it's sort of worth it. I see it going just based on the incentives. Yeah. And I guess what role does LL play in that world? For me, if there's going to be robots everywhere, I want them to be safe and reliable. I want them to have that five nines of performance so that we can have the best versions of them. And that we're not having unnecessary loss of life, unnecessary bad outcomes. Because as soon as these things start getting deployed into reality, the situation right now is observability for robotics. It's not great in terms of the toolset. People need to very much build it themselves for each robotics company. And it's very repetitive. They're all building the same toolset. And that was the inspiration when I spoke to this cross section of the founders. And I was like, keep describing to me the same problem in their own solution. And I was like, man, this is the definition of a Cambrian unbundling. Someone needs to build this so we can have all of the specialists build the very best in class and then sell access to everyone else. Instead of everyone spending the $5 million a year of headcount, the Tesla can throw it at it. Other people can't afford to do that. And it doesn't make sense to do that. How can breaka and alloy work together? Talks to do that. Oh, we're chatting at the moment. We got a lot of robots in us. A lot of data. Yeah, we do a lot of flying at the moment. And yeah, I mean, it is a-- like, it is a problem. You have all of this data. And the problems, the relationship with different parts of the robot causing different problems is very nuanced and sometimes very hard to pull out of that data. I mean, we were talking earlier about, you have kind of right now you can cherry pick data sets that you really like. But to ingest this huge volume of data when you have hundreds of robots flying, very difficult. Very difficult. And it just mathematically can't work, because if you've got people reviewing the missions, and then you start having-- you're going to have a one-to-one ratio of humans to robots in your fleet. It's just-- Yeah. It doesn't make sense. Yeah, and it's interesting, because the-- we've known about this problem for a really long time. And it's still hasn't been solved. And it's partly because it's pretty tough. Yeah, it's technically quite a challenging problem, mostly driven by the fact that data is multimodal. So you've got that complexity. It's like different formats. And it's just so much that when we talk about context windows for LLMs, right, the biggest right now would be a million tokens. And that's doubling every year, which is awesome, obviously, more's lower and whatnot playing out. But when you talk about a Ross bag or a single mission file from a robot, that might be a trillion tokens, or at least tens of billions, because you're dealing with maybe 100 gigs of data of different kinds. And so even if you assume it's doubling every year, it has to be 1,000 times. So you're probably looking at at least 10 years before the context window can fit a single mission file. And so that's why we probably in the next 10 years can build a pretty good business around trying to solve this problem for people, because they're not just going to be able to shove it into an LLM. That's why OpenAI is not going to eat our cake, because it's just technically too difficult for them to get performance of that with context size. Yeah. And I think it also helps companies build their data mode, as well. And I think if a company can make better sense of their data and make it more useful, they can actually build that mode of experience faster. Because I went in and I did a decomposition of where the robotics company spent their time. And like more than half of it was on data curation, so reviewing sort of missions that have happened and looking for issues trying to recalls them. And then QA. So like we've done a training run of the model. We need to just make sure it's kind of doing what we expect. But like that felt to me, like the same experience I had gone through as a software developer working at LUCY in the early days or even prior, before the advent of like Vacell or other tools like that, that had made deployments and CIA easier. And segment I/O for analytics and amplitude. These tools made things more accessible. So more companies could exist and thrive. And they just hasn't been the winners in those spaces for robotics yet. And it can't be a robotic podcast or conversation without mentioning the SkyNet question. [LAUGHTER] What's your answer? What's your response to the SkyNet scenario? Robot's taking over Armageddon, Arnold Schwarzenegger, [LAUGHS] I think-- Yeah, it's an interesting one. I think the most scary thing in my mind is just how good very big AI models are at manipulating people. I think that's probably the scariest part of AI for me. Like people are quite easily manipulated. And even now, it's really hard to just getting more and more difficult to tell what's real, what's not real. Do you mean where it sort of is sycophantic and tells you you've had a great idea from when it's terrible? And you're like, wow, I'm so smart. And then you go through the terrible idea. It could be. Yeah, it could be. It feels innocuous, but it's pretty dangerous. Yeah. Yeah, gases you up too much. (laughs) Yeah, I think, like, yeah, there's just, there's so much capacity for bad actors to use it for, for things, and I feel like, like I don't see like the sky net kind of thing happening. I see us doing damage to each other because, you know, someone has used these systems to manipulate a group of people to their kind of, their advantage. Yeah, and they would already be incentives within the system for the big model companies, open our, anthropic, et cetera, to increase retention and win users by changing the model to tell you what you want to do. Yeah, and it's not even, so just play out like a little thought experiment, right? And it's already happening, so it's not in the future. We just mentioned, right, that their models improve through these interactions, the RLHF, like the different humans using the tool. So their incentive is already to make you interact with it more. And if you're the retention PM who's thinking about how to extend conversation length, right? The split test you're running is, oh, what if I like ask a follow-on question, hey, would you like me to do this follow-up task? Oh, yeah, and you go, oh, yeah, please, that's exactly what I wanted. And now your conversation continues. And that as a feature that came out, right? Yeah, yeah. And I went from not doing that to doing that. And I definitely observed anecdotally, my conversation's got longer. Yeah. 'Cause I take it off, I take it side-deer and go, that's a good idea. Yeah, please, go ahead, why not? Yeah, 'cause I mean, these things are oracles, right? Like they, you ask them, they're oracles of knowledge. Like you go to them to find information and you believe, you pretty much believe any so. Just play out the social media arc that we saw over the past 15 years. Exactly, it's almost like, almost on steroids. So like the Facebook or Instagram PM was essentially building the, you know, the Poke machine of modern humanity. Yeah. And now these guys are doing that, you know, much more useful and, yeah. Quote and Quote productive, right? Productive, right? Yeah, I mean, that was a great analogy. Someone used to me, actually, the Poke analogy for using cursor and why it's so much fun. It's like, right, and you're out of the problem, you're like, hey, it solves this problem in this code this way. And it like, does it work, doesn't it? Yeah, exactly. Exactly what I mean. Like, it either does it or it gets it kind of wrong, but it's kind of close. And it's like the same dopamine of, you know, pulling the lever and you just want to keep going back. Yeah, yeah, I'll get it this time. I'll get it this time. Yeah. I see it's been two hours debugging time. They wouldn't take me five minutes if you just went into the code. Yeah, yeah, that's true. When we're getting AI Poke used to something like that, because like, even my account, at least the credit, what would that look like? What would be different about it? I don't know, do you guys just want to work that out? Brendan's in for a check. I don't do gambling, but competition, I think, is interesting. You're at the frontier. It's a new technology. You want to see other competitors do well to a certain extent. Like, have you guys come across any, I know Joe super early, but you guys come across any sort of competition? What's it like in the industry at the moment? Yeah, I mean, I think for us, they definitely are starting to be competitors out there. So I think we had a bit of a head start, which was good. And now we're kind of starting to see some US competitors appear that are doing pretty similar stuff to what we're doing. I think our focus on making robots is really easy to work with. He's kind of a unique thing that we still have. But yeah, this-- I mean, you know, Gen-A-I on robotics is starting to become a huge space. And there's a lot of companies starting to do a lot of similar stuff. So voice control, I think, is starting to gain traction as well, like being able to talk to a platform. We're starting to see if US companies do that as well. And I mean, yeah, for us, we just want to make sure that we're moving fast enough to stay ahead of them. We definitely have a number of competitors, I would say, that they fit into two buckets. And I'm broadly excited that they exist. Because obviously, it validates that it's a real problem. And a lot of these people obviously have come from maybe a bunch of years in a bit working on a point solution robotics company and going, oh, actually, this should be a platform. But we probably shouldn't keep repetitively building the same thing over and over again. And so they either are companies that have been around for five years and sort of existed for a prior generation. And then now trying to bolt on AI features and figure out how to remain relevant. Or there are these new startups who are similar, sort of have come to this realization, seen the market emerging, and are doing a much more similar thing to us. So I would consider those actually much scarier than the bigger incumbents. Because they've made a bunch of like, I've worked in companies where it's been around for a number of years, and you make a bunch of decisions early on that are pretty hard to unwind. And it's not as easy as going, oh, the direction's now this way. Great. We'll just throw everything away and start again. Yeah. Well, guys, we're getting to the end of the podcast. Thank you so much for coming in. It was a great leap into the future today. Learned a lot. Maybe if we ended up with a couple of, I guess, crazy robot stories, it's something I'm interested in. You obviously see a lot of cool stuff. Anything, you know, you're comfortable sharing. We had the very, like, quite an early version of our software. We were trying to work out what radio network to use between the, you know, all these different things. And we ended up just using CV radios. So they could all talk to each other over the radio. And there was just a really weird thing we had going on. But we had all these robots out there talking to each other over the radio. In that true language room or their own. By the way, they're all talking to each other, moved to this position. Talking to your fleet of brains. Come on. But it's very, very stuff. Joe's saying anything interesting in the first six months. I mean, lots of interesting things. Like, one of the most exciting parts, I guess, of working in a horizontal play in the space is that you get to just meet so many different companies working on so many different things as stages of development. One of the interesting sort of side effects of that is, like, despite sort of the timeline, the length of time. I'll often now meet, like, a founder who's in sort of a certain stage of development in their robot journey. And I'll have seen someone that's maybe one year ahead or two years ahead. And so I'll have quite a weird asymmetry with them. I kind of can guess what their problems might look like in a year or two. So I mean, in terms of, like, specific crazy things, I probably can't say anything about, like, active customers. [LAUGHTER] I mean, it's been interesting when I go over to say the US, and I go to, like, these hack houses where people are working on either humanoids or, like, by modal robots with two arms. And they're all, like, folding t-shirts right now. Like, that's kind of the thing. And working on these new, sort of, new age vision language models and different architectures that are different to how people approach robotics before. But it's interesting just how many are doing the exact same thing. And I imagine it's the same every wave. Like, there is this, like, local gravity pulls to the same kind of-- I think, I see they call them, like, top-hit ideas, right? Like, you end up in the same thing as everyone else. And it's a bit of a slow-moving thing that doesn't quite get to escape velocity. I don't know what saying everybody who's doing that is in that camp. But it just was interesting. You got to this building. And then maybe 10 companies doing pretty much the same thing in the same building. Yes, well, what about you, Brennan? What's-- can you tell us the craziest company you've ever been pitched? Well, the craziest robotic company, like, honestly, when we went to break up-- [LAUGHTER] These guys are curious. These guys are curious. Yeah, the pitch, you know, come and talk to R2D2 or CP3O. They'll talk back to you in natural language as well. I don't know, D-Lake, if you can bring up any of the break of videos. But yeah, just to find a passionate group of people that's building this technology right on the ground floor in Sydney is super impressive. And it gives me hope for the next generation of generational startups that come out of Australia. Yeah, super excited to see where you guys go. I would say one somewhat crazy thing, which is pretty pervasive, is this-- and I think this will change over time. But right now, maybe because a lot of robotics companies don't yet know what exactly their core thing is, there's pretty defensive over their data. They're like, oh, we don't want to work with any kind of providers because our data is our secret source. That's how we're going to solve autonomy. That's why we don't want to show it to anyone, even a provider. But I'm like, well, where does your code live? Oh, and GitHub. OK, interesting. So you're OK with GitHub seeing your code. So do you use Redshift? Do you use these tools? So there's sort of this weird, different mental model in this space right now that I think will shift. But it's like-- and I ask you, sometimes with certain people, what do you do with that data right now? And it's like, OK, well, we don't actually look at 99% of it. But we can't share it with you to get more value out of it, because that would violate the value of it that we keep. But we don't look at it. So yeah, I call it a bit of a paradox that we're currently just breaking that cache from the two at the moment. Because when we put it in front of people, and we're like, hey, we can summarize this mission instantly and tell you the jump-in points that are the most interesting to jump in. You don't have to review this two-hour long video footage anymore. You can just jump to what's relevant. That then blows them on to like, how do we give you more? But yeah, breaking that initially was really challenging. So guys, I know that you were already attracting some of the best talent. But if you had to give a quick pitch to the people watching today, why should they come and work for Breaker? Why should they come and work for Alley? And why should they come and get interested in Build Australia? Yeah, I mean, if you are, if you love robots and you want to work on a very difficult problem with a super motivated team, you know, Breaker, we're hiring, we're doing about to kick off another hiring sprint, and we're looking for great people to join the company. I would say, Eloy is a really interesting company because of the fact that you get to work cross-sectionally with so many different types of robotics companies, something that people come up to curve quite quickly on, they get to see maritime robotics, defense robotics, they get to see agriculture, and you get to learn a lot. So if you're a voracious learner, passionate and hungry, incredibly smart, we are also hiring, and we've raised one of the best precedes in Australian history to go after an incredibly, incredibly ambitious mission, so we'd love you to be a part of it. And I would say to people that love Australia and are worried about Australia, and want to get involved in a bit of an open-source project, chuck me a DM on Twitter and we'll get you involved in the Build Australia movement and keep going out for it. Awesome, I'll sign up too. And before we go, just want to bring up, as we do, at the end of every episode, we're trying to get a very special guest on the podcast, a guy called Cliff, he's also in Surrey Hills, so the countdown time are 50 days without a response from Cliff. He's going to respond one of these days. Cliff, happy to come to Canva and record the episode there as well. You'll have a great time, we'll get some great guests on the Oversupply podcast. And if you want to connect with any other guys, check out any of the content we mentioned today, over SubscribePodcast.com. Very big thank you to our main sponsor, Vanta. You got, you guys on Vanta, do you need the special code? 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