Powering Precise Location for Physical AI

Right now, somewhere, a company is making a move in plain sight. The street reads the headline, "Autonomy AI sees the signal." We deliver it before the market catches up. Autonomy AI, your models, our intelligence. Request a private strategic briefing at AUTNMY.AI. And it's been two long years since you've been here on the road to autonomy. Two years, too long. But during that time, I know you've been very busy building and shipping. How has the business point won navigation evolve over those two years since you were last on the pod? Well, first, thanks for having me back again. And I apologize it's been two years. We have been exceptionally busy. I've been to Europe now three times in the last four weeks. That's been a lot. And, yeah, I mean, the theme has been expansion. I mean, there's been a lot of tailwinds with all the physical AI progress that's been being made. Customers that we started with that were small, now becoming big. And what looked like a little bit of a dip coming off of COVID and everything has rebounded and then some. And I think we have tailwinds from all kinds of stuff that are making that happen. And location is, if anything, more important than ever. We're really happy to see that. And I think we've also had a lot of commercial success just looking at how do we get into not even just robots. But, you know, lots of other applications that are at scale today. And so, you know, been able to build this incredible business that has applications that are at scale consumer level. And is really helping bring in the forefront of technology, which is, you know, personally where I love to sit. So, yeah, it's really an exciting time. What are some of those applications? Because when you were on two years ago and before that, you were on several times, I think this might be actually your fourth time on here. We had a lot of conversations around location for autonomous vehicles. But your technologies evolved, the markets evolved. You're going deep into physical AI. What are some of the new applications that point once powering from a location perspective? Yeah, I mean, so some of them are new and some of them are really old. And so we started the company with this notion of, we want to be on everything that moves. And that hasn't changed. It's just that category's gotten bigger. And I think the vehicle stuff is still super interesting. Shipping on vehicles takes time. Like, it's complicated from a tech perspective, a sales perspective. You know, we've done it a few times over now. And I think we have over 100,000 vehicles in production today on the roads with our stuff. But, yeah, it is still early days. So, the new use cases, though, that we're seeing are actually taking some of the, I would say, classical problems of what's used as an example, surveyors, right? That's, frankly, one of the oldest industries in precision location. And we've seen that there's been this almost consumerization where you can make products that are way higher performance, way easier to use. And that has ushered in just like huge volumes and interests of how do you take, you know, best and breed service companies like us and combine them with these companies who sell in hardware and really build amazing products for the customer. So we just recently announced the partnership with this company, Emlid. And they've, like, deeply integrated point one into all of their products and ship them to every customer. And so it's like those kinds of scale. That's really what's changing. And so, you know, that's like tens of thousands of customers, you know, in the first month. Like, it's really amazing. The other one that I'm like, I have to admit, it was not on my bingo card when we started. Autonomous lawnmowers is a big thing. And I mean, these things, they're amazing. They're like little self-driving cars. They just wake up every morning and mow your grass and, you know, we've seen just an incredible amount of uptake from those. And I think the technology is now at a point where it's so affordable. You kind of have this like super rumba thing, trust me, it works way better than a rumba dust. And it wakes up and like, you just have like a perfectly manicured lawn. And that's the consumer level, so, you know, hundreds of thousands of devices. And then we even see it at the, you know, professional level, you know, when it's mowing, like, mediums, mowing golf courses, mowing sod farms. I mean, I had no idea there was so much grass. We've done several episodes on autonomous mowers. I think autonomous mowers are fantastic. Or I let me have a lot of golf courses. And boy, oh boy, you better not mess up that green with that mower. That rotation is very important on a golf course. The house, yeah, we can get away with it. But the golf course, you cannot ruin that green. It seems to me, if you want the autonomous mower, it doesn't know exactly where it is. And these, you know, like by an inch, you can ruin an entire green. How do you ensure the accuracy for these autonomous mowers on golf courses? Yeah, I mean, it comes back to like our core value prop. So, you know, point one, we do specialize in a lot of different types of technology. All with this common goal of how do you get to like, a handful of centimeters of accuracy? So in our highest accuracy service, I mean, we're talking two centimeters, like it's almost unbelievable. And you get to the point where it's like you literally have to calibrate like the GPS antenna because it's that, it's smaller than the antenna at the level of precision you have. And so, yeah, I mean, the core idea is we are leveraging a bunch of things that we've built. So one of them is RTK. We have now one of the largest professionally owned networks in the world. And that technology, you know, it's been around for a long time, like, you know, we talked about in previous conversations when I was doing the grand challenge in 2005. Like, yeah, we used the form of RTK GPS back then. What we've been able to do is drive it now to a scale and a price where it could be in consumer devices and still have like this like insane level of accuracy. But it is like point one is evolved into not just an RTK network. It's like, we're doing the whole stack. So there's, you know, the software that makes that work. We even like help companies find the right hardware vendors and we end up being like, like a design partner and, you know, just making that success happen. And I think that's, that's really proven to be highly valuable as we've started to scale out. How should we think about point one? Should we think about as a navigation company, a location company or a, hey, we're not going to let you get lost company? Hey, we're really a location company that's like, we like to say that, you know, there's like the blue dot everybody knows. We want to make that blue dot work everywhere, like, and when we say everywhere, we really mean everywhere and, you know, that we can't do that on day one, like, so we've started with, hey, we're going to make that blue dot work with incredible precision, incredible liability outside. And that's super valuable for a ton of use cases that we're servicing today. And then we said, okay, cool, we're going to make that blue dot work in more places. So we built software that lets it work in, like, parking decks and, you know, other kind of GPS difficult places, urban canyons, et cetera. And then, you know, in the future, that blue dot's going to work inside and, you know, in all different types of locations and it's continuous. That, that's kind of like V1 of point one. Here's this world of, well, once you've done that, there's a lot of interesting things that you can do for coordinating fleets and robots and even people with robots. And so we're starting to see that emerge already. And the most exciting thing about it, in my mind, is that location doesn't just become about, like, the one robot, it actually becomes about, like, how do you coordinate fleets? How do you coordinate, like, you know, this modern autonomy world that we're trying to build and think about the problem not as, like, individual robots, but, like, literally, like, intermixed society of these things working together. And to me, that's, that's like the future that we're all really trying to build and excited by. The individual robot is just a step along that journey. I remember, oh, 10 years ago, 12 years ago, we were at CES near the parking. You had the red Lexus that you had at Joshua's self-racing cars and you were showing the parking deck and it was super, super impressive. The only downside was it took an hour to get from the convention center to where you were, but it worked well. The demo worked great. Yeah, that was early in the company's journey and getting a prime spot in CES was a little bit outside of our budget, but, you know, being the creative Silicon Valley startup, we figured out that renting the UNLV stadium is super cheap on CES weekend. So we did that and, yeah, I appreciate you coming to the demo. And that was the early beginnings of, you know, what We've been able to prove and I've had a few customers that now are at real scale tell us they went to that demo and that was the thing that got them convinced so I'm very proud of that demo. To this day, we're always going to remain scrappy. We still have the reflexes, but I think this is a big piece of showing people not just telling them that this is possible. We can show you that this really works. And then history, you were kind at Self-Race car Thunder Hill. You put me in the car we went around the track autonomously. So that's another thing for the history vaults. Yeah, actually, so to follow up on that, we ended up sponsoring the India Autonomous Challenge, which is a really awesome event that's put on and let's students be able to build these incredibly impressive cars. They're like basically full-scale, you know, indie cars going like almost 300 kilometers an hour and this year they were actually doing wheel to wheel like at 300. It's wild at Laguna Saga. And so, you know, they're all using point one for the positioning and that's great, but there's this whole notion of, hey, like being able to take the technology demonstrated at the limits has always been like a piece of what we'd like to see. And I mean, there's a separate thing of like I have a soft spot for universities and people being able to kind of have access to this technology because it's what got me started. Yeah, I mean, I think that those types of demonstrations are really important and like I wish we would see more of them in the industry. It's wonderful because the reason I wanted to highlight that, I mean, we're friends at on Pradio. The company has has evolved and grown and I love it that you're you're expanding and to say which one is a term different verticals, but you still have location at its core. So, you know, it's a very difficult verticals that you've expanded to that that's booming and we even have an index for it, road to autonomy, the autonomous spots index is last mile delivery, how are companies using your technology for that last mile delivery. Yeah, it's it's amazing sector because we have customers that are I think at all kinds of different levels of autonomy. I guess you could call it using point one and it turns out that customers, you know, they're still delivering things with people and bands and you know, that's turns out that's how most of us get the things that we order online all the time. It turns out that they have a huge use for this technology because if you can get a parcel, not just to someone's address, but literally to their front doorstep and know it got there. So, like, raise the efficiency of, you know, these logistics operations by like very significant percentage points and at some of our customer scale that translates into a lot of money. And then, you know, we have other customers that are actually doing, you know, delivery robots and so like server robotics as an example, they're doing a lot of really advanced delivery to be able to get, you know, goods to people in a, you know, efficient package and having the system know where it is is like a pretty core function of these, these robots. And so, you know, we're, you know, helping in that, in that regard and a lot of that processing and everything is ultimately, like, and a lot was existential to having these companies be successful because, you know, the robots are possibly getting lost and everything it's like creates a nuisance and then, you know, people, you know, have a revolt on something that can be actually like incredibly valuable, you know, utility in a way to be able to get goods in a efficient and quick manner. So I, you know, I really do see our role as being, you know, a key enabler of making these technologies successful in their deployments. We don't do everything, obviously, like our customers have a huge amount of work to make this whole system work. But we're proud to be like, you know, a part of that that takes some of the load off of their table. I believe the team are doing, you know, great things that's served. And I mean, the gentleman's got grit and he keeps building that business and building it. And I think he's in a better place than he was before. And if anybody is wondering, go listen to the last earnings call. It's all there on the earnings call. But I want to highlight from a technology standpoint point when you're 100% more accurate than outdoor GP. 100 times. Yeah, yeah, it's, it's a, this is one of those like scientific, I don't miracles in a way where, you know, GPS was this thing that was invented like 50 plus years ago. We don't pay for it. I guess indirectly, maybe through our taxes. You know, it's this pretty asset that you can just use. It's kind of incredible in this way. But it's not super accurate by itself. It's only about five meters. So we use this technique called RTK that allows you to take like a known point on earth, put a really high end GPS receiver in it. And then effectively like use the data from that station in conjunction with like your real GPS receiver. And when you combine them together, you go from that five meter accuracy to five centimeters and now like down to two centimeters inside of our solution. So there's a whole bunch of complexity on like operating that network at scale and then having the software that does all that signal processing. We do all that. And so you don't have to worry about it. And like the closest analogy I have is it's kind of like, you know, when you use your phone and you're calling someone, you don't think about like how complicated 5G is and all these like very like all the towers and operations and maintenance and that goes into running an AT&T or Verizon. And so, you know, a lot of ways these carriers, they're like a utility that you just build on. And it's insane and really valuable how much that has changed like just our current, you know, we can walk around and, you know, watch an HD movie on your phone if you wanted to. You think about like the 90s how insane that sounded where you were paying like I don't know six cents for text message or something. So there's this I think very strong reality that taking problems and pushing them into a network makes it so that everybody who's building on top doesn't even need to like think about those problems and they can start at this much higher level of abstraction. That's like the first level of it that we built and we've built many other levels now on top of that. So there's the network, the service, the corrections, all this observability that goes into making sure it's working and the stuff that we have plans is going to take that and just push it even to the next level. So yeah, there's really I think an exciting future, you know, for obviously our customers that are already on point one and then, you know, for the companies that haven't even been founded yet that are all going to try to be solving the next, you know, autonomy problem to be able to start from something that's far greater than zero. I think on that line of thinking, then are we going to go from two centimeters to one centimeter accuracy as it evolves or how do you see that evolving? Yeah, I mean, the, you know, the evolution of the business becomes not so much about chasing the centimeters because you get to a point of diminishing returns honestly. But it's more about how often can you get to two centimeters and this is kind of the like really hard thing with robotics in general is like everything is a probability. Yeah, so you're like how often are you able to do the thing and, you know, I think we've all started to kind of experience this is consumers when you're working with like your strategy PT or whatever your favorite agent is. Like the responses are not deterministic, like there's some level of like variability in the robotics world that's like all the time, like, you know, this is how you're dealing with things. And so our job is to try to narrow that distribution so that you're always going to be pretty close to two centimeters as often as humanly possible. And then very importantly, you also want to know when you're not in that two centimeters and be able to tell the user and this is like the equivalent of when your AI is hallucinating. You really want to know when that's happening so you don't just go and like confidently make the wrong decision and like you said, go and move like the wrong deck height on the green of the golf course because that's not a fun day. Now that's this is the part of why, you know, positioning is not as simple as just go get a GPS receiver and plug it in, it's actually like a much more difficult sensor fusion problem. And when done well, it's kind of the difference between a robot that works 90% of the time and a robot that works 99.99% of the time. This key and if you look at the industry, we're location going down to the centimeters really makes a big difference and it's a matter of, are you going to have this process of the year or unsuccessful year is the agriculture industry. Because if all suddenly you run over the crop, you've got trouble until until next year, are you seeing adoption in the ag industry of your technology. Yeah, I have to say like I going into this was not like super read up on like the agriculture industry and I have developed such a deep appreciation for how complex farming is and actually like how advanced the technology already is there I think it's like you know John Deere kind of has this line where it's like oh we've been doing autonomy for 20 years which I mean it's true to some degree but like the real thing is how much the ecosystem like can use the technology I'll give you an example where we have customers that are literally able to understand like exactly where they planted a seed and there are these crops that like they grow down they don't grow up so you have no idea that the thing is there there's no visual representation but since they memorize the location when they planted the seed they can just apply water or fertilizer or pesticides to that one location save like 80% of the actual like normal cost that they would have of those materials and have like the same or better yields and so like net yeah they're saving money and it's also like a healthier product because there's less you know chemicals and whatever that were put on that actual device to use less water like I mean this is like really where I'm like this is how robotics makes the world better like it's not about automating things for automation sake it's about literally solving the problem in a better way and so AG is probably one of the most exciting places where you're starting to see the real benefit of automation or even I should call it more like precision because a lot of times it's still like a guy driving the tractor or monitoring you know equipment and it's about how do you make like the actual end effectors and everything more effective at what they do? I guess to me is one of the most important industries in robotics Danny Bernstein the team at reservoir I've been doing a really good job of trying to shine a light on it we did a podcast with Danny and Google DeepMind so DeepMind Google DeepMind Robotics is starting to get in there and put exposure on it because if we don't automate farm we don't put robotics on farms I'll just say very bluntly we're not going to have enough food to feed the world because of the labor shortage that's there on farms there's I put the labor shortage with over the road long haul trucking but there is a more intense mission critical I'll dare I say shortage on farms and it all comes down to labor and when you start putting robots on farms you need accuracy you got to pick the corn you got to pick the cotton whatever might be you need accuracy yep and it's a lot of it like if you're three centimeters off and you know the agriculture is also like it's an unforgiving environment like I mean you've got diesel hydraulic fluid mud like you're operating in all weather like these guys they really understand robust it's a passenger vehicles looks like a walk in the park compared to you know what they're doing so yeah I definitely agree with you it's an existential problem and then moving out of the dirt in the mud and moving into say the laboratory I don't know why I decided to say that well it's almost Halloween so we could do young Frankenstein we could channel Mel Brooks here on a whole thing but humanoids it's something like Mel Brooks might have came up with they made a movie on it and he's no longer with his gene wilder was brilliant at that movie just for the record humanoids have to know where they are I keep asking humanoid companies a very simple question how do you stop the humanoid from going in the pool and I saw in Japan and this was in the in the Nicae that there is a humanoid ambulance now that will come big humanoids up it's a test service but I was like okay it's all about vocation because that one centimeter two centimeters are you working with humanoids yeah I mean we do have a few customers that are doing both humanoids and also quadrupeds they're in the same camp in my mind and you know there's I think you know the the big unlock if we're honest about those has been the you know foundational models that are able to actually take this incredibly complex mechanical structure and make it do useful things and so you know we've been able to build you know humanoid robots in terms of like the motors and the drives for a long time it's it's really been the end to end controls and everything that are right new and enabled kind of the amazing demonstrations you see you know even the guys at Boston Dynamics who are arguably one of the leaders in the field it's they've went from a lot of very painfully hard-coded controls to now these incredible learned behaviors and so you could almost see Atlas doing back flips and all kinds of crazy stuff it's amazing and I think you know the the big challenges how do you actually make these things commercially relevant and able to do something that's going to deliver value and a lot of that's going to be they have to be able to traverse space they have to be able to like go from one end of a hospital to the other or one end of a factory to another and the place where location matters is how do you make it so that they can do that efficiently safely not fall into the pool to your point you know there's a lot of other things that you know when you have effectively a map and a location you can be way more certain about what the world is and not have to just completely rely on local perception for every single decision and that also increases the speed that they can operate and at the end of the day I mean that's the real metric is like can these things create utility that's equal or greater than humans and I think that's that's only going to happen by giving them more data more context and that's really locations of an incredibly powerful vector that it is and we need to do that you need more compute but I'm curious from the location perspective let's just say we put a humanoid at your house humanoid my house humanoid Bob's house Rob's house Roger's house how does it work because all of our houses are different we live in different geographies different sizes I might have steps you might not have steps how how how does the location work because it's just completely different environment you know this is the thing location is not one of these problems that there's some magic silver bullet technology that solves at all and this is kind of the long-term reason for point one to exist frankly is taking all of those different almost like point solutions so whether it's part TK GPS, LiDAR, camera, radars some other crazy force transponder sensors you're able to take all that data and then convert it into this like relatively simple concept of like where the heck am I and then in some cases you can provide the context around oh yeah by the way there's stairs there or there's the handle for the door or hey there's an elevator over here and so if you can provide where you are and some of that contextual information the foundational models we have today are actually able to do like a lot of the other like okay how do I place a foot on the next level of the stair that I can see and actually climb the stairs with a fair degree of success and so I see this as there's kind of the two sides of the global problem of navigation which is like where we solve and then there's the local problem of like okay I know I'm on this staircase how do I go that's where like these models really are amazing and like are able to show working progress today so yeah if I were going to build a you know humanoid that was going to take a package from my house to your house and you know we didn't with a hundred miles away you know you'd be able to do that I think with a lot of this technology we have today and it's not that far away do you think this is a broad question do you think that a lot of these robotic startups and roboticists location is top of mind or do you think it evolves as the product evolves like oh wait we really need to know where the heck this thing is and GPS is not highly accurate yeah I mean for better words it's really hard to do almost anything if you don't know where you are I mean that's a that's a pretty obvious statement now granted like there are some very narrow application things like you know the cuckoo robots that are in car factories painting things like they know where they are in the context of you know I can measure the angles of all these joints and calculate with insane levels of accuracy you know where the end tool is but that's not the kind of robots that like we're really trying to work with we're trying to figure out like how do you get you know this next generation of like truly mobile robots to be able to work in the real world and I think you realize pretty quickly when you start these systems that it's the locomotion part of the problem is a big one and like that said it's rarely the thing that sets like your company apart so you're really looking for like how do I get past this problem as fast as possible and then like work on the thing that I'm really good at like I don't know harvesting lettuce or something and so like you know there's a I think we're starting to see as companies are moving away from the like hey we're going to build this like general purpose everything box to very application-specific in autonomy, you're going to have to be able to leverage these pretty horizontal parts so that you can have focus on the specific application that you know a lot about, you know how to sell into all the traditional things that you need to build the actual business. I think that's going to be the evolution of this as we get out of, you know, the 1.0, like, barely out of the lab stuff, and now into like, okay, this stuff really works, and we're going to see it scale. I know see it scale. Starting next year, Hyundai put out a press release. I haven't seen photo, but they did put out a press release that the Atlas robots are going to start coming out of factory in Savannah next to their meta plan. So if they do start coming off the factory, they'll be interested in watch. Tesla obviously is very public with their optimists and ambitions. That's going to be something interesting to watch. And the market seems to be, I'll use the term frothy for humanoids. And boy, oh boy, do I have flashbacks to 15 years ago, what you and I went through when the autonomy bubble. I'm not saying that's happening. I'm just saying you and I have the battles guards to relive what happened there. And a lot of it seems familiar. And you just slap on humanoid. You got a billion dollar valuation. You know this, you slap on the word autonomous. You get a billion dollar valuation. It doesn't matter. But that's the ground side. Since we spoke last two years ago too long, and I'm not going to stop harping on this, is you're now working with autonomous air drones. How is it different from location for when you're up in the air until you're down in the ground? How is that different? The stakes are higher when you're in the air because you really can't get it wrong. And a lot of the customers, there's two camps, really. The first is the folks that are doing like, we'll call drone inspection. So they're flying basically a camera or maybe a lighter around. And they're trying to like map something or see something. And so that's, you know, we have a lot of folks now doing what they call drones as first responders. So like drone comes out of the box, flies down to a crime scene in progress and is able to track the bad guy, you know. And I mean, this stuff sounds like science fiction. It is awesome to see, like, it is really like amazing. So that part, you know, obviously knowing where you are is pretty important. And then, you know, there's the, you know, a future where it's not just the drone, it's actually the whole fleet of first responders. All have this kind of situational awareness of, hey, here's where, you know, the police officers are, here's where the ambulance is or the firefighters. And that's something we're seeing. The other side on Ariel is being able to do delivery. And I think, you know, it's, this has been something that, you know, we've heard a lot about, you know, Google as a thing, Amazon as a thing. And obviously there's like the big independence, like zipline and now many others man of flight tracks, like the list goes on. And, you know, we're working with several of them now to be able to not just make it so the package delivers on your doorstep, which is a thing. But also, how do you get the drone back to the facility and actually dock so that it's able to get its next package? And the thing there is that at scale, you have a lot of these things like all operating in a pretty close space. And so in, you know, airplanes, you always talk about like the separation and the separation ultimately drives safety. And your separation has to be proportional to how well you know where you are. So it turns out if you have better location accuracy, you can now fly in tighter quarters and create higher density and do more deliveries. So location not only is like an enabler again for the one robot, it's actually an enabler for scale on the fleet. And so it's, I would again say almost like an existential part of the problem, but it's not the thing that's necessary going to make them more. They have a million other hard problems this all. And so we're just seeing this pattern as like, hey, we can help make location, you know, a problem you almost don't need to worry about. - There was a viral video and I'm gonna say, we don't know if it was AI generated. So I wanna state that because Amazon did not comment on it, but there was a video where the Amazon drone dropped the box in the pool. Whether it was AI generated or mistake, I don't know, but it went all over the internet. Now, hypothetically, if that drone had a point one system and if it wanted to have known that was a pool, no, no, that's not a drop zone, that's a splash zone. - It would absolutely know that the location that it had is a pool. So we are definitely, unless you have a two centimeter pool, which probably is fine, we would be able to tell you if you were dropping a pool or not. And so yeah, this is, I think a classic reason that you need to have high precision accuracy, but also, let's be clear, you gotta also know what the surface looks like. Now, the clever thing that a lot of our customers do, and this is true in automotive, where they don't only use our stuff to know where they are, they actually use our stuff to help build newer maps of the place, 'cause if you think about it, it's you have a camera and then you know where you are, you can kind of build your own little street view car. And so a lot of our customers actually end up using us not just to know where they are, but also to build maps. And when you have both of those things being accurate, it's really hard to drop stuff in pools. - We seem to be on an anti-pool theme, by the way, I just noticed. - No, we're definitely not on anti-pool. We're pro pool. I just don't want the pool to get ruined. So just send the record there. - Okay, fair. Save the pools. (laughing) - Yeah, we'll get, we'll get the insurance man to road autonomy. Save the pool, keep the robots dry. Save the pool. (laughing) - It can become a voting slogan there. As drones are expanding, it can give you probably the most populous market in the United States for drone deliveries to Frisco texas market, just north of Dallas. And there is a lot of drones looking forward to going to visit some drone operators out there in a few weeks and getting a first-hand report and doing a field report on it. When does air traffic control for drones that ends up in Frisco texas, you have this precise location. Can you do it, can the companies do it in house or do you see your location powering potentially in air traffic control for drones at some point? - Yeah, I mean, I think in the first version of this, the companies will do it because they have the most contention in the places that they're actually going and delivering. The FAA is going to control a lot of this. I'm sure that will be the net result of it. But I think that having the high precise location is going to be existential because the other problem for drones is like, you don't just care about where you are laterally, you also care about your elevation very accurately. And these things, they're operating in a relatively small air space compared to commercial jets. And so you do have a pretty reasonable probability that hey, there could be an incident. Now, in fairness, they do have like local sense and avoid type of things, but it's always better if you don't have to rely on that. And so yeah, I think as the density goes up, the need for centralized cross vendor or de-correlation will happen. And I absolutely see as being a part of that. I don't think we're going to go build the whole system. That's not kind of our business, but we are definitely going to be a big piece of making that possible. - You're in the business of location. And one of the big things staying on the drone topic now is that to be see the statements in our piece that have come out of the Department of Worms Secretary Heggstaff, there has been a large call for drone technology to put them into GPS tonight, environments in the hostile environments also known as theater for combat. Is do you see any of your technology being used for military applications since location is so important? - Yeah, I mean, I come from a background, before.1, I developed some of the highest anti-jam and anti-smooth technology that's available in GPS. And it's one of those things that we take for granted as civilians, but when we sell even to customers in Finland, they're right on the border of Russia and there's jamming every day. And like the guy's just trying to operate his tractor and it's like he can't because there's this radio interference. And so I think the unfortunate reality is that this is a, it isn't need and it's a very pressing need. We are doing some things very early on to see what.1 can specifically address in that market. And a lot of it starts with how do we do the things like around that problem. And then yeah, I mean, like it's always kind of on our roadmap of how can we increase the places that we operating and that will include places that are compromised from, you know, an EW perspective. So that is definitely on the roadmap and something that, you know, you'll hear more about. That says there really is next year. - Well, looking forward to hearing about that. And the company recently closed a $35 million Series C led by Coach Leventors, congratulations on that. I love it because it wasn't a large race. It tells me that you're running a capital efficiency business. How are you planning to deploy that additional capital? - Yeah, I mean, And so we are at this point now where we have just seen incredible tailwinds with everything that's happening with physical AI. And one of the things that I hear from customers is, man, we wish we knew about you guys sooner. And so that tells me that there is a little bit of an awareness thing that we're trying to work on. And that means that hey, we need to invest in getting more sales folks able to talk to people and getting the solution out there. And of course, like, you know, we're investing in the core technology to your point. I mean, we built, I'd say, an incredibly efficient and, I'd say, a capable engineering team that although we may not have like hundreds of engineers, we're able to deliver like an extremely competitive and, you know, performance solution. And so I think there's a different DNA that we have is kind of this almost foundational company where we want to be efficient and we want to be a company that like our customers can rely on us being here for now over 10 years old. You know, we have a real business, which is nice. And I think, you know, what we see is, you know, growth that's just really, really exciting, you know, more than doubling year over year. So I think I love about having known you on this throughout this journey is that you're not saying it's sticking into silo, you're constantly evolving the business as the market evolves. And I give you a lot of credit for that because obviously, 10 years ago, when we first met 11 years, 12 when there was, we weren't having a conversation around humanoid. Yeah, we would, we would geek out on different sensors. This is when Velodyne was still around and, and video was, was barely a spec and remember when Joshua and video was, oh, and videos are, oh, okay. And nobody paid attention to them. Boy, how time's have changed. But, but I give you a lot of credit for always staying on the cutting edge. And if you want to say it, now the businesses becoming more mature, it's highly diversified. And now you're launching your first event, you got an event called fuse, you're putting locations on the map, you're going to get a GPS pin for this map. How's that going to work? Yeah, so we will have the location of the conference to, I don't know, how many degrees of latitude and latitude precision, but I can also give you the address. Yeah, it's, when, you know, we've been talking to all these customers. The thing that we've on earth is that a lot of people understand that locations like a really big problem, but there isn't like a place or to really talk about it that's, I would say, you know, a balance of not being like an academic conference and not being some like product conference, it's really like, how do we talk about like the system and the problems about solving like the real issues that come up when you're building? So yeah, we actually started a conference series, we just, I just got back from France doing our very first one in to loose. And our second will be in San Francisco, and it's kind of like a big deal for us on the November 19th, we have an incredible speaker lineup with, you know, all kinds of folks that are both like deeply technical, but it was also like shipped at scale, talking about, you know, their specific journey, not in just robotics generally, but like in the context of location. And I think like it's, it's one of these like unsung problems in robotics because it's, it's hard for us to relate to as humans, like fundamentally is like a different way of solving this problem. So yeah, we're super excited to put together this conference, it's really the first of its kind, have this amazing speaker lineup, and then yeah, folks and check it out, it's fuse.point1nav.com, and yeah, we'd love to, you know, have folks join. And I think it's, if France is any indication, you know, people walked away and we're like, this is like one of the most useful conferences I've been to. And you hit the nail in the head, you talked about scale, and the vinegars have been there that scale, for businesses to survive, it needs to scale. And as things become more connected, physical AI, you know, takes off and goes into sectors that we have even thought about, location is going to be the backbone of all this. Aaron, how do you see the future of the location services evolving? And at its core, where do you want point1nav to be? I see there being two sects, you know, the availability of high accuracy positions, so like, we'll call it less than a meter for now. It's going to become something that like we just take for granted. And so, you know, I think eventually you're going to see even your fellow is going to have like a level of accuracy that is going to be like pretty amazing. And you know, we see that coming from the market on all the major players today. But that's one element. The other element is that there's going to be a lot more visible autonomy in the world. It will become common that you will see like an unmanned, you know, a street sweeper and unmanned, you know, whatever your lawnmower is, all these kind of jobs that are out there. And I see that it's like, they're just going to work and you're going to take you for granted, not think about it. That's actually success in my mind. As always, we talked about this in the autonomous vehicle industry. It's like, you get in a Waymo or any car that's like done well. And like in the first two minutes, you're out on your phone and just like, it's like boring. You know, that's success. And so, this is kind of our philosophy. And point one is, I think uniquely positioned to be in the kind of like nexus of a lot of this very fundamental problem of knowing where you are as a robot. And then also knowing where all of your peers and other things you care about are. And so we are doing everything we can to build towards that future. And, you know, I think so far, you know, our customers are extremely excited to have us be a part of that journey and help them deliver, you know, the best applications. What is the future point one? I'm in this for the long haul. Like we really, I think have this capability to build like a generational company in the sense of there is going to be one of these companies that are out there that ultimately is commanding what is location, like what is tripped where are things. That can be, you know, some ad support business. That's not what I want to build. I want to build it in a way that's we're actually delivering value and people pay for that value. And then that's kind of it. And I think that's that's going to be what's really exciting. If you think about the future for robots, we're going to have new use cases, new demands, frankly, for what is a path even. And like that, to me, is where point one is really going to have a very bright and very exciting future built upon like this very robust foundation we built today. There's new robots, new demands, new challenges, but have no fear point ones there to solve the location problem. The future is bright, the future autonomous, the future is point one navigation. Aaron, two years, too long, I'm not putting up with that. That timeline is going to shrink. But thanks for coming back on the road to autonomy. Thank you, guys. Always a great funerary. Billions and soon trillions in value will be created in the autonomy economy. By the time a trend becomes consensus, the alpha is already gone. The gap between uncovering signals and reading headlines is widening fast. When it's a headline, it's no longer a signal. Enter autonomy AI. We decode signals before they move markets, giving you conviction in the autonomy economy. Autonomy AI, your models, our intelligence, visit autnmy.ai. 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