Brett Adcock - Shawn Ryan’s First Interview with a Robot | SRS #292

Combining this in the physical realm of robotic action seems to multiply the downside effects exponentially. What safeguards are in place that we can put our trust in to prevent the potential for downstream harm to humans as a result of bad programming or computing errors? Yeah. Yeah, we don't want the Terminator popping out here when we let this work, right? I mean, I think, like, we were chatting about this outside, like, you know, I think one thing to say, like, four years ago when I, like, you know, started the company, there was, like, no path for humanoid robots, like, to make it into, like, people's homes in the next, like, 10 years.

There was, there's no good story. There was, you had, like, big hydraulic humanoids out there. They were all, like, hand-coated to do certain tasks. what you really need is like a cheaper electric uh humanoid that like uh you basically can like use use like neural nets like use like basically an ai first strategy with there was there's none of that existed i think we're like we're thankful now like looking back like that we like uh feels like we somehow pulled like 10 years of the future forward we have like electric humanoids that like are reasonably priced that can do like a useful human work with neural nets uh and it's just like I think it's just an incredible place to be in getting those questions, which is like, how do we make this work now at scale in a safe way? Because that's the spot we want to be in, not trying to make this work for 20 years. So I think this is a very, very tough problem. We have to get the product cheap enough. We have to make enough of them. We have to make it with the performance work in like very complicated things like walk around a house and like do dishes like laundry like very complex things like small kids can't do this like it takes adults to kind of do

like this level of work and we need that all done in a mechanical system that doesn't have any humans around for maybe most of this that does it autonomously and not makes any mistakes and then like like like your fan mentioned like we have to do it safely over time it's just man it's just an incredibly complex problem um i think for us like we have a safety strategy both uh intrinsically we want the robot hardware and the robots around humans to just be safe all times and separately we have a there's a bunch of like semantic safety and other things that we need uh like that we have either put in place or put it in place now to make the robot just like work safe in the environment like uh you have a candle at home you don't want the robot to accidentally knock it over uh it's like a that's like an intelligence thing uh in a lot of ways um or there's a boiling pot of water like making sure we're like very safe around it um and then there's like the intrinsic safety of like making sure like this this mechanical thing in your house is like safe around everybody around it uh i think the the direct answer is like still a lot of wood chop uh of getting this place getting this thing to a point where it's like uh uh we trust it to be

autonomous next to my kids all day long in my house that's the kind of one in your house we've We've had many robots now throughout my house in testing for the last year or so. And I've had, like, you know, kind of near my kids in some aspects, but we're always, like, we're always, like, monitoring it. What do your kids think? Man, they, like, it's just, like, kind of normal for them now. Do they try to talk to them or, like... Yeah, talk to it. Yeah, they want to, like, they want to go, like, they want to go, like, jump on it and touch it. And, you know, we do kids things, you know what I mean?

Like, they want to go touch it and talk to it and be around it. And we're still not at that stage yet where I feel comfortable enough to, like, let loose and say, here, you know, here's a robot. and my kids are there, and I feel okay, and we're not there yet. I think we will be in the next several years. What's the longest they've been around any one particular robot? Um, we've had a robot in my house for, like, maybe a couple months doing work kind of on and off, you know, daily, sometimes every other day. And, you know, the kids are kind of at school or sometimes at home, so they weren't always around whenever the robots were running, but a lot of times.

and um and you know that was just like our home robot do they get attached to them they name it emotionally different names for the robot and um yeah they love it and it's actually a question where i stand in the office of like you have a robot in the home and it's like uh it's got some like character to it a little wear and tear do you like want to keep that robot or do you want like a new one that's what i'm wondering what's the emotional attachment i think kids are like the perfect my kids my kids wanted it they wanted it there we're not getting rid of this guy yeah it's got a little banged up a little bit here and there and it has a tear here and they just like loved it that is that's wild man yeah that is wild honestly in our lifetime we will be fortunate enough for every human to i think have a humanoid like almost like a phone and car wow yeah we were talking i mean just some of the stuff that you just mentioned i mean the complexity of the problem that you're solving here i mean all these little problems that i didn't like knocking over a boiling pot of water i never would have like it's just like just thinking about something that it happens every day and then you think of all the things that happen every day in just a regular household

and it's like problem city man it's like a fun house of problems there's just problems everywhere it's like hardware problems ai problems uh problems scaling and commercializing and getting the system reliable manufacturing problems like we we have a problem fun house if you want to come my campus here and check it out i'll bet you do i'll bet you do well some people say i some people say ai is that is in an economic bubble and as of this recording polymarket says there's going to be an 18 chance that the ai bubble will burst by december 31st 2026 what do you think about that Is AI in a bubble?

Absolutely not. I think you'll see some of the most transformative events in technology happen over the next 36 months we've ever seen in our... Ever? Ever. I don't feel like we're in a bubble here. I feel like we're barely scratching the surface. I'm watching AI in a human body do human work early. It's early. We don't have, you know, we, we don't, we, like at some point here this year, we'll have thousands of robots. We have like, you know, we have hundreds now, like, but like we, we need like millions of robots to make an impact. That's just going to take some time and it's going to be crazy cool.

So we're just, we're at the start line of that happening, which is like, how do we get AI out into the physical world at scale? That, that, that'll for sure work and it'll go really far in our lifetimes. And then separately we have AI now that can use computers like humans and can think where I've shown you a little bit of that here before the show. And, you know, that will manifest in a point where, like, you know, both in the physical and digital world, you basically have these little mini-humans that can do human-like work and can think and use computers and use machines. And, I mean, that's going to lead to such a productivity, like, we measure, like, GDP per capita.

But if you're able to make, like, as many synthetic humans, like, you know, millions, billions, tens of billions of synthetic humans, in the case of the digital world, maybe trillions, that'll lead to the, I mean, I think the greatest increase in productivity we've ever seen in our lifetime, and ultimately, like, reduce goods and service prices to unprecedented levels. Like a true age of abundance. Wow. Wow. I mean, I'm just curious, what do you think, what will humans be doing? I mean, I hope I don't have to like, I woke up today. I was like, I'm in the dishwasher, getting my kids breakfast, like just like busy work that I like, my kids are sitting there.

I'm like doing work. You know what I mean? Like, I wish I was just like, yeah, I just, uh, wish I wasn't doing that stuff. And then I'm like, uh, all throughout my day, I'm like trying to call, you know, call the car service and then trying to get on my flight and, you know, coming here and it's like ordering lunch, like all this stuff I'm doing all day. And I don't want to do any of that. I don't want to be like fully free. I get it. All that burden. No, I totally love it. And I just want to be like clear-headed. And I want like my AI to run a little Brett Adcock operating system and run my life.

And all these things I have in my head about what to order and pay his tax bill and like do this meeting and I have to go back and do an engineering stand-up. I want all that stuff to be in my like operating system and like a human in a box. So you're basically saying the way this is going to turn out is your brain, I'm going to butcher this. you're basically exporting your brain and all the tasks that are going on in your brain you're you're you're disseminating it to to robots i'm gonna delegate all this out that's amazing that's like we'll we'll do that in like 24 months like we'll have all this stuff so good that you'll like uh you won't like go order food anymore like book stuff like do a lot of work behind a computer like physical stuff in the world of like um doing laundry and dishes and just the bullshit legwork yeah i don't like no does anybody want to do that like i don't want to do it i don't yeah so like you clear all that for my life like i gotta spend time with my kids like enjoy life like kind of be like like i guess like clear-headed um do stuff i really love like i love working but i don't like doing all this busy work yeah um it's just like not it's just like manual like just like labor i'm doing behind computers or like in the physical

world and just like i want to delegate that out to my ai to do and fully automate it out that's i didn't i don't know why i've never thought about that i've never thought about it like i've always looked at it as fear i've always been like oh shit they're going to take everything over it's a compression algorithm like we're basically running a large-scale compression uh so like i think you know my my my the way i look at it now is uh we basically have built like synthetic human intelligence that can use computers and machines so like i'm going to delegate out all this busy work on both my digital life and physical life to like to robots and they'll just do all of it um but it's it's good i mean like there's like we have ai systems now in our lab at hark that can use computers like a human can it can talk to you it can like uh or just i made a phone call to ours right before we started and talked about my schedule and how to ask for things and i ask it for things and have it do things yeah you had a chicken chicken salad ordered to deliver to your office.

Yeah, exactly. Exactly, but no, like nothing besides a single, like, hey, make this order. And you can spin up computers to do that virtually, and then physically, like, I'll have all this work done by robotics, both in the commercial workforce and the billions, like manufacturing and healthcare and construction, and every human at some point will have a humanoid just to do all that busy work for you. And not only that, but like something to come home to that you can talk to that will know you. wild yeah it's like the yeah it's gonna happen now which is like really gonna be fun yeah yeah I'm excited to introduce to you the newest member of my family we call him Stanley we got Stanley It's past Christmas, and pretty quickly my focus became making sure he was safe while still giving him the freedom to actually be a dog.

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I use Spot On so Stanley gets the freedom to run and explore, and I get the peace of mind knowing he's safe. Let your dog roam with Spot On. Go to spotonfence.com slash SRS and use code SRS for $50 off the Nova Collar. That's spotonfence.com slash SRS and use code SRS for $50 off. well i would like to do a little bit of a life story on you if that's does that sound good to you yeah let's do it where'd you grow up uh central illinois central illinois yeah like a small town like uh 700 people 700 people yeah wow that's that's even smaller than where i grew up yeah where'd you grow up i grew up in small town chillicothe missouri how small about 8 000 people time yeah no we didn't have uh we didn't have anything 700 people man um what were you into um yeah so like you know kids sports computers like uh i got into computers really early uh did a bunch of sports um you know we i grew up on a farm so it was corn and soybeans my my uh my family was third generation of this so no kidding yeah yeah so third generation of three Three generations of farmers.

Three generation of agriculture farming. And then we switch over to AI. Yeah. We're doing humanoid robots now and AI systems. But yeah, no, I got really interested in computers like really young. Started a bunch of startups in high school and college. What kind of startups? You know, at first, just mostly things on the web, like selling things, did a bunch of like different types of like products I was selling on the internet for like throughout like high school and college. Small like drop shipping, retail electronics, like all kinds of things. Legion marketing and just fun stuff. It was like nothing serious, you know, just like playing around the internet, trying to make some money. Just I didn't grow up with money. So it was like internet was a way to like, you know, maybe make some money.

like it was really fun um you know i loved like the ability to go out and create things and I kind of control my destiny, so it was just something I attached to really early on. Right on, right on. Do you have brothers and sisters? I have a brother, yeah. What, I mean, what, is he a farmer? Colby? No, he actually runs an AI defense company called Scout. No kidding. Yeah, basically building autonomy and like AI models for defense in the military. So you guys both got into AI? We both got into AI. We live like a block away from each other today. Are you serious? Yeah, we grew up together really close.

went to same same college uh we're like different ages a couple years apart and then uh and then we were in new york for about 15 years together and then uh he just moved out to california we live literally a block away uh see him almost every weekend he has a startup like basically 10 minutes away from uh from mine of you know where i'm at now and uh he's doing great man what i mean what do your parents think when you're coming home with with what you guys are involved in and what you're what you're creating um because you still such a wild you know what i mean from farmer to to this honestly like uh i think one thing my my parents both drilled into i think both of us like really early was like um you know farming is like very entrepreneurial like my dad was like you know ran his own business like you know uh you kind of have to go out there and put the work in or you're not gonna get paid um so early on he's like listen if you want to control your destiny and, you know, if you want to make money and, you know, like, be able to actually, you know, like, do what you really want in life, you need to, like, run your own business.

And that was, like, beat into our heads, like, growing up. Like, you know, at some point, you need to, you know, you need to probably get out of here, get out of farming. It's not doing well. And you need to start something on your own. And so just kind of just, like, by default, I was like, okay, this is what I'm going to go do since I was a kid. Yeah, but you got some proud parents, man. Yeah, parents are great. Wow. Yeah, they're like, what the hell's going on here? What are you doing? But I've been doing pretty crazy stuff for a while now, so I think it's gotten to a point where it's like, you know, even at Archer, we were building like 6,000-pound electric aircraft, and before that, doing, you know, internet startup stuff.

But it's kind of been, you know, working on crazier stuff now for a little over a decade. Were you building stuff as a kid, too? Yeah, constantly building stuff. What kind of stuff? Stuff on the farm, building stuff on, like, in software and internet. just like, I just love building stuff all day. I'm like very like big into science and mathematics. Like, you know, I'm like more of a visual learner too. Like I like building stuff and seeing it and touching things and even like honestly doing internet for like, I did like, I was like, I did work in the internet and software for like 10 years. I just like always sat there every day, like wishing I was working on hardware.

Stuff I could like touch with my hands. Stuff like when growing up was like, you know, I was like rebuilding computers or just like on the farm and building stuff. I always envied things that you can go touch and build. Wow. Basically, like atoms. Man. So where do you go? Where'd you go to school? I went to University of Florida. University of Florida. Yep. Where do you go from there? So after school, I moved to New York, and I started working on software startups. And during college, I was working on basically a bunch of side, small, internet things. and um and then uh kind of like shortly after college i started a company called vetery and the goal was to basically build like a i got really um kind of going through college is like you got to look for a job you had to go find something full-time and um got caught up in like the whole interviewing process of like looking for jobs i just thought it was so broken like applying for jobs and like never hearing back and like you have to go through headhunters and then it basically became like a somewhat of this like you know boys club of like trying to figure out where do you went to school and then like certain people knew other folks of like how to get in and there's just like a wasn't very much a

meritocracy and I just thought the whole process was extremely broken and so I started Vettery as we were basically an AI recruit marketplace or the goal was like if we can get all the world's talent and hiring on one platform understand their needs really well can we make matches at scale like without like any humans involved and uh like the head of the industry is like hundreds of billions of dollars a year i won't i won't even i won't i won't use it no like i know i just hear i keep hearing everybody gets ripped off ripped off it's so expensive like pay like fifty thousand dollars a hire it's like insane and then they'll and then they'll coax the guy out that they just brought to you and have them go to another job i was like yeah they'll be like they'll force you in this role so they get paid a commission so veteran veteran is a connector yeah connector uh well funny enough we ended up selling to like the world's largest recruiting company that does staffing but like let's leave that for a minute but we um basically started in uh 2012 and um and the goal was like how do we put like a lot of job seekers and a lot of employers on a platform understand their preferences and match them at scale like just like how to use algorithms at the time we were

like let's use AI, but it was basically like how do we use a lot of algorithms to figure out like what people want and then make matches. So you can just push up a button, connect the right folks, and then make placements. And then we ended up charging, most of our revenue came from subscriptions from big companies like big banks or startups or tech companies basically looking for talent. We started just in tech in the US. So at one point we had about, I think about a little under 20 or so cities globally that we were operating in, but most of it was tech. talent, the tech space is, you know, at that point.

How long ago was this? Started in 2012 and then ended up selling the business in 2017 or 2018. So about five years, six years. Right on. Yeah. Then where did we go? Okay. So, um, veteran was like a really tough, I like basically went, like, I didn't have much money, went like fully all in the business, uh, went into debt at one point in 2015, the business was having a tough time. And then we ended up selling, ended up doing really well. The business like completely hockey sticked in growth when we got all the things figured out and just like- Vettery? Vettery was. And then ended up getting approached by the world's largest recruiting company.

The same groups you and I were talking about. The same groups we were trying to take out of business. And they were like, oh, we want to acquire the company. And at the time we were like, I was like completely dead broke and put everything out of the business. It was like, I think it was at the point, almost seven years in. And, you know, we were excited about an acquisition a year before that, like $10 million from one of the big tech companies. And they came in at $110 million. And it was a good time for me. I felt like the business was doing well. I learned a lot, and I was kind of ready for my next chapter.

So I ended up selling that business to the Deco Group. It's like the world's largest recruiter in the company. But you didn't even have it for sale. they just approached you? Yeah, we didn't hire a bank or anything. Uh, listen, at the time we were doing like, I don't know, 20, 30,000 interview requests like a week. Like, so that was like no humans involved. Like think about how many humans would take to do like 20 or 30,000 interview requests. It's like, you know what I mean? And then manage all that processes. So we were like, it would, the growth was just unbelievable. And, um, and there was like, there's something better to like a human jam and you enrolls, right?

Like, it's just like, you need like, um, And then to the extent you can get, you know, all the world's, like, talent there and all the world's companies looking, you can really create an amazing environment where you can get people to, like, the right jobs. And right now, it's not like that. It's like a really black box, like trying to both finding talent and looking for a job. It's just a terrible experience. So we kind of, that clicked. Yeah, the world's largest recruiting company came in and said, we got to buy this thing. Yeah, I'll bet they did. Yeah, I sold the business. And it was great.

It was a good time for me. I really at the point was a point in my life where I really wanted to do something much bigger. And so I took about, I basically took about a year. And so it took about a year of time I got the term sheet to sell to when we actually sold and closed. long process you have to go through like tons of docs and then you announce the deal then you actually close the deal and then it went into escrow then it finally hit my account it's kind of like one of those processes and um i want to go work on something really important hard and uh a couple industries that i've i've been interested in robotics and aviation and some areas of security for like basically since college and um i basically spent a lot of time trying to figure out if i was either going to work on at the time school shootings like basically 10x And I was like, man, there's got to be something to do here.

And we can, you know, and then secondly, I really wanted to work on like flying cars. Like having lots less sci-fi as a kid is like, man, like I really want to go. There was a near term problem of like, we got to go help with security in schools, K through 12, mostly in the U.S. And then how do we, I want to work on flying cars. And I ended up making the decision to work on flying cars at the time. So in 2018, shortly after the sale of Vettery, I started Archer Aviation. And basically the story here is you can build an electric aircraft that can take off like a helicopter. If you take off like a helicopter, you don't need to place the airports outside of cities.

You can place them inside of cities. Think about like a helicopter can take off from a building or a helipad. And so if you can take off vertically, you can basically nestle the aircraft inside of cities. Half the world lives in cities today. It's, you know, by like the middle of the century, it'd be like 70% of the world. And you just like can't get around. Like it's just gridlocked everywhere in major cities. It just like sucks to go like 20, 30 miles. It takes like an hour in most cases. So basically you can design an aircraft that can take off vertically and then fly like an airplane. So you can get like a lot of distance.

And you can basically then re-architecture the whole aircraft to be fully electric. The reason you want to do that is for cost and safety. You basically can make it like a lot less expensive you can put a lot less parts in the aircraft that are also good for safety. So basically you can build like an electric flying car that you can move around. So instead of like calling an Uber or driving that might take you an hour in LA or SF or New York, you basically can fly there in 10 minutes. And if we can pool everybody together like in a kind of like an Uber pool style business model, you can do it for as cheap as an Uber.

But the problem was like, I didn't know anything about how to build electric aircraft. I mean, where do you, yeah, I'm just... I know you just sold your business for $110 million, but where do you get the confidence to go, I'm going to build vertical takeoff and landing flying cars now? I mean, listen, I didn't wake up to this world learning how to build software. So I learned how to do that and run engineering and run the company. And there was a lot of through trial and error. um and uh i just felt like i just felt like i could learn it i started uh uh in industrial system engineering at university of florida so um and then you know ran engineering and ran the company at vetery uh so i basically just hit the books i tried to learn as much as possible about three subject areas first was like electrification which like you know at the time like electric vehicles were really doing well, and even drones.

Vertical takeoff and landing, like vertical lift, which is like traditional rotorcraft or helicopter. And the third is like winged aircraft, like airplanes. You really need wings. So you basically have to learn about those three subjects. So I basically bought my basement downstairs at home, where there's every possible book on these subjects you could match in, and started reading as much as I possibly could. And this was during the year transition. As I was transitioning out of Vettery into Archer, I was reading every possible thing. And then I found a small community of folks that were like hosting, uh, onsite, uh, like either half week or week long courses for this.

Um, and so I would go to these, sometimes they're sponsored by NASA or by colleges or whatever it would be on like basically rotorcraft or electric propulsion. or winged aircraft aerodynamics and I would basically like try to like like learn as much as possible. It got to the point where I was like completely obsessed with this algorithm I was building on electric aircraft sizing. Like how how do you actually like how would you actually build an electric aircraft? So electric aircraft which interesting is like in rotorcraft like you basically want to make to create the most efficient lifting device possible. You need as much of like as the rotor disc area like in terms of surface area as you possibly can. That's why the helicopter rotors are so large. We want that to be really large. That'll reduce power and get

Brett Adcockyou up off the ground. In electric aircraft, the problem you're starting with is you have like 1 30th of the energy as you do in kerosene in a battery pack. So you're just like you're off the

bat of 1 30th less range or 1 30th less energy. And so power becomes like the dominating factor of how to basically build electric aircraft. Like, how do you get power down as much as possible? You really want a lot of disk area. A lot of disk area is, well, one, it could be good for power, but it's also bad because you have no redundancy in the system. You have one rotor blade. If it doesn't go well, you go down. With electrification, you can basically build much smaller, like, basically, rotors and be able to fully electric. And the reason you can't do that with traditional kind of like turbo fans or engines is it gets too inefficient at these sizes.

You can't build 12 like propellers on a helicopter. The efficiency just drops like to nothing. So with electrification, you can. You can size down electric motors to small sizes and they're still 90% efficient. So like small electric motor on the table or a big one the size of your chair, same efficiency. When you do that, you create a lot of redundancy across the system. So you can build like an aircraft with 12 electric motors. So the rotors are underneath? Are they underneath? The problem here is you can design it however you want. You can put a bunch of rotors along the wings. You can put them laterally across the fuselage.

You can make one big one. You can make 30 small ones. So how do you design it? That's the problem I hit in 2018, was how do you actually do this? And so it basically was like a crazy man trying to design this algorithm to what is the ideal aircraft design? design, and then how do I go build it? So I was actually at a Hyatt Regency Hotel in Atlanta in 2018. It was an electric propulsion week-long design course and like an aerodynamics course for winged aircraft. And I met a guy there that was basically in the engineering department at University of Florida. He was doing his PhD in aerospace and I asked him what he was doing there. And he's like, I'm from University of Florida. I was like, oh, I went to school there as well. And he's like, I'm like, what are you doing here? He's like, oh, I want to go like do a career in E-VTOL aircraft. And it's called electric vertical takeoff and landing. So, you know, a helicopter is a VTOL and you put a little E in front, it's over electric. And he's like, I asked me what I'm doing here. I was like, oh, I'm starting a company to do this and I need to figure out how to go build these things. And he's like, well, listen, my professor runs a small drone lab. He's got a full building. He's got 12 PhDs.

why don't you come down and like meet him and see if you can start building aircraft with him so i flew down that weekend to go meet um his professor that runs all of basically mechanical engineering aerospace and uh long story short is i ended up taking over like his lab and um and me and him and his team started building aircraft in 2018 and 2019 down at university of florida and i temporarily moved down there with my my daughter at the time and my wife living in Gainesville, Florida, like, um, and, um, and it was great. Like we ended up building, I ended up funding a lab, uh, right off of Archer road, a new lab, cause we needed more space. I mean, I'm calling the business Archer aviation is the main road down of university of Florida.

And I spent the next like year, year and a half, basically like, um, modeling and ...holding electric eVTOL aircraft. Holy shit. Yeah, and it was a great time in my life. And the problem is there was no intersection of folks that knew electric, new rotorcraft, or new airplanes. There was no Venn diagram of overlap. Gotcha. So there was nobody in the world that understood how this all stuff works. So I had to go from scratch, like learn it, from first principles. And then ended up moving the company out to California basically a few years into the business. And then, you know, things took off from there.

We, like, built bigger aircraft. I took the company public within three years of starting it. We're a $6 billion publicly traded company today. And, yeah, designed basically, like, now four or five generations of aircraft at Archer. And it was hard. You know, it really set me up well for, like, you know, doing figure and cover and the rest of the stuff we can talk about later. but it was hard. Even going public was probably one of the hardest experiences of my life. Really? Why is that? We went public through a SPAC process. So you know SPACs at a time like four or five years ago were all the rage.

And it was a special purpose acquisition company. So it was basically companies that were going public through a merger, a reverse merger. And it was hard because in 2018, 2019, coming off of software, I had never done hardware before. So A, it was like hard to raise capital. And B, there was nobody funding like deep tech, electric vertical takeoff and landing, like companies. Like, you know what I mean? The big venture capital groups were not funding SpaceX or Tesla or Rivian, like none of these were getting funded by traditional investors. They weren't raising money from the named investors we all know about now.

Oh shit, are they always behind like that? The mandate for most of these VCs in the Bay Area, or Silicon Valley and stuff, are not to do hardware. They don't really... And if they do hardware, they don't do deep tech. They don't do like rockets and autonomous vehicles. And I don't think there's a single, you know, top VC in the U.S. that's invested in a humanoid company. No shit. And as of last six months ago now, nothing. Like, they just don't do this stuff. And so, like, I ended up going all... So, you know, like, you know, made, just made $110 million and, or just sold the company for $110 million.

I made a lot of money, like, personally. Ended up going all in on Archer through the IPO, like, through going public. I, I put, like, all, all the money I basically had. I bought a house and the rest of the money went all into it. And, and it was a stressful period. So we went, we went public through a SPAC. And the reason it was tough is we ended up getting to a point where we just couldn't raise enough money privately. like it was uh it was either like raise you know 100 million dollars privately at like you know some valuation three four or five hundred million dollars or or is like go public and raise

Brett Adcocklike a billion dollars wow and uh we ended up going public and raising a billion dollars

wow um you've got a huge appetite for risk and we got sued during it oh really yeah like we got sued by uh basically like boeing and a big uh big startup that was founded by larry page google founder. And, um, that's gotta be intimidating. Yeah. It was, uh, I woke up to like a front page of New York times article about, oh shit. Yeah. It was, uh, it was crazy. I mean, the backstory is I, um, the, I took, so Larry Page started a company and, um, in the Bay area about 10 years ago called Kitty Hawk. And they were the, like, they did a great work over like 10 years in electric, like VTOL aircraft. And, um, I ended up taking, I ended up taking basically the, the core 10 to 15 folks that were there all came over to Archer within the first two years.

Wow. And they retaliated by just trying to harass us while we were going public. And so, yeah, it was just a crazy story, getting public. Ended up getting public, you know, billion dollars on the balance sheet. And we just started building like aircraft and started building the service like thinking about the app and how you're going to check in and how you're going to build places like real estate to fly into and yeah and then like the engineering work we had to do around there of designing you know it's basically it's basically a flying robot you have like battery systems electric motors sensors embedded software and control systems and basically like the robot you saw this morning uh like very like you know that's like it's a flying it's a 6 000 pound four passenger piloted robot and it has 24 degrees of freedom on the system like wing wing flaps uh we like we have a we tilt the front like the leading edge six uh motors 90 degrees for basically take off vertically and then go into forward flight and then all the propellers uh fan blades on uh have variable pitch propellers so it's like a highly overactuated system that needs like a really good software like no human can like fly it basically without uh really good uh control software what ella what

altitude is it flying um about a few thousand feet so about two to three thousand feet above ground level and that's what it would normally be yeah like traditional helicopters fly at these levels i mean what what i think about i think a lot about tesla and and all the ev vehicles that coming out and you know it's the government just seems so far behind on ai you know and you just brought up gridlock and all the cities i've always wondered why aren't when are we going to go full ev i know there's a lot of pushback about that you know for for from an overreach standpoint but if you if you just think about the traffic in the cities and if you have the ai you know processing all this that even even without air vehicles i feel like a lot of that would go away because the the the ai will route you the quickest yeah it take all the traffic patterns into account and it would just flow yeah a lot easier yeah but there's all this government regulation i think it's also hard because like if you look at the number of installed cars in the world like billion and a half or so installed cars we make like 80 million or so cars a year in the world it takes you like, you know, on an order of like 20 years

to replace all the cars. So if all the cars were electric and autonomous today, autonomous cars have like autonomous hardware in them. It's not like you can just go out and retrofit all the cars in the world right now. Like it's a hard problem. Well, I mean, if you look at Tesla, for example, I mean, it can self-drive, right? It can come get you. But when you're driving, if you take your eyes off the road, it wakes you up, you have to come back. I mean, it seems it's inviting more error end of the road by, by doing that in my, in my opinion. Yeah. Am I wrong? It could be more dangerous. Uh, we're just in this transitory state right now where in like five years, like everything will be like fully autonomous and trusted and fine. And you won't have to do that.

And we're just in this transitory, we're in this chapter in the, in the book, uh, for the technology roadmap here, we're like, we're living through it and it's like a little messy and it's not quite like straightforward. And, uh, we don't quite know where it's headed next, but where it's is at some point in, like, five, whatever years, where, you know, when our kids grow up, like, they're never gonna have to think about this. It's just gonna be autonomous from the start. It's gonna be, like, you know, by default native. Yeah. And it'll be trusted and easy and safe. I think we're just, like, living through this period right now, which is, like, a weird thing.

But, like, if you close your eyes long enough, you'll have this autonomy and electrification everywhere. How long do you think it'll be? I mean, so I live in the Bay Area. Like, you can take Waymo's now. Like, I can take Waymo's everywhere. It's unbelievable. They're already all over over there? They're everywhere, yeah, they're in my, I'm in South Bay. But they were in the city for a while, and now they're in, you know, they're in Palo Alto, Menlo Park, like, San Jose, like, all over the place. They're really great. I take it, it's like, my wife and I, we go to dinner and stuff. On the weekends, we take Waymo, and it's like, it's so fun.

It's like, it's, it sounds so, like, like. It sounds so basic, like you take away mode, it's fine. It's just, it's awesome, man. Like it's great. You have like, it's the car drives so human-like and it's such a great experience like not having a human there to be frank. Like I love it. You know, I order so many like whatever, Ubers and stuff and come and the car smells or it's dirty or whatever else. And it's just like, you know, it's just easy. It's really cool. So like technology is like in like the early chapters but it's all here. Like we're gonna have autonomy at scale like everywhere it's just going to take some time to roll that out so it's the time it takes to um get the technology mature enough where they can run enough cities enough places and then it's the time it takes to get the install base of autonomous hardware and software in all these places that's going to take some time too we just can't snap our fingers we just don't have enough install base of autonomous vehicles in the world i think like tesla's got like 10 million cars in the road and like um maybe there's thousands or so of like waymos you have like a over a billion cars on the planet so you need to like like like you know make a large fraction of that all

autonomous um so you're looking at like uh this isn't going to happen in a year or two it's going to take some time when are we going to see your vehicles the aircraft um we have them now we fly every week in california uh the challenging part with archer is that we are governed by the federal airspace so to fly passengers and charge money we have to have like basically a type certification from the faa uh that process moves at the speed of like the post office and the faa is not incentivized to put anything in the air unless they know for sure it's going to be really safe the safety standard for us that we want to certify to is one times ten to the minus nine in terms of hours of reliability before a catastrophic event so that's um one in a billion hours we can have a failure yeah you can't like to be able to uh that that is like uh that's the but that's the standards when we fly it's like one of the safest form of transportation we take and it's because of those standards like uh uh governed by the faa um which is great i'm like you know we're like that's that's that's the bar you need to be at and that's the bar you need to hit especially taking passengers over cities with aircraft overhead uh you need to be at those

levels so uh that's like the that's the long pole in the tent for us and that's wherever you go if you go to Europe, it's YASA, or CAA in China, wherever you're going to go, there's federal mandates to get basically an aircraft to take passengers. So we're in the middle of the FAA certification now. We hope to be certified in the coming, as soon as possible, basically. But it's not something you can like, there's not a date on the calendar of like, you'll be certified here. You have to work through a very long and slow process with the FAA to get through And then we're also dual tracking that against a couple of different entities globally now to make sure we can get certified and get in the air.

But it'll happen, man, the aircraft. It's just, again, we're in like this chapter. We're like flying cars, electric, you know, aircraft, or just like it's early. It's earlier than like AVs or EVs, autonomous vehicles, electric vehicles. But it'll happen. It'll happen in our lifetime. We'll be taking these things around. Well, I mean, what do you envision? Let's fast forward 20, 30 years. Yeah. What do you envision? What does it look like? Do we have roads? Do those get ripped up? What does the sky look like? Yeah. What does everyday life look like? Yeah. The really important thing to hear about the airspace is that it's three-dimensional, and the roads are not.

They're 2D, and we've built cities now and houses and restaurants all around these places. You can't, like, there's nowhere to go. There's, like, no more roads to build in these cities. so you uh you have left with no choice if you and then humanity are moving to cities we have this like secular trend where we all want to live in cities right now it's like half the world lives in cities it'll be like 70 by 2050 um so we're like all moving to cities the roads can't grow anymore and we want like we're like we're constantly moving around going to work or going restaurants and just like and it just it's like it's like uh it's like this uh it's it's getting it's basically getting worse it's like this the arteries are hardening here around the around this it's getting worse and worse and it's just like it's some of the worst time to spend on a road in traffic it's like so soul-sucking yeah like it's just like the worst it's just like the worst like like time to lose um so the good news about the air is it's three-dimensional you can stack like basically an infinite amount of, say, roads in the air.

Different altitudes. Yes, at different altitudes, and even laterally. So you can basically build little tunnels in the sky, and you can basically stack them, and you basically can put orders of magnitude more things in the air than you can in the road. It's the same for below ground with tunnels. So the future of travel in cities is below ground in tunnels and above ground in the sky. The boring company. Yeah, exactly. Just like dig tunnels. And it's great. The only problem with tunnels, with the node system on the ground, or sorry, on the ground with, say, we call them vertiports, but basically like real estate for flying cars, is you can, let's say you had like, you know, 10 different, or even like, you know, 10 different vertiports inside of a city, places to like take off and land from.

you can travel between any one of those routes. So it opens up like, you know, basically exponentially more places to go to. I can go to like any node on the system at any time. So hold on, hold on. So you're saying in order to take off and land, you'll have to go to specific locations. You won't be able to do it from your home. Yeah, you're not going to take off and land from your home. Okay. Just because like acoustics in the neighborhood, it's gonna be too loud. You need like a decent amount of infrastructure for that, for charging and for passengers and cleaning and like checking in and stuff like that.

They'll be like in your neighborhood and you'll like Waymo there or walk or take a bike. And then you'll get on these and they will go to any node on the network. You can't do that with tunnels. Tunnels have to go to A to B. You can't jump to another tunnel downstream. Like, you know, I want to jump to another tunnel like 100 meters down. It doesn't happen in tunnels. You can do that with the sky. You can basically jump to any node on the network. It's exponentially more routes you can basically do with like less real estate. And then you can basically stack as orders of magnitude more traffic and humans in the sky.

So my ambition is that you're going to be, for most trips that you're traveling over 20 minutes, all of that will move to the sky. And not only that, but you will have cities being transitioned to a point where you can live well outside of cities and get to cities really fast. The reason we live in cities is because we're working there and we have friends there. And we have like, it's, yeah, it's like, I want to be like, I want to go to dinner with somebody. I want to see my buddies over here. And, uh, we want to go to work over here or like go to the mall over here. It's like, everything's there.

And that's what we want to be. We're social creatures. We want to be there next to other humans or some of us are. And, um, so, uh, yeah. So anyways, uh, but like, you know, now that you can fly this 150 miles an hour in the air with no traffic, point to point, like no stop signs, no construction, no things jumping out in front of you. You don't have to like travel different distances. is you're going straight from A to B in most cases. So you're removing 10% or 20% of the distance just by going point to point. And then you have nothing stopping you going 150 miles an hour most of the way there.

You can live like far outside of cities and get down to city center in under 30 minutes. So will these be personally owned or will this be like an Uber service? It'll be like an Uber service. To get cost down, you'll basically just like pay per trip. You'll pull up an app and you'll go like, I want to go downtown to whatever, it's 40 bucks and i'll be there in under 30 minutes and you'll you'll you'll say great i want to be there that time you'll hit a button it'll be on demand you'll ride your bike over or walk you'll get in one it'll leave in seven minutes and then you're basically flying right down to town Holy shit, and you're saying this will be in every neighborhood.

This will be very accessible to everybody. Yeah, you're designing the whole electrification allows you to reduce the cost and the safety burden of all this. Wow. We have like a normal helicopter could have like 100, 200 like safety critical components that any component gives out, the helicopter can go down. An electric aircraft has none. You can lose a motor, you can lose a battery pack on board and still fly safe without having this. And so just from a safety, from a part count, from a cost, from an acoustic signature, helicopters are loud and very noisy, and it's just a much better technology for this.

Have you been in one yet? I haven't flown inside of ours yet. I've also been inside of our aircraft. Um, and, uh, we basically have professional, uh, basically, uh, pilots, uh, at the company. Test pilots? Yeah, test pilots. And they do, they're career test pilots and they're unbelievable. I'll bet. Um, you know, a lot from the, a lot from the military, a lot from the big aerospace groups and they're, they're just professionals. What do they think? I love it, man. This is the future of aviation. Man. Uh, everything's going electric and, uh... This is so crazy. Yeah, it's crazy. It works. Like, it's, uh, it's crazy.

It works and crazy we're in the right time period to make this happen. Yeah. And, you know, the good thing about, you know, Archer now is we've demonstrated, the hard part is, like, being in the wrong, like, the hard part is, like, making sure you're in the right decade. You don't want to, like, go do this and you find out, it's like, oh, it's like a 2040 event and you can't get it done. It's just like a, it's just like a waste of time. And so the good news, you know, for Archer is we, like, we're in a sweet spot here where this is going to happen, aircraft now work. We're certifying now with the government bodies like the FAA to make it happen.

We have a good balance sheet with cash. The team's great. And so it's just like, you know, get certified and get this thing going. Damn, that is... You're really changing the world. Well, we're at the start of it. But, you know, hopeful to make this thing work. Where are we going next? Humanoids? Let's... Yes. Let's do it. Yeah. How did this idea start? Yeah. So, um, you know, it's been like five or six years working on like a pretty crazy robotics work at Archer and, um, like the ultimate like meta problem in robotics space is can you, can you build like a general purpose machine to do everything in the world?

like much of what, say, humans can in the world. And I have this big belief that, you know, we have a weird biological species. Like we look, we're like, you know, we have these weird hands and arms and legs and certain height and sensors. And then we ended up building this world around us so we can interact with it. I mean, if we get dropped into Mars today, we're going to build like coffee cups that we can hold and stairs and doors. And we're going to build this stuff again. And it's like the human operating system. We're building things we can use and operate in that makes it easy for our lives.

And we built it around the form factor that we are. Meaning if we look differently, the world would look different. Our Expresso machine would be different looking. We might not even like Expresso or caffeine in this case. So we built this whole world around us. The holy grail for robotics is can you basically build a general purpose machine that can do what humans can, which for me is like a humanoid robot. And a humanoid robot is just a robot that has like a human form. So it has legs so it can walk upstairs and walk over like, you know, uneven terrain or say things on the ground and bend down, which legs are important for, or reach up.

It has like arms. in hand so we can manipulate objects and do things like, you know, grab the stuff, open these gummies and, you know, fold laundry and do real work. And then we have the right sensors so we can, like, see the world and understand what to go do and use, you know, our biological neural net to kind of figure out how to reason from. Um, and, um, you know, having worked on like, you know, kind of like aircraft or, you know, now five or six years, I, I thought it was like pretty possible to go build, um, an electric humanoid robot and electric is important for cost and it's important for safety and it's important, uh, because the performance will be much greater.

And at the time, I mean, one of the best humanoid robots then was probably like the Boston Dynamics Atlas, it had like a hydraulic system. It was like really heavy and big and high torque and very leaky, like the oil is everywhere. And also didn't run very, like maybe ran for 20 minutes on a single charge. So you needed to kind of radically transform the hardware. And then you needed to figure out a way to build like an AI brain. The humanoid is so complex. It has like, let's call it like 40 degrees of freedom. And degrees of freedom is like a joint. So like an elbow is a degrees of freedom. You know, shoulder's got three.

A ball and socket has three, like a pitch-on roll. And our robot has about, let's call it 40 degrees of freedom in it. Each degree of freedom is a motor that can spin 360 degrees. So if you only look at how many positions the body could be in at any given time, like this is a position, this is a position, and keep moving, the amount of states. It's, mathematically, it's 360 degrees to the power of 40 actuators.

Brett AdcockSo there are more states in the robot than atoms in the universe.

There's more positions the body can be in. No shit. By far. It's a much greater number. Done the math a few times. Very confident in this, even though it sounds ridiculous. So you just can't code your way out of this problem. Like, how are you supposed to write code? Like, how's a human supposed to write C++ or code to tell the robot at any given timestamp what to go do? Like, if I want to grab this, I need to move my whole upper body and maybe lean over, and I'm moving my fingertips and my hand, like, my wrist and hand get in position to grab this. Like, it's an intractable problem for code. So, um...

I mean, you were saying earlier, I'm going to butcher this, but it's updating the foot 200 times a second. Yeah, our controller is running... For balance. Our whole controller, so we have a main computer, is processing what to tell all the joints to do, 200, maybe more than 200 times a second, to make sure we can just balance and then we can like do the task. It could be like reaching over and grabbing this or balancing. If we run that too slow, we just like don't have enough feedback. Then we just fall over just like, yeah, we have to fully balance. You know, it's dynamic. So it's if you, generally if you power it off mid run, it's going to just fall down.

It's not like a four-legged dog or quadruped robot where like any given point is usually statically stable. So it makes it very difficult because you have to be able to even move your hand. I'm moving my pelvis. And my whole body, my torso's moving, my head's moving, like all of it becomes very complicated now. It's not just like move my hand, it's like move my whole body to get my hand in the right spot. So every joint, all those 40 joints have basically position encoders. We know exactly what position the motor's at, or even the case of the knee or this. And we have force sensing, torque sensing on board.

We have the ability to detect all the forces that that knee is seeing. It could be really high when it's walking, or it could be like you know it could be like it could be powered off and have no forces on the leg all of that feedback and is as being sent in the main computer and then we're telling uh all the joints what to do uh over 200 times a second some of the other feedback is happening at like five or six kilohertz so the force feedback is happening six five six thousand times a second to the motor control on board and we do the motor control the brain for all the motors has done it locally at the motor level because it needs to happen so fast that's being fed back to a main computer that runs a control software that tells the rest of the whole body what to go do at every time stamp to keep balance starting something new isn't just hard it's terrifying before i launched the sean ryan show those what-ifs were loud. What if nobody listens? What if this fails? Walking away from what's familiar to build your own thing takes real faith, but it ended up being one of the best decisions I've ever made. Whether you're starting a podcast or launching a store, it helps to have a partner

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That's shopify.com slash srs. so getting back to the original thing is my bet you know we're like three and a half years old or something like that at figure i bet three and a half years ago in 2022 when i started the company was that this was possible now and my like my view is like it was i don't over some 10 or 20 years this will work. And so I basically started on this endeavor to go basically rebuild from the ground up humanoid robots and AI software to try to see if you could make this work. At the time, there was no good precedent. There was no precedent for showing that there was no AI that ever worked on a human or robot in history. And there was no electric humanoid hardware that was remotely okay to show it would work and there was no hands there was none of this stuff wow so i actually had i actually had a lot of trouble even i saw that i had a lot of trouble early on even like getting people excited about this because they're like what the hell are you doing um and so i ended up having to like basically self-fund a lot of it in the first i the first year i saw funded all of it no kidding yeah and it was a lot i mean we got the business to a million a month to burn in month four and uh but it was like i knew what to do we built a 40 person team and

like as fast as possible and um i knew how to spin up hardware and software and again you know the the key characteristics of robotics like electric motors battery systems uh you know control software embedded systems and sensors and then even within like electric motors we build actuators. They have a rotor and stator and a gearbox and sensors, electronics and wiring and connectors and multiple sensors inside of there. And then firmware, it lives on the, say, the microcontroller lives on the motor control side. And then we have thermal characteristics, it's hot. And then you got to all make that work at very high speeds and high torques, meaning motors don't like working when they're not moving. Motors hate not moving. Motors want to run on They're designed to run highway speeds.

They love that. Like whether it's a generator, like something, you know, an appliance in your home, or like an electric car, they want to like run at like highway speeds. They're designed to run at full RPMs. That's when they're the most efficient. When motors are stuck and not moving, but holding power and holding forces, they're all, it's a really bad point of the torque speed curve. So they're not built well for this. So humanoid is used all the time. Like when we're standing, we're like not moving but holding forces, when we're like holding something out and like giving me the gummies, like it's not moving now but holding forces. It's just a really hard engineering problem. Just that one little aspect, which is like hardware umbrella, just motors. And so we have whole teams in those areas, just in that one little area here doing like rotor design, electromagnetics design, stator design, gearbox design, sensor design, motor control design, like all of this inside of teams.

It was an enormous lift to just get the team members there to do it. So we spun up a team to go operate that really quick. And then, you know, now, like looking back, I think we raised, you know, you know, 2 billion or so. Like now it's a much different story. We have, you know, we ended up building figure one, which is our first generation robot and had that walking in under 12 months. So from when we... From inception to... Wow. Yeah, from when we... And we had basically incorporated the company in 2022. Our goal was like, can we get a robot walking by itself, these dynamics, in under 12 months?

And we did it. We did it with like two days left in the year. And at the time, I think it was the fastest time in history for anybody to do this. And then from there, continue to build the capabilities. We built generation two, figure two, which is that guy right there. He's our second generation robot. and um and i think one thing we did before we kind of moved even to gen while designing gen two is um i think it's probably like 2023 at the time we um we did a demonstration where we basically wanted to put this k cup k cup inside this curic and run it it was just on a very pretty simple like like not nothing crazy but we had a you know curic machine coffee cup and a k cup and we had to go grab the k cup open you know open the curic put it in close it run it and then you know make coffee and um you know it sounds simple but like for a humanoid robot to do that uh is extremely hard and then we wanted to do all of that with just neural networks it sounds simple but i mean simple task give it to a four-year-old yeah exactly i mean the dexterity on the hands of that thing is just to hand you the bag of gummy bears yeah yeah yeah then can you do it with neural nets on board it's crazy you not code your way out of it

Can you have a, can you take in camera pixels and then output trajectories for the motors through a neural network? No code. And we did that in 2023 on figure one. And it was like probably the, probably the most significant demonstration we've done in four years now, almost four years, where we were like. Internally, we were like, you know, how do we get neural nets to run on a humanoid? And I don't know, I think it's probably one of the first examples in the world to ever have shown that. And, you know, this was like, game on. This is like, we have, let's go build really good humanoid hardware.

Let's make it cheap and really reliable. Let's make sure we can do what humans can from a hardware perspective. Meaning, you want to look at like a phone, where you can just add new apps to it, like the Do Laundry app. and the hardware doesn't need to change in the same exact hardware. Like humans don't need like new hardware to be able to go off and like learn how to do new skill now in the physical world. So you want to build the humanoid hardware so it's like can do everything basically a human can or as most as possible. And then you want to go all in on neural networks because you just can't code your way out of this problem.

And that was the first moment in 2023 where we're like, hot damn, this is going to really work. This is going to be humanoid robots, hardware gets good, and then you're basically going to be, this is going to be a data play to train neural networks to run on humanoid hardware and do what humans do. And then we launched, you know, we launched Figure 2. We did a lot basically more work. We started unveiling Helix, which is our neural network stack internally that we do here. And now we've designed Figure 3, which is our third generation robot you have here, which is like the best humanoid hardware in the world by far and we're now running robots that do like i watched it you know the other day uh unload dishes and fold laundry we had figure twos at bmw last year that worked six months every single day every uh six months every single day it worked a 10-hour shift every day for six months and um we had uh it was just it was like the first time for us getting robots out to the real world doing real stuff like you know it's fun doing like you know demos at the office and showing it can really work but the real like uh level boss is like how do we get robots out and yeah the clients fire us do they love it does it work and the goals we have for clients is hard

because we have to do human work so we get like human kpis in terms of speed and performance like humans like you know in the case of manufacturing they don't like you might mess up every once in a while but you like refix it so you're not you're not messing up every single time you're pretty fast in most cases the humans are there not like you know quitting or not show up to work but sometimes that does happen um so it's like it's hard it's a hard bar to go hit and we have to wake up every day and be able to do that and so we had robots in the manufacturing line uh they have a they they basically have a basic body shop that basically builds like x3 and x5s and january of What was it? 2025, we started building our first BMW X3s on the line, and I bought the first four that did that. They're on my campus now. One's at my house. And they didn't build, obviously, the whole car. There's a ton of parts, but we did a part of the whole process.

What's BMW's feedback? Um, they're great. I mean, the BMW is, like, if you go into, like, a car manufacturing company, they're, like, the best roboticists in the world. There's robots everywhere. There's, like, these giant 12-foot KUKA, like, manufacturing, like, uh, like, robot arms on the floor. They're bolted to the ground. They're massive. These things are carrying car chassis around like they're kids' toys. The cars are so big and so heavy, you can't, human can't hold it and pass it around. So you basically have machines that are building the car and then moving the car. So the whole body shop line is only automated end-to-end.

And it's like, not end-to-end, but like there's humans involved, but like the car is being like built by machines. And then there's machines everywhere. There's special end effectors on every machine. They're switching these things out. Basically in real time, like grabbing a big end effector. The end effector is something that is grabbing a part. These end effectors are the size of my chair. They're switching them out in seconds, one or two seconds. They're doing it really fast. And then they're basically building a car with this. There's robots everywhere. And so, like, BMW, like, they're like, it's been a privilege to see how, like, much automation has gone into automotive.

It's unbelievable. These machines, like, kind of make what we're doing and sometimes look like little toys. No kidding. We were doing something very complicated, but the car manufacturing is just like no joke. So what specifically were the figures doing? Yeah, there's a body shop line that's basically building the rear header. It's like the back plate. So the body shop, they basically build the car by putting basically sheet metal together, welding them onto the chassis, and then they're basically building the car around that. Like you end up putting the seats in, bolting them down, putting the car doors in, wiring them up, the harnessing.

and we were in the body shop line helping basically attach the rear head like basically putting the rear header on this fixture so we so today um we basically are last year when we're there uh we basically take a piece of sheet metal and we basically put on this fixture and we do that over and over again and they do that you know 10 hours full shift and uh there's three different parts on those three parts go on this thing rotates and this big giant kuka machine like this robot arm goes and spot welds it and switches it switches out to another effector and then grabs it and puts it down the line so like these these uh these facilities are being like fed this these parts into the machine and we were like we were a piece of that and um the goal was just like can we run robots every day you know are we gonna get like ass handed to us you know is it gonna be easy it's gonna be hard and uh i think it was in the middle i think we like um And we got the robot to a great spot where it was brand every day.

It was great. I think the biggest learning lesson we took away is we had, I really cared about, can we do that? And can we like clone it times a thousand, times 10,000? Would we have any issues scaling? That was the part for me. Like, is it just like, you know, does it completely shit the bed and he's like, we need to rework our plan and go back to the office. Does it do it incredibly well? And you can just copy paste this thing to everywhere in the world. Like how does it, how did it work?

Brett AdcockAnd the biggest learning lesson we got was that the robots, the robot that started the first day at the start of six months and the robot that ended the shift that day was the same like

even though we had multiple robots in operation every day we had like the same robot that did the start and the finish wow and it was cool like you know like it was same robot ended six months later and this was the thing where you know the worry was that humanoid robots couldn't last a month couldn't last a week in these kind of environments and uh you know wear and tear it's like it's running like a you know 40 degrees of freedom motors every single day can they operate really well. I think from a hardware perspective, it did an A plus job. I think from a software perspective, we did like a, I would say a B, B job, B plus. We, and that's mostly from like my perspective, like the architecture decisions I made to scale. We, about half the stack we had like traditional like code and heuristics in. So like the controller to walk was done by a C++ controller.

it was done by code the walking you saw today we had back then was done in code okay the rest of this we had a bunch of other stuff in there done by neural nets and like some of the perception stacks some like you know some of how to move parts around everything else and you know this was a year and a half or so ago when we were first launching and um and i was like man this the the the biggest problems we're having is the coding parts get stuck the robot like either doesn't see like the right uh like doesn't like see something right on the part and misses the the object detector doesn't really understand what's going on the controller when it gets out of bounds of like what it's ever seen before like you have carpet in here now and it's like really squishy the robot's doing fine which is great but i think our old controller not do well it's like you have like really shaggy carpet here and it's like yeah and so like uh and it's like not very it's like it's like you know it's harder for a robot to walk around and um so that that that was like we had a really difficult time uh seeing that even though it did well every day seeing that scale to like lots of robots so we went back to the office this is about

a year and a half ago and said we need to basically refactor everything into a neural network and one of the big like and i think we just announced helix two two or three months ago now I forget, like end of last year. And it's basically entirely down the stack, including the controllers and neural net now. There's like no code left really on the robot. Maybe some code in certain pieces, but mostly just almost all of the thing is like a neural net at this point. We removed the need for like almost over 100,000 lines of code when we launched Helix 2. And so what you saw today was just like a robot that we can put now back into, say, the factory and these places that will run only on a neural net.

And I think we're running these robots right now. We're getting ready for deployment to customers and they're running incredibly well. We have robots running like basically now in 24-7 shifts without stopping, without any faults for like days and days. We just went like over, we just had like record time this past week on the robot running until we saw like a fault. Like almost, yeah, basically a whole week. Holy shit. Like they can run like four hours or so, five hours, and they need to charge. Another robot knows that, steps in, steps behind the robot, say, and gets ready for work. The robot then backs off.

Another robot swaps and spot. Like in the next 10 seconds, it's doing work again. So we can run that now in 24-7 shifts where they're talking to each other, all autonomous. No humans or you can go to bed, whatever. And they're running that shifts all day and all night. And we do it across multiple use cases now at the office in 24-7 shifts. and it's just like we're running them hard what kind of stuff are they doing at your office we do a few things we have a logistics use case that we run in 24 7 shifts constantly we really like it's done with the neural net it's moving packages around and uh it's a really good use case we like uh we like it and we um we want to like i want to run in for months and have failures and we still we still we see failures right now and it's most of it's in software robot gets to some spot where it feels unsafe doesn't know what to do and it'll stop for a little bit and then the you know the The robot's not on the line for a couple of minutes.

We call out a failure and we're not happy with it. We have robots that are greeters and visitor bots that walk around the office all day, 24-7. So you're over the office, you're getting lunch or you're walking around, you're interviewing with us, you see robots everywhere. And those run in 24-7 shifts, all day, all night, weekends, Christmas day, whatever we run them. Greeters? Yeah. How do they greet you? Come talk to you. They'll just come talk to you? Yeah, they'll come talk to you. And you can go talk to it and ask for things. We really wanted to go like, you know, the end state for us is like it's going to replace like somebody like meeting the candidates that are interviewing there, taking them to the conference room, getting them water or coffee, like all of that end to end and whole experience.

Shit. Yeah. Right now, they're walking, I mean, right now they're walking in the office, like at nighttime, they're walking in the office everywhere. And it's a good, it's a good stress test for us because these are neural nets that are running for navigation or planning or manipulation or whatever it would look like. And it's hard, and this is a noose thing. It's not like these things have been around for decades and we understand that they're really mature, they're not. So we really stress test them like crazy by running them all the time. What's a conversation you've had with a robot? We've been really working on deep memory, because I think one thing I really don't like is these conversational AIs you talk to that don't know anything about you.

It's not much to talk about. It's like, what's the weather? You ask things about Wikipedia or something. It's like the way to work. It's just, it's kind of nonsense. It kind of feels really stupid to me. So we've been working a lot on deep memory. So it will actually get to know you. Oh, yeah. Yeah, it needs to know who you are. Like, who am I talking to? Is it Sean and Brett? And then based on Sean, like, do you have their permissions to tell the robot to go do something or not? Like, if you're visiting, no. You might be able to get coffee or water, but like, if you want to have it, like, go do something new, it, like, won't do it.

I've not even thought of that, either. Yeah, yeah, like, we want to understand that. You want to be able to command it. Yeah, what are the permissioning systems and authentication to the robots? I mean, like, you know, like, robots in my house, my kids are going to be like, hey, give me ice cream. every 10 minutes, and you can't have the robot doing that, right? Imagine I get home from work, and the kids are just like, you know, through pints of ice cream, and the robots are just getting whatever they need. Like, it'd just be chaos. Yeah. So what is it, voice recognition? Yeah, you have to do voice for something.

Something's voice isn't enough, where, like, if you, like, think about it, like, an extreme example, you wanted to go, like, order food or spend money or send a wire, like, voice recognition won't be enough. You'll have to do a higher level of authentication. How would you do that? Facial recognition. OK. And then if you have perhaps even finger press scanning is possible too, but facial is what you really want to do. Gotcha. So all those systems are not robust enough right now. We're working through them. And the goal is to get it super robust. But we want to have conversations with the robot.

We want to ask it to go do things. You want the main modality to be speech with robots. So you want to just, like, hey, man, go make me, like, go make me, like, go make me food or, like, when I'm gone today, do the laundry after you, like, after you unload the dishwasher, like, you know, do laundry in, like, my kids' rooms today or something like that or text it. So, like, language is, like, super important UI. So we're, like, spending a lot of time on speech. You can text it, too. Yeah, every robot we have has 5G by default on board. We actually run 5G by default now. Uh, so every robot off the line has 5G enabled, um, like, uh, we have, like, a T-Mobile 5G, uh, T-Mobile's an investor of ours, and every robot has an eSIM card for, for T-Mobile 5G, so it comes with a line, we use 5G for all the main network, so if you want to, like, um, you know, if our, like, if our systems want to tell the robot what to do or do something, we do it through 5G, and, um, and so, yeah, you can, like, you can text it.

So you could be at work and say, hey, I want to get the pizza out of the freezer, put it in the oven. Yeah. 425 degrees, 15 minutes. Yeah. I mean, we can't do that in right now, but, like, that's the goal is, like, we've got to get there. Like, we've got to get to a point where, like, that is certainly possible, and you want that to happen. You want to be like, yeah, I'm at work. When the groceries come, make sure you put them inside and put them in the fridge and do all this. Or they wouldn't even know that. Go check the mail, have it on the counter when I do it. like all feed the dog yeah everything like watch the dog make sure the dog's okay yeah holy shit so it's it's a nanny housekeeper gardener it's uh the jetsons all of it yeah it's gonna be all of it i mean you might want to garden you might want to do it all this physical labor we do today i think will be optional in the future so you'll like you might like gardening um you know you like mowing the lawn you just like mow the lawn if you don't want to mow the lawn don't mow the lawn like all this will be a choice holy yeah and you said it's gonna it'll download apps for different you want to think about the software layer like you want to think about

the like so for us like um what's so powerful about a humanoid is you you don't want to go out and change hardware whenever we have a new like app on your phone you just like download it and connect do new things now like it's got my bank account now i can do bank account stuff or you got to download it, you got a calculator, you can do calculator stuff. You really want to treat the hardware like this, where you basically similar to a phone, where you don't have to change the hardware for new capabilities. You want it to learn how to do like... You know, complex towel folding or like unloading the dishwasher, making coffee on a Keurig, like all this, like walking the dog. Like these are like almost like the matrix where you get like plugged into a system that re-uploads like weights into the neural net weights into the robot where it can like learn new things. So that's what we do now.

Like if the robot, like if we can't do package logistics well, we get data for package logistics. We train our Helix neural net for a week, and then we load it to the robot, and it can, like, then the same robot that was, like, folding towels, like, the week before, can now just sit there for 24-7 and do logistics work and package work. Wow. Nothing changes. Where is this going to go first? Consumers, businesses? You'll ship into businesses first. It's the engineering complexity that we have to ship is, like, proportional to the variability that we see on site. so um the veritability at homes is like extremely high it's like it's my home is chaos like kids are just like just dismantling the house it's like it's basically in real time uh and then there's just like food or they're eating snacks toys like it's just like it's just chaos and then like you know if we go to your house and my house we probably have like different appliances or different toasters and different microwaves all a little different everywhere we go so the home is just like this, like tons of entropy, like tons of veritability, a wide distribution of tasks.

It's like the, it's like the ultimate like challenge for robotics in the home. It's like the hardest, most variable thing we got, we got going. And in the workforce, it's like, you have this like work cell that you're doing. So like, if you're doing like manufacturing logistics or, you know, a lot of tasks, you have like this area you're doing work in and you can basically kind of write down on a piece of paper how to do every step. In the home, you can't do that. You can't write down a piece of paper. I can't write down a piece of paper how I'm going to interact with your house. I mean, you've seen it. But the next assembly line or the next conveyor system, it's like, I kind of know what to do. It's like, I get the package, I flip it down and I need to do it every three seconds. You kind of have a good understanding of what to go do.

So it just makes it easier. It's like the analogy would be like highway driving for autonomous vehicles that's just happened sooner because the veritability is lower than in the city gotcha um so it'll happen first to scale and then the industrial thing has a good good thing where it's like you kind of have your own work area so the safety areas are not as high the hardest thing in the home will be uh once you figure out how to get performance there meaning it's capable of doing everything in the home like so you can go to your home and do everything the longest pull from there is going to be safety where like me and you feel safe like being like having this here with our kids and that is um that that's going to be the hardest challenge by far and um that's gonna take some time it's a very there's some trust that needs to build there's a tracker that needs to be built there's like system safety engineering that needs to be done extremely well um so that just and then the home like you can charge like 10x you can charge like 10x more in the commercial market than you can the home home needs like 500 bucks a month your carly's and those will be you think those will be around 500 bucks a month yeah i think it'll be like that level like you

know that like order of like more magnitude yeah um yeah so i think um and then the commercial workforce you can charge like 10 times more um so like so it's just like the commercial and then In the commercial market for humanoids, half of GDP is human labor, maybe a little under half. So it's like 3 billion humans in the workforce contributes to 40-something percent of GDP. So you're talking about the largest market in the world is sitting in the commercial workforce. So you have that, plus the variability is lower, plus you can charge 10 times more. it's like the like for investors are like dude why would you ever work why would you ever do homework You know what I mean?

Like, why would you like spend time over here when you can just go over here and build like a $20 trillion company? And my answer for that is just like, I just want robots in the home. So don't really care. You know, like we got to make that work. Yeah. I mean, you say in 10 years, every home will have a humanoid. I don't have every home in 10 years, but we will have- Pretty close. We will have in 10 years, you have like two long poles. You have like a long pole with manufacturing enough volumes for this. And then you have a long pole where you can actually technically do the work fully end to end.

My belief is that the hardest thing in the stack is not manufacturing. The hardest thing in the stack is, sorry, the hardest hill right now is

Brett Adcockcan you put a robot into your home today and do the five hours of work you need without ever seeing your home before.

The first group to do that, I think will become like the largest company in the world. And you can do that with maybe a hundred robots. No shit. Yeah, I think you can solve a general purpose humanoid robot. I think you can solve general purpose robotics with maybe like hundreds or low thousands of robots. Maybe a hundred. How so? At this point, the issue we have, so we can go into my home today and we can do little pockets of work. We can do like, I can unload the full dishwasher. I can, once the laundry's in the basket, I can take it, walk it, and fill up the washer and run it. And we can do pockets of work.

We can like take the laundry, put it on my bed, and we can fold it all. And then, so we're doing like little spots of it. And it's pretty good. And, but there's a lot more spots to go fill for like long horizon work, just that. And we have to be like extremely robust to maybe different types of clothes or like different types of like, I don't wash my jeans, like that type of thing. And all these different like veritability that you might see. And we haven't been able to, as of today, that's like, that's the hill we got to go solve. That hill looks really hard. So how, I mean, how, let's say, let's fast forward 10 years, I'm getting one of these guys, I put them in the home, how does it, I mean, do I train it, do I personally train it?

Hey, when you're emptying the dishwasher, the cups go here, the plates go here, the silverwares go here, the forks go here, when you're doing the laundry, I want these ones washed cold, I want these ones washed hot, this is where they go, this is where the jeans drawer is, this is where I hang my shirt. yeah is that how it works is it yeah you'll get a you're gonna teach it you're gonna robot in a box you open it up robot get out it'll start talking to you uh it'll ask you um to show you the house and um you'll it'll you'll you'll say like you know it'll say like you know can you walk me through your home and it'll follow you around and you will tell it all that like you would um let's say let's let's say it you'll say you had a friend staying for two weeks at your house that you know needed to like cook and use your stuff like like you know you wanted to wash clothes and stay in one of your rooms like you'd walk that person around and you'd be like hey man this is um this is recycling here this is where trash is at uh like here's here's where you get water like uh the the trash goes out every you know every monday uh you know this is uh i you know we do blankets uh on the couch but like you we want them in the the cabinet when they're done

you know what i mean like or we want these over folded and put it over here like like all these things you have in your home that are like uh you know important and um and like just like you would like walking somebody like human around for the first time that's what you'll do and the robot will semantically understand, like, we'll, A, have, like, we'll remember all of this, and it will learn based on what you want, and your preferences, like, what to go do. Holy shit, it'll be that, so it's just, like, turning a human being. This is, like, not, this is not 10 years. We'll do this, this is really soon.

Like, I think in the next, like, I mean, I'm hoping this year we can, like, drop a robot in your home and do a good amount of stuff. It's just, we'll see. I mean, this is like, this is like solving like the holy grail of robotics. This is like solving for a good general purpose humanoid robot. Maybe we don't solve it this year. Maybe we solve it next year. Maybe we don't solve it next year, but it's 2020. I don't know. Like we're, we're close. We feel like we're in the red zone with like, we feel like we know the architecture. We have the hardware. We know, we know how to get the data. We put the data in, the robot does it.

We need to like now like learn how to generalize. We need to not like, like move deeper into pre-training for, we, we know the directions we need to go ahead. we think to solve this and we're seeing a lot of both positive transfer and um a lot of just like uh we're seeing internally the we think the right direction to make this work when you were talking about you know trusting the robot with your kids what what are i'm just curious what are your concerns yeah at archer i haven't thought about this i think at archer was always like the i'll never like feel safe i never feel comfortable like recommending arch like people to fly in archer and letting people fly an archer until like i like would fly an archer aircraft to my kids um that's the level of safety we need to get to it's like a really high bar um that's what you want though right to take a aircraft like that around um so i think the same thing for figure here is um we'll be we'll be safe when or to me it will be safe when i feel comfortable putting the robot around my kids i have a one-year-old and yeah four-year-old and seven you know i mean young kids. They want to jump on everything and, you know, it's like, they're like, yeah,

and the robot, like, you know, the robot needs to be extremely safe there. So that's another hurdle. It's like getting to general, like solving general purposeness, getting safety to work and then making enough of them. Those are kind of like the equations from here. Listen, we have a good plan, only what to go do here, but now it's like execution that we got to go do to show that it works. Right on, right on. You want to take a walk around this thing? Yeah, let's do it. Perfect. Most people blame stress, sleep, or just getting older when the energy starts to fade. The brain fog, the slower recovery, the feeling of running on empty by midday.

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all right this is our uh figure three humanoid robot it's uh we actually unveiled it last year my god yeah it's about 130 pounds five foot six and uh we basically designed it to do most things like a lot of things humans do 130 pounds 135 pounds yeah it's uh fold laundry do dishes do manufacturing logistics um you know i think a few things here that we like made improvements on this is our third time basically running through three generations of robots. We reduced the weight and mass. We made the robot skinnier, but also same strength and speeds. We upgraded the sensors on the robot. It basically sees through cameras. We have better our fifth generation hands on board that have a camera, tactile sensors, basically improved grip.

We also have on the robot, like basically more compute on board for running our Helix neural network we also spend a lot of time on uh just basically making the robot more safe so they all have kind of the squishy layer of foam on it so yep go ahead so if you let's say somebody pushed it over and fell over i mean what's the durability of these i mean depends how hard you push it but like uh for the most part we we fall robot can get back up just continue to do work uh it depends how you fall. Sometimes we break necks. Sometimes it's fine. All right, turn around. Another thing too is like we basically, the robot's almost fully soft wrapped. One thing we can do here is we basically can make clothes for the robot, which we do for both our customers and internally. The clothes can be put on by like any person. So we can basically unzip it, take clothes off, put clothes back on. We don't need tools to do so.

and um can we see can we see what's in there uh yeah basically it's the torso uh you can't see any of the internals no they're all inside the structure uh so inside of here we have basically a battery uh gpus computer uh power distribution um basically the brains and all the energy are in the torso wow um and then uh and then basically the robot is basically left with basically 40 joints. So all basically electric motors and the motors that have like basically tons of sensors on it for balancing and doing work. All right, turn around. All right, we can walk with it for a minute. All right, let's do it.

All this walking and all the robot movements are all done, again, through a neural net. There's no code helping us do this. Holy shit, this is awesome. You want one? What's that? You want one of these? I want a couple of them. You want a couple of them, okay, great. Dude, whoa. Yeah. Let's go back this way. Let's turn around. Can it run? Let's see how fast it can go. We have running, we have, I don't know if we're on the running mode, but let's go as fast as we can. We do jog with the robots out. Really? On campus, yeah. I think this also looks cool, right? Got high tops on. Looks awesome. Yeah.

And you said there's cameras in the hands too. Yeah, cameras in the palms. Right here in the palm. So we can see the fingertips when it's grabbing objects, and then every single fingertip has tactile sensor inside so we can basically touch like touch forces as we're grabbing objects can it shake my hand uh i don't know uh maybe can it squeeze my hand there you go there you go will it crush my hand no it's not gonna crush your hand dude that's pretty stir that's like yeah i can't move it we can pick up like 40 pound boxes off the floor and we can also fold a t-shirt so. That is wild. Yeah. Is this the power button? Yeah, don't push that. Okay.

We had a, we had somebody in the office our day, uh, it was like, I, I feel like I need to push this. I'm like, it's literally going to turn off if you push the button. And how, how long does it hold the charge? Uh, it depends on what we do, but anywhere from four and five hours. How long does it take to charge? It takes about an hour to charge. So we can do about four or five hours on, we can charge for an hour um you know humans take breaks during the day to eat and do other stuff and uh or or what we should do a lot of time office we'll sub another robot in during the meantime wow yeah we actually charge uh here inductively through the feet so the feet have like um basically have like uh charging pads robot steps onto and we charge wirelessly we can charge we can basically charge in one hour through that whole process holy just by standing so in case the The robot has a task where it needs to stand a lot.

We can just stand there and charge. So it just stands on a mat. We designed it in-house. Like an iPhone charger. It's like an iPhone charger. Yeah, and it can charge about a kilowatt per foot. It's about two kilowatts it can charge. When is this going to be available to the consumer market? As soon as we, like, make it work really well. And so I can send it into my house, and my kids don't ask for ice cream every single day. And, yeah, so we're working on them really hard. I think, you know, we've been testing in my home fairly recently and we'll be shipping these robots out to commercial customers here really shortly can i ask who the commercial customers are yeah we have uh we work with uh bmw we work with one of the largest logistics companies in the world i work with berkfield they're like one of the largest real estate companies in the world they have a giant portfolio of companies uh and then we have like two more customers we'll be announcing the next like 60 days congratulations yeah thanks that's amazing so we're gonna try to ship as many as possible we can this year wow we also make these uh on site next door at baku it's our um production manufacturing facility and we make

about one every kind of like 90 like 90 minutes or so now you can make one of these in 90 minutes when we run the line um the lines are running about every 90 minutes we make one and then that that'll greatly increase even in the next like several months here wow yeah wow yeah what do you i mean at full capacity like um our office our facility yeah our facility there can do uh maybe upwards of like $40,000 to $50,000 a year at like full capacity. But we need to design for much higher, like we want to get to like a million units a year and, you know, like within this decade. A million units a year.

Yeah, for sure. I mean, you sell like, we sell over. It's like building a country. It's not, I mean, like you sell like over a billion phones a year, easy. So I think it's going to be like a robot for every human. So you'll need like a cell phone style manufacturing. Shit. Yeah. So I can push this? Oh, yeah. It has push recovery. Give it a little push. I mean, a little harder than that might be nice. Harder? Harder. Dude, what? Yeah. Yeah. There's better balance than I do. Yeah, same Dude That's crazy. Yeah, this is three and a half years. We had we had this walking in three years since the start of the company It was crazy. You're like basically the week of year three. We were walking this thing at the office this one like the thing is this is like a We're going to go through like this whole iPhone lineup where it's, you know, iPhone 1, iPhone 2, iPhone 3.

It just gets better and better. And I think human rights will take like more radical steps between those. Every year, we're roughly building a new robot every year. We'll just get like dramatically better than this. Damn. Our step up from here even to the future robots will be, I think, perhaps the most dramatic step up we ever make. Wild. You want to take some pictures with them? Let's do it. dude that is insane what do you think awesome i want one you want one yeah let's get you one man um wow like so that in the same that you said the hands can sense three grams of pressure yeah we basically have the fingers and we have tactile sensors on every fingertip and they're really sensitive um and we have a camera in the hand that can detect when the fingertips are in contact with some surface it could be like something we're touching and then within there every joint can kind of also feel sensing and track the position every like you know part of the hand so the hands like the hands are really good uh honestly we're working on hands now for like close to four years it's probably one of the hardest engineering problems we have on the on the hardware side.

It's probably as hard, and we have our next generation hand that we kind of teased a couple weeks ago that has like basically full... I think it gets a full human level dexterity with this hand. Are you serious? It's got as many joints on the hand as a human hand has. There's still a lot of work to go do, but like it's now... it's now a huge step up where we actually even currently are. And the hand now can like fold laundry Do you think it'll hit a point where it can outperform a human? More dexterity in a hand than a human? I don't know. Better balance, faster, stronger? We already have better balance than a human.

The robot on one leg could balance better than a human can. I don't know about... Humans have a lot of degrees of freedom. We have a few hundred degrees of freedom. Our hands are very dexterous. I would say if we can do close to human dexterity in terms of, like, that would be a huge win. You'd have robots everywhere. Yeah. And, you know, and then we're gonna still have a lot of trouble getting to, like, full human range of motion. Like, small things, like, you reach inside of a washer and you kind of, like, move your head as you're, like, getting in. Or sometimes, like, some people get on, like, you know, get down to the ground and, like, kind of get in the washer to grab some on the back.

We do a lot of crazy stuff. Yeah, that is. And, you know, so it's like, even like a 12-year-old can kind of do, like, most things in a house, you know what I mean? Like, they can jump up on countertops and all kinds of crazy stuff. Humans would be tough. But, like, I think we can get, like, very soon we'll get to, like, pretty close to most of what humans can. You had a pretty close relationship with OpenAI, correct? Yeah, they led my, so Sam and OpenAI led my Series B, co-led my Series B with Microsoft. That was a few years ago now. So we raised about a little under 700 million in our Series B, our second round of funding. And they joined my board and then we ended up spending basically a year with them working on, well, I mean.

I'll give you the background. The goal was to try to advance AI models for humanoid robots together. And they have some great folks that have worked on LLMs and chatbots and things. And at the time, we had a full AI team internally. So we were basically working weekly, daily, on basically how do we advance state-of-the-art language models for robotics. And, you know, like, yeah, I ended up firing them a year, a year later, but in splitting ways, but listen, they're a great team. I like the senior leadership and everybody there, Sam included, like we're great to interact with. um the issue lied for us of like um there's nobody's ever put like advanced like language models into these systems and made it we have to like produce like action output on the robot and it's like a very different thing than like um next token prediction for like language models um we ended up finding that the team we had in place you know my team lead the folks we have here all from google deep mind or certain areas of like you know top ai programs and they're really good. The team now we have is over 50 or so on our Helix team internally. We just found that like that team we had internally, we just ran like kind of circles around them, like every day. We had a

hard time getting, like, you know, in robotics, you gotta like run the robot, see how it does. You know, like you want to run a new like AI experiment or do some ablations, like and some evals, you need to like run the robot at the end of the day and see how it does. Like sim is one thing, you can get certain far running simulations and looking at loss curves and stuff, But at the end of the day, we need to see how the robot does. And we just had a hard time getting him in the office. We had a hard time basically advancing stuff together as a team. Ended up, the strategy we had internally and the team we had was just complete superstars.

They're the best robot learning folks on the planet that set a figure. And it got to a point where I got a call one day. We were also week to week showing them how we were doing all this work. And I got a call one day saying like, hey, we've been watching your progress, it's unbelievable. And we're thinking about doing robotics work internally. And I was just like, this is over. Like, yeah, just get out of here.

Brett AdcockLike, this is like, we're teaching you how to do like robot learning. You're seeing our progress.

We had like a couple of the, you know, Sam and a couple of the co-founders on site at one point, we were right before this and they saw it and they were like, wow, this is like, it was doing like this neural network on the table and they were just like, Jesus, this is amazing. Shit. And I was like, you know, they were still at a point where they continue to want to work together after this. And I was like, there's no way we're gonna teach you how to do this stuff anymore. And also, we just like got no value out of the whole relationship, very little. I mean, listen, it was helpful having them lead the round.

It was like, there was some good brand association there, but like beyond like that, there wasn't much. So we ended up, you know, we're gonna chart our own territory. we're going to do AI ourselves here. It was also just became like a, to be frank, like it became like really hard to recruit. We were like, you know, I, I have to spend a lot of my time hiring like, like on the AI team and, um, we bring candidates in and they'd be like, oh, you guys do the robot opening ideas and models. And I'm like, oh, no, not really. No, we have a whole AI team internally. We do model development here ourselves. Uh, you know, like we're advancing ourselves and it just wasn't the perception from the outside. It was just hard. Uh, so that also wasn't helpful for us both hiring was not great and we were like you know there was like an information passing back that I think wasn't really helpful for us long term if we're gonna be competitors so we decided to split ways I decided specifically to split ways but they have a great team I think they're doing robotics now internally Um, sounds like it. Yeah, exactly. Yeah, yeah, exactly. Uh, I was like, I got a call saying like, yeah, like, you know, partly like, uh, the partly feedback I heard was like, we've made so

much progress at figure and they've seen that, that they were, you know, they opening, I started out as a robotics program. They were trying to solve AGI through a lot of the first three, four years, they were just like all in on robots. If you Google like OpenAI robotics, it's like old 2016 2017 2018 2019 like you know maybe like maybe like 2019 2020 something like that they end up pivoting into like large language models maybe 2021 something like this but they're in robotics from i think 2016 2017 for like many years maybe three or four years um trying to solve like agi through robotics there's um you know there's this other we don't need to get into it but like it's it's you know it's unclear if you need an embodiment or not or you know at the It was unclear whether you need an embodiment or not to, like, truly get to, like, above, like, peak human intelligence.

And they had a hard time in there, but there was, like, part of their thesis was, like, get back into robotics at some point. And I think we just, we accelerated that here at Figure. And, you know, I think, to be fair, like, to be, like, somewhat humbled is, like, it's, we made, like, I think we made, like, ten, I don't know, five to ten years of progress in, like, three years, four years. Like, we just, like, it just felt like this should have taken 10. Even right now, it feels like we're not even four years old yet. Four years old and end of May or something like that. Like, I couldn't believe when we started the company three and a half years ago, we'd be at a point where you can get a humanoid robot even here, doing the stuff it's doing here, but, like, let alone, like, the real stuff it's doing now and, like, 24-7 commercial work in the home.

Like, it's neural net driven. Like, we can make them every 90 minutes at the, you know, when our lines are up. Like, it's just, like, it's crazy. So, yeah, we decided to part ways. Man, I mean, I don't think there's too many people in the world that can say they fired the biggest AI company on earth. I mean, that's a ballsy move, but it makes perfect sense. And, man, again, just congratulations on everything. I mean, that is, that's just crazy. You know, I've done a – it's just very surreal for me to unveil some of that. I mean, I know we didn't unveil this, but it's the first podcast it's ever been on.

Dude, Sean, I have not taken a robot to, like, a podcast. Like, I get asked every week to do this. This is the first time. And, like, love your show and want to get them here in Tennessee. It's the first time a bot's been out here, something like this. Thank you. Yeah. It's really cool to be able to do this, like, once-in-a-lifetime opportunity type stuff. Thank you. No problem. What about military application? Yeah, we've decided not to do military stuff today. And not to say, like, the robots won't be good in military or helpful or, like, my belief right now is, like, it's just too difficult to do both.

like the ship into the home, ship to like, you know, top Fortune 100 companies in the US, and then also put like, you know, like militarize the robots. I think it's just too hard in one umbrella. I think there's a huge opportunity like to save lives and help on the military side. But I think it becomes like, you know, we do have, you know, we do have like a very advanced system here. The system can, you know, unlike a car, if a car became sentient, like, you know, you can like walk in your house walk upstairs go in your room it's like not gonna come chase you like a robot will just walk right up your stairs and open your door the humanoid robot you know this is a very different technology we've got to be very careful with it um so i think because of some of that and some other things uh we like we know we've drawn a line here to say like uh you know we want to stick with uh you know Consumer market, commercial market, and go to harden the paint with that.

I think there are and will be incredible opportunities for companies to go into the military. To be frank, these robots would be great there. Like, they can just like, they can, you know, like some of the most dangerous missions are like, you know, going to close quarters and houses. And, you know, yeah, that stuff is like extremely dangerous. Human owners would be great at that stuff. Like opening doors and just making sure the house is, you know cleared like clear house you know what i mean it's like i could see it for a whole ton of stuff i mean not not even just going on target but centuries gate guards yeah i mean roving patrols i mean all of it totally just armed security it's it's wow you know i mean you kind of have somewhat of a a treatable asset too you can basically i think you can make them relatively cheap make a lot of them just put them out to work do you think you'll get into it in the I don't know. As of now, no, but there's a part of the story here where you're like, you could make this obviously really safe for humans there. But there's a whole part of the story where it's like, I think it just becomes, you know, to be frank, when we sell to commercial customers, even homes, it's not like selling a robot arm on a stand. It's like these commercial customers need CEO approval.

we can't get them through without the ceo like these major companies like coming to see the robots and saying we're going to announce this relationship with figure and we're announced humanoid robots in our facilities and it's just like a it's a very you know it's like a there's you know it's like if you watch this i'll make that announcement yeah i think it's fucking awesome it's awesome but like i know just like it is like a you know it's and then that makes it that much harder than if we have like a new military uh side of things um why do you think they're hesitant Is it, is it replacement of human jobs?

I mean, Jack Dorsey just, I mean, he just let go of what? 10,000 people. Yeah. Like almost half of his, half of his personnel because of AI. Yeah. And his stock went up because of it. I think, you know, I think it's probably because the robot is human-like and can do human-like work. Gotcha. So I think it's just scary for, you know, it's a scary thing that like do what humans can. I think it's, you know, you have similar scariness folks have around like digital AI and how that will basically manifest in the future. So I think that's a real thing. Like I think the robots can do human-like work and it will continue every year to do more and more human-like work.

So, but like that, you know, we just gotta, we just wanna be very careful about how we position this and what we do and also how we communicate it. Yeah, yeah. What's next for the robots? We wanna solve general robotics at Figure. We want to, we think of ourselves truly as like at the frontier of like this robotics AI lab that needs to build common sense reasoning in a robot that can put in every home. How do we drop it into your home it's never been and you can just communicate with it and get to start doing work? That's the problem we want to solve here. That's the problem. If you solve it, you can ship billions and millions of robots.

There's also a business where if you don't want to solve that, you can definitely ship robots. You can ship them in the commercial workforce. You can ship them in the military, as you mentioned. There is a path to go build a business doing that. But the biggest business in the world is if you solve general purpose robotics, where just through speech and talking to the robot, it'd feel like you had a human in a bodysuit. It can understand you, nod, go off and do things now after your task. Like that's the problem we want to solve at Figure. That's like a large scale, like it's like an AI lab problem at this point.

We like, we talk a lot about how we're trying to like, we're like, we're trying to give AI a body here at Figure. And, uh, so we have this embodiment. We need to put like really. sophisticated eye onto it to be to be able to command it and that's the that's that's the biggest problem we're trying to solve if you're if you're with me in the office every day i am um working that down with no sleep basically as like as hard as i possibly can and it's a very very difficult problem at this point it's um it's largely constrained by getting the appropriate data into the into the network at scale i think if we could snap our fingers and get a pile of data that we really needed into helix stack i think we would solve general robotics right now wow what should i be asking that i haven't asked yet about figure general about figure um i mean there's a lot of stuff going out with china and manufacturing a few other things but like i think you know i think maybe to summarize i think where we're at is i think if i had to like um if i was like watching this and i wasn't following the story i think the one thing i would like to convey that, you know, is like, we are so close to like making this happen now.

And it's only until, you know, people can come online and like watch our stuff we put out, you know, but when people come to the office and experience it and see the robots and you can talk to them and some of the stuff you're doing here today, it's just like a full like emotional experience that is like really hard to convey. And it's just crazy to just, it's, it feels like we're living in the future. It just feels like we're living here. Yeah, it's crazy it works. It's crazy it's working. But we're now in the... We now have a line of sight to make this happen, which is exciting in my perspective.

Super exciting. I think it's going to be super transformative for the world. And I think what we're going to try to do over the next year or two is try to get this out further at scale and get everybody to feel this more and more. You feel it when you come to our office and you feel it when you're next to the robots, but it's like hard for the we're such early innings about about this yet like for takeoff that it's uh it's hard for the whole world to really feel this yeah yeah have you seen do the robots interact with each other yeah what does that look like right now they communicate with each other when they need to like um so we have like robots that are running these 24 7 shifts when one robot gets like down to like low state of charge let's say it's like 10 percent uh and it's a few percentages away from, we'll dock it before it's at 1% or something like that. It's at 10%. The other robot will get ready to sub in. It will come walk over, sit right behind it. And then when the robot is ready and knows that it's there, it will then back away and the other robot will go in to do operations and do work. That other robot will then go over and start charging. If any of those robots have any problems throughout, it could be hardware or software, they will go and go to

like basically like the hospital in our office. So they'll go to a certain place. When they know they're going to the hospital, we have another robot coming in to the main docks to start subbing in and getting ready to go. All this communication is happening like robot to robot. And it's unbelievable. And the robots are getting really robust. We can like, a year or two ago we would like, there would be like certain motors that you would lose communications with or other types of comms or could be hardware failures or sulfur flares, whatever, let's say it's the knee, lose your knee, like can't stand anymore.

You know what I mean? Like you fall. Today, that doesn't happen. We can lose a knee. We can hold its position. We lose full comms of the knee. We can stiffen the joint and we can limp off. Holy shit. Yeah. Actually, I'll post some of the next week publicly about this. I've never, it's like, holy shit. So we can lose like a lower body motor. And it literally limps offstage, like off the main line it's on, heading to the hospital. It will limp all the way there. While it's limping there, another group from the healthy part of the hospital will then come in and re-sub it in on the dock, while another one undocks while it just lost its knee to go in and do work.

All that's happening through robot communication levels. You can be literally asleep while this is happening. We run them 24-7. It could be at 3 in the morning, and it will happen. uh it's it's it's a it's insane um this is happening like i saw this in the last like few months that's happening out right now this is not even like the future stuff future stuff is going to be robots building robots we're designing robots we will have robots building robots here and then they will go out and they will just do autonomous work and they will like charge themselves they will go do work you'll speak to them sometimes sometimes you won't need to do and they'll just do work, and they'll just be, like, everywhere.

I say this again, but I think we'll walk out. It'll happen first in probably the Bay Area. We're based in the Bay, and a lot of companies are in there for robotics. But I think you'll go to the Bay Area at some point, and you'll see more humanoids than humans in the next 10 years, for sure. Yeah, that is... I can't even imagine what that's going to be like. It'd be weird. Do you think that they will bring... Do you think manufacturing will come back to the U.S.? Yeah, we're going to bring back. Because of this? My view is that we don't want to bring back manufacturing that's already overseas. We don't want to make shoes, make toys, things like that.

I don't think we have the will to do this. I don't think we have the know-how to do this, as well as some of the Asian manufacturing groups. When I'm overseas, so I've walked a lot of the high-volume consumer electronics lines and stuff overseas. Some of the most impressive things I've ever seen in my life. it's like you walk these lines and they're just shipping electronics like crazy and every line they have this box of automation inside of it called a little tiny robot inside of there that's moving some, whatever, a phone enclosure or something like that. And it's doing it through an automated way and moving it around a little conveyor and it's moving to the next station, maybe a human's doing something and it's going down the line, it's going to the next station that's got a robotic system in there, completely customized and different from what you just saw and they have lines and lines in floors and floors of this and then buildings and buildings.

And you're like, holy shit, each one of those boxes is like a figure style complexity. And they have like hundreds of them. And they need to run them at high rate. It's just like, it's unbelievable, actually. It's not trivial, it's very complex. And they've been doing it for several decades on these lines. So I think one is like, I don't think that stuff we want to move back. I think we want to move back the high-end robotic stuff that's going to be like super transformative for us in the future. All the futuristic tech. Yeah, we want to bring back flying cars. I want to bring back like humanoid robots, like the stuff that's like highly dynamic, very intelligent systems, like the next generation, like manufacturing 2.0 stuff.

Gotcha. So we're doing that right now in California on our campus. We have a fairly large campus in the Bay Area and we manufacture right now, like, whenever 90 minutes or so. And we'll continue to spin that up, and then we'll put, you know, we'll talk more about it, but we'll put more investment here into U.S. manufacturing for the future. Right on. So we're going to design humanoids here. So these are all manufactured? We manufacture those in California. Right on, man. Yeah, man. They walk off the lines, they walk over. It's like, 90 days ago, We're like making a little bit, but now we make like, there's like seven robots that are all doing like end of line checkout by themselves for like an hour and a half.

They do their own burn-ins, all OEOL checks. So they're self-looking at each other, self-calibrating. They're doing like burpees. other shit to make sure they like they're okay. If they fail, they go into a triage place. We understand why to fail, like that shouldn't happen. We should always fix that and it should not fail again. Like how do we fix the manufacturing process so the next one doesn't come out and ever have that failure. And now we've gotten that process really dialed, I mean, dialed in. We still have issues, but like it's fairly dialed in. And so the robots come out, do a couple hour check and when they're done, they just walk over.

And at some point we'd love to get, like for them to get inside their own box and another one, like get it ready to go and put it on a pallet and we can just start shipping them out. It will get in its own box and another one will throw it on the pallet and ship it out. For sure. Yeah. That's not hard things though. These are like, that's not, you know what I mean? Yeah, it's just interesting to think about. I feel like it comes off the line, gets in its own box, gets loaded on by another robot and then shipped off. The scary thing for me is those are like very rigid body things like cardboard and moving boxes and maybe using machines and stuff like those are like the scary stuff a couple years ago was like laundry that like literally moves it's like really never in the same spot it's like when you touch it it's like actually moving or we do like these like packages on this manufacturing conveyor system that like you you grab it it's literally moving white it's moving because the conveyor is moving down and then the packages are squishing each other and then the package itself is moving because it's plastic when you're grabbing it those are the hard things that are compliant that are like

really difficult for robotics because they're not like they're not like stationary when you touch them. So those are things that were like, man, that's going to be really tough to fold laundry. And for with code, it's been impossible. The reason you haven't seen like package logistics and stuff, some of the stuff automated is because like these bags are just like heart, they're

Brett Adcockcompliant. They're just tough. You can't model them. And now we have like, we put it all in a neural net. They basically instantly worked. When we were working with our, we have a logistics

customer we're working with. They do like soft packages and we sign them. They're like, we want to move these packages on the conveyor system and we've put videos out about it and stuff the first month we um signed them uh inga who runs you know accounts was like we need to we need to uh we need to do we need to do this for them or they're gonna be really unhappy and i was like i was like dan that's like a compliant material that uh is moving while you're touching some of them touch and they're there's something hard inside some of them are squishy they're like there's tons of we're gonna move every three seconds we got to find the barcode put it down and put it in the middle of the conveyor every three seconds of package.

I was like, it was 50-50 shots works. And it's got to be with a neural net. And we got a bunch of data, trained it, policy, and right away it worked. And I was like, holy shit, this is like, it worked really good. And for some reason, the neural nets do extremely well under those high veritability environments that's extremely diverse. They can learn the representations extremely well across a wider distribution. and um they just love it folding t-shirts towels like packages like no problem wow stuff that would like you know you're replanning very fast as you're as these things are all moving it's doing that in real time it's just like it just works deep deep deep learning just works on humanoid hardware. Yeah. Crazy, crazy stuff. We've all seen it. The Department of War is operating in a world that's changing faster than ever. That's why so many guests on my show talk about the importance of continued innovation and technology in the military. But here's the problem. Working with the Department of War can be complex. For many companies, the process isn't always transparent.

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didn't really see this like a lot internationally. And you know, we sort of looking at it, looking at it, I basically started reading a bunch of like research reports and other things. And I found, I stumbled upon this technology, this like basically technology and kind of like terahertz radar so basically like uh or sometimes also called millimeter wave technology where it's basically a like um uh basically high frequency like uh like uh it's basically like it's radio it's radio uh rf it's like radio frequencies basically done at a very high frequency like in the two to three 400 gigahertz and um it's basically like similar to you know when you're in an airport and you go in there and you like hold your hands up and like the lg systems scan you, they're like a couple of feet away, they can see like anything, anything you have, like, you know, if you have knife, gun, vape pen, whatever.

I read a research report that showed, and my goal is like, if you want to put in schools, you can't scare the kids. You have to be able to, so, sorry, back up. My view in schools is if you want to solve it, you have to solve it from a perception perspective, meaning you have to see if people have, you have to understand if people have guns on them or not. You can change, there's a regulation side that some people chase, which we're not chasing. And then there's a, how do we actually know if people have guns on them? Because if you know a kid has a gun on them, you can go and take it away. And then majority of all school shootings are unplanned.

Most of them, almost all of them are some kid bringing a gun in habitually. It's like their uncle's gun, and they bring it into school every day for three months. They get in a fight at recess, and they shoot something, they shoot it, the gun. Sometimes they shoot somebody, somebody they shoot it. And that is majority of all things, all gun events. The ones where you see like a planned event that's like on like CNN where somebody's like coming in with a machine gun or an automatic weapon, it happens like one or two times a year. It's on the front page of the news. The majority of all the cases, like 90 something percent is all happening from unplanned.

Folks are bringing in guns all the time. and then they're shooting it. So you basically, what you can do is you can stop all those. The planned ones are very difficult and maybe impossible to stop. But the 90 some percent of all other shootings, you can actually, I think you can avoid those. Meaning like you can prevent them by knowing if somebody has a gun on them. You can do it the old fashioned way, which is like metal detectors and all this other stuff. But like, it's just like, that's not, we don't want the kids to go into school like that. That's just like not, I want my kids going up. So basically the reason why I got obsessed with terahertz imaging is you could basically do this at a larger offset, 10, 20, 30 meters away.

You can do it at a high frame rate, and you basically get back a point cloud. You basically get back an image. It's like a three-dimensional camera image almost, but it's done in a radio frequency. You could look at it almost like an optical image. And the reason that's interesting is because like if it's basically people bringing guns in habitually and you can scan them at entrances you're always coming in through a few doors at a school you're not going in anywhere anymore and the schools also have all procedures now for this like for this stuff you basically can do like offset scanning at you know five or ten whatever meters away you can scan people as they're walking in passively like just like as like you know just walking in don't need to stop anybody and you can basically scan you know most guns that are brought in schools are either in your pocket waistband or backpack it's like most of all guns are being brought in there and you can basically find them and if you know that you can basically like stop it will find it will find a gun in a backpack yeah no shit yeah so um it's it's amazing it'll find a concealed weapon anywhere there's like you know yes it's there's printing in a backpack yes you can find

them in backpacks you can find them in waistbands and pockets so the story is so i found this research report done by a few of these guys that were at NASA Jet Propulsion Lab. I write these two guys and they said, sure, we'd love to have you over. I get over there and they're like, they tell me the whole backstory. They're like, listen, we developed this technology for standoff distance detection for the Iraq and Afghanistan war. It was funded by the US government. We worked on it for 10 years. And when the war stopped, funding dropped to zero and we were done. We And I'm like, oh, it sucks. And then I'm like, okay, well, I guess keep me posted if this thing ever works out.

And then towards the end, they're like, oh, you want to go see it? I'm like, what do you mean, see it? They're like, it's in the basement, it's done. We did it. And this is in 2017, 2018. So this is like, I was like, oh, yeah, let's walk down. Walked down to the basement. There's like this tarp over this machine. Took a tarp off. They had a guy with a mannequin that's sitting there with a gun underneath a shirt, like, I don't know, three or four meters away. It turned this machine on. It was built like 10 years ago. It had like a computer tower inside of it. And then it had like a little screen next to it.

So I started this machine and they basically moved over to the screen and the screen showed like as clear as day, like a photo of the, you can see the exact gun. You could see it in 3D, you could see it in 2D, you could see it in power. There's a bunch of other ways we can look at the data, but it was just like crystal clear wow and i was like what what happened here like we basically got to the end of this program and we don't have any more funding so it's done and i basically made the decision you know long story short i ended up chasing archer at the time i went and built archer and at the time i only had like a like you know this was a big endeavor for me like going from software like you know deep tech hardware so i basically decided to put cover on Hold and Chase Archer.

And then about two years ago, somebody came to my office, one of my investors, and was like, hey, I'm looking at trying to solve school shootings. I was just back from LA, and I'm trying to solve it with CCTVs, like the security cameras. He's like, the problem is, like, you can't, you won't know until the gun goes off. And you won't, like, brandish your gun. You won't pull the gun up until you're, like, trying to, like, shoot it. So it's just, like, way too late. I told him a story about how I went down this path in here, and he kind of looked me dead in the eyes. He's like, I have kids, and you have kids.

Like, you have a fiduciary duty to go build this. And it was right when my daughter was also applying for first grade, and we were worried about it at schools, you know what I mean, just looking at, like, the fence, and just, like, kind of anybody can go in. You know what I mean? So, like, I was like, shit, you know, I got to go do this. I ended up spinning the technology out of Jet Propulsion Lab at Caltech. And I own it. And started cover two years ago. The OG team that built it is with me now. No way. We put an office in Pasadena. It's the main office is right next to JPL. And we've been working on this now for two years.

I've been self-funding the whole thing. And we will have, we have a prototype that already works last year. and we'll have a full-scale prototype out, like, I hope by summer, like in our lab. And then we, hopefully, if all goes well by end of year, we're beta testing in school. Wow. And we'll put it in that figure campus first, even. Wow. This is like an optical play, like, can you see it? This is an AI play saying, can you detect it now? There's 130,000 K-12 schools in the US. There's like 60 or 80 million K-12 students. It's huge. and um but it's not just schools it's stadiums and airports everywhere hospitals malls every any venue you can movie theaters i had my last baby a year ago just like anybody can walk in the hospital it's just like just doesn't matter they don't check you in it's just like scary and so anyway um we're we're getting close here and um the technologies we designed are incredible actually we designed all of it like we designed the whole system that i saw redesigned the whole system i saw seven years ago last year but it was just too expensive the systems we were using were like certain parts on it were like 50 60 000 so we moved all of that into a into a chip and we spent last year and a half doing that work those chips are in our office

Brett Adcocknow and working those chips are like seven dollars instead of fifty thousand dollars

there's only a few groups in the world that could make them and design them we co-designed We worked on the design with them, made them, fabricated them, and we have them now in our office. They work. We use many different, we use a lot of chips, but they're really cheap. And that's important. So K-12s will have a large budget, and we need to be able to get the cost down to make it affordable for every school. That's what I was going to ask. I mean, how are you going to get this in school? A lot of schools won't do, they won't even hire a security guard. Yeah. There are big budgets, both at the federal and municipal level, like a lot of money that are going into school, like schools are getting subsidized for to put in a lot of stuff.

Good. They're putting in CCTVs, like cameras. They're putting in like ballistic chalkboards, all kinds of stuff in the schools. There's a lot of cash there. The schools also spend a decent amount per student. And I think we get the cost down a reasonable amount per student that both public and private schools can afford. But we could have already had our systems beta testing in some schools by now if we didn't pivot a year ago. We spent the last year trying to like 90% decrease the bill of materials, like the cost. Wow. It's just like that's needed to go big and make this really work well. I think we'll...

Are you going to put anything else into it? Any other, like here's an example. When I think of this, would there be a way to maybe facial recognition? Who's enrolled here, who's not? Just for example, like the shooter that happened up in Nashville a couple of years ago, the Covenant School. Yeah. Went to school there, but not at the time. Yeah. You know, and so if they would have had some type of facial recognition on top of what you had, that's, that's, like, this person doesn't go here, this person hasn't gotten this. Yep, 100%. We'll have cameras, maybe even some audio, like mics, like, cameras will be really huge.

Like, you can really do a lot with, like, just RGB cameras and understand what's really going on. You'll also get a lot of semantic understanding because guns are like, they're hidden somewhere, they're concealed. People are not walking in with like handguns and shotguns like into school. They're like, they're in like in a waistband and a pocket backpack. We can be really thoughtful about if somebody, you know, clearly doesn't have anything, like anything in their pockets when they're walking in, but they have a backpack. We can be thoughtful about like, we probably need to scan a backpack. So, and we maybe need to spend more time like getting higher frame rate on this area.

And then as you mentioned, like a lot of understanding about like uh does this person belong here or not uh it's just like is this a weird time for somebody to be like leaving and walking back into the school so there's just a lot of semantic grounding we can put into the models to really help like understand if there's threats or not the schools are set up really well to do like random locker checks now and like uh okay this doesn't look okay or not like the schools are really well equipped for that it's just like we don't know what's happening we actually think now that there's probably like like perhaps like tens of thousands of guns that are being brought into schools in the u.s across you know 130 000 schools every year i think we're finding what we're finding now is a very very small percentage of them were found that are brought in and then from there what we're also finding is actually a similar small percentage are actually being reported because if you report like a student that has a gun they're going they're going to juvie so we're also finding out we think a large percentage of like we're finding a large percentage of guns are even found and then of that we think a large percentage are not even

reported because like you know and could like put you know what i mean could like wreck this kid's life um which is you know unclear like what we should do here you know for that that's like that's terrible um but we think there's like we think there's like maybe tens of thousands maybe hundreds of thousands of guns that are being brought in every year through the schools wow we're finding you're reporting thousands and you're seeing hundreds of shootings. So our view is that we think it's actually happening, like, you know, as a percentage, it's low, but as like an absolute number, it's quite high.

Yeah, so I'm excited about this. We, it's in some way, like, I, you know, I write this prediction every end of every year for like what, you know, will happen in the spaces I'm in, which is like flying cars, like robotics, like AI and weapon detection and stuff like that. And like, I did a post in December, Like, here's what I think on these four areas. And, like, overwhelmingly, like, the most support I got, like, publicly was just for cover. It just, like, I think it, you know, it just, like, hits, I think it hits in a really good way with a lot of folks, maybe especially parents. So... Everybody's worried.

We're homeschooling. Yeah. Because of this shit. That's a big reason why we're homeschooling. Yeah, I hear you. My wife and I, when we think about where we put our kids and stuff, too, it's just, like, something we talk about every time, too. And it's like, you know, and it's like, it's probably like a low occurrence rate, but if it did happen, it's just like, you can't recover from that, you know what I mean? I mean, it's just every school I go to, I'm like, man, like, you guys got to, this just happened down the road. I had a good buddy, like, had his house breaking into, he's got family and stuff, it was like six months ago, and he just told me when I was talking to him last, he's like, the sense of security we have now in our home is just like, we'll never get back.

And I just like, I didn't know, I didn't know what that felt like, like feeling like we were secure before, but we lost it now. And now we definitely see it and feel it. And it's like, we're never gonna be able to get it back. Yeah. And I've had, like, you know, I've had, like, some close people I know that have been involved around this stuff. It's just like, it's terrible. And so, you know, my agenda here is, I think it can be prevented. I don't know if you're gonna prevent all of them. I think you can prevent a lot of them. And then if you even have like, there's no real security there at all right now, but even if you have security, there's also like a sense of like, shit, I gotta bring a gun in here now.

And there's like real sophisticated AI that's in all these schools that can catch it. I think that's another big thing. You have that at like TSA when you go through PreCheck. Yeah, it's a deterrent. So you have like that, but we can also find it. We can see underneath, through backpacks and stuff. It happens at specialized radio frequencies. It happens at 200 to 300 gigahertz, and it happens to get at 600 gigahertz. And in between those bands, there's either FCC rules that prevent you from doing it, or there's atmospheric attenuation, meaning sometimes there's enough moisture in the atmosphere at certain radio frequencies that the radio frequencies don't do well and perform well.

They perform well at these certain radio frequencies for the imaging stuff we do. So it's actually quite a hard technical feat. I, one of the reasons I didn't do it and did Archer is because I thought the cover stuff was actually harder than doing flying cars. And I actually think it still is. We still like, it's hard to, it's like, it seems like pretty obvious. Like it's like a way airports have, I do it 10 times higher. So it seems like, and you look at Archer, like shit, man, that looks really complicated or like a figure. Cover is just like super niche area of folks that it haven't, like there's the folks spending like in this space or like they're doing like they're doing work in weather and space and they're not doing this for like shootings and like security and stuff there's like there's no industry for this and luckily we have like the world's best terahertz experts at cover that are working every day on this and they're really passionate uh they're probably not getting paid enough and they're just like super passionate about solving this problem and um so anyway i think um i think the through line for covers i think it'll work i think we'll be able to demonstrate it hopefully by end of this year. Like we'll be able to say like we have it at

like we'll have it at figure campus first and then we'll put it in uh in like schools like hopefully on the west coast and maybe maybe one or two and we'll see how it goes. There's um you know there's a how do we market this like what do we tell the students like teach parents there's like you know there's a lot of stuff here we need to get right but if it goes well from there and we're getting low false positives like what we really want to do is make sure we don't freak the kids out. We don't want to, you know, think it's a gun, but it's a crayon box. That'd be terrible. So, like, that's really an AI problem.

So, we basically want to make sure, like, we have, like, low false positives around the whole sys stack. That's a really hard problem to solve, especially for us, where you can be, like, partially occluded on certain areas of the person or the weapon. And then we need to, like, know what we see. It's actually, is it real or not? And so, funny enough, if you come to our lab, we have, like, just guns everywhere. And they're all bricked. You can't actually shoot them. But all day, we try to figure out how to put guns on humans or mannequins, and we try to figure out how to detect them. So how does it work?

Is it shooting frequency and then detecting the response when it hits something solid? Yeah, that's exactly what it's doing. It's basically shooting out a radio frequency. It's like electromagnetic... It's like a little wave format that goes out. Very similar to how your Wi-Fi works in your home, or 5G. Same type of concept. It's just on a higher, different radio frequency level. But think about your Wi-Fi, and you want to, in order of 20x or so, the radio frequency level, it's operating in a few gigahertz, something like that. But we operate at much higher frequencies, like 300 gigahertz. So you want to, whatever, call it 50, maybe it's 50, 100 times this.

And then basically it shoots us out and this waveform comes back and we review it and we look how long it took to come back and we use beamforming a couple other techniques to figure out what happened. But you're basically, it's same as like traditional radar technology, but we can shoot it out, comes back. It's not ionizing, it won't hurt you. Like it's perfectly fine to be around like your Wi-Fi. And we can basically get a, we can get both a 2D image, what's happening in a 3D point cloud. The 3D point cloud is what's really important. So if you have like a weapon on you, like in your pocket for whatever, or say I have one on like my chest, for example, we will start getting back the signals back from the top surface of the gun before we get your chest stuff back.

In the case of your chest, you have a lot of water in your skin, and it'll somewhat attenuate in your chest. So then we'll get back an image from this, and we'll reconstruct it really fast. And we can reconstruct it into somewhat of a three-dimensional point cloud like you do a camera. So you can basically get almost like it looks like an op. I showed you earlier today the vision from this. It looks like kind of a camera image is what you get back. And so from there, you can kind of like visually see what's really happening. In the case of the gun, you can see the gun. You can see the trigger in some cases.

Yeah, and sometimes it might just be the handle or the side of a gun or different places of it, but you can see it through materials. It could be backpacks, it could be clothing or a jacket. But most guns are all in the waistband pockets or backpacks, which makes sense, right? You're not wearing it around your neck on the outside of your shirt or things like this. So that's where most weapons are entering school. We have probably one of the best data scientists in the world that is obsessed with school shooting, and he puts up the best school shooting analytics. He does it daily. He's done it for five years.

He's working with us through this, and we've done so much work on how people, how students enter schools, how they exit, emergency responses, what solutions are on campus now for this, like, what data we find on, like, where guns are at, what type of guns and weapons are there. There's, I think it was, like, 200 nice stabbings last year. 200? Yeah. It's like, it's so high and so dangerous. Like we're trying to, like we can detect knives. Like there's, you know, vape pens, whatever, whatever. It's not a metallic thing. It's like we can, it doesn't matter what the object, it looks like. Different metallics will actually like come back to the radar system a little bit differently.

So you can kind of maybe sometimes tell if there's like a gun, like a metallic signature or not coming from the material. But the technology is like really kind of straightforward in a sense of like, it's RF technology, like radio frequency technology. and you get back like an image. And we can use that image to build like a neural network to then look at it and say like, what is this thing? What time of day is it? Who is this human? Like, is this a dangerous threat or not? And we need to do a really good job of making sure we're accurate in those readings or not. If we're not, we're going to cause havoc.

And if we're right, a lot of times we could basically start saving lives. And that's, I mean, there's on average one shooting every single day. And like more than that, like there's over 300 or more or so shootings roughly a year, if you look back the last couple of years. So like every single day, I mean, there's less school days in a year than 365, but like roughly every day, there's a school shooting in the U.S. That's just the K through 12, not colleges. But that's about, that's looking at the 130,000 K through 12 schools in the U.S. I can't, do you think this will be out in a couple of years?

Yeah, I think we'll get it out in a couple of years. We have a team working day and night on this. We'll, you know, we'll probably, I'll probably increase funding into it this year significantly. and we'll take a bigger push and head count. Yeah, but right now all things are on, like can we get the first full system in a really stable spot that works? And we've had to do a lot to increase the field of view because schools are several meters wide, multiple doors, sometimes double doors to get in. We need to scan all of that all the way through. So it's like a natural aperture that students are walking into, which is good.

You're not walking inside of a building, you know, like through a brick wall. You have to walk into a door entrance. And we're trying to, yeah, basically we're trying to get that fully. complete this year. Man, that is solid work, real solid work. Let's talk about Hark. Let's do it. Ready? Okay, so, I mean, I think my pitch here is like, I've been working on like one of the hardest AI tech, I think humanoid AI is like one of the hardest AI technologies on the planet. It's just like an incredibly difficult problem that I've been, my team and I have been working through day and night for the last four years.

So it's like, okay, we want to go, like, build, like, a crazy sci-fi future with, like, flying cars, AI humanoids. And then on the other half of my life, I'm, like, using, like, an AI chatbot, like a frontier lab, like Gemini or ChatGPT. And it's so stupid. It doesn't know me at all. It doesn't remember anything I'm saying. Can't see what I'm doing. It can't use tools very well. It uses the Internet, like, really poorly. Can't even order me a sandwich if I needed one right now. um and like uh it doesn't feel very futuristic it felt futuristic three years ago but now anymore it's just like it's just not very good it feels like i'm like in an incognito window searching google that's all i can do doesn't have access to my accounts doesn't know any of this stuff meanwhile i think like for me like i was just been sitting here for three years thinking like we're gonna get like jarvis out of this from iron man we're gonna get something crazy crazy out of AI. It's going to move to a point where it can listen and speak naturally like a human. It can see the world. It can use tools like a browser and terminal. It can do real work for you and help you out. It'll know you really well. It'll know, Sean, it'll know everything you're

ever doing, all your stuff, and be really personal to you. We don't have anything like that now. I got this stupid chatbot that doesn't remember the last thing I said to it. And so I decided to like, I said, like, there's two things here that are extremely broken. One on the AI side, we have, like, extreme, we have, like, we have, like, a lot of gaps to get to, to get to, like, like, like, extremely personalized, like, AI intelligence. There's just, like, a lot of, there's a lot of, like, missed opportunity now, last, like, few years, a lot of, like, a lot of gaps there. And the second thing is we're like interacting with these AI systems to like old pre-AI computers.

Like you're bringing up your phone or your Mac or your computer. It's like they're all designed like 20 years ago. It's like a really old interface. The chatbot's an old interface. It's the wrong interface to AGI. You're not going to get to Jarvis with those. So we have to go rebuild all the hardware from scratch. holy shit yeah and i don't see anybody i've been waiting i've been sitting here for like a year and a half being like somebody's going to do this really well and i can't wait for it and nobody's doing it i mean look at apple they're just like what are they doing like i so i started a new lab last summer called hark and it's an ai lab and we're going to basically design what comes after the iPhone for AI. And we're going to design new models that are extremely multimodal that can solve this. No shit.

Yeah. And we have, like, the world, some of the, I think, some of the world's best AI folks of all time. And we have, like, we have the lead designer from the iPhone, Abadur on the team. I mean, it's an iPhone 15, 16, 17. so this is going to wind up being a device is it going to be a device a family of devices yeah and um this will go really far it'll replace your phone and computer and you'll you'll have like native ai systems that are always on always thinking always understanding always there to help like doing stuff in the background crown. Like, we'll have near-perfect memory. We'll know everything about your life and what you like and don't like, and be able to even, like, act as a coach and say, like, hey, you said you'd do this over 90 days and you're not doing this over here.

It'll just, like, it'll just... Whoa, it'll hold you accountable? Hold you accountable. Oh, shit. Yeah. Yeah, we have, we've been... We have hardware in our lab. We have... We work on AM models now. Like, stuff is crazy cool. And, yeah, we're going to, I think we'll probably come out of stealth by the time this thing airs here between you and me. Holy shit. And we're self-funding it right now. You're self-funding this one, too? Yeah, I'm self-funding right now. And, yeah, the team's great, man. We're, uh, I think we're, yeah, I think it, I think it just, I think it's going to be a massive opportunity.

And, um, I see the Frontier Labs heading in a, a really great place for them, but a very different place than where we're headed. Yeah. What are you most excited about? I just want to, like, wake up to, like, I always, like, think about, I just want to wake up to a world that's, like, that I'm, like, excited and inspired. i just like um you know i love doing this stuff i could have retired like 10 years 12 years ago uh 15 years ago so like i think um i just want to work on cool crazy shit and um i'm just excited for a world of flying cars and humanoid robots and helping prevent school shootings and jarvis I mean, how do you keep it all together?

I don't sleep. You're innovating four major things. The trick is just to not sleep and always work. I'm good at that. You know what I mean? You get me. That's how you do it. It's super simple. No, I mean, listen, to be honest, I've had to make some tons of personal sacrifices. I think 10 years ago, I would have a part of my life that would be dedicated to golf trips and you know doing the annual like college trip with like my friends and stuff like i don't do that anymore i spend i have like my family and i have my companies and that's all i do and um and i really i do like a few podcasts a year not much i'm excited to come here because like i love your show and get the story out too you're great at it and um so i you know i just like protect my time and just like i go all in on these things like my now my kids and i have my work kids you what I mean like and so like uh which are like you know these are my like like they're like kind of like babies like I go you know make them need constant care and attention uh so I have like this family and I need to like uh I go all in on it and I do everything else less good you know what I mean I'm like a shitty college friend if you like you know what I mean if I had seen you in a little

while like just like not gonna spend the half a day with you on Saturday if you're in town I haven't seen you in 10 years so which is unfortunate I wish but like you know I care about these things more I care about doing this stuff really well and I'm really happy at it uh you know I'm happy with family and happy with like things going to work and you know to be frank i just i i was born and raised on a farm man and i get to do like work on this cool shit every day and um and you know i i got billions behind it make like going for it great teams that work like their asses off like teams that are you know here it came with and uh it's great and i like um fired up to come every day and work to try to make this thing happen and i hope these things all work it's just but like uh I don't know, these are also hard businesses, so.

It's pretty incredible. I mean, a farm boy from a town of 700 people now building that thing, flying cars, keeping kids safe, and park. I mean, American Dream is still very... Much alive and well, that's fucking cool to see. It's cool. I feel just internally grateful to, had a shot to do this. I feel like, you know, young entrepreneur Brett, 20 years ago had been like, no fucking way you get a shot to go do this stuff, you know, and it's great. I just, yeah, I just, I'm taking a, I'm probably at, I feel like peak career and my team with me is like peak team, peak resources. The stuff I'm working on, I feel like is very important for the world, which is also great.

I didn't, you know, doing veterinary, it was like there was a part of me saying like, okay, is this like the thing I want to spend my whole life doing? And I have that here, which is great. These are like the things I want to spend all my time on for the next like 20, 30, 40 years. So it's good. I'm just like, I just don't want to screw it up now, you know? Oh, yeah. It can work. We're doing a pretty damn good job, I think. All right, we're wrapping up the interview. I got a hot question to ask you. You ready? Let's do it. For decades, movies taught us to fear robots becoming self-aware and turning on people.

But in the real world, we still don't have public evidence of conscious machines. What we do have are real cases of robots harming people from Robert Williams being killed by a Ford industrial robot in 1979 to the viral 2025 Unitree H1 malfunction that showed how violently a humanoid system can lose control. Plus, long-standing research warnings that robots in homes can create privacy and security vulnerabilities in ongoing global debate over autonomous weapons. So is the bigger threat not conscious machines at all, but obedient machines that can still malfunction, be hacked, surveilled through remotely controlled, or turned into tools of intimidation, assassination, or state power?

i don't know how that person gets up and goes to get goes outside every day if you're that scared um so i i i think like uh the the futures is this future it can be like molded and morphed and like it's what we want to do with our time um and if we want a future full of like robotic systems that can help us out and free us of our times and things like this, we're going to wheel our way to make that happen. I'm a pretty optimistic person. I feel that having millions and then billions of humanoid robots on the planet is just going to be such a magical and important thing for the world. Are we going to have bumps along the way? For sure. Are they going to hurt somebody at some point, I think that's bound to happen at some point with enough scale. But I think the spirit here for humanity to get this done, I think is here and I think it's going to be one of the most important technologies of our lifetime. I think in some way this AI stuff of we're generating AI systems that can be embodied and can use computers, it's going to be one of the most transformative technologies we've ever been through. We're building synthetic humans at scale. And it's both scary, but also I'm very excited about that future.

So I think my view here is, yes, there's a lot of really difficult things that could go wrong, that perhaps maybe will go wrong, but I think we need this, just like we need cars. And I think just like we need a lot of things in life, airplanes and things. I think these are important technologies that really move society forward. Um, so anyway, I happen to believe that this is, like, extremely important, will save lives, and, like, I think, increase prosperity across, like, all of human civilization. And I think, uh, I'm excited to be working on it, but I think there is a lot of truth to what, you know, like I said, it's gonna be a really hard road.

Yeah. I mean, it's just an incredible advancement. And, you know, I know there's a lot of fear around AI. I have a lot of fear around AI. But we're gonna go through it one way or another. And, you know, I do think things are going to be a lot better on the other side of that. You're not stopping it now. It's like the, it's like, it's go time. It's going to happen for sure. And I think it's going to be fine. Like, I think, you know, I use AI every day. It's like, it's fine. It's like nothing, you know, like it's a chat bot. Like, I think, yeah, if there's a different path to go down from here that could be good or bad.

I think my bet's on high probability of really great. There's obviously always a path that could not go well, but being conscious of that and basically doing everything possible to steer it in the right direction is what we have to do at this point. This is not something we can turn off. I mean, turn off the internet. You're going to stop people from trying to build systems that make us more productive and do what will work. I don't think that's not happening. So all we can do is basically do it the right way that has the best positive effect on the world. Yeah, you know, another thing that comes to my mind is when we're talking about interacting with the humanoids.

Yeah. People, you know, and I've had this discussion on other podcasts too, but people are gonna look at that for advice, relationship advice. And I mean, I think there's, you know, a lot of important things they're gonna be talking to this thing too about advice certain people and i think that's a big fear of a lot of a lot of folks too it's already happening with chat gpt and all these other clod and all these other things anyways but who are they getting advice from before that problem i mean you know what i mean it's it's i think it's the caliber of person yeah totally but yeah it's who you spend time with yeah yeah last question what advice do you have for future founders i have a few things i think are i wish i could like maybe said differently also like pass down like young brett like 20 years ago um i think one is like uh just go just start building i feel like a lot of folks get too caught up in this thing that's like going to be hard. It might not work.

And you can just like, it's just so easy to start a company these days. So many great tools. Just go learn. I think there's never been a situation where I haven't like done something and then learned a bunch and then haven't reset from that feedback. So almost like little stairs I'm climbing over and over throughout time. And so if I just wouldn't have started and wouldn't have moved, I wouldn't have learned this information. So it's like a lot of information coming in, recursively self-improving and getting better over time. This could be simple things like hiring and doing accounting or running an engineering team or trying to ship a product or getting feedback from customers.

I'm just getting, I think I'm getting, it's like a sports player, you're getting better with more practice. And so I think the most important thing is just go. I also think the thing I learned a lot in my lifetime is like what you work on is really a defining moment for like for founders and it could be founders of any in any industry tech non-tech or whatever you're generally going to go and just try to like have this like have this kid that needs a lot of attention and then at some point it's like you just can't abandon this thing and you got to keep like spending more time with it and it needs a lot and it's like constantly working on the problems with it. So it's like not the fun things, you're working on all the hard things. It's like this problem funnel I have where I worked on the hardest, most pernicious problems at the company. So you got to really love it. And it's not like you can be there for a year or two. You have to be there for sometimes a really long time. And even if you're successful and even if you sell your company or whatever, go public, you're getting your stock locked up or you're investing out over many periods of time.

it's you're got to be in it for quite a while and i find that for me the things i work on as like probably the most important things i could be doing with my decision making and that's happening at a micro level inside the companies where we work on week to week month to month but it's happening at a macro level where like where do i spend my time like i'm 39 right now like where do i spend my time as 39 year old brett and where does like 20 year old brett and 25 year old brett spend my time as an entrepreneur and i generally have this philosophy view that harder things are easier. Meaning there's a non-linear effect here for starting companies that are easier versus harder. Meaning starting something that could be a hundred times higher outcome is generally not a hundred times harder. So doing figure is not a hundred times harder than doing another robot company. It's probably three times harder, maybe five times harder but the total addressable market and opportunity is probably millions of times bigger than another like robot that's like on assembly line moving back and forth and so i think there's like this non-linear effect to like decision making here that is extremely important where

harder things that have like larger outcomes are like usually easier to recruit the best talent in the world that gives you a better lift to build a better product and a better team that team and better product and maybe even a bigger industry because it's harder will give you like more capital coming at you for disposal to be able to like make the right investments you need into the right say equipment or people or personnel or whatever marketing to basically make you more successful. And then you're generally worth like working inside a bigger dressable markets like TAMs that, you know, potential acquirers or public markets or other folks that really want to see and have like basically a disproportionate outcome. They want to, they want a high risk reward. They want to, you know, investors and things and even people, they want to like go in and like if it they want like a hundred X or a thousand X.

They don't want like a two X. And generally for venture, like 90, 95% of people fail. So if it works, you really want to go, you want to hit a grand slam. So I think my philosophy is like spin, like choose wisely, like a young Brett spin, choose wisely what you work on, young entrepreneurs. And then I would try to be as ambitious as possible. There's capital for that. And there's humans for that, that want to work at really crazy shit. We have them at my companies and they're incredible. You met some of them today. They're just like my design lead and a bunch of other folks here that are just unbelievable at what they do. They're the best in the world at what they do.

But they want to come here and they want to try to do something like it's never been done before. They don't want to go off and design the next car or do the next AI product everybody else is doing. They want to be here, signing something revolutionary. So I think that's like, somebody don't stress enough. And I think the last thing is like, there's no rule book for this, which is like really unfair. And there's a lot of people out there that will teach like, here's what to do. And they're generally coming from folks that haven't done it before. And the signal of noise out there is just so high or so low.

Like, I mean, you get a lot of noise out of like in the market. It's very noisy about like what to do and what successful means for building a team or hiring engineers or like executing a product. it's very difficult and very few people in the world know how to do it really well consistently and so i found over time it's been really hard for me to get the right advice and um so i think it's been a lonely path and for folks out there that are on that path It's lonely, but I believe in you. You can do it. And I think that's... I've never had somebody for 20 years I could call and just like, what should I do in this situation?

I never have had it. And I wish I had. But there's no book. There's nobody to call. And I think that makes it really hard. But it's possible. You can just go do these things and it works. So for the folks out there that really want it, and it filters out everybody who doesn't really want it. And you can tell, the folks that want it. If I talk to people, they say, well, this is hard-ass hard. I'm like, you just don't want it. You shouldn't be doing this. You're going to get completely wiped out. You are. And it's like, it's the great filter. It's the folks that, you know, you went through BUDS.

Like, it's the great filter. It's 95% of everybody will fail, and you'll devote your life into it, and time, and maybe all your money, and your brand, and you'll be embarrassed, and you'll fail. Most will fail. And it's only for the folks that will, like, I will, like, you know, I will do whatever it takes to go make sure I make this happen. There is no failure. Those are the folks that do well here. And you can bend the world and you basically can mold the future to how you kind of want to if you try hard enough. And the goal at the end of the day is just to not die. If you don't quit, you won't die.

So like, anyway, I think, listen, I've been playing this now for 20 years, still playing it. I feel like I'm in the early innings of my career now. I want to go ship at scale these systems. I haven't done that yet. We're like an inning, we're Brett in one. Wow. And so like, but for everybody out there that's in that, I just think it's, I believe in you here. You can do it. That's great advice, man. Cool. Well, Brett, fascinating interview. Love everything you're doing, man. Like incredible stuff, huge advancements. Sean I'm a huge fan of you and just everything you do so I mean having me here and I mean going through all this is just it's been great thanks for having me. Thank you. It's been an honor. Great. Cheers.

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