Moonshots with Peter Diamandis - The Man Taking on Tesla in the Race for Humanoid Robots w/ Brett Adcock | EP #116

Episode Date: August 22, 2024

In this episode, Brett and Peter discuss Figure’s 2nd generation Humanoid Robot, Figure’s collaboration with OpenAI, how Humanoid Robots will impact jobs, and more.   Recorded on Aug 13th, 2024 Views are my own thoughts; not Financial, Medical, or Legal Advice. 02:16 | Company Unveils New Humanoid Robot 36:26 | The Future of Robots and Work-Life Balance 48:24 | China's Robotic Revolution is Coming Brett Adcock is an American technology entrepreneur and the founder of Figure, an AI robotics company building a general-purpose humanoid robot. Previously, Brett founded Archer Aviation, an urban air mobility company that IPO’d at $2.7 billion. He also founded Vettery, a machine learning-based talent marketplace that was acquired for $110 million. Learn more about Figure: https://www.figure.ai/  Learn more about Brett: https://www.brettadcock.com/  Follow him on X: https://x.com/adcock_brett  ____________ I only endorse products and services I personally use. To see what they are,  please support this podcast by checking out our sponsors:  Get started with Fountain Life and become the CEO of your health: https://fountainlife.com/peter/ AI-powered precision diagnosis you NEED for a healthy gut: https://www.viome.com/peter  Reverse the age of your skin with Oneskin; 30% here: http://oneskin.co/PETER    _____________ Get my new Longevity Practices 2024 book: https://bit.ly/48Hv1j6  I send weekly emails with the latest insights and trends on today’s and tomorrow’s exponential technologies. Stay ahead of the curve, and sign up now:  Tech Blog _____________ Connect With Peter: Twitter Instagram Youtube Moonshots

I am curious how you think about Optimus and Tesla and Elon. So inspired by what Elon's done in the last like 20, 30 years. It's been just unbelievable. We need more like really real players. I think Tesla's a really real player. I mean, you know, highly capitalized, great engineering team. And I think they're actually heading in the right direction. I'm tracking the robot companies coming out of China.

It's been a lot of time touring kind of what high-rate manufacturing processes look like out there and it was just, it was shocking. I mean, listen, you're amazing, but the star of the show here is Figure 2. So do you mind if maybe we open up this podcast with a quick look at Figure 2? Yeah, sure. Yeah, so I guess welcome to Figure. Yeah, so I guess welcome to Figure. Everybody, Peter Diamandis here. Welcome to Moonshots. On today's episode, we're going to do a deep dive with Brett Adcock, the CEO of Figure Robotics, Figure AI. He's going to be giving us a tour of his shop and Figure 2, his new robot release, if you're watching us on YouTube.

We're going to talk about what he thinks about Elon and an optimist. Talk about the robots in your home, when to expect them, and his projection of 10 billion robots on the planet by 2040. He just did a monster round with 700 million or so from OpenAI, Microsoft, Jeff Bezos, NVIDIA. And we'll talk about how he's integrating OpenAI's software into his figure-two robot. An extraordinary conversation, one of my favorites. All right, if you enjoy conversations like this, please subscribe. Let's jump in. Over to Brett and figure AI. Hey, Brett. Good to see you, my friend.

Yeah, Peter. thanks for having me. Yeah, I know for sure. It was super fun to come and visit your office, I don't know, it was like two months ago. It was before you rolled out figure two. And I have to say, you know, I said to you there, the speed at which you're iterating designs is pretty amazing.

And I didn't feel that kind of an energy since the early days of me seeing you know SpaceX back at Falcon one days so congrats on that yeah thanks you know I think everybody really I mean listen you're amazing but the star of the show here is figure two so do you mind if maybe we open up this podcast with a quick look at Figure 2, if you don't mind? Can we go take a quick sneak peek on the shop floor? Yeah, sure. Yeah, let's make sure it's not being used. But let's give you guys a quick tour of the office. Yeah, so I guess welcome to Figure.

Thank you. Yeah, so I guess welcome to Figure. So we're well over 100 engineers now. We're based here in Northern California in the San Francisco Bay Area. We just unveiled last week, Figure 2, which is our second generation humanoid robot. And right now we're manufacturing about one a week in our facility here in California and we have you know several of them here now on the floor so here's you know a quick look at figure two robot that we're already starting some tests on right now. Amazing I know your

team is about to activate it. If you're going to say that the principal differences between figure one and figure two, I mean, just for folks, you know, the company's like two years old or less, right? You've gone from like zero to infinity super fast. What's the difference between what upgrades did you make in figure two here?

Yeah. I mean, there mean, there's several. So- Your top five. Yeah, so I think first is we tripled the amount of CPU and GPU on board, just for more overall compute and inference. The second is we almost doubled the battery to about 2.3 kilowatt hours.

It's all on board the system in the middle of the Corso. Here, next to basically the compute in in GPU We had all the wires all internal so there's no external wires cabling electronics That's really for reliability and for overall packaging We also have exoskeleton structure. So all the outer shells of the robot actually take loads which is opposed to So all the outer shells of the robot actually take loads,

which is opposed to how we did the first generation robots. This would be more akin to how you do it, like say, aviation. My last company Archer, the skins on the aircraft take the loads of the vehicle. So I think it's pretty unique here for a system like this. We also have six onboard cameras, so we have more perception, more ability to see our surroundings.

Where are the cameras on the robot here? We have them in the head, in the back, and in the lower torso. That's good. And I assume that the Exoskeleton helps you reduce overall weight of the robot. Yeah, it's basically like overall, the parts will get a little bit stiffer as they get

a little bit wider. We found that having one structure for both crash loads and stiffness is the right ideal mass trade. And Figure 1 had kind of like both structure and outer shell for loads. That's just really not ideal where you, you know, like the structure is really sized by crash loads. So then you end up having basically double mass in a lot of ways. Yeah.

And the hands, have you made improvements on the hands on the? Yeah, so these hands- Hold his hand and show us what it looks like. So our fourth generation hands now, and we've made like quite a lot of improvements over the previous generations. Better sensors, better packaging, better for mass, better strength, better speeds of the

fingers. Overall, just better dexterity and control of fine-grained manipulation that we're doing on board the robot. We need to do human-like applications, so the more. We need to do human-like applications. So the more here that we can do human-like tasks and grab human-like objects, the better for generalization of a robot. Amazing.

And it's standing, what, about five, six? Five, seven behind you? Yep, about five, six. Yep. Yeah. Amazing. All right, thank you for the quick glance. You wanna hop back into your conference room? I love the beams up there for carrying heavy weights.

So how many figure robots are up and operational right now inside the facility? Yeah, we have a little under ten in our facility here, and then we're in process of building as of right now basically one a week. Yeah. Amazing. You know, Brett, one of the things that I saw when I was there, you showed me figure one, and then figure two, which hadn't been released yet, and then drawings for figure three, which I won't talk about, which look beautiful. But can you talk about your rapid iteration strategy here?

I mean, how do you think about generations and redesigning and rebuilding? Cause a lot of companies like get to something and then fix it and then sell it for a long time. Doesn't sound like your strategy is that. Yeah, I think. I think the rule of thumb here is that roughly you need probably minimum three hardware versions to get to a point where the

hardware is relatively commercial reliable like bug free. And our goal is to in the limit make this basically a software limiting issue for us. Which means we need really capable hardware that's really reliable, it's safe, it's low mass, and it's like low cost. And we can manufacture it really well. That's like a light, a lot to bite off in like the first version hardware and get that right. It's just too difficult.

I mean, it's like getting the iPhone one right and getting everything okay. And I had the iPhone one and it was just not the greatest phone in the world. But like iPhone three and four were like certainly the greatest phones in the world. You know, same for cars, right? Like the Tesla roads, they're probably not

the greatest car in the world. And I have three Teslas now, they're incredible. Probably the best car I've ever had. So we basically want to be on this continuum of rapid hardware iterations where we're basically looking at different heuristics of things that we need to mature over those hardware continuum and making all necessary improvements so that the hardware is, at some point, very mature. I think our first generation hardware, figure one, was mostly trying to get roughly the architecture trades right. All the details of the engineering system for, as a battery is an example, what is the energy? Is it going to be hydraulic?

Is battery powered? What type of battery? Cell chemistry? From there, what type of cell? Is it cylindrical? Is it prismatic? Pouch? How are we going to pack those?

Thermal propagation, all those different trades you have. That's just the battery alone. Then you have the rest of the whole system. So that becomes an order of like 100 or 200 decisions you have to make to go out and build a robot. And you don't wanna have to be in a situation where you have to get all those right. And I think we got most of those right on figure one. We did even better job on some of those decisions

on figure two. Figure two is really about getting to a feature complete robot. It has all those systems on it, whether we're going to build or buy it on the robot that are working. We built most of it. So that's software with those firmware embedded systems, control software, all the hardware systems on board, the actuators, electronics, wiring, battery systems, cameras, sensors. And then, you know, so we think we got roughly to like feature complete, hardware complete on figure two.

And so we're really excited there. And then, you know, future generation for us will be, how do we get the costs down by well over order of magnitude from where we're at now? And how do we get the ability to manufacture an unprecedented scale that we've never seen before in robotics? I know that. You know, one of the quotes I heard you say is, everyone will own a humanoid and labor

will be optional. And those are pretty provocative and I think actually true. Let's, you know, for everyone to own a humanoid, and I want to get into this for a quick moment You said reducing the cost 10x You know Elon's been aggressive on a price tag he's not always been right on price or schedule But I think do you think of these these humanoid robots as a ultimately? converging on a price per kilogram of total weight?

And what do you think 10 years out, 20 years out these things will actually cost? So I spent all year now looking at how cheap we can make these robots. And the answer really lies in like a bottom up bottoms up analysis of the entire build materials bomb, bomb cost, where we take basically a list of call it roughly 1000 parts. And we like start automating that down. And then we start understanding that real scale, how we're going to procure those parts, whether we build or buy, scale, how are we going to procure those parts, whether we build or buy, and what contractual volume estimates we can get with prices there.

I feel... It's super volume-dependent on pricing, I imagine. Yeah. Massively. Every consumer device or car that we know of has been as basically like, follows a very high correlation with manufacturing volumes. So the only real way to get, you know, like consumer electronics prices down is by high volumes.

That's the only way we know of so you really want to make a lot of the product to get the cost down So I yeah, I think like Over a long enough period with enough high volumes I think you're getting these costs down like sub twenty thousand dollars a unit like really cheap And that's amazing because if I were gonna You know lease a twenty thousand dollar car, you know That's costing me like a hundred bucks a month at most and so, you know, why not get to Yeah, you think at the end yeah

I was saying especially if it makes you money like if it can go out and do work and things like you know, I could like actually be in the workforce or it can do Things that you would be spending time on during the day if it can actually I be like a real utility here, I think, yeah, how many would you want if it can make you money? Real quick, I've been getting the most unusual compliments lately on my skin. Truth is, I use a lotion every morning and every night religiously called One Skin. It was developed by four PhD women who determined a 10 amino acid sequence that is a synolytic that kills senile cells in your skin and

this literally reverses the age of your skin and I think it's one of the most incredible products. I use it all the time. If you're interested check out the show notes. I've asked my team to link to it below. All right, let's get back to the episode. Yeah, I mean when we first spoke I remember you said something that was kind of shocking but in retrospect makes sense Correct me if I'm wrong, but I think you said your estimate there would be a market by 2040 for as many as 10 billion humanoid robots Do you still hold to that? They're like, if these robots can do everything a human can, I have to think

that we'd be able to put three to five billion in the workforce and I don't see any reason why every human wouldn't want to have a humanoid like you do a car or phone I perhaps even more important than a car phone where they can just do all the work that you just don't want to do all day Whether it's you know Walking the dog getting coffee doing errands Doing laundry chores like I mean every day I go home and clean up toys, right? So like there's just like, like, I could have a robot just just clean up kids toys two, three hours a day

every day, no problem. Like, it's like endless work every day. Yeah, I can imagine that. There was something else you said that really hit me philosophically. You said it's a moral imperative to have these kinds of humanoid robots because as we get to AGI and digital super intelligence, correct me if I'm wrong here, but you said if we don't have those humanoid robots, the AIs are going to be having us do what they say and it's a lot better for the human soul if the robots are doing what the AIs said. Correct me where I'm wrong there, but that was an interesting point of view. I hadn't heard before. I think a pretty depressing future would be one that we solve AGI and that lives in a box, like not in the physical world.

And in order for that AGI to do anything in the real world, it would have to ask or force a human, you know, through wages or whatever to do that action. And I don't know about you, but that seems like a really kind of downer future. And please, please plug me into a higher to more kilowatt hours. Yeah, like the like, like the collective consciousness of humanity's intelligence is sitting there, wanting to do things in the physical world,

and having to pay humans through wages to do that or through force, that just seems like, I don't know, just a terrible future. I was interested in the mission statement you wrote. I just recently saw some documents that you put out. The mission of figure is expand human capabilities through advanced AI. I'm curious, it didn't say about humanoid robotics. It was expand human capabilities through advanced AI.

How did you end up there? Do you see yourself as an AI company ultimately? We do see ourselves as an AI company a limit. It happens to be robotics. In the limit, all the challenges that we face to do what we set out in our mission are ultimately going to majority be AI problems and hurdles. And I think there's this dream that we're all having here now at Figureware one day we have these robots out in the world

doing like really important work. It's really needed for humanity, helping to lower goods and services prices to hopefully bring a world of abundance. And I happen to think that that'll free up a lot of the time me and you have, we all have to do things like we really, really love. really love. Amplified by robots and AI, you know, to do far more per unit time than ever before. Yeah, exactly. Like, if we could just spend time on what we

really wanted to do, what would all humans do with their time? I think that's one of the most important questions is what, you know, I recently, I've been working on my my next book Which is called age of abundance and I heard you in a previous interview talk about robots enabling an age of abundance What do you how do you describe that what do you think that looks like what did you mean by an age of abundance? well, I think one of the interesting things about humanoids is mean by an age of abundance? Well, I think one of the interesting things about

humanoids is we can put these robots in, the goal is to put these robots into the physical world with no additional infrastructure needed for them to operate. So you can put robots into the workforce, so we don't need to go build new systems and new electronics and everything else for the robot to work with. And it can just, like a special purpose machine,

we go in there, we got to try to architect everything and make new space and build a new machine and roll it out, integrate it like a humanoid just integrates right into the world. You can just do human like things the next day. And if we have robots, ultimately, we'll build robots themselves from a manufacturing perspective. I was going to ask you that that that iterates very quickly down to. Yeah, I mean, you can basically bring most manufacturing perspective. I was gonna ask you that. That iterates very quickly down to a huge. Yeah, I mean, you can basically bring,

most manufacturing today, it's just like, got a bunch of machines and you have humans, that's basically it. And if we can do human level manufacturing, you're basically at a point where you could theoretically have robots building robots. The price here just collapses to nothing. And those robots can be put into the world to do work. So what

is that cost of the work? It's the cost of you renting the robot out and it's the cost of that land. And if you have renewable energy on that facility, like that, you know, this work area, then that cost will be very small and the output will be really high. So you can basically create a world where goods and services prices are trend to zero in the limit. And GDP spikes to infinity. Yeah, I mean, like, yeah, you basically can request anything you'd want would be relatively affordable for everybody in the world.

It's interesting, when you look at GDP of countries, they scale with population and access to energy. Population and energy is work. So it feels like this will become a mandatory part of any nation that wants to survive and thrive in the decades ahead. I think it'd be super important to figure this out. In your mission statement, you said, hence the goal of

figure is to develop general purpose humanoids that make positive impact on humanity and create a better life for future generations. These robots can eliminate the need for unsafe and undesirable jobs, ultimately allowing us to live happier, more fulfilling lives. And I buy that, you know, I love the idea of robots doing the jobs that are dull, dangerous and dirty, cleaning the toilets, you know, cleaning the rooms, you know, because most people, I think do work, most people in the world do work not because they love that work, but because they have to do it to get food or insurance, whatever the case might be. But the question ultimately is,

I also think these robots will, you know, I've got a niece who's a plastic surgeon and I'm like, don't go into that. You know, robots are going to become our ultimate surgeons. to that, robots are going to become our ultimate surgeons. Is there any job you think that robots aren't going to be able to take on if we want them to? It certainly seems that over time, both digital and physical intelligent robots will do more and more things a human can really well. And I think we're really just like in, you know, we've been seeing that though with technology

over the last several centuries, but I think we're seeing that very much accelerate this slope of that curve is accelerating. And it's accelerating in really interesting places with, you know, with large language models and it's almost accelerating the wrong, different direction than we probably have thought like, you know, 10 years ago. So I, yeah, I happen to think that over long enough period of time, we'll have automation fit with our physical or digital automation that we'll be able to do as probably the majority of things that humans can do today. Just to note, I checked this morning,

and there are 8.2 million job openings in the US. So it's not like there's no need for, there's no jobs available. I think the big news, and congrats on this, is the financing you just did Which is extraordinary just for those who don't know You raised 2.6 billion from open AI Microsoft Jeff Bezos and video I know my own venture fund full disclosure bold as an investor very proud of that That's a lot of money Yeah, we raised

675 million at a 2.6 billion valuation. money. Yeah, we raised 675 million. Yes, at a 2.6 billion valuation. Yeah, yeah. Yeah, we're super proud. We have like, we brought a lot of new investors, including OpenAI and Microsoft, NVIDIA. And yeah, great to have your support. It was good. It's giving us the ammo now to really take the next step of our in our mission of Rolling these robots out commercially and making really viable And that's that's really where we're at right now. It's like, how do we take? you know, right, we're you know, we're putting out cool videos and That's great. But like the next big step is like how do we get those in the workforce working every single day and we're you know

we just showed that we just got back from BMW and, you know, and like basically close to two weeks, basically doing a full trial there. That went really well. BMW actually just put out a press release about that. We'll be going back here in the near term. And the goal is like to go back and do useful work continuously. And we couldn't be more excited. It was it was both hard because we were like outside of our

comfort zone in the office. Also just like really energizing when we got back like we can do this like this can be done. Yeah we're like everybody here is fired up that like we get a chance to try to go do this over the next few years and I didn't mean likefinancing here, what's holding us back now? We have more cash than we need at the stage of the company we're in. We have great partners like OpenAI helping us with models. We have great companies like Microsoft helping us out with training and video on GPU hardware, other simulation work.

We have the world's best AI robotics team ever put together. We have figure two now, which is I would say the top humanoid hardware in the world. We're doing some of the best AI learning work in the world. We see this small light in the tunnel, which is like this is what robots can really do. We're all just working really hard at this point. Would you say that what you're doing now is only possible because of the state of AI? I mean, is artificial intelligence and a mass amount of compute the thing that made this possible now?

Because, you know, I mean, we've been talking about robots for God knows, 50 plus years. I built robots in high school and college. I didn't call them robots, I mean, to call them robots, but they were nothing in comparison. But is it now, is it AI that made you say, now I'm gonna commit? Because you put like $100 million of your own money

into the kick this thing off, right? Which is a significant step for an entrepreneur. I think there's only a few different things. I mean, one is like the whole ecosystem. It's not just like it's not just the models. It's, you know, the it's the overall infrastructure for for training, for inference and deployment, deep learning algorithms that can support large scale imitation learning and

reinforcement learning. So there's just like a, it was several building blocks there on the AI side that are all like maturing to a point where you can deploy these policies, like embedded, embodied policies in the world and they work, which is pretty unbelievable. I just got back from taking a Waymo last month in the city and it was just very special. And it's just pretty clear it can just drive like a human can with enough data. And same with our robot. When you see our robot in the facility doing kind of the new generation work that we're

working on now, it just feels magical. I think a separate thing is like the whole like hardware system. It's really hard to know if it was like 10 years ago. This was really possible with like torque density of actuators, batteries, battery systems, energy density there. I would happen to think that, you know, like the best humanoid robots 10 years ago were all hydraulic systems. Those are like 3000 PSI systems. They leaking hydraulic fluid all over the place.

Yeah, like leaking oil everywhere. Like, like intractable to put next to human, you would kill you could kill a human with those next to those systems. So like, certainly like that was the wrong architecture decision 10 years ago. It'd been unclear for me if 10 years ago that would have been possible, assuming you even had AI, that you could build a electromechanical system that would work at the levels we have now 10 years ago.

I would probably think not. And then you think it's a stop. I do think it's a convergence of a whole bunch of things. The theme for my abundance summit next March is convergence. And thank you for joining, because I think what you're building is the exact principle example of converging technologies, making new systems and new business models possible.

How did you connect with OpenAI in the first place? I mean, that's a big step. Yeah. I got introduced to Sam a few years back and we got to know each other a lot better and spent a lot of time together in 2023 and you know ultimately they wanted to get back into robotics and specifically around like AI for you know embodied systems and you know now here we are, working on next generation AI models for our robots to make that work. And they're supporting us on that. That's been, I would say, so far a 10 for

10 system. We happen to think they're the best vision language models in the world. They're the best implementators of those models in the world. And, you know, we're trying to push the boundaries now on how to push that work as hard and as far as possible in the robotic space, which we're just, you know, we've just been starting in the last like several months. I imagine there's a lot of benefits for them as well. I mean, you mentioned embodied AI. There's some theories that say, listen, we're not going to get to AGI unless we can embody AIs to understand the embodiment gives them

an understanding of the universe and allows them to explore. And then there's the other idea that we're going to hit a data wall to get to AGI. And humanoid robots are a means for collecting a lot of data to help shape future models. Can you speak to that a little bit? I think it's becoming more and more clear that some level of output actions in planning is important to take their kind of

next step in intelligence. What we're trying to do here is we're trying to help complete that last leg of like actions and reasoning that we're seeing from kind of some of the best kind of world models that we're helping to work on here internally At the end of the day if you can like talk to a robot and it can output actions like useful actions in the real world That would just be an incredible Technology for the world that we're trying to work on here whether you want to call that, you know Advanced AI AGI, whatever like that's just such an important focal point for us to try to get to is how do we output intelligent

actions into the world and do useful things. So most of our focus on the AI side is on that topic and how to make that as scalable as possible and generalizable. I mean, I have to imagine, you know, GPT-4.0 and or, you know, the multimodal versions of GPT-4 are key for you, right? Having figure C and be able to understand. Was that a relatively... When you started, that didn't exist. The multimodal models weren't there was Was that the conversation you had going on with Sam was he sort of like? You know sort of Was he part of your inner conversation of what's going to be possible in the future?

I think yeah, I mean like one of the biggest breakthroughs we have is we have like with LLMs and you know VLMs more specifically specifically, we've had this semantic grounding that's occurred in robotics. We have the world's knowledge in some way, the knowledge of a zip file for the robot to access and understand. And that bridge from robot to human was never really here before. If you want to talk to, you know, autonomous car and say, drop me off from the, you know, on the curb over there on the right, there was no real semantic bridge for that in the

world. And, you know, arguably, we have that now we have like that semantic bridge has been built in the world. And what we're really lacking is this like, like, I guess, reasoning and planning and perhaps actions from that system to, for us to provide useful work in a robot. And so I would say you've had this like unbelievable technology has been opened up and we're seeing some really cool stuff right now in the world, like, you know,

with different technologies all over the world in AI, but like one of the things people are not talking a lot about is what does this mean for robotics? This means a robot knows everything you're saying. It knows what you mean. And we have all this grounded in human-level data, meaning we have all this semantic world's knowledge is written by humans for humans, which

is an incredible ability for a humanoid robot that looks like a human to really have really high efficiency transfer rates. So we like the way humans open up jars is pretty similar to robots or humanoid robots to open a jar. So like the affordances are roughly you know really high affordance levels as it relates to humans work. So this is like unlocks like an ability for humanoid robots to really tackle like general robotics, like how do we talk to robots and how do we output actions that everything a human can do. And there's, there seems to be at a point in time where we can really try to see if

we can crack that. So you mean that we're going to see the normal course of interactions with robots be like you speak to a human. It's like, can you please go grab that for me? And it says, what do you want me to grab? And you say that thing over there and you point and it looks. And it understands the stapler or the bottle of water and so it's got contextual knowledge and geometric and what you call positional knowledge. How

far is that? Yes, this is all realistic today. Yeah. It's not, it's beyond even all those things like in the neural net weights lives the material of the plastic bottle roughly mass characteristics Sure and friction, you know characteristics and how it will feel to grab and All of this is in the weights I Work I work on longevity because I want to see as much of this stuff as I possibly can Yeah, how what kind of hours do you work? to see as much of this stuff as I possibly can. What kind of hours do you work? Because I know your passion, Brett, I know your dedication to this and you are a kid

in a candy store. What's your, and you have to balance family as well, what's your work week like? Yeah, I would say I work almost like basically almost seven days a week. There's really no time I'm like really not working. Except with home like with the you know wife and my kids. How old are your kids? Do they do they get what you're doing? We just had a family day at figure so you know my daughter is five and like was like and my son is two so we had the robots walking around. All the kids were so excited.

It was really cool. Yeah, they get it. They talk about dad building robots all the time. And you know, I think like, yeah, it's like, yeah, I think we actually had probably 50 kids here like last week. Like watching all of them like see the robots and touch them and yeah, it was pretty special. You know, I think about that. My boys are, I have two boys who are 11, 13. I can't wait to have them see what you're building here

and I think about the fact that their future and your kids future are going to be You know if your numbers are correct, and I think that they are They will be more prevalent than cars are out there, right? There's like a million cars like a million other vehicles and we could see you know five to ten, I'm sorry a billion cars out there, a billion other vehicles. And so it's gonna be a very different future for them. I asked a friend of mine what's it gonna be like when you're seeing humanoid robots walking around the street all the time in five years and

his answer was interesting. He said, it's gonna seem normal. Yeah, can I tell you something? We have a lot of folks here who have been around robots for a long time. They're gonna be like, as soon as we do something everybody's gonna be in awe and then nobody's gonna care anymore. It's funny, sometimes that happens. We were walking figure two now around the office quite frequently. And the first few times, like everybody's just like stopped doing work. They're like fist pumping from the conference room or whatever, taking photos. We have this like, we have this really crazy video where everybody is falling around the robot the first time I

walked in the office with like their phones out, you know, and we do it now pretty regularly. And nobody cares. Like nobody is just like, oh, the robot's close to me. Like, you know, like that's it. It's pretty unbelievable how used to all the stuff we get, right? Yeah, we adapt so quickly. It's like, becomes boring. I remember the first time I got like one of the first Model X's and, you know, the door wings come up and everybody's snapping photos and looking at it and then it's a nuisance

after that Yeah, yeah, yeah, we get used to things really quick. I don't know. It's uh, even like using, you know Like large language models and stuff today like chat GPT. It's just like I use it pretty frequently during the week and it's just I Like it's totally normal part of my workflow. Yeah, it is it becomes just an extension GPT-5, have you had conversations about integrating that and its derivatives or the mythical strawberries that's being unveiled? Do you get any early views of OpenAI's content for a figure?

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I am curious what you, how you think about Optimus and Tesla and Elon. I know you have great respect for him as an engineer and entrepreneur. What are your thoughts there? I just have to be so inspired by what Elon's done in the last 20, 30 years. It's been just unbelievable. I think they're doing a great job at Optimus, and I think they have a really good engineering team. I think they're making really good progress. And I think they're doing a great job at Optimus. And I think they have a really good engineering team. I think they're making really good progress. And I think they're actually heading in the right direction. Like the vector for where we need to go as a society

to integrate and build humanoid robots, I think they're following a very good direction. So I think they're going to be a really real competitor with us. I think the world needs them out there doing this. And yeah, I hope they do really well. I think we're at a point in time where the window has just opened now for humanoids to be possible. I don't think it was really possible 10 years ago. So it's going to be a little bit of a race

here to get volumes out the door in terms of manufacturing. And you get the AI training sets built and deployed on the embodied systems. And yeah, it's going to be a more important time to make this really work. So yeah, I think overall just like very, I think they'll do very well and I'm very glad they're tackling it.

Yeah, I think when he walks into a new industry like that, he credentials it in a big way. Did they serve as sort of a stocking horse for you to keep the team? Do you guys like look at it and go, oh my God, how'd they do that? Or, you know, ours is better. Is it provide a little bit of that kind of like

gamified motivation for the team or are you guys just open loop otherwise? I think we try to like make, we try to make all of our decisions from like a first order reasoning, like what was the right decision to make. If that's like super important for every company to really do is like,

I think we have our own mission vision values that we care about, it's very different than any other company and we want to head a certain direction, I think we have our own mission vision values, what we care about very different than any other company. And we want to head a certain direction like vector space like that we think is the right way to go longer term. So I think that's like where we really ground ourselves and like the decisions we make. I think there'll be things that we do a lot differently than other groups, you know, longer term, because we're just making

these decisions like in a vacuum with knowledge that we have. And going through that. Yeah, I think they're a really good competitor. So for sure, we want to be we want to be winning and we want to compete, you know, overall we. So yeah, I think, you know, our goal is to build the best humanoid robotics company in the world over here, I figure. And I think since the marketplace is arguably near infinite, there's plenty of room for

two or three significant players on the planet. I think the way I look at it is we need more like really real players. I think Tesla is a really real player. Like I mean, you know, highly capitalized, great engineering team, heading the right direction like longer term, moving fast through those high rate iteration cycles and milestones that are needed for engineering teams that really prove out the product is getting commercially viable.

And what we're lacking in humanoid space is that. We have a lot of groups that have been around for a long time, around the hoop. And it does not look like there will be a lot of players that all win. It looks like there'll be very few that make it through this chasm, crossing the chasm here that's needed for getting us to market. And I think many will die trying to bridge this. I hope that we live it figure, but we have like 14 peaks to go climb now. We have a very hard road ahead to go from where we're at now,

which is like two year old company to a commercially viable real business. And that's what we need to go do. We have years, single digit years to go prove that and get into markets. We're charging forward as hard as we can to ship our product into customers and make it useful. Yeah, I think most people probably don't realize is you're only two years old, right? And what you put together in terms of team. And I think this last round of financing, if I looked at what, you know, if you had said to the average person or average technologist or venture capitalist, what's the advantage that Elon has for

Optimus? It's he has a manufacturing, he has a car company there that could use it. He's got compute. He's got capital. I think this last round gave you parody, if not in some places. It's like it's such a it's just like a such a stupid argument though because like you could say that about every company that's and why they can't be disrupted you could have said that those are all Texas weaknesses 20 years ago when they didn't have any of those none of them. There's already groups making electric cars and somehow they won. So like that's not really what happens in real life. Like that's not the, that's

not, those attributes do not set the winner. I'm not saying I set the winner, I'm just saying that you, those attributes were advantageous and and now you've got the capital, you've got the compute with OpenAI and you've got BMW and so forth. So. No, no. I think like all the building blocks that we need to do to build a healthy company are all like starting to show up and that's good because we need like those are like requirements that are needed in our long-term roadmap and we just got to put all those pieces together very intelligently and then not die in the market and make it work. Not dying is a great part of the business plan.

Can we talk about China? Because I find that absolutely fascinating. So China succeeded on the backs of low-cost labor, and that's going away. We hit COVID, and no one wants to manufacture it, and the shipping costs. And so I'm tracking the robot companies coming out of China, because I think that for so many reasons, like their aging population, their one child, per family policy, all of that, and trying to actually maintain a manufacturing base all requires robotics. I see Unitree and a few others.

What do you think of the Chinese robots? Are there any that seem like good competition out there? I just got back from China a couple of months ago, and it was one of the best visits I've done in my career, to be honest. Went to a bunch of manufacturing-focused companies in mainland China, and it was just crazy. We were touring one facility, and I was like, what's that written on the wall over there?

And they're like, oh, that's just our motto for this building. I was like, what's that written on the wall over there? And they're like, Oh, that's just our motto for this building. I'm like, what does it say? They're like, if you're having a bad day, just work harder. And I was like, these guys are, they're animals over here. They're just like, they're just trying to build and ship. The work ethic was really high. The sheer will of the country to try to be like, be like, compete and win is really high. And I was floored.

I was just, I was like, man, you have, you have like- Have you been there many times before? I've not been there, like, I would call it like a lot. And, you know, specifically was like, it's been a lot of time touring kind of what high rate manufacturing processes look like out there. And it was just, it was shocking. I think, I think the, you know, I think we have in the humanoid space, like we have like,

you know, figured an optimist here, you know, outside of China. And I do think China is like the next group of folks that are Are gonna be really competitive long term in the humanoid space. I think they have to be You know I used to when I used to go to China every year and bring a Group of abundance members with me and we'd go and visit all the top tech companies and I remember the motto There was 996 like a great lifestyle was 9 a.m. to 9 p.m. six days a week. That was the work ethic. And you know, everybody, China had the

reputation as being copycats, but you know, sure, they copy a lot of things, but they also did a lot of authentic new development work there. Is that your experience as well? My experience has been that those folks out there want to win. They want to do it at the lowest cost. They want to do it at the highest rate. And they'll stop at nothing to try to be number one. And that's like, you know, think about what startups are. It's like it boils down to like those key principles you start a company with that are

successful. You, you have nothing and it's just sheer willpower to get there and to go in and they have that in spades in China and they do not have the resources we do here in the States. Is that, you know, like we said before, does that really matter that you have like all these things or is it, you know, is that, is that, we said before, does that really matter that you have like all these things or is that is that is that is ultimate crutch. And so I think I think there are going to be some unbelievable robotics companies come out of China just for the just because of the sheer number of projects being worked on and with the will that I saw out there Is second to none. Yeah, I mean I think in the same way that Israel developed an amazing defense industry because they had to To survive I think China and Japan and South Korea with dwindling populations and aging populations

Are gonna need to develop an incredible Robotics industry to survive and thrive and maintain a GDP Yeah, so you you take Archer public Which was an incredible success and congratulations on that And after starting that running that for a number of years You break away to found Figure and if I'm correct, you know, you made a commitment. You put a significant amount of capital on the table to start the company, which you

were able to do because of your previous exits from from Vetteri and from from Archer. But I think when I when I first heard your presentation and I brought it to my venture fund, what I was so impressed by, which clinched the deal in my mind, was the team you built. I mean, it was an extraordinary group of engineers from the top AI and robotics companies or tech companies out there. Can you just, word of advice for founders who are starting a company? I mean, you're a technical founder as well, which is important, right? But how did you recruit your team?

Yeah. So, my belief is that in order to ship a really good high quality product, you need the world's best team there to go do that. Especially against the difficulty level, we have a figure of succeeding, the odds of success are always pretty low. So you need to give it everything you got. You need the best team here,

on-site every day, work hard. You need to have a high functioning workaholism. So I spent the first year basically trying to map out the what the organization needs to look like in terms of skills and like, what does the ultimate org chart need to do to support like a really high functioning team to build a product. And I spent the first year just basically head hunting all that whole team by hand. And like, you know, cool, I was cold email

and then calling drafted off letter would give the off letter go do dinners try to close on board, you know, 3690 day on boarding, bring them in lead the engineering decisions and direction and, you know, work on those projects with those teams. Like, I think, you know, it's been a huge payoff because we've gotten, like, now this point where I think we have, like, one of the better teams ever built in the world for this. And it's like snowballing. We're able to track a really high-quality talent over all our

disciplines. But in the early days, in the early days, Brad, I mean, how did you get that first dozen? Was it your conviction? Was it your capital commitment to it? I mean, because in one way, you had Tesla bot, I don't know if it was called Optimus back then, you know, and so Elon tends to suck the oxygen out of a room on the stuff that he does. Convincing people to jump where they were and join you, how did you do that? That jiu-jitsu is really important. Yeah, I mean the pitch for early figure was we're working on humanoids.

We have this big mission to advance human capabilities with AI. We believe in AI first in the market. We believe a vertically integrated approach to hardware design is important. We're living in the largest ham, or we're working in the largest ham in the world. It's below half of GDP as human labor. I'll fund the first several years. There's no funding risks in the near term. And, you know, it's my second time going around building hardware and building a hardware team.

So, you know, having done it, I think, decently well at Archer, you know, we're getting back in the unit from scratch, did even better this time in terms of like setting the right direction and mission vision values of the team. And then I just spent a lot of time with those folks saying, you know, come here, let's go out and build this commercial, let's build the best organization we possibly can from early days. The early folks got all like founding, you know, founding member stock, which also was helpful and beneficial, got good salaries, I was, you know, funding myself. So it was

like, you know, it was being a part of like a from scratch startup, but like almost like cushioned by my ability to self-funded for multiple years, good equity. You know, by the time we had five or six people in the team, they were all superstars. And then that was like, we're risking for the next, you know, five or six folks that were joining. So was able to find folks that really believed in the space and believed in me. A lot of folks that used to work with me, my last two companies, a lot of folks that were new as well. I had a you know, I had my first

two people were folks that I've worked with that, you know, were like my first employee at Vetri, my early employees at Archer that I worked with. There were like, you know, so it was, you know, three of us, day one, basically, that have all worked together, added some more folks on my old team at Archer, added some more folks from Boston Dynamics and other organizations that are really great. Soon enough, we had a dozen people that were superstars in their discipline. And then, we walked our robot within 12 months of incorporating the company.

So we worked really hard and got out of the gates pretty fast. And now it looks like, okay, everything looks great then, but I was in a WeWork phone booth for five months making cold calls, trying to convince and talking to, you know, wives and husbands and telling me convince there's, you know, spouse to join and it was hard. Yeah, not gonna lie.

I bet. What did you give the chances of success back then in the early days or to get to the point where you are now? I mean, if you had to give a thing back then, would you agree, like, yeah? Yeah, I would not have ever assumed that we would be at a place now. We've really, you know, I think there's the,

you know, I look at everything as like, how well is the product doing as it relates to like, the roadmap into commercialization? We're still, you know, we're not successful. Like, we're not even shipping. Yeah, of course. But like, you know, we're not like, we're not successful. Like we're not even like shipping. But like, I think that, but like, you know, we've been around for, I don't know, like 20, like, you know, a little over, like a little over two years or something like that. Unbelievable.

Like the amount of the hardware that's doing the AI systems and working in X-GNOS was policies. Like the, the, the look at the human noise now versus like 10 years, it's unbelievable. And we don't ever walk into the office and like things go backwards. Like they always go forwards. Like we're not like, you know, sometimes we have like a couple days where like, you know, a couple of robots break and we don't make progress because we're fixing them or whatever else, or a lot of meaningful progress. But most weeks we're like making pretty decent, like if folks are gone for a week, they come back and be like,

this is a whole new company, it feels like. So every week goes by, we're making pretty substantial impact. So I would say we far exceeded my early impressions of where we'd be at two years from now, yeah, two years ago. I'm curious, what did you think would be really hard that turned out to be easy? Nothing easy but was easier than you expected. Well, I thought maybe like the opposite will do. I thought like we'd be able to procure a lot of supply chain to go build the robot. Like electronics

boards, motors, actuator systems, battery pack systems, cameras, like lights, like speakers, like we like speakers on figure two, I thought maybe go to Alibaba or go to Amazon and buy screens like basic screens, speakers, lights. These things have to be about the shelf, right? Like you have to go buy those things and they come in from Amazon and you put them on a prototype. Like that's like, that's like what that should be that easy. It's still not that easy.

Like we're making custom speakers. Like how is it possible that we're making custom speakers in writing custom firmware for some of those areas? Like how is that even, it doesn't make any sense that that's even possible. So going into it, a little naive of like these sensors for torque cells or whatever, like would be procured and would come in, I wouldn't have to do it. Like we make our torque cells, like four cells here,

which need like a flexure, the board, they need to be gauged, they need to be calibrated. They need to be tested. Integrated, there's like, there's software and firmware on there, and that's got to work then at really high rates. It just still boggles my mind there's no mature supply chain across all this stuff. It's just unbelievable. I'm assuming that that's not your first choice, that you'd rather buy from a reliable supplier

versus vertically integrated everything. Everybody would always choose to buy something if it's like easy to procure and not the only vendor in town. Everybody would always choose to buy nobody in the right mind would ever want to build in that case. It's just enormous effort and burden to maintain it and to QA it and to fix bugs and to pay human salary and manage humans it's just like it's just a hard it's like a hard thing to do and you'll get you'll get through the human phase pretty soon yeah what what

percentage of the robot is manufacturing house do you think like rough order is it like 75 percent 90% by whatever but whatever metric you want a weight or we probably look at how much of this is like we're designing ourselves I don't know I don't know the exact number of top ahead but I have to think it's probably like 70 80 percent of things we're designing at this point for the robot there isn't there is an advantage of controlling quality and pulling out overhead or margins out of the vendors. I remember I was visiting Elon's shop in the early days and he was in this conversation by some supplier because a lot of

these suppliers are all defense aerospace and they're just extraordinarily expensive and he was like screw them we'll just make it ourselves was was the attitude I don't know that's what we like we've been around for two years so most of the engineering decisions around the build materials and the supply chain would have been let's get speed by getting parts in the robot, get robots to AI engineers, controls engineers, let's get work done. So we would have made those decisions quite quickly to outsource that work to get robots up and running faster.

So, and I think longer term, we would have worked the supply chain to own it better, to have less risk, to reduce the margin profile across all the supply chain. But there's just like, yeah, I think we thought that was easy. It became like a bloody hell. So what's the flip side of this, a thing that you thought was going to be hard and turn out to be easy? Would it maybe be the AI integration? When you started, did you imagine you're going to have to build out your own AI models?

We still do a lot of our own AI models here, which is maybe not super well known, but we do, we have a whole AI team, we do most of the lot of work ourselves. I would say across this, we leverage some group, like OpenAI, we work with on new models and stuff and use their VLM for some things. So I think that's been really helpful. I think AI systems is probably the one that's been like, wow, this is really working. And it's, you know, you think about

like the split of like, what percentage of the things are you gonna have to hard code and code to go do, which is like, you know, more classical controls and heuristics, what percentage of things can we do through neural networks? And I, you know, I would, I would have thought going into this, my, I guess my thoughts two years ago was like, you know, a large percentage of the stack would be written in heuristics and code, call like 95, 90%. And then as we are able to, you know, write neural nets for those that are at equivalent performance, we will just take those level of like code or C++ and remove it with a neural net.

And it's kind of been flipped. Yeah, all the nervous is working for like a small team with like, you know, we don't have like a ton of tooling and infrastructure and things almost like right off the bat with like, everything like just like, like using slam or perception systems and object detectors and planning and speech to speech reasoning, everything, that's stacked like the high and low levels have been working incredibly well. And so yeah, I think it's pretty magical.

I just like it would take us such a long time to code all this stuff. Did you see the movie Oppenheimer? If you did, did you know that besides building the atomic bomb at Los Alamos National Labs, that they spent billions on bio-defense weapons, the ability to accurately detect viruses and microbes by reading their RNA? Well, a company called Viome exclusively licensed the technology from Los Alamos Labs to build a platform that can measure your microbiome and the RNA in your blood. Now, Viome has a product that I've personally microbiome and the RNA in your blood. Now, Viome has a product that I've personally used for years called Full Body

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I've asked Naveen Jain, a friend of mine who's the founder and CEO of Viome, to give my listeners a special discount. You'll find it at Viome.com slash Peter. I remember you talking and describing to me the time when figure one put the Keurig cup and made you a cup of coffee and you're like, we're trying to code this and then we just had them watch somebody do it like a dozen times and they're able to model it. I'm curious, is the way you're interacting with figure two like, hey, watch me pick this thing up and put it over here and now you do it.

Is that conversational, you know, and the visual models, is that where the state of the practice is? Yeah, we're like literally talking to a robot to go do something and it does it. So what's like the most interesting thing you've had figure, you know, do for you? I mean we can literally talk to our robot and it can like do tasks right now, which is like, unbelievable. I mean, like the end state for this is you really want the default UI to be speech. You just want to talk to the real I want to when I'm like, like, yeah, I another now another way

to think about it is like, I'm on the robot. I'm like, you know, one way to do is like, I pull my phone out or my laptop out. And I'm like, you know, opening a terminal and like trying to get a command to the robot to go do something. And the robot's like standing right there listening. And I'm just like, it just like wants to be talked to. Like, you just want to just be like, put all this stuff away. And it's be like, figure two, you know, go do this.

And we're doing that now and it's just magical. It's really clear that the default UI for human or robot is going to be speech. You really just want speech to speech reasoning to get really high and you ultimately at the end state want to talk to the robot and have it be able to learn as it's in the environment through vision and sensors and you want it to get better over time and it certainly seems like they were heading in that direction. Yeah, I remember Rethink Robotics used to like move the hand for them and say do this again but yeah, I mean speaking to it and showing it what you want if it doesn't understand. Can we talk about robotic safety?

I mean, where are you on safety and how do you make sure there's no errant firmware upgrade that turns robots into overpowered slayers? I know, I mean there's enough there's enough dystopian Hollywood movies. I don't want to you know Bring them forward, but how do you think about safety? How important is that? Where does Asimov's laws come into your mind and practice? there's like many ways to think of those we have like the Like this system safety engineering side of like making the robot like actually really safe when it walks around the facility and does things worth next to humans. There's a whole like architecture, architecture is actually designed from top, like, like the

bottoms up to make that a safe safe system that ultimately we can like put a safe hardware system into the world and it will basically react like we would want it to in all these different various conditions. And I think that's just one piece, like we need to save hardware around humans. There's another piece of like cybersecurity and other things like we don't want anybody to have like root access to the robot and be able to take command of robots and to do potentially bad malicious things with them.

And then you have other things like what happens on the onset of AGI, how does that really impact the safety of the robot? So I think there's like many things we're doing here as it relates to like the low level read-only firmware on the robot as it relates to what is the lowest level code sitting at the robot that can't be overridden say So it's more kind of like the you know, three three laws I mean, it's pretty cool you get you get to think about you know, the laws of robotics you want to instill in your robots Yeah, I mean like a lot of this stuff is like if we don't think about this now we have to do like full Architecture rebuilds which affect the system quite a lot. So we kind of have to start thinking about all this stuff now to design. So help me understand this. So right now can a robot

mechanically have enough velocity and torque to harm you? Because a lot of the sort of automotive robots, you know, they put cages around them and so forth and there have been designs where it's like okay I'm just going to make the robot so it can't build enough velocity, it can't outrun you, it can't, you know, sort of you put that kind of a constriction on it. I mean the robot's like 150 pounds. You know, it certainly has enough like gravitational potential energy no matter what to hurt you. So if it fell off a bunch of stairs and was falling on you, like it certainly could hurt you. So like no matter what to hurt you. So if it fell off a bunch of stairs and was falling on you, like it certainly could hurt you. So like, no matter what I think whether it doesn't have even has like, you know, torque sensing applied, so it can't hurt you

next to you. There's certainly a scenario where it could be harmful, no matter what. So I think, yes, this is for sure a system that can be harmful to humans, if not designed properly. Or it has a certain episode or fault on the robot that somehow is next to a human and hurts them. So this is something that has to be done very thoughtfully from the beginning as a system safety architecture.

And then we have to gradually prove out performance of that CC system over time through an incremental approach. So like our first robots in the work cells in the workforce will be isolated from humans. If humans enter those work cells, we will shut the robot off. Over time, we will go from there to like fully next to humans collaboratively. And that will be like a gradual phase of it. Time frame, best guess, is that two years, five years? I actually don't. We're mostly concerned on trying to get the performance up of the system in the first

few years and the reliability. That's probably the hardest thing we have to do. You want to go and see a robot working full like whether it's like, you know, it's they'll see it like a light curtain, like a like an artificial cage, or the robot. I think solving like a collaborative robot next to all humans longer is like super solvable. I think the hardest hill we have now to climb, which is harder than that, is getting the robot to do end to end work

every day without like failure. Like, day without failure. It makes local failures. Sometimes I miss an object, but I go and re-grab it. So we can fail locally, but not globally. We have certain performance outputs. Let's say we go into a warehouse. They're going to have a certain amount of output per day of packages or whatever they're going to do, of SKUs. They'll need to go hit.

If it's a bunch of robots doing that, they'll still have those same performance goals. So we know if we miss a package, we just got to deliver it the right way on time. So I guess what I'm trying to say is, yes, I think we'll solve this decade, humanoids around humans and interacting with them closely. But before you ever see that, you'll see, it's like the analogy of Waymo, right? You saw it in Waymo in certain permitting areas of San Francisco before you saw in other cities.

Sure. And you saw it with the practice drivers in the seat, watching everything. Yeah, you've seen it with everything, even like autopilot, right? Like you've seen it on highways doing it well, as for beta testing the new software updates for other types of concept operations. So like, I think for us, we're just, you know, we're at this period now where we need to

prove that it can work and do useful work, even on a confined perspective. And then over time, like, yeah, we got to build in the right system safety certification almost to, like, make sure it's ubiquitous. I can walk around humans It can like give items to humans it can you know, and we'll have certain safety precautions We do next to humans to make sure we're not Operating at full torques and full speeds next to humans. Do you think as mobs laws would should actually be incorporated? You know, they're pretty fundamental, you know, don't harm a human or do something that you know, they're pretty fundamental, you know, don't harm a human or do something that causes a human to be harmed or by, you know, not do something that by not taking action causes a human to be harmed. I mean, that sounds pretty

fundamental but it sounds like it's the AI layer. Yeah, there's certainly a select number of really important do not override read-only instructions that need to live on the robot that can never be altered. That's like for sure. And then, do you imagine, figure, I mean, so one of the biggest advantages of having a robotic workforce is that they can all learn when one robot learns a task they all know the task and that requires sort of a you know sort of central control is that going to be you know is that like one central control for a BMW plant or is that figure on a global level where

there's a sort of mission control that is watching all robots and Learning from them. Yeah you Sorry for us We would want Robots as a fleet doing continuous learning and continuous training on that data set so It'll be a situation where we have millions, if not billions, of robots on the planet, hopefully someday, that are all continuously learning as a group. We're doing offline training on that, and then the robots are basically getting smarter

collectively. It's like as a collective intelligence. That's for sure what's happening in the direction we're heading towards. You want what's so powerful about this is like humans, you know, my kids, like they learn how to walk. They learn how to walk. They're mostly failing, like learning not like what not to do in some ways. They learn new things. That takes a lot of time. Once we know things like really well, we really don't forget it.

Rarely do we forget, you know we forget how to walk or certain things. That's happened throughout history, but most of the time we really don't forget. So for robots, one of the biggest advantages we have is once one robot learns a certain task, every robot in the fleet will know this. And so it'll be very exponential in terms of like the amount of new, you know, almost like almost like the matrix, like, we will plug like what we'll teach robots will learn to like human demonstrations and through reasoning, like, like how to do something. And once it's been able to demonstrate

that several times, and we've been able to, you know, like close the loop on that, like, that's worked really well, and it's a reward system, every robot in the fleet will know this. That's why I think future surgeons will best be done, surgery will best be done by robots, where when robot is seen, millions of different surgeries can be the best reliable surgeon out there. Can we wrap up a conversation, just talk a little bit about jobs, and can be the best and reliable surgeon out there.

Can we wrap up a conversation and just talk a little about jobs, because I have to imagine that people are still fearful about robots taking their jobs. We have like really good feedback so far. Our goal is to really be able to do a lot of the jobs that are not desirable by humans. I mean, you mentioned earlier in this podcast, we have like 8 million US jobs that people just don't want to do. Like, we want to do those jobs.

And we want to do the things right now that like, that are potentially harmful and dangerous for humans to do. And a lot of those jobs have like very high unemployment rates, very high, like, very low, like retention, like, like really high, like low retention rates. And we want to start trying to do those and try to help automate. And, you know, like we've been doing that as a world for like several centuries, like my my family was farmers, right? At some point, we had half the world was

farmers. I grew up on a farm. Like 80% of the world was farmers. Yeah, like everybody was farming. And now, you know, like you want to, you know, not very many. So like, you know, I grew up on a farm, like that's like, you know and nobody's mad that we're all not farming like you know what i mean like nobody like i'm like you're not out there being like 80 everybody should be farming right now like that wouldn't be great right for all like um plowing fields and uh harvesting corn and soybeans like that's not that i don't think that would been productive state for

humanity in 2024 do you remember um when at the the Fukushima nuclear reaction reactor and then DARPA had the DARPA Robotics Challenge? Have you ever seen those videos where the robot was just you know laughably incapable of opening a door or climbing steps? Yeah. I mean I think that's the is it how is the Defense Department and the government a client or a near client? How do you feel about plugging into that world? Yeah, we won't do anything defense related at all. It's like in our manifesto online, we think the civilian market is just orders of magnitude

bigger than defense. And it's not in our interest to build a war machine of any kind, either non-kinetic war machine. So we won't even have conversations. We won't take phone calls with anybody in this area. Fascinating. How do you feel about civil police and security? Right now, no.

We're not touching any of that stuff. We don't want to give any requirements that are needed to have the robot produce harm to any humans. Like, our goal is to do work. We want to do work. We think that freeze, we think it significantly helps the economy and helps lower goods and service prices and do good work for the world. And I think it's much needed. Like I think, so like we're putting all our eggs in that basket right now.

What industries do you see next? I mean, you basically have... I mean, it's every industry, but where do you think you want to play? I mean, you're probably getting a ton of solicitations, right? Yeah, we have like taking it a step at a time. I mean, these companies are big. I mean, we like these companies we're talking to, like our master, we could ship 1000s of robots in these groups. So, you know, for us, we'd rather work with only a couple of groups right now and do that really well than like opening up to, you know, hundreds of groups at the moment. But at some point in the coming years, we'll sell to anybody. And we're starting our production line next year. So we'll start with a few as we, you know, have have engineering really close with those customers and making sure that the product really works well. There'll be a bunch of bugs and process improvements we need to make to make those a well-oiled

machine for the market. We want to do those with those customers now. And as we get to some level of product maturity, we'll branch out to more and more customers. And something that we're going to spend more and more time on is also like robots in the home. And... Yeah. When can I own a robot in my home?

Because I'd like to put my order in now. Every six months that goes by, I go to a couple of folks here and I say the timeline for us getting home is accelerating. And it... One of the things that'll be really helpful for us getting to the workforce, it'll really help us get system reliability up, safety up, and the cost down and volumes up for manufacturing, it'll really help us in the home. Because you really want like, you'll probably have like an order of magnitude pricing collapse going into the home from the workforce.

Sure. And you really need economies of scale to get there, and you really need a safety certified system in the home. So like you need a really safe product in the home. So we are using the workforce in a lot of ways to boost drop that vision for us. And but I think from a performance perspective, I think we'll start doing early work in the home

and then like, you know, I think the home for us is an area where, yeah, I think it's accelerating in my mind every six months that we- Okay, but give me a guess. Is it three years, five years, eight years? I would say within the next three years, we'll definitely have robots piloting in homes.

Yeah. Nice. Okay, I wanna to volunteer early on. I'll pay. We'll probably start with some lock homes here in our facilities and start giving the bugs worked out, understanding how the system architectures all work. But I'm interested in seeing what problems we face that we're not prepared for that are limiting our ability to get in the home long term as well. Amazing. So last question for you, Brett. Manufacturing, you're scaling up, you're building a manufacturing plant for figure. Yeah, we're actually starting our production line next year. Where's it gonna go? Where are you gonna do that? We're gonna do it here in California, like close to engineering. So we really work out the kinks on like more of a traditional like kind of pilot manufacturing line or production line. And then from there, we'll start announcing our intentions for like we're like, like high

rate manufacturing will look but our production line is being, we're starting to design it as we speak. We'll have robots coming off the production line next year in 2025. You're scaling it for what kind of volume you think? We'll start with hundreds of robots and then thousands. Like we really want to get the pro- what's more important for us than just having like, you know, here's 3,000, 4,000 robots out is getting the process really dialed in for how to do that.

And then also making sure those robots that we're producing are working really well. There's a situation where anybody easily can get into where we have too many robots that don't work well and you're basically in this recursive loop fixing them, always having them down. Volume doesn't really help. So you really need the system reliability to be at a certain point and the production like the performance of those robots then into the use cases to be pretty high. I do not feel like building thousands of robots is,

it seems super tractable to go do. Now building like hundreds of thousands of robots is a different story, then building millions is a different story. But building like 2000, 5000, 10,000 robots is just, at this point, you know, building, we're building one a week, so it might seem, you know, and then we'll start building like one a day, and then we'll start building

multiples a day here next 12 months. So like, I think, but it seems like pretty straightforward path. I mean, we make cell phones almost by hand in the world to make a few billion a year, like, this is more complex than a cell phone, but far less complex in a car. So yeah, I feel like the path to making thousands in the near term is just not super difficult. What's the difficult part is making those thousands to a point where they're really useful and really work. That's the name of the game for me.

Brett Adcock, I'm a huge fan of what you built and excited for figure twos roll out into the world. And actually what I saw with figure three is absolutely gorgeous. So I'm excited for that as well. Thank you for all the hard work you're doing. And I do think this is a way of uplifting humanity and creating an age of abundance. So much appreciated. Let's do it, Peter. See ya. See ya pal.