Bernt Bornich – Founder and CEO of 1X Technologies on the Future of Humanoid Robots

Welcome back to the Casey Adams Show. Today I am joined by Bernst Bernick, the founder and CEO of 1X. Thank you so much for coming the show today.

Oh, appreciate it.

So we are here in your beautiful HQ in Palo Alto. Thank you so much for having me today and to jump right in, man. You guys have truly revolutionized modern humanoid robots in the home. And I saw you talk about in a previous interview how you, you knew you wanted to build humanoid robots since you were a kid. How did you know that when you were young? What led to you wanting to pursue that at such an early age? And even as an idea, the idea.

Is really old, right? I mean, people, I don't know, maybe the first one is the golem. But I was really lucky. I grew up with like a dad who loved to build things. Like we would build soapbox cars for the local races. We'd go like all in. We would build welded aluminum frames and like proper like chassis racers and stuff for when I was a small kid. So I really just loved building things. And then I moved to generation where I just like, I discovered the computers, right? The really early ones, and I got really into programming and then one day I just like connected the two and like, hey, I can write some code, can make something move in the physical world. I was like, it's pure magic.

Yeah.

Yeah. Picked apart all my mom's kitchen appliances because they had motors. Wasn't the most popular thing I've done, but yeah, just basically a tinker as a kid and I think I was 11.

Wow.

When I like thought back about like, when does this happen? Where I was looking at like, what was going on with actually the. Now it's called the Honda Asimo, but back then it was just called like, it was the P3 or something. The early Honda Humanoids. And I was like, this is what I'm going to do.

Wow.

This is what I want to build.

You have this, you know, early childhood memory and just idea of like, hey, humanoid robots, where does one even make begin? You know, going in, growing up in Norway, now, you know, we're here in Palo Alto. You raised all this money, built incredible products. Looking back, did you say, hey, this is going to be my lifelong pursuit? Or did you ever have a plan B? Or like, what were the, what were your goals as a career? Even when you might have known, hey, I want to build humanoid robots. Did you want to work in a.

Company or was it always, I want.

To build something myself?

Well, I'd say like structure and planning is not my Strongest. So life has taken many strange paths. I've done a lot of different things before I did this. Right. But it's always been the thing that kept me passionate. Right. I always like the side project. And I think even though it seems like this field is just like happening right now, right. It's like now is where it's happening. It's not new. Right. I studied robotics and now electronics. I've been in the field for a long time and we used to build pretty good humanoids back in the day too. Not as good as we do now, but so I think it's more that like finally the technology is viable from a commercial point of view. And also a lot has happened on the AI side, but also on the hardware side, we finally have visibility on the goal here, right. We want to get to an abundance of artificial labor. That's our mission, that's what we're on. We're just moving it as fast as we can. And it's no longer this like incredibly visionary thing. It's actually something that's like. It's an engineering problem. Like we know what to do. It's a lot of work. And it starts with having these robots live and learn among us. Having them in our homes and documenting them into our families and having them part of society.

That's so fascinating. You know, a huge product. There's Eve and now Neo. And you just said it yourself, but with Meow and how you guys view the product, it's about being in the home. Why is that so important when it comes to a go to market of being in the home versus being in a factory and doing more maybe simple or more complex work?

Yeah, I think there's at least two angles. There's many, but there's two main angles to it. So we can start with a very simple one, which is there is nothing that scales as fast as consumer. Like if you think about like the PC, right? It took off because consumers started buying it. If you think about the most modern, best example is the iPhone, like smartphones, right? We got to a billion devices on the planet in just like decade. And this kind of adoption does not happen outside of consumer. And for these kind of like zero to one inventions where you really, really change how people's lives in general just work and function, you need your early adopters, like your evangelists, the people that cheer for you and help you make this happen. And that exists in the consumer market, not in enterprise. Now there's this other thing that is actually even more interesting, which is how we Learn, or I'd say how any creature learns, not just humans, but across the animal kingdom. And it is this beautiful correlation between diversity and intelligence. So if you just see the same thing over and over, you're not going to learn much. If you take this to the limit, it's pretty obvious. If I'm moving this from here to here all day, it's all I do. And I'm in a gray cell. I see nothing else. I was born here, I die here. That's all I ever did. My cognitive developments are going to be pretty bad. But this is actually kind of like true all the way to the limit, which is very interesting. So if you look at what drives intelligence across AI, it is directly proportional to the diversity. How many different things you've seen, how many different ways you've seen the same situations, different situations, all of these things. So there's this concept, there's this misconception that we get intelligence in AI models today because we have a large scale of data, the Internet, typically, and then we have a large scale of compute, and we get intelligence, but it's not actually true. We have a large diversity of data and large amounts of compute. But of course, if you've seen a hundred million things in a bunch of different ways, it is a large amount of data. But the large amount of data itself doesn't help. It actually kind of hurts you. You want as little data as possible with as much diversity as possible. And there's nothing that's more diverse than a home, right? Yeah. This is beautiful, chaotic thing you call life. I know I have two kids. It's pretty chaotic at home. But also, just like every home is different, every home is different every day. And I think something also incredibly interesting that people might not fully have realized yet is how much of our cognitive development comes from the social aspect. And living with these robots in your home, it is quite different. Right? Because when you think about, like, how work is social, like, if I have a coffee cup and it's empty, is it dirty, or do I want a refill, or do I generally keep my cup throughout the day, or, like, just going to the kitchen and getting me a Coke in the fridge for a robot, maybe my wife's there and, like, you need to navigate that social situation, but work is social. And it's just such an important aspect of intelligence and something that, of course, we really want our robots to learn. We want them to know these beautiful nuances of our life, like hold the door open for grandma and be careful around children and all these Things now.

That'S such an interesting perspective. I mean, especially with these robots being in the home. I know when I first saw Neo and the contents of you and your team put online it, you know, you may see human robots, but the intimacy of being in the home where you're like pouring your coffee, doing your laundry. I'm curious to know your perspective on the cognitive shift that needs to happen for this to be so accepted by consumers. Because I know myself having one, I would sign with that today. Right. But for some others, which obviously a lot, maybe it's my parenting, it took them a while to understand the iPhone, and there's a later stage adoption. I'm curious to know how you. What you view as the inflection point or has it already happened and then things are just catching up.

In terms of the acceptance, I think it's actually. This is surprisingly easy. So we've had a few voluntary and involuntary experiments up through the years. I think one of my favorite ones is actually way back in the day, and this was Eve, our previous humanoid. And we were between offices and we were in a WeWork, and we didn't have that much space in our office. We ran the robots in the hallway instead and in the WeWork. So there's other teams, other people, they're interacting and like for the first day, right, everyone's like, what the heck is going on here? And then day two was like, the secretary by the door is not even looking up when the robot is passing by, and people is like, kind of like nudging it to the side to get to the coffee machine. It's just like it's not there. It's like part of our wife. Like, humans are so adaptable. Now you touched on something else which is quite interesting. We're very adaptable, but not all of us are necessarily like that interested in learning new things. Or maybe, maybe we can't, maybe we won't. Like. Adoption of technology is generally often a barrier from a. From a skill perspective. But Humanoids is this beautiful interface that is just so natural and I think it's so nice that it can actually get us away from screens, get us away from keyboards, and bring us more back kind of like to the analog and the interpersonal and these kind of connections. So using a humanoid like Neo, where all you do is like, talk to it, tell it what you want to do, there is no, there's no adoption barrier. Just tell the robot what to do. And of course, there's work left to make sure that that always works as well. As it should. And that that's just like a seamless experience and all these things. But it's getting there. And I think once it really gets there, there's not going to be much of an adoption barrier because it's just how we interact.

Let me toast sense, especially like the WeWork example. Like you might know that you see it for first time, it's whoa. And then you just get, you adapt to it. And I'd be curious to know if, you know, for those that are watching this video or listening to this audio, if they haven't seen the video or understand the use case in your eyes, when it comes to a Neo humanoid at home, what are some of the things that humans should be thinking about in the future that, you know, the humanoid can do for them if they aren't familiar already?

Yeah. Let me start by being very practical, right? I'm just going to say like, okay, I have a robot at home. Yeah. And what does it do?

Yeah.

And that's. So there's two ways the product currently works because there's a lot left to do still on the intelligence. Some of it is progressing incredibly well, but we're not fully there yet. Right. There's some things we need to cover with humans. So there's kind of like what I call do my stuff thing. Okay. It's a bad name. We'll find it better. But that's what's happening now. Right? I'm here with you and the robot's at home. And I've just told it to today it's do my white laundry, vacuum, tidy a bit so you can vacuum. And there's a instacart package coming. So it receives it at the door and it unpacks it in the fridge. Wow. When I come home, this is done. Wow. It's happening today. It's happening now. Now, the robot isn't able to do all these things by itself. Sometimes the human needs to step in in what we call teleoperation, which basically is that someone is remote controlling the robot. Right? The robot tries to do something. Can't quite figure it out. Someone takes over and remote controls this task. But from my perspective, it doesn't really matter. I come home and all this is done. Yeah, yeah. But this is also one of them ways that the robot really learns. This is learning from expert demonstrations. Right. This is very similar to how we learn, except I wouldn't control your body, I would just show you how to do the task. But actually being able to control your body is even more efficient in how to teach you how to do the task. Now we have the auto mode, which is when I'm home. Then the robot operates in companion mode so you can speak to it. And it's just generally this great companion in life. And I think there is something really magical here. And I like, it's not a pet, but it's not probably human either. It's something else. And I kind of view it as my Hobbes. If you ever have Calvin Hobbes and it's going to be there all throughout your life, right? It's going to remember everything, the good and the bad and everything that happened to you. It's always on your side and it's part of your life. And you can just like tell it to sit next to you on the couch and like chat about life. Watch some Netflix. Yeah. Or you can ask it to go get your Coke in the fridge. If you do that today, about half the time it will come back with one. Okay. The other half you're like wait a minute, mold. We get it staring out the window and you're like, hey Neo, you're supposed to get me a Coke. And what's really interesting about that is that while doing that the robot actually learns. So this is how we have the robot live and learn among customers keep improving. So in the beginning now this product isn't for everyone, it is for early adopters. It's for the tech people out there that like don't have to be techie but like usually they are. They're like always dreamed of having this, right? And it is something that's going to some extent even redefine what it means to be human in that it changes what we value in humans. Right? Just like the industrial revolution changed us from valuing muscle power to intelligence, this is going to change what we value and getting to be part of that and getting to be part of like shifting humanity into where we're no longer constrained by labor.

At least here it's so fascinating you say that because now like having lived with my now wife, I got married four months ago for we've lived together for five years. And when you think about the at home dynamics of, you know, you're doing laundry or dishes and you're know, trading responsibilities, if that is delegated and you're just there the dynamic completely ships of layer what you're responsible for or just the, the idle time that maybe you were spending doing these, you know, chores around the house. And I love that you got practical of like and this is what it's doing today. And I'm curious to know, just like when someone experienced the iPhone for the first time, or, you know, Scott Abbott for the first time, you're obviously building this company, you're familiar with this product. What did you experience as a user when it was finally in your home? Did anything change from maybe what you thought it would, you know, how it would interact or how you would feel or what was that sort of first impression for you with it being your home?

So I'd say, first of all, the first robot I had in my home was the E robot. And this is years ago. So we've been doing these experiments for a long time before we started now moving towards commercial sns. And the first thing we realized was how important the dialogue was. Because first when we did this, we actually didn't have audio even all in the beginning, so the drawbox would just do the stuff. And we just figured out how incredibly awkward it was to have this thing doing things next to you. You can't talk to it. And it's just like, it did not work. It was like, okay, we need to get that thing now. We need to get that done. So that helped a lot. And then it teaches you some humility and how hard most things are around the house, how hard it is to do these tasks and how incredible humans are. Because the first product we had with Eve, right, it had a wheeled base, so it was still very capable as a humanoid. And it was balancing, could sit down on his knee, two arms, all these things. But, man, there were so many things we couldn't do in the house. We're like, okay, we're not going to beat biology here. We can't simplify. We actually need to build something that is, as a human, if we're going to kind of brownfield deploy across our society, then it needs to be as a human. And I think this is like a double blessing because first of all, it allows you to do all this work. But secondly, it actually greatly simplifies the task of transferring knowledge from humans into the machine. And we want these machines to again, back to all these nuances in life, right? But just incredible. Just like, in general, be very good learners so we can easily instruct them what to do.

Absolutely. There's so many directions I want to go in this conversation, but I do want to take a step back because I know in the early days of the company, you would think about, know, why has this failed in the past? And thinking through cost and efficiency. And now what I believe you talked about is just like Vertical integration of the product. How has that become more important since the early days of having, you know, being vertically integrated and understanding unit economics, especially for something, as we talked about before we started, it's very capital intensive, you know, this industry, to build this, to make it work. What have you learned from the early days of all these different key points here?

Well, I think maybe one thing you didn't mention, which I would say is from day one, something we thought about, but that has been even more important than we initially thought, is safety. Like, if you're going to have these humanoids living among us, they need to be safe. And that means you actually need to design, from a first principle point of view, a system that is safe, meaning if things go wrong, can this actually severely hurt the human? And that's been, I think, maybe the hardest engineering task to design NEO in a manner where, just like us, right, it's soft, but not just that it's soft, it's very light and it's very low energy. And that last one is a bit technical from like a physics first principles point of view. But what a lot of people don't know is that generally in robotics we have these systems which are very heavily geared because we want the robots to be strong. So we have a high speed motor and we gear it down so motor spins super fast. The joint moves very slow, it's very strong. This means whenever that hits or touches something, this thing that is spinning at 10,000 rpm needs to stop immediately, which it can't do. So you get this. Even though the robot isn't very strong, it's just very high energy and dangerous humans don't work like this at all. Like if we were really in a hurry in the morning and we're running to each other around the corner, it's probably painful, it's probably awkward, we're welcome to die, right? So, like, we want to design machines that have these same kind of dynamics that animals and humans exhibit. And you can see this when you see how our robots move, that just, it looks way more natural. And that's because that's what nature does. It minimizes energy, right, Calories spent to achieve your task. And if you do a really good job on this, you can actually design robots that are largely safe, irrespective of software. And I think that's something we just have a responsibility to do because we're going to roll this out in society at large and we want to minimize the amount of harm that can happen. Now, cost talked about is of course, essential. I like often to use like computers as an analogy here, because these kind of devices that are kind of, they're general units of work, they only make sense at scale. And it doesn't matter whether it's a car or a computer or a phone or like whatever it is. Like if you make a few, which always happens first, then it's niche and it's for something special. It's very expensive and generally doesn't make that much sense. Now when you get to scale, it just becomes this incredible tool that is the most efficient, most reliable way of doing almost anything. Right. Your phone is the best camera, generally there are some better. But generally it's also the gps, it's the telephone, it's your browsing device. It's like it's all of these things in one. And if you think about the complexity of the device, you couldn't really defend it unless you used all of them. Or like when you write a document on your computer in Word and you're like, that's one heck of a complicated typewriter. Right. Think about what humanity went through. We create like nanometer level chips for you to be able to write. Right. It's not the most efficient way to write a document, but it's still the cheapest, most reliable way to write a document because it has such a scale. And humanoids is this. And you just dial it to 11. Right. Because it's general labor. And that only makes sense if it's more cost effective than the specialized labor. And that only happens if you have scale. And the only way you get to scale is to get Costa. So cost is just super important. And of course no one's going to buy a hundred thousand dollar humanoid for the home. Right. That just does not work. Yeah. Or maybe, yes, you're out here. Okay. But you're not going to get to Kia. You're not going to get to see all.

Yeah.

And it needs to be capable. Right. Like if you have something that's safe and very affordable, but it's not capable, then you have a toy.

Yeah.

Like that's, that's a different market. So like it actually has to be able to do the work. And we've worked really hard on ensuring that this robot can do almost anything that a human can. There's a few things it can't do that humans can, but it's very few. Right. Yeah. This is coming back to like how magical humans.

Yeah, no, absolutely. And you know, there's on that note of being capable, at what point do you, the team or humans that want it to not be capable of, like, you know, this. There's a little dialogue, and I think it's. Some people may see humanoids as scary or, oh, my gosh, having one of my home is maybe interesting, and you have to really understand how it's helping you. But in your perspective, when you think about the future of humanoids, you talk a lot about. I heard you talk about in different interview how, you know, 2025, you want to make thousands of humanoids and you want to tax every year in the sense of tens of thousands in 2026, hundreds of thousands, 2027, and millions, you know, into the 2000-30s. When it comes to scaling to that capability, like, where do you see this going in terms of. I don't want to say the. Like the fears, but, you know, and I'm for context. Right. I just got married. You think about having kids in the element, two, three years. Like, do you want a humanoid rocking your baby? That's what I'm trying to think about, of where this is going, how you view it in the home, in these intimate moments that are safe, that are practical and that are capable presents.

Well, first of all, I want you to have humanoids in your home so you can spend time rocking your baby. I think that's a very human thing and not something we want machines to do irrespective of safety. Now, we also don't want to rock a baby from safety perspectives, but, I mean, the way we're working about this now, we're trying to be very cautious with respect to safety. So there are things we don't do in the beginning. We will do them in the long term, but not in the beginning. Cooking. Right. Can't wait for my robot to cook. But we're not going to ship that in the beginning, because no matter how safe your robot is. Yeah, no matter how safe your robot is, if it has, like, a kettle of boiling water, it's not safe anymore.

Right.

So you want to make sure you avoid dangerous objects in the beginning and then ensure you really, like, gradually roll this out the test and ensure, like, again, like, should have really good safety metrics before you approach these things. Now, I do think, like, with respect to how society evolves, it's really interesting that these kind of technologies, to me, they're not about removing from people, they're about giving. Because I don't think the value we put on humans should be tied to the mechanical labor you can carry out. Right. That's not. That defines who you are. And there's A lot of tasks that I really wish we could spend more time on. Right. Like taking care of each other and all of the mechanical stuff that needs to happen around that. I don't think that's something we should do. I also think it's going to have a pretty huge role with respect to just in general loneliness, companionship. And this is kind of like almost epidemic across society, right?

Absolutely.

And it doesn't replace humans in no manner. Neither does it for companionship, but it kind of adds to it. And like I said, like a dog also adds to that, but it doesn't replace a person. And this isn't the dog, it's something else. But it does add to it. And I think that's some of the magic that I'm really looking forward to. And then in the long term. Right. It's hopefully going to shift everyone from thinking what they have to do to what they want to do. I think that's generally a good thing.

Absolutely. It's so fascinating. And even tying the. The humanoid. But also just this, this wave of AI going on and OpenAI invested in one Adsen 2022. And you know, you think about robots being mechanical and doing labor versus them, like being intelligent and being able to learn from tasks that. And how has the last couple of years with OpenAI, these large language models impacted your view on humanoids, where they're going and what they can be capable of long term? Just how has the last two, three years been for you and for the company? When it comes to this way that's happening right now.

It'S kind of like following a parallel path. It's not the same thing. So, like, the relationship with OpenAI has been very good and we exchanged a lot of notes, but we don't necessarily work on the same problems. Right? Yeah. So we train our own foundation. Foundation models are for robotics. Now. What's very interesting about this is that we're seeing that now that we get towards agentic behavior, which is what everyone is working on now in AI.

Yeah.

The data from Humanoids is actually way more useful than the data from the Internet because this is actually agents. It's agents in the real world. And everyone talks a lot about what we call verifiable problems. So say think about math or coding, where you can like run an experiment and then you, you actually have the answer. So you can check the answer. So that means you can have your model learn whether or not got the right answer. Try again. It can learn. Right. And we even have. And we actually have this in Normal English language. We call it grounding. You want to ground your experiments, it's because it's literal ground and robots actually allow you to ground everything, right? That's how we verify all of our hypothesis. So you robots allow you to move out of this paradigm where like there's a very small subset of problems that you can apply reinforcement learning to, to where you can apply reinforcement learning on kind of like anything. And that's how we humans learn. And we do have some pretty interesting results where we're starting to see kind of early day breadcrumbs of some unique results that you would not see without robots when it comes to intelligence. And I'm pretty, I have a lot, I have a lot of conviction that like you're not going to get to AGI without having robots. And it's going to play a very central role.

Why do you think that.

There'S so much of our intelligence that actually comes from interacting with the world? Like how much of our understanding of the world that comes from interacting with the world. And also trying to think about how to say this simply, it's a bit of a deep rabbit hole. But you know, when you learn something, generally what you do is that you have some mental model of things and then you say, I'm going to take some action, I'm going to do something and I hope this will end up in some result that I wanted. And then you do that and you see if the result actually was what you wanted, scientific method would be like, you have a hypothesis, you carry out your experiment, you observe the result. The Internet just has the result. You don't actually know, like the one who came up with this line of text or the person that moved in this video on YouTube or whatever, what was that person thinking? What was the action they were trying to take? What was their assumptions for what they did? Like, you don't have this with robots, you actually have this. And this is how we learn and we see that, like there's like clear evidence that at least part of our reasoning naturally appears in this process. And another thing that people might not fully have caught onto yet is we think of like the Internet as this enormous thing, right? Like the Internet is so big, the it's going to be like decades till we have data that is even remotely as large as Internet when it comes to robotics. But this is actually not true, not at all. This is like if you look at the plants you just talked about, we're out scaling, we're just a couple of years away from having data which Starts to get to the same amount of information that's added to the Internet every day. So that actually happened.

Millions.

The humanoids in homes learning in the real world. Yeah. It's more data. Wow. So you will be training on that instead of the Internet. And of course that data is. It contains a lot more information, right? Yeah. It's touch, it's audio, it's what you're seeing, it's what you're feeling. Back to what I said about like, hey, why did you do what you do? What did the result in? Yeah. And it's part of all of our life.

That's so fascinating. Even hearing you think through and articulate AGI and humanoids in the home and how you think about things. For you personally, what's been in moments that you can reflect on over the last five, 10 years where maybe now the Neo, maybe it was Eve where you were surprised by what you saw. Even knowing everything you know about the product and obviously you know what these are capable of.

I think maybe the first time I saw the robot fail at something and then figure it out.

That's crazy.

Yeah. Like trying to open a cabinet and like failing and then, oh, there, I got it.

Yeah.

And this is. You can just like start interpolating for now. Like, where does this go? Right. Like, it's because you see this kind of like ability for self improvement. And that brings us back to something else that I think is quite unique about what we're building with nio from the safety aspect. Because when we talk about safety and robot being soft and no energy, it's not just about safety for people, it's also safety to the robot and safety to your home. Right. So being able to kind of explore, experiment and learn and your robot should not break, but also it shouldn't damage your door. Right. If the robot is trying to figure out how to open your door, you can try a few times and then figure it out. And we do this all the time. We don't even think about it. Right. We're just like, oh, that kind of door. Right. And like, this is actually a surprisingly hard problem for robots to be able to explore like this without breaking. Yeah.

See, see, these are like, these are thought patterns that I think especially myself, but I would assume the general population, you don't even think about like the human nature that goes into learning. You might know it and understand it, but seeing that in a robotic format, it's like you, you, you have to kind of detach yourself from what you know to then understand like what these Robots do need to learn and they need to go through that quote unquote human like experience to come have that pattern recognition.

Yeah. If you look at nature, right. There's just like all of these kind of soft squishy things that try to learn because that's the safe way to explore and learn. You don't find kind of like hard, more industrial type animals above water. Interestingly enough, if you go below water where everything moves like really slow, then you have some. Right. Like crabs, et cetera, are built more like an industrial robot. But above water where like kind of fast dynamics dominate, you don't see any kind of creatures like this because it's just so fundamental to intelligence that you need to be able to safely explore.

Yeah, absolutely. So just to boot the conversation a little bit, you know, as I mentioned before, we were talking a lot about the robot itself, but from a company perspective, I've interviewed dozen hardware founders and know the, the saying hardware is hard. And you know, in the early days of building 1X, when you're raising capital, you know, getting backers, what were some of the most challenging parts for you and the team to get backers for this and especially to go execute it? From the onset.

I mean everything was hard. What do I pick? I think hardware is hard, but I don't think hardware is hard mainly due to the capital. Like that's part of it. I think hardware is hard just in general because it's. The physical world is really messing and if you don't really work with trying to kind of like work on that, it's very hard to understand like how messy it is and how much can go wrong and how long things take. Right. It's like this iteration cycle on hardware compared to software. It's just, it's such a different beast and the cost of mistakes and then planning ahead. Like you, you know the direction that I chose 10 years ago for the hardware where I said kind of like, okay, we're not going to build these kind of classical robot systems because I know that doesn't work because I've seen all these robots before try to do this. It works in a factory, but it doesn't work in like unstructured environments. Like a whole. Yeah, yeah. We need to build something that's low energy and compliant and kind of like a human. So we made some choices. They stand today and we've spent a decade now on refining those choices and now we're moving it into large scale manufacturing. If those choices were on, we would have to go back a. Yeah. And These are like fundamental, like we don't use gears in our robots, we use tens, loosely inspired by muscle. If we had chosen to go for a gear based solution instead, like we would have spent a decade on the wrong problem. Right. So. And like these kind of things in hardware is just incredibly hard. Now of course, if you want to make it even harder, you do, you, you really invite this to yourself. Then you do it on something like humanoids. That has never really been done at scale before because then no supply chain exists. Yeah, right, yeah. So you get this choice. You can go and like pick components from existing products and put it together and call it a humanoid. There's a lot of companies doing that. Then generally you end up with something which is this kind of like stiff, heavy, dangerous industrial machine, because that's what exists. That's like industrial robots put together in humanoid form. Or you have to kind of develop your entire supply chain by yourself. You have to figure out like all of the manufacturing, all of the automation, all of the processes and really build that out. And that takes a long time. Right. So when I say we're a vertically integrated company, like some would say we're like stupidly pretty integrated. We have everything from special alloys for die casting aluminum, all the way off to foundation models in AI. Right. I don't think you find a company that's more vertically integrated on the planet.

Yes.

And takes a long time and requires a lot of capital. But in the end it also makes it probably the most exciting problem to work on because you just get to work with so many smart people across such a huge variety of domains in science.

Absolutely. It also seems that the market opportunity is so vast and I've heard you have these different statistics around how many humanoids may be on the planet in 10, 15, 20 years. What is your prediction on that? When you think about 20, 50, 20, 35, 10 years from now in terms of scale, in terms of adoption, how should people think about this? I think your perspective on this would.

Be great to hear. This is really interesting to do the math on this. So I think I can answer like in the end and then go backwards. So there will be more humanoids on the planet than there are people. There's absolutely no doubt about that. Because at least everyone wants a humanoid. But you won't weigh more than that because it's general artificial labor. Right. If you remove the constraint of labor in society, it has some pretty cool downstream effects. Right. Like sustainability. That's just a given. Right. Why would you do anything in any manner that is not sustainable. You don't have to cut corners. You have infinite labor. And you say infinite labor, but there's never infinite. Right. Because you need to produce them, you need energy, all these things. But corners. The robots can go and build more power plants, they can build factories. Right. You actually have infinite labor. I think it's really hard to look into the crystal ball and say, how does society look post that. I am very much a techno optimist, though, and I think it's going to be a beautiful world and it's going to enable us to do such amazing things together with machines. Absolutely. And I do hope we get to a future where we have humanoids not just doing laundry, but building particle accelerators, doing experiments in labs across the globe and figuring out the fundamentals of science. And then if you back it up from that, there are some things that has to happen. Like you need to have robots building robots.

Because that's fascinating.

If you're going to build 8 billion robots, you literally run out of labor. Right. It's like iPhone or Apple kind of ran out of labor during scaling. They were shifting large demographies of people in China across the country to try to satisfy labor demand to scale and had to move into like other countries in the region because they ran out of labor. Yeah, that's crazy. And that's phones. Yeah. And it takes. It's not like you can design a very good humanoid like we do. And it's not that complicated to assemble, but it's still significantly more work than a phone. Right. So you need to do that. And then you need to think about, okay, do we have enough aluminium? We actually do have enough aluminum, but it will be pretty impactful in aluminum. We don't have enough copper, we don't have enough magnets. So we need to do mining, we need to do refinement. We don't have close to enough chips. We need to build chip fabs. So there's a lot of this infrastructure things that has to happen. But I do think that will happen increasingly fast as you roll in more and more artificial labor into the mix as you build up.

That's so fascinating to think about more humanoids than humans. You know, as someone that I'm also very much so techno optimist, I think it's hard to not think about, you know, with anything like downstream effects. Right. Where even, you know, you look at iPhone and how many good things, but also creates things that are maybe addiction, maybe too reliant on it, in your opinion.

We're.

I want to Call down on like things you fear or things that it could be affected in terms of society. But how do you think about that? Like the downside in any fashion of society, the world, when it comes to having more humanoids than humans, they're going to take away a lot of this human experience, more or less that we have recognized for all humanity until now.

This inflection point in time.

Yeah.

I think it is a real issue now. The good news is that I think it's a local issue in that it's a one generation issue. If you look at smartphones, Right. My daughter, she never knows where her phone is and you see this tendency now of people having these clamshell phones, kids instead of having smartphones, not because they're getting forced to, but just because they don't want to be part of that.

Yeah.

They've like seen their parents go around. It's all we were the same with our parents. Right. I'm not going to be like you, I'm going to be better. So I do think like society has a tendency to fix this and then you're just left with the upside. Right. And for smartphones, I mean think about the access to information. Right. Like all over the globe. People like being able to take an education online on this cheap device communication. Like how much it connects us across borders and teaches us that we're all kind of at the core, we're the same. Right. I think the same will happen here. But I do think we want to really work hard on minimizing the short term pains. But generally technology always moves society forward and everyone's standard of living just goes really high. And again this is, it is the same, it's just turned to 11. Right. But yeah, it's. And it isn't as, it's not as alien as you would think. Like when you talk about like more robots than people on the planet, we're pretty close to having more smartphones than people on the planet.

Yeah.

And it's not that long ago since they started scaling that. So like this is doable. Right. But it will have a huge impact and hope we can do a good job so that that impact is incredibly positive across society from the get go. And then I'm very confident that in the long term of course this will help with so many of the challenges that we have today as a species.

Yeah.

Nice.

I love what you said around and like the one generational challenge and I look at my nine year old niece who's, she doesn't know anything besides. Oh yeah, like I've heard of, you know, Facebook and mom and dad talking about that and the, the information, it's fascinating to think about is like, you know, our kids, children, how, how they will perceive humanoids, you know, and, and they're growing up and how it impacts them so very God saving.

And, and even before you go there, I'm actually like, I'm super curious about that but I'm also super curious about something that's way closer which is how will generally like our customers perceive humanoids because we have worked with them for a long time. So when we have like we're testing them in employee homes, right? Yeah, absolutely. And we have our use cases of think like this is. Oh, this is how it works. Like this is great. I think as we start to expand to what I call like real customers, we'll learn so much and that's going.

To be so exciting when in the m. Fascinating. For someone that's watching this or for someone like myself, when could they expect to be able to have a humanoid on their own doing these function for that.

There will be some in 2025, so this year that's amazing. But for most people I'd say next year. Wow. Yeah, that is exciting. It's coming. Yeah, it's coming really soon. And again like expectation management here is absolutely not going to be perfect. This is super early. Yeah. But it's going to be a lot of fun and it's going to be useful. Absolutely. And I think a lot of people will enjoy the journey.

I'll say Roxanne, I'm very excited for it even too. I remember when we were in the process of setting up this interview, I was on a family beach trip a couple of weeks ago and I'm showing my uncle who is very tech forward. I shown the 1x website and sharing with him but prior to me showing it he probably had really comprehended okay humanoid and, and he lit up and he, you know, at first like oh, that's scary losing weight. Like I wouldn't have to do X, Y and Z. Like healthy. Super helpful. And I think once you get to that standpoint and then once it's, once your friend has one you're, you know, it becomes more standardized as you said. You know, we were walking down the hallway. It maybe makes you turn your head.

To a couple days in a row.

Then it's just there.

I think it's maybe the most sticky product ever because I promise you that once you don't have to do your own laundry, tidying or cleaning or like Any of these things, you don't go back. Yeah, but pennies, the dependency of it.

Being done and then if you were.

To remove it, how you feel when you go to the cabin or whatever. I have a cabin where we don't have a dishwasher. And whenever I'm there I'm like, oh, man, it's like going back is hard.

That's fascinating. And, you know. Two more questions before we wrap up here. If you go in some direction, this conversation has been super valuable to me and I hope so for the listeners as well. When you think about the future of humanoids in the home, we've covered a lot of ground today, but what excites you the most when it comes to the applications in everyday life and even those outside of tech that aren't maybe East Tecnologia Optimist. What would you think would excite the world to really bring these into their own, into their environments?

I think it's the connection between human, when, between like man and machine. I think it's living with this other artificial being that more and more like, understands you as it learns about you and how you kind of bond with this through not just talking to it, but doing things together. There's something special about, like, doing things together. Right. That brings us closer and I think it's the first time we really do that with a machine. Yeah, that's fascinating.

And last question. You know, we talk a lot about in the early part of this interview, like growing up in Norway, wanted to know you knew you wanted to do this as a young child. What would the 11 year old version of you think about, you know, what have you created in the world today and what would you tell your inner self to see how far you've come today in the term of doing it to the company where humanoids have moved.

They would be very happy, like where it ended up. And I don't know if there's that much more that could have done better, to be honest. Well, dang, no, but I'm like, I'm just incredibly lucky. I mean, and it's not just about skill. It's like born 10 years earlier, it would have been too early. Born 10 years later, it would have been too late. And it's just like all of these, like, things around you that is basically just luck, right. That comes together and you get to do your dream. And I think, yeah, I just want to be thankful, be, be along for the ride. And there's, there's decades left of work to do and I can't wait.

It's a beautiful vision and just passion there. So before we wrap up, I know you mentioned people viewers could possibly have these in their homes the next handful of years. Where's the best place for everyone to just really stay in touch with everything that you and 1x are doing? And where's the best place to just follow along the journey?

Follow along on X. I mean, our website is great, but if you want to stay up to date, follow us on X. And we, we kind of like, to large extent, we like to build in public. Right. We've been pretty transparent and open with what we do and I think we want to continue to do that and hope everyone follows along and enjoys the ride.

You guys have had such a cultural zeitgeist with a lot of the cool integrations, streamers, kaisernademy people. So it's really cool to be able to really sit down and understand it. And I think that people listening and watching. If you made it this far, I hope you can appreciate just behind the humanoid right. What you and the team have and so knit in what they can expect. I know I've learned so much. So thank you so much for taking the time to come to show today. I really appreciate it.

That's amazing. Thank you for all the good questions. Thank you.