Utopia or Dystopia? Humanoid Robot NEO Has Arrived at Our Home | 1X, Bernt Børnich

1. 0:00 – 2:00

   Intro

   1. UHUnknown Host0:00

      So I think accepting failure and having that as part of a culture is incredibly important, because if, if not, you're not innovating, right? Most of the things you do that has never been done before will just be plain out wrong. In hindsight, it might not just be plain wrong, it might be, like, borderline stupid or, like, how did we ever think this was gonna work? But that's, that's just the nature of the game. That's, that's how innovation works. I think the only thing that's not acceptable from a culture point of view is you didn't really try, you didn't give it everything you had, or you didn't actually reflect over why did it fail so you can learn. It is how we make progress. Can you do this under pressure? Can you keep this culture where failure is okay even when there's pressure? And if you manage to do that, then you get great innovation. Focus on the things that make you happy. It's gonna be a long journey, and if you're not having fun, you're not gonna make it. There's this notion of, like, being a founder is, like, grind, grind, grind, and it is, and it's gonna be a lot of grind, and it's gonna be a lot of dark days, but there has to be also a lot of fun to make it worth it. The best cheat code I have is pick a problem that really excites people. We do humanoid robots. It's really freaking cool. [upbeat music] Thanks, NEO. So my name's Bernt Børnich. I'm the founder of 1X, and we make humanoid robots for the home. We thought about it for a long time. We just got really annoyed that everyone was posting robotic videos online with, like, 4X, 5X, 6X speed because robots generally don't move naturally, don't, don't move at human speeds. We just thought it was really funny, like, let's make sure, like, in every frame, there's a 1X. And our mission is to create an abundance of labor through these intelligent machines, how life will be when you actually have a humanoid in your home and you can really focus on enjoying the time we spend together, right, and the things that make us human.

2. 2:00 – 5:45

   When a Humanoid Robot Becomes Your Roommate

   1. UHUnknown Host2:03

      When I was a small kid, I got ahold of my first computer. It kinda, like, clicked, right, and that was really magical to me. You can write some code, and you can have something else move in the physical world. You can combine these two. As I kinda started looking at everything around me and, like, how, how things that move very efficiently get things done and, like, how much the physical world matters, I decided I wanna make humanoid robots. I got really inspired by Honda ASIMO back in the day. The most magical thing about ASIMO was the interactions with people. It wasn't an industrial automation system. This was actually kinda straight out of Star Wars, right? It's this humanoid robot that can walk around, run around, hand you a bottle of water, and make sure that all these chores we don't wanna do every day, like, we don't need to do them. We can have robots for this, right? That's really what also motivated me when I started 1X, just look at why did ASIMO actually fail. So if you look at ASIMO, they followed what I would call, like, the classical robotics regime, the same as we see mostly in factories and work cells of how you build this, and it's not really inspired by nature and how we humans are built and how we humans move. This made it very hard for them to actually be able to do useful things outside of the lab because the system they built really had, had to make a lot of assumptions about the environment, which doesn't work in the real world, right? Because in this creative chaos around us in everyday life, that is where so much of our intelligence comes from and our lessons learned, you cannot really make that many assumptions. Things change all the time. We have to make it safe. We make... have to make it affordable, but it can't be a toy. It actually has to do the work. It has to be very useful, 'cause if we want these machines to be truly intelligent, also if we want these machines to behave in a manner where they're aligned with us, they have to live and learn among us. So 1X was started about 10 years ago now. Really, it started out from the perspective of how can we make humanoid robots that can actually have a real impact on the world. Norway was very good in the beginning. We had very little attention. We were all by ourselves. It was just a group of people coming together, spending every waking hour figuring out how to solve the pro- solve the problem. We moved a lot of talent over to Norway. The field at that point was very small. Thinking about, like, who was, like, really the best people in humanoid robotics back in, like, 2015, 2016, right? It wasn't that many people. I remember still when, like, on the Humanoid Robotics Conference, we could, like, fit everyone in one room. This created this kinda, like, very exciting ecosystem where everyone was basically almost living together and just living and breathing this problem, really became this great group of friends that just went on this adventure together. We were very early in this space. There weren't that many believers. It's always challenging to raise money. The space isn't really something people believe in yet. Around, like, 2017, I would say, is where we struggled the most. We actually had fundraising locked in. We were one signature away from wiring money, and then COVID hit, and that's probably the most painful thing I've done as, uh, as a founder. So we went down to half the number of people to get through COVID, because, of course, in the beginning of COVID, there was no raising money. Everyone was just sitting on the fence figuring out how, what happens now. And of course, these were, like, people who had moved to Norway to be part of this, like, giving up everything they had and, like, they wanna be part of this dream, and they were all in, right? And having to let go of these people are, of course, extremely, extremely painful. There are two ways we lose, right? Either we lose velocity or we run out of money, and those are the two things we need to make sure never happens. The first year was really about proving out can this be done, really laying the foundations for a new paradigm in how we design robots. We decided to go in a new direction, right, a different paradigm in robotics. It's not that no one has ever done tendon drive systems before or, like, cable drives, but no one has really worked deeply enough and long enough on the problem to make it work. It's not easy to catch up because you need to sink a lot of work into this to make it work. It's also pretty exciting because it gives you a real moat.

3. 5:45 – 9:54

   Why Building Humanoids Is a Whole New Level

   1. UHUnknown Host5:45

      If there's a lot of energy when I move, then when I step on the ground, there will be a huge impact, and this will disturb me. It will disturb the ground. Like, it's not a good idea. So you wanna make sure there's as little energy as in this as possible. It actually just comes back to kinetic energy. We have a very good intuition for this. We learn this in school. If a car moves- Twice as fast is not twice as dangerous, it's four times as dangerous because it follows the square. And this is also true for robotics. So if you think about the traditional industrial robots, they typically have gears that are about 100 to one gear ratio. So like if your arm is moving like this, something inside here is spinning 100 times faster, and there's just an enormous amount of energy in that rotation. So you can think about it, something here spinning at 20,000 RPM, and then when your arm hits something, this needs to immediately stop. There's no way it can immediately stop. It's going like at a blazing speed, right? It can't immediately stop. And everything we do when we interact with the world is collisions, right? Whether we're taking a step or whether I'm just touching my, my watch or whether I'm picking something up, it's all collisions. And the way this is typically solved in factories is that you know exactly where things are. So you will see the robot move and it will kinda stop just before it touches the world, because it needs to touch the world very slowly. And this works amazingly in factories and has kind of been the groundwork for, like, robotics working well over the last 60 years. But if you're in a home or in a garden or whatever, you don't have a calibrated factory, so you don't know exactly when to stop, and that's why we need these very low energy systems that can be safe, both with respect to people but also with respect to itself and the world. You don't want your robot to damage your furniture, right? And of course, you don't want the robot to hurt you. But if robots are gonna be able to live and learn among us, they need to be able to explore in the world. They need to be able to learn through trial and error, and that means you just... You need to be very low energy. You need to be soft, you need to be compliant. And humans are just an amazing example of this. When we did the early first deployments years ago, right, and we tried this out in homes, the thing that really struck us very early was how almost everything you do is social. So even just getting something in the fridge is a social act, because likely there's someone in the kitchen, and now you need to clearly kinda communicate your intent. I'm going to go to the fridge and open it, make sure you're not in the way, make sure you do this in a safe manner, and you can't really separate these two problems. Like, any kinda labor that you do among people is kinda social labor. Really, intelligence comes from diversity. That was a great insight that we had pretty early on. When you flip the light switch in the morning, there's light, and if not, you're pretty annoyed. Because humanity has mastered energy for practical purposes in everyday life, it's just abundant. And this same thing is going to now happen to physical labor, and this is really needed because there's not enough people getting born. We don't have enough people to take care of our elderly, and we see, like, prices of goods and services increasing. Everything is inherently limited by our ability to effectively serve labor. The question then becomes how do we get there as quickly as possible? So most of the humanoid robotics companies you see today, they are more component integrators buying off the shelf and integrating into a system. And this in itself is pretty hard. But the journey we set out on here with the tendon drives and our unique motors and everything else, this means that we have to do everything ourselves because these components don't exist. So we spent the last 10 years, right, building not only the foundational technology, but also actually the machines that can build these components and automation equipment and everything needed to build the factory. It's going to be extremely challenging because manufacturing always is, but we've done a very good job in simplifying the product. Make sure you don't have anything that requires special alloys. Make sure your product is very light, so you don't need that much material. Just simplify, simplify, simplify, minimize part count. Through this, reduce this from something that has the complexity of a car to something that gets closer to having the complexity of, let's say, uh, say, like some kind of electrical appliance in your house, right? And the way we do that is just building it all ourself, having our engineers sit in the factory, make sure design, manufacturing, automation, everyone's in one room, really create a very, very efficient process. This is

4. 9:54 – 11:43

   In This Industry, Failure Comes First

   1. UHUnknown Host9:54

      back in 2018. I was at a stage and this was the old robot, Eve, was one of the first prototypes we had, and we were opening this health conference where we were talking about robots in healthcare in the long term. And I'm standing on the stage together with my robot and exactly well-timed as I say, "Safe," the robot decides to accelerate backwards, hit the wall, and then face plant next to me, bring with it, like, all the balloons that was in the back and just, it just looked like it had a really rough night, like sleeping in the balloons. I screw a lot of these things up through the years. Things don't always go the way you planned. So I think accepting failure and having that as part of a culture is incredibly important because if, if not, you're not innovating, right? Most of the things you do that has never been done before will just be plain out wrong. In hindsight, it might not just be plain wrong, it might be, like, borderline stupid or like, how did we ever think this was gonna work, a- as you get more knowledge, but that's, that's just the nature of the game. That's, that's how innovation works. So I think first of all, like foster a culture where failure is okay. I think the only thing that's not acceptable from a culture point of view is you didn't really try, you didn't give it everything you had, or you didn't actually reflect over why did it fail so you can learn. If you give it everything you have and you learn from your failures, then you should embrace and celebrate failure, right? It is how we make progress. This is hard to do actually. It's, it sounds like it's the cliché, right? I mean, it sounds like something that should be pretty straightforward, but of course, we're under a lot of pressure to make this happen and we need to deliver. We have timelines, we have schedules, we need to hit our manufacturing milestones. That's really where the importance of this comes in. Can you do this under pressure? Can you keep this culture where failure is okay even when there's pressure? And if you manage to do that, then you get great innovation.

5. 11:43 – 12:43

   How Robots Learn

   1. UHUnknown Host11:43

      Let me go through, like, how does the robot learn in general? How does it actually work? It begs the question, how do you get to a system that's intelligent enough that when you ask it to go and get a Coke in the fridge, it at least manages to do it sometimes, and we need to bootstrap. So you start with internet data, of course, because we have a lot of it. Then you have some synthetic simulated data, and then you need some robot data. And to get that robot data, we typically use teleoperation. So that means we have a human that actually embodies the robot, and you see through the eyes of a robot, and a robot moves like you move, and it's a pretty magical experience. It's kinda like, "Hey, my hands are somewhere else, and I can do something anywhere in the world." And it's a very nice way of transferring knowledge from a human into a machine. And once you have a bit of this, you're now able to do these tasks autonomously, and from there, you can kinda, like, iterate on it and learn from the real world. In the end, it's about having enough of these robots in, out in the real world, learning from just trying things. You have to be able to experiment. You have some hypothesis about how to do something. You try. You see how it went, and you try again. That's how we learn, right?

6. 12:43 – 14:21

   Build Before the Market Exists

   1. UHUnknown Host12:44

      Traditionally, scale does not happen first in enterprise, and this might be slightly surprising, but if you look at the history of highly innovative products, they almost never happen in enterprise first. They happen in consumer, and this is just because enterprise is risk-averse, and there are just too much red tape and barriers, right? From IT departments to labor unions to risk-averse CEOs, it just takes a lot of time, while if you have a good product-market fit, nothing scales the way consumer adoption does. This is true for a lot of products. There's a very good example of this is ChatGPT and the rollout of digital AI. OpenAI really tried an enterprise for a long time, and they couldn't really get it working, and then they released ChatGPT to see what people do with it, and people figure out this incredible diverse set of, like, tasks they can do with this tool, and they bring it to work. And now you would think that then finally you succeeded, but you don't. Now enterprise actually says, "No, no, you can't use this here. This is new and dangerous. We can't do this." After a while, people actually get so annoyed that they kinda say, "Oh, if I can't use it here, I'll go work somewhere else where I can use it because this tool makes me so productive." And now we've created so much bottom-up pressure that you're forcing adoption, and now you can start top-down and do great in enterprise. But you have to create that forced adoption through bottom-up pressure. Humanoid robotics is no different. If you wanna do this in the next few years, not in the next few decades, you have to go through consumers. You have to find your early adopters and your true believers that can really help you push this forward and be part of this journey. Then, of course, it will be used in enterprise because it's gonna greatly improve your productivity, but it has to happen in consumer first. If you run

7. 14:21 – 16:00

   Lessons for Deep Tech Founders

   1. UHUnknown Host14:21

      a deep tech company, you're not really sitting that close to your customers in the beginning. You're trying to f- solve this fundamental problem, that if you solve it, your market is there. It's like if you cure cancer, you're not wondering whether or not people will actually buy your product. And if you figure out a way to take energy and turn it into any kind of labor, any kind of product and service, clearly your market will be there. It's more a question of: Can you actually solve the problem? And of course, you get into product-market fit questions once you start to deploy this and how you make it, like, gradually useful because the problem you're working on is such a big problem that you can't really just say, like, "I'm gonna just sit here in my lab and work on this for 10 years, and then I'm gonna go out and, like, launch this product." First of all, you of course want it to be aligned with humans and how we want our robots to behave aro- a- around us. But also, of course, you need to show it's useful. You need to create revenue. You need to build a business because this is a really long journey. But fundamentally, it is a deep tech-type journey, where it's more about solving the problem than really ensuring you sit close to your customers. And once you solve the problem, then you can start caring about how all those small details start, right? That takes this from being just a solution technically to something that's, like, packaged as a great product. We are just starting. Already this year, hopefully, we're gonna have something that is very useful. But in the next few years, this will change the way we live. Focus on the things that make you happy because it's gonna be a long journey, and if you're not having fun, you're not gonna make it. And I think that, that's, that's undervalued, right, because there's, there's this notion of,

8. 16:00 – 17:06

   Build Something That Excites People

   1. UHUnknown Host16:00

      like, being a founder is, like, grind, grind, grind, and it is, and it's gonna be a lot of grind, and it's gonna be a lot of dark days where you just need to, like, pull it together and just get it done, but there has to be also a lot of fun to make it worth it, and, uh, that just means work on the interesting problems, right? The best cheap code I have is pick a problem that really excites people. If you wanna find the best people in the world to come work at something, do something that excites people. We do humanoid robots. It's really freaking cool. And most people come in, and they, like, say hi to a robot, and they're like, "Oh, man," kinda like, "I wanna be part of this. I wanna do this." So whatever it should be, right? Do something that matters. As long as I get to do this, I think I'll be pretty happy. [upbeat music]

Episode duration: 17:09