Meet NEO, Your Robot Butler in Training | Bernt Brnich | TED

• As a species, humans have made energy abundant and accessible.
• We are on the verge of a future where labor will be as accessible as energy.
• Humanoid robots like Neo are being developed to assist with everyday tasks.
• The home provides a diverse learning environment for robots to develop intelligence.
• The journey with these robots aims to give us back time and redefine our understanding of what it means to be human.

As a species, humans have mastered energy to the level where it is, for all practical purposes, completely abundant.

200 years ago, no one could have imagined a world where energy was so accessible that most people would take it for granted. If you had asked the smartest person on Earth whether we could one day summon light with the flip of a switch, they would have said it was impossible, even if the brightest minds worked on it together for an eternity.

But today, it's just that easy. Energy is everywhere, all around us, all of the time.

Now, what if I told you that the same is about to happen with labor? We are standing at the gates of a future where the work needed to build the products we use, the services we rely on, and even the chores in our homes will be as effortlessly accessible as energy is today. This will enable you to explore new frontiers and focus on what makes you truly human.

Thank you. Thank you. Neo, your best.

It's an amazing machine, Rightese. So I spent the last decade of my life working on building humanoid robots like Neo robots that will hopefully soon be able to do almost anything that we could imagine.

Now, whether this is helping you with the dishes, helping you do your laundry, or whether this is helping your aging grandmother, there's never really been a time better for robots. We have an aging population in need of help, and we have a large labor shortage across most of the global economy.

And there's much, much more. But even more importantly to me, these robots promise something greater than just the ability to solve the problems of today. They can solve things that we cannot do today. They can give us back things like time.

As these systems and AI now become both physical and intelligent, we can start to work towards a future where we actually have an abundance of labor.

We can start towards lifting humanity out of this constant battle over scarcity of resources and create a world where everyone has what they need. And I think that will, to some extent, actually redefine what it means to be human.

Since around the year 1400, when Leonardo da Vinci made the mechanical man, this is kind of like the first example of a humanoid robot. These things have been mainly a thing of science fiction, not reality. But this is changing—the robots are actually here.

When I say "here," I don't necessarily mean in videos. They're actually here in our homes. At least if you work at 1x where I work, we now have them in quite a few homes throughout the company.

And already later this year, I hope some of you guys will have it in your homes and join us on this journey. So that means Neo is now part of my daily routine.

It does some of the chores around the house. Some of this is autonomous, and some of this is done through remote operation. As it's learning, I talk to it. I treat it kind of like a butler, like a companion. It's part of the family.

And I think it's actually incredibly interesting to also see how this social dynamic develops because it's of course incredibly useful and fun to have it do stuff I don't want to do around my home.

But it's also really fun to see the beginning of what this relationship will be between man and machine as these AIs become physical. Now, like I said, the hardware is actually here.

It took us about a decade of very hard work, but also many people that came before us and spent a lot of time doing the foundational research for us to finally be able to build a machine that can do almost anything that a human can do.

But it begs the big question, of course: when will they be fully autonomous? When will they actually become truly intelligent? And what is the path that will actually take us there?

I think this will be very obvious in retrospect. They need to live and learn among us. We actually need to take these machines, adopt them, and let them learn just as we do.

The general convention has been that robots are going to first happen in factories. So we're going to put these robots into factories; they're going to do the dull, repetitive, dangerous tasks that they're good at.

And as they do these repetitive tasks, they get better and better. Right? They get more intelligent. After some time, we can put them into our homes, and they will be able to do our laundry—they will build our skyscrapers.

But this is actually categorically wrong. We've tried that. Back in 2022, we took our previous generation wheeled humanoid, Eve, and we put it in the industry, and it actually went really well.

We solved a lot of kind, narrow, specific tasks, and it got really good at them really fast. But then, after about 20 to 50 hours, the robots just stopped learning.

If you think about it, it's not really rocket science. If you're doing the same task over and over every day and it's the only thing you're doing, you're not going to get very intelligent.

There's no information there. You also become very narrow-minded. If you think about what a factory is, it is essentially a process that we design to reduce diversity and variance.

You want your factory worker to need as little information as possible to be able to do the job and get a high-quality, repeatable product out. This is kind of the opposite of what you need for intelligence.

You need diversity; you need to challenge yourself. You need to do new tasks every day that you don't know how to do. There’s a great parallel here to the early days of large language models.

When we use these models today and they're getting really good, we forget where they started. They began with a lot of people trying to make very narrow models. If I take an example, if you wanted to make a very good writing assistant to write poetry, then you would train it on all the best poetry in the world.

Makes sense, right? But then it wouldn’t really work. We started training these models on all of the Internet—the complete diversity of all human knowledge. They started working; they became kind of smart.

They began to be able to, to a certain extent, reason and understand, "What is the question you're asking and how should I answer?" This is also how we humans learn.

We need a large amount of diversity for us to be able to develop into intelligent beings. So why should it be different for robots?

It really begs the question then, what is the equivalent of the Internet? How do we find this kind of Internet-level diversity of information for our robots?

We come to the conclusion that the home is probably it. The home is this beautiful, chaotic thing. It's a messiness that is being human. I want to take a small example here.

Think about a cup. Now, of course, there are many cups in the world, and you want to be able to figure out how all of them work. Even if you look at one specific cup, it can be many things. Is it dirty? Is it clean?

Is it on the table? In the cabinet? On the floor? It can even have a social context—someone's using the cup, someone's waiting for the cup. Like, why is the cup even there?

And this is just a cup. Now, think about expanding this out into everything and every object and everything going on in your home. That's the kind of diversity we’re talking about to get to proper machine intelligence.

Like any good scientist, we had this hypothesis, and now we have to test it. In 2023, we brought our robots home. I have had one in my house for quite a while, and it was of course doing the standard things like emptying the dishwasher, but also bringing me a cup of tea while I was enjoying playing board games with my friends or serving cupcakes at my daughter's birthday party.

Pretty quickly, it became clear that this hypothesis was indeed the ground truth. The home is this incredible diverse source of data that lets us continue to progress intelligence.

So we thought originally that it was going to be this, but actually, it was this. Let me show you how this actually works in practice.

Thank you. You're doing a good job. It's a bit noisy, but hopefully, you can still hear me.

What you see here now is just a subset of tasks that Neo can do. This is a mix of autonomy for things the robot is good at and some remote operation where someone's guiding the robot to do expert demonstrations on how to do these tasks.

As we have an increasing number of these robots throughout homes living among us and learning more, more of this becomes autonomous until hopefully one day, all of this will be fully autonomous.

If you follow along in the field, a natural question to ask at this point would be: why doesn't everyone do this right, if it's so obvious?

Well, it actually turns out it's incredibly hard to make a robot that is safe among people. Robots are traditionally quite stiff, high energy, and dangerous.

This is very different from how Neo works. Neo has tendons that are loosely inspired by human muscle. This makes Neo a robot that is quiet, soft, compliant, lightweight, safe, and really able to live among us and learn among us.

Let's see if he figures it out. It’s a hard one. You can do it, Neo. I said he's the best, right?

This is still, of course, incredibly early. We're at the beginning of this journey. But I do hope that not long from now, just like we take energy for granted around us, we will be able to take labor for granted.

We might not even remember the day where there wasn't always like a helping hand available for anything we wanted to do.

But as these machines go around in our society and learn, to me, this journey is about a lot more than just you not having to do your laundry.

It's about creating a future where we actually have time to focus on what matters to us as humans and getting rid of these constraints. But also, it's an opportunity to have these machines help us solve some of the outstanding questions that we still have.

Can we have robots build robots? Can we have robots build data centers to progress AI? Can we have robots that build chip fabs to help us accelerate the adoption of AI?

I think it's getting pretty clear that we can have all of these things. But it goes even further than that.

I hope we can get a future where we have human-aided robots like Neo that are actually building particle accelerators, building labs. We will have millions of robots around the world doing high-quality, repetitive experiments in labs and helping us progress science at a pace never seen before.

I hope that in the future, through this kind of symbiosis between man and machine, we can start trying to answer some of the remaining big unanswered questions about the universe and our role here.

And I think if we can do that, that will, to some extent, redefine what it means to be human.

Thank you.