Physical AI: Could Training Data Become a $45B Market?

Sce Pike (0:00)

China, for example, have data collection cities.

jd.com, the Amazon of China, is essentially trying to create a city where they would employ a hundred thousand people in that city to collect their everyday lives, to train robots. They're having just everyday citizens go and pick up headsets to do their daily routine.

Rob Kelly (0:41)

Welcome to Media and the Machine. I'm Rob Kelly. AI is the biggest technology shift of our lifetime, and this show is about how to profit from it. I'm a three-time founder and CEO of content-driven businesses, and each week, I talk with the people on the inside of AI and content, the ones building this new world and learning what works firsthand. I'm an optimist about AI, but I'm also a realist. So every show ends with me asking our guest what AI means for our jobs, our families, and our future.

My guest is Sce Pike, VP of AI Growth and Solutions at TELUS Digital. She built and sold two companies. Ernst & Young bought her digital consultancy, Citizen, and ADT bought her smart home company, Iotas. SayNow has her site set on physical AI and robots. We break down Google's recent breakthrough, where its new Gemini 4 Argon taught a robot to play cornhole, and it made seven shots in a row. But what makes data skills like that possible, and who's going to supply it? We get specific about what AI labs want, and why robotics companies like Figure AI are getting into the data collection business. We discuss why robots might need a billion training hours, plus our forecast of a $45 billion market by 2035 That's just collecting data for physical AI.

Then we explore China's data collection cities. Imagine 100,000 people recording their everyday lives just to train robots, and why she thinks China, despite being behind the US and LLMs, can be number one in physical AI. Plus, a robotic centaur with chainsaw hands. As always, we close talking about AI's impact on our families and jobs, including advice for her kids. They're artists, and they're rebelling against her AI optimism. Please enjoy my conversation with Sce Pike.

This Gemini 4 Argon playing cornhole.

Yes. It didn't just play cornhole, it sunk seven shots in a row.

Sce Pike (2:33)

I think one of the things that was very nice about that demonstration is going from real to simulation.

So taking a real video of a human doing a shot into a cornhole. So watch that video and then put it into a simulation and simulated the physics of that, of the, what do you call it? The bag, the hacky bag or whatever, right? Going into the whole.

Rob Kelly (2:58)

Bean bag.

Sce Pike (2:59)

The bean bag, right? And so it simulated it and then it actually took it into its own practice and learn over and over again after like how much force it needed, what's the trajectory, right? And so it watched itself do that and learned over a period of time to get to understanding how to make that shot.

What it didn't show was the robot picking up the bean bag and then throwing it. Contact physics, meaning like how hard it had to pick that bean bag up, how soft it had to hold that bean bag, when it threw that bean bag.

Rob Kelly (3:38)

So it's not quite the AlphaGo, Deep Blue type moment for physical AI.

Sce Pike (3:44)

The ideal scenario, the end game is like I have a robot in my house. I show it how to sort my laundry and put it into the laundry machine and push the buttons and then take it out, put it in the washer. You show it once, how you want it done, and it will just perfectly mimic you. I think that would be the breakthrough moment, if it could mimic anything that you did.

I mean, that would be the end game, because it's not just household chores. You're talking factory floors, you're talking retail, you're talking hospitality, right? It's just, if it could actually watch you do something once, twice, three times, whatever, and then actually do the task, that would be the end game.

Rob Kelly (4:30)

And the overall definition, just of physical AI, is it simply that we're going from using AI for digital reasoning to physical action?

Sce Pike (4:42)

So, physical AI, when I say physical AI, it encompasses both robotics as well as automotive, autonomous vehicles as well. So, physical AI to me encompasses anything that is action oriented in the physical world.

Rob Kelly (4:56)

So, physical models versus LLMs. I just want to contrast the two because most people now are familiar with learning language models, LLMs.