Ken Goldberg

Exactly. So Fei-Fei Li is actually at the center of this. She builds this data. So she plays a pivotal role. When all that gets put together, suddenly it's a revolution. And that's a big moment in robotics and history. We apply it to robotics. And so her system was called ImageNet. And so the system that we designed for grasping, we called DexNet. As an homage to her. Oh, that's great.

Exactly. So Fei-Fei Li is actually at the center of this. She builds this data. So she plays a pivotal role. When all that gets put together, suddenly it's a revolution. And that's a big moment in robotics and history. We apply it to robotics. And so her system was called ImageNet. And so the system that we designed for grasping, we called DexNet. As an homage to her. Oh, that's great.

So DexNet was our system. We worked on it for five years, and we basically applied deep learning techniques to be able to figure out where to grasp objects. And it started working better than anything had been done before. And I was so surprised because I had been trying to work on this problem, and then I suddenly was able to pick up almost everything we could put in front of it. Oh, wow.

So DexNet was our system. We worked on it for five years, and we basically applied deep learning techniques to be able to figure out where to grasp objects. And it started working better than anything had been done before. And I was so surprised because I had been trying to work on this problem, and then I suddenly was able to pick up almost everything we could put in front of it. Oh, wow.

So DexNet was our system. We worked on it for five years, and we basically applied deep learning techniques to be able to figure out where to grasp objects. And it started working better than anything had been done before. And I was so surprised because I had been trying to work on this problem, and then I suddenly was able to pick up almost everything we could put in front of it. Oh, wow.

Yeah, no, that's a really great point. There is a critical point when you get enough data and suddenly it starts working. It took a lot. It was 80 million plus images that Fei-Fei put together. Right. And in our case, we had 7 million grasp examples that we had found. And then it started to work and it was like, oh, this is so exciting.

Yeah, no, that's a really great point. There is a critical point when you get enough data and suddenly it starts working. It took a lot. It was 80 million plus images that Fei-Fei put together. Right. And in our case, we had 7 million grasp examples that we had found. And then it started to work and it was like, oh, this is so exciting.

Yeah, no, that's a really great point. There is a critical point when you get enough data and suddenly it starts working. It took a lot. It was 80 million plus images that Fei-Fei put together. Right. And in our case, we had 7 million grasp examples that we had found. And then it started to work and it was like, oh, this is so exciting.

And think of it with a very simple gripper, just a parallel pincer. So you would put a bin of objects in front of it and it would start to pick them one by one and put them out. And so we would test it by going into the basement of the garage. We'd just throw all kinds of stuff in there. And it would just pick them up consistently and clear the bin. And we would try and fool it.

And think of it with a very simple gripper, just a parallel pincer. So you would put a bin of objects in front of it and it would start to pick them one by one and put them out. And so we would test it by going into the basement of the garage. We'd just throw all kinds of stuff in there. And it would just pick them up consistently and clear the bin. And we would try and fool it.

And think of it with a very simple gripper, just a parallel pincer. So you would put a bin of objects in front of it and it would start to pick them one by one and put them out. And so we would test it by going into the basement of the garage. We'd just throw all kinds of stuff in there. And it would just pick them up consistently and clear the bin. And we would try and fool it.

He must have been elated. It was so much fun. There's a story where we got invited to show this to Jeff Bezos. And he invited us down to this event in Palm Springs. He said, bring the robot. I want to see this. We had never left a lab before, so it was a big deal to put it on a truck. And we weren't sure it was going to work. We had like 300 objects that we brought with us, got it all set up.

He must have been elated. It was so much fun. There's a story where we got invited to show this to Jeff Bezos. And he invited us down to this event in Palm Springs. He said, bring the robot. I want to see this. We had never left a lab before, so it was a big deal to put it on a truck. And we weren't sure it was going to work. We had like 300 objects that we brought with us, got it all set up.

He must have been elated. It was so much fun. There's a story where we got invited to show this to Jeff Bezos. And he invited us down to this event in Palm Springs. He said, bring the robot. I want to see this. We had never left a lab before, so it was a big deal to put it on a truck. And we weren't sure it was going to work. We had like 300 objects that we brought with us, got it all set up.

He came in the booth and it was working. And we were so relieved. And he was trying it with different things and it was just like it was in the lab. And everything was going great. And then his assistant was standing there and took off his shoe. And he said, well, can I try my shoe? And I remember my mouth goes dry. Because of all the things we've tried it with, we've never tried a shoe.

He came in the booth and it was working. And we were so relieved. And he was trying it with different things and it was just like it was in the lab. And everything was going great. And then his assistant was standing there and took off his shoe. And he said, well, can I try my shoe? And I remember my mouth goes dry. Because of all the things we've tried it with, we've never tried a shoe.

He came in the booth and it was working. And we were so relieved. And he was trying it with different things and it was just like it was in the lab. And everything was going great. And then his assistant was standing there and took off his shoe. And he said, well, can I try my shoe? And I remember my mouth goes dry. Because of all the things we've tried it with, we've never tried a shoe.

So I have no idea. But what can we do? We have to say, go ahead. Otherwise, it feels all mapped out, maybe.

So I have no idea. But what can we do? We have to say, go ahead. Otherwise, it feels all mapped out, maybe.

So I have no idea. But what can we do? We have to say, go ahead. Otherwise, it feels all mapped out, maybe.