00:42:06 · Jim Fan
And the second thing... Second area I'm excited about, also really regular, very structured, and isn't that demanding on safety, is self driving wet labs. A lot of scientific experiments, like, you know, in chemistry or in drug discovery, are still carried out by humans. Even though there are special equipment to do chemical mixing, that people don't do it by hand anymore. But think about those biology experiments. Still, there are a lot of humans in the process using those equipments. We can completely replace that with an automated robot pipeline, and it's gonna look very similar to a programmable factory, but this time applied to scientific discoveries. So you can collect data and program this whole line by demonstration instead of by hard coding. And then there is the agentic fleet. So we discuss a lot about single robot, but what about kind of having this life mind of a whole fleet of robots all working together? Then we can run these agentic flows, right, these multi agent flows controlled by a central O1 brain to break down and distribute a task to a whole fleet of robot so they can better support these factory assembly lines and also multistage, right, like scientific experimentation. And then finally, home use. I I think home use is just a lot harder to be fully automated. It's way more unstructured. Right? Every house is messy in a different way, and then you you for sure have a lot of safety concerns. Right? There are kids, elderly people, and these robots, they weigh a lot, and it's not fun having any of those robots fall down and fall on a person. So I think home use, and then there's also privacy and all of those concerns. I would say home use is still a bit out there, but I really wish that we can see that in five years. If not five years, definitely by 2040.
00:44:06 · Molly Welch
[00:44:06] S0: Very inspiring examples and application areas. Thank you, Jim. You've been listening to a special episode of Radical Talks from the Radical AI Founders Masterclass series. A special thank you to NVIDIA's director of AI and distinguished scientist, Jim. If you like what you hear, please be sure to subscribe and leave us a comment. Thanks for listening.