Whether you’re a robot or a college student, it helps to start with the fundamentals, says a leading robotics researcher.
While robots can do amazing things, compare even the most advanced robots to a three-year-old and they can come up short.
Pieter Abbeel, a professor at the University of California, Berkeley, and cofounder of Covariant.ai, an AI company, has pioneered the idea that deep learning could be the key to bridging that gap: creating robots that can learn how to move through the world more fluidly and naturally.
Or as Abbeel refers to it, building “brains for robots.”
Teaching robots new skills is similar to taking classes in college, Abbeel explained on the latest episode of the AI Podcast.
While college courses may not immediately qualify a student for a job, the classes are still important in helping students develop fundamental skills they can apply in all kinds of situations.
Abbeel uses the same approach in his robotics research. At last month’s GPU Technology Conference, he showed a robot learning to navigate a new building it’s never been in before. His talk will be available here starting May 1.
The robot was able to do that because it was applying principles it had learned by navigating other buildings. “What were [the robot’s] courses in its college curriculum were the many other buildings that it was also learning to navigate,” he said. “So it learned a generic skill of navigating new buildings.”
Similarly, college students should look for classes that can teach them skills they can apply broadly.
For younger students interested in getting a head start in AI and deep learning, Abbeel encourages them to look into physics.
“When I think about the foundations, the things you would learn early on, that will help a lot — they’re essentially mathematics and computer science and physics,” said Abbeel.
“And the reason I say ‘physics,’ which might be slightly more unexpected in the lineup, is that physics is all about looking at the world and building abstractions of how the world works,” he said.
Abbeel also recommends getting involved in research.
“It’s a lot about taking initiative, trying things,” Abbeel said. “The research cycle is a lot about just trying things people haven’t tried before and trying them quickly and understanding how to simplify things.”
How to Tune into the AI Podcast
If your favorite isn’t listed here, email us at aipodcast [at] nvidia [dot] com.