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UC Berkeley’s Pieter Abbeel on How Deep Learning Will Help Robots Learn - Ep. 82

UC Berkeley’s Pieter Abbeel on How Deep Learning Will Help Robots Learn - Ep. 82

FromThe AI Podcast


UC Berkeley’s Pieter Abbeel on How Deep Learning Will Help Robots Learn - Ep. 82

FromThe AI Podcast

ratings:
Length:
24 minutes
Released:
Apr 11, 2019
Format:
Podcast episode

Description

Robots can do amazing things. Compare even the most advanced robots to a three-year old, however, and they can come up short. UC Berkeley Professor Pieter Abbeel has pioneered the idea that deep learning could be the key to bridging that gap: creating robots that can learn how move through the world more fluidly and naturally. We caught up with Abbeel, who is director of the Berkeley Robot Learning Lab and cofounder of Covariant AI, a Bay Area company developing AI software that makes it easy to teach robots new and complex skills, at GTC 2019.
Released:
Apr 11, 2019
Format:
Podcast episode

Titles in the series (100)

One person, one interview, one story. Join us as we explore the impact of AI on our world, one amazing person at a time -- from the wildlife biologist tracking endangered rhinos across the savannah here on Earth to astrophysicists analyzing 10 billion-year-old starlight in distant galaxies to the Walmart data scientist grappling with the hundreds of millions of parameters lurking in the retailer’s supply chain. Every two weeks, we’ll bring you another tale, another 25-minute interview, as we build a real-time oral history of AI that’s already garnered nearly 3.4 million listens and been acclaimed as one of the best AI and machine learning podcasts. So whether you’re contending with challenges in marketing or mathematics, astrophysics or paleo history or just trying to find an automated way to sort out your kid’s growing Lego pile, listen in and get inspired.