#237: Deep Learning in Robotics, with Sergey Levine June 24, 2017

from Robohub Podcast· ·

Sergey Levine on applying deep learning techniques for end-to-end design of robots.

In this episode, Audrow Nash interviews Sergey Levine, assistant professor at UC Berkeley, about deep learning on robotics. Levine explains what deep learning is and he discusses the challenges of using deep learning in robotics. Lastly, Levine speaks about his collaboration with Google and some of the surprising behavior that emerged from his deep learning approach (how the system grasps soft objects).

In addition to the main interview, Audrow interviewed Levine about his professional path. They spoke about what questions motivate him, why his PhD experience was different to what he had expected, the value of self-directed learning, work-life balance, and what he wishes he’d known in graduate school.