Datacast Episode 33: Domain Randomization in Robotics with Josh Tobin

The 33rd episode of Datacast is my conversation with Josh Tobin - the founder of a stealth machine learning startup and previously deep learning & robotics researcher at OpenAI. Give it a listen to hear about his background in mathematics, his time as a CS Ph.D. student at UC Berkeley, his wide-ranging research in robotics at OpenAI, the importance of working on the right problems for junior researchers, his initiative with Full Stack Deep Learning, and much more.

Josh Tobin is the founder and CEO of a stealth machine learning startup. Previously, Josh worked as a deep learning & robotics researcher at OpenAI and as a management consultant at McKinsey. He is also the creator of Full Stack Deep Learning (fullstackdeeplearning.com), the first course focused on the emerging engineering discipline of production machine learning.

Josh Tobin is the founder and CEO of a stealth machine learning startup. Previously, Josh worked as a deep learning & robotics researcher at OpenAI and as a management consultant at McKinsey. He is also the creator of Full Stack Deep Learning, the first course focused on the emerging engineering discipline of production machine learning. Josh did his Ph.D. in Computer Science at UC Berkeley, advised by Pieter Abbeel.

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