Episode 8
Josh Tobin: Research at OpenAI, Full Stack Deep Learning, ML in Production
Josh Tobin holds a CS PhD from UC Berkeley, which he completed in four years while also working at OpenAI as a research scientist. His focus was on robotic perception and control, and contributed to the famous Rubik's cube robot hand video. He co-organizes the phenomenal Full Stack Deep Learning course and is now working on a new stealth startup.
Learn more about Josh:
https://twitter.com/josh_tobin_
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Timestamps:
01:32 Follow Charlie on Twitter (twitter.com/charlieyouai)
02:43 How Josh got started in CS and ML
11:05 Why Josh worked on ML for robotics
15:03 ML for Robotics research at OpenAI
28:20 Josh's research process
34:56 Why putting ML into production is so difficult
44:46 What Josh thinks the ML Ops landscape will look like
49:49 Common mistakes that production ML teams and companies make
53:11 How ML systems will be built in the future
59:37 The most valuable skills that ML engineers should develop
01:03:50 Rapid Fire Questions
Links
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
Domain Randomization and Generative Models for Robotic Grasping
DeepMind Generative Query Network (GQN) paper
Geometry Aware Neural Rendering
OpenAI Rubik's Cube Robot Hand video
Weights and Biases interview with Josh
