DNN 7: Reinforcement Learning | Research at Waymo, University of Oxford | Shimon Whiteson Deep Neural Notebooks
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- Science
In the seventh episode of Deep Neural Notebooks, I interview Shimon Whiteson.
Shimon sir is a Computer Science Professor at the University of Oxford, where he leads the Whiteson Research Lab. He is also a Data Scientist at Waymo (formerly the Google Self Driving Car Project). His research specialises in Reinforcement Learning (RL), Cooperative Multi-Agent RL, to be precise.
So this interview is all in the context of Reinforcement Learning. We talk about his journey - how he started with Machine Learning & RL. I ask him about his thoughts on the state of RL - about how the field has progressed and changed since he started, about how it has become so popular in the last few years, and about the challenges being faced.
We also talk about his research at Waymo, about recent projects from his lab, and about the scope and future of telepresence robots, one of which was developed under his guidance. We also talk about the infamous Reward Hypothesis in the context of RL and Philosophy. In the end, he also shares some advice for people starting out with RL.
Links:
- Shimon Whiteson: https://twitter.com/shimon8282
- Whiteson Research Lab (WhiRL): http://whirl.cs.ox.ac.uk/
- Teresa Robot: https://whirl.cs.ox.ac.uk/teresa/
- RL workshop at Machine Learning Summer School, Moscow: https://www.youtube.com/watch?v=RAw0Chs7QKA
- The Reward Hypothesis: http://incompleteideas.net/rlai.cs.ualberta.ca/RLAI/rewardhypothesis.html
Timestamps:
03:42 Beginnings in Computer Science06:13 Beginnings in ML
07:15 PhD at UT Austin
10:40 Intersection of Neuroevolution and RL
14:10 Research directions since PhD
16:35 State of RL
20:33 Simulation for RL
22:07 Research at Waymo
25:30 Multi-agent RL
33:25 Recent projects at WhiRL
41:30 Teresa project and Telepresence Robots
48:08 Bottlenecks for RL and Robotics
49:45 End-goal for RL, Human-level Intelligence
53:45 What do you find most fascinating about your research?
55:38 RL & Philosophy
1:01:20 Keeping up with latest research
1:03:28 Advice for beginners
Podcast links :
Youtube: https://youtu.be/bbrYZDgPI9M
Apple Podcasts: https://apple.co/2TLUZ0y
Google Podcasts: https://bit.ly/2TIyvh6
Spotify: https://open.spotify.com/episode/3936aEvSwsIhfwQfURmDb9
Anchor: https://bit.ly/3gpMi65
Connect:
Twitter: https://twitter.com/mkulkhanna
Website: https://mukulkhanna.co
LinkedIn: https://linkedin.com/in/mukulkhanna/
In the seventh episode of Deep Neural Notebooks, I interview Shimon Whiteson.
Shimon sir is a Computer Science Professor at the University of Oxford, where he leads the Whiteson Research Lab. He is also a Data Scientist at Waymo (formerly the Google Self Driving Car Project). His research specialises in Reinforcement Learning (RL), Cooperative Multi-Agent RL, to be precise.
So this interview is all in the context of Reinforcement Learning. We talk about his journey - how he started with Machine Learning & RL. I ask him about his thoughts on the state of RL - about how the field has progressed and changed since he started, about how it has become so popular in the last few years, and about the challenges being faced.
We also talk about his research at Waymo, about recent projects from his lab, and about the scope and future of telepresence robots, one of which was developed under his guidance. We also talk about the infamous Reward Hypothesis in the context of RL and Philosophy. In the end, he also shares some advice for people starting out with RL.
Links:
- Shimon Whiteson: https://twitter.com/shimon8282
- Whiteson Research Lab (WhiRL): http://whirl.cs.ox.ac.uk/
- Teresa Robot: https://whirl.cs.ox.ac.uk/teresa/
- RL workshop at Machine Learning Summer School, Moscow: https://www.youtube.com/watch?v=RAw0Chs7QKA
- The Reward Hypothesis: http://incompleteideas.net/rlai.cs.ualberta.ca/RLAI/rewardhypothesis.html
Timestamps:
03:42 Beginnings in Computer Science06:13 Beginnings in ML
07:15 PhD at UT Austin
10:40 Intersection of Neuroevolution and RL
14:10 Research directions since PhD
16:35 State of RL
20:33 Simulation for RL
22:07 Research at Waymo
25:30 Multi-agent RL
33:25 Recent projects at WhiRL
41:30 Teresa project and Telepresence Robots
48:08 Bottlenecks for RL and Robotics
49:45 End-goal for RL, Human-level Intelligence
53:45 What do you find most fascinating about your research?
55:38 RL & Philosophy
1:01:20 Keeping up with latest research
1:03:28 Advice for beginners
Podcast links :
Youtube: https://youtu.be/bbrYZDgPI9M
Apple Podcasts: https://apple.co/2TLUZ0y
Google Podcasts: https://bit.ly/2TIyvh6
Spotify: https://open.spotify.com/episode/3936aEvSwsIhfwQfURmDb9
Anchor: https://bit.ly/3gpMi65
Connect:
Twitter: https://twitter.com/mkulkhanna
Website: https://mukulkhanna.co
LinkedIn: https://linkedin.com/in/mukulkhanna/
1 hr 5 min