Trends in Reinforcement Learning with Pablo Samuel Castro

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Today we kick off our annual AI Rewind series joined by friend of the show Pablo Samuel Castro, a Staff Research Software Developer at Google Brain.

Pablo joined us earlier this year for a discussion about Music & AI, and his Geometric Perspective on Reinforcement Learning, as well our RL office hours during the inaugural TWIMLfest. In today’s conversation, we explore some of the latest and greatest RL advancements coming out of the major conferences this year, broken down into a few major themes, Metrics/Representations, Understanding and Evaluating Deep Reinforcement Learning, and RL in the Real World. This was a very fun conversation, and we encourage you to check out all the great papers and other resources available below.

We want to hear from you! Send your thoughts on the year that was 2020 below in the comments, or via Twitter at @samcharrington or @twimlai.

To follow along with the 2020 AI Rewind Series, head over to the series page!

Thanks to our Sponsor!

Thanks to our friends at Pachyderm for sponsoring the show!

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Connect with Pablo

Resources

Join Forces!

“More On That Later” by Lee Rosevere licensed under CC By 4.0

2 comments
  • Deven
    REPLY

    This episode didn’t appeal to me at all. It was waaay to academic and theoretical. I would have done a PhD in this subject if I wanted this much detail. Overall I love your podcast but can you guide guests to connect their talk and papers back to the real world and how we can apply ML to business and customer problems?

    • sam
      REPLY

      Hey Deven. Thanks for your comment. I try to keep a good balance between research and application on the podcast, and also try to connect research with application, but I admit, some of my interviews are very much on the academic side. We’ve talked about labeling them and/or splitting them off into separate feeds (there would still be a master feed), and I’m wondering if you’d find that useful?

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