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Trends in Reinforcement Learning with Pablo Samuel Castro

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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.

Thanks to our friends at Pachyderm for sponsoring the show!

At the end of the day, real-world machine learning is all about the data. You already know this, but manually cleaning and transforming data can be exhausting, inconsistent, and error-prone, and is not the path towards getting your models into production, especially when your data, models, and code are constantly changing.

Right now, TWIML listeners can enjoy 20% off of Pachyderm Hub and build production-grade data science workflows in minutes, without ever having to configure a single piece of infrastructure.

Imagine being able to automate your entire data science workflow and reproduce any result from any point in time — in seconds, and with complete confidence.

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