Music & AI Plus a Geometric Perspective on Reinforcement Learning with Pablo Samuel Castro - #339

This article from Practical AI features an interview with Pablo Samuel Castro, a Staff Research Software Developer at Google. The conversation explores Castro's work, touching upon his passion for music and its influence on his Lyric AI project. The discussion also delves into his research papers, specifically "A Geometric Perspective on Optimal Representations for Reinforcement Learning" and "Estimating Policy Functions in Payments Systems using Deep Reinforcement Learning." The article promises a broad overview of Castro's work, connecting his diverse interests and research areas within the field of AI.

• •The interview highlights the intersection of music and AI, showcasing how personal interests can influence research.
• •The discussion covers Castro's work on reinforcement learning, including a geometric perspective on optimal representations.
• •The article mentions specific research papers, providing potential entry points for further investigation into Castro's work.