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Next Unicorns: Empowering robots to think for themselves via AI with Covariant’s Peter Chen | E1796

This Week in Startups

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Reinforcement Learning in AI and Robotics

This chapter explores the complexities of reinforcement learning through the lens of game strategies, contrasting simple games like Pong with sophisticated ones like Go and AlphaGo. It emphasizes the critical role of high-quality data, the challenges in robotics data collection, and the importance of delayed rewards in AI decision-making. Additionally, the chapter discusses third-person imitation learning and the adaptability of robots, revealing how tailored datasets enhance robotic training and autonomy.

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