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Generative Video WorldSim, Diffusion, Vision, Reinforcement Learning and Robotics — ICML 2024 Part 1

Latent Space: The AI Engineer Podcast

CHAPTER

Adapting Robots through Learning and Automation

This chapter explores how robots can adapt their strategies by learning from past experiences and correcting mistakes in unfamiliar situations. It emphasizes the role of in-context learning and the need for automated processes in shaping robotic environments, highlighting the limitations of current machine learning approaches. Furthermore, the chapter discusses future research directions and the founding of a robotics company aimed at enhancing real-world applications of machine learning.

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