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#114 - Secrets of Deep Reinforcement Learning (Minqi Jiang)

Machine Learning Street Talk (MLST)

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Emergent Intelligence in Reinforcement Learning

This chapter explores the complexities and limitations of reinforcement learning, focusing on the philosophical implications of intelligence and emergent behaviors in both natural phenomena and language models. The discussion highlights the potential for language models to drive innovation while also raising questions about their ability to produce genuine novelty without human input. It delves into the relationship between data generation, meta-learning, and the necessity of human feedback in assessing AI development and creativity.

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