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Large Language Models and Emergence: A Complex Systems Perspective (Prof. David C. Krakauer)

Machine Learning Street Talk (MLST)

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Emergence and Intelligence in Complex Systems

This chapter explores the distinctions between knowledge and intelligence, emphasizing how intelligence can emerge with minimal knowledge in complex systems. It critiques mainstream interpretations of emergence in large language models (LLMs) and discusses the gradual transition of behaviors across different scales. The conversation further delves into the implications of scaling laws, symmetries, and evolutionary convergence, highlighting how these concepts shape our understanding of intelligence and emergent properties.

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