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#038 - Professor Kenneth Stanley - Why Greatness Cannot Be Planned

Machine Learning Street Talk (MLST)

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Exploring Open-Endedness in AI

This chapter examines the intricate dynamics of education and progress in machine learning, focusing on the significance of diversity in thought and approach. It emphasizes the potential of open-ended processes to foster innovation, contrasting them with traditional optimization methods. Through discussions on algorithms like POET and the implications of population-based search, the chapter highlights the continuous evolution of intelligent systems and their relationship to natural evolution.

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