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EP 316 Ken Stanley on the AI Representation Problem

The Jim Rutt Show

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Exploring Open-Endedness in AI

This chapter focuses on the concept of open-endedness in artificial intelligence, drawing parallels to biological evolution. The discussion includes the innovative Pickbreeder experiment, which encourages user-driven creativity in evolving digital images, and compares different neural network training methods. It also challenges conventional notions of representation in AI, highlighting the need for a deeper understanding of how advancements in performance relate to representational capabilities.

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