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Understanding Model Collapse in AI
This chapter examines the phenomenon of model collapse in artificial intelligence, illustrating how AI systems can fall into a feedback loop that degrades the quality of their outputs. Using humorous examples, it discusses the dangers of relying on synthetic data and highlights the impact of training biases on AI performance and creativity.