Model collapse guts AI's intelligence as it feeds on its own output. Training on AI-generated junk reduces models to echo chambers, detached from reality. Culprits are statistical approximation errors, functional expressivity limits, and flawed learning procedures. We can fix this mess with rigorous data curation, model distillation, and human oversight.

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