In this episode, we explore the rising concern of "data collapse," a phenomenon where AI-generated synthetic content floods the internet, making it harder to distinguish between human-created data and artificial noise. We delve deep into how AI's, like GPT4, create data, the potential dangers of over-reliance on synthetic content, and the concept of "model collapse." Using a compelling case study, we illustrate how AI systems can degrade over time when trained on their own outputs, potentially filling the web with unreliable information. Tune in to learn how this could reshape the digital landscape and what it means for the future of AI.

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This podcast was generated with the help of ChatGPT, Mistral, and Claude 3. We do fact-check with human eyes, but there still might be hallucinations in the output.

Music credit: "Modern Situations" by Unicorn Heads