When A.I.'s Output Is a Threat to A.I. Itself

The article explores how AI-generated content may lead to a feedback loop, with one AI's output becoming another AI's input, creating a cycle that can result in deteriorating quality and diversity over time. Known as 'model collapse,' this process may pose a threat to AI's ability to produce reliable and varied results, affecting fields from medical advice to historical knowledge. To mitigate these issues, the research emphasizes the importance of high-quality, diverse data, and the need to avoid reliance on synthetic data.

• OpenAI generates roughly 100 billion words per day.
• AI-generated content may become ingested by future AI models.
• Generative AI can deteriorate when trained on its output.
• Model collapse results in lower diversity and quality of AI output.
• AI faces 'collapse' by converging to similar representations.