synthetic-data

Model Collapse: Why AI Trained on AI Slowly Falls Apart

Model collapse is the progressive degradation of generative models trained recursively on synthetic data, documented in Nature (Shumailov et al., 2024). Errors compound and rare data vanishes, but research (Gerstgrasser et al., 2024) shows accumulating real data alongside synthetic data, tracking ratios, and verifying generations prevents it.

By Aisha Patel · 8 min · Jun 19, 2026