What is Model Collapse?

What is model collapse?

Model collapse occurs when AI models are trained on AI-generated data, causing progressive quality degradation. Each generation loses information and amplifies errors, eventually producing low-quality, repetitive outputs.

How It Happens

Model A generates training data
Model B trains on Model A's outputs
Model B loses tail distribution information
Each generation amplifies errors and reduces diversity

Signs of Collapse

Increasing repetition in outputs
Loss of nuance and detail
Convergence to common patterns
Declining performance on edge cases

Prevention

Use human-generated training data
Filter AI-generated content from training sets
Monitor output diversity over time
Track quality metrics continuously

How does this affect production?

If your fine-tuning data includes AI-generated content, or if you're using AI outputs as training signals, you risk quality degradation over time. Monitor output quality continuously to detect early signs of collapse.