Model collapse

Model collapse is a degradation that can occur when models are trained repeatedly on data generated by other models, gradually losing diversity and accuracy compared with training on human data.

Model collapse sits in the Foundations part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.