In artificial intelligence, model collapse, also known as "AI inbreeding", "AI cannibalism", "Habsburg AI", and "model autophagy disorder" or "MAD", is the degradation of machine learning models from uncurated synthetic data, or from training on the outputs of another model, such as a prior versions of itself. It has colloquially been referred to as the AI version of mad cow disease, fundamentally caused by feeding something to itself. It is unclear to what extent the model collapse threatens the long-term development of AI models, and techniques have been proposed to mitigate the effect.