Catastrophic Forgetting — AI Glossary

Catastrophic forgetting is a phenomenon where a neural network rapidly loses previously learned knowledge when it is trained on new data or tasks. Unlike humans who can learn new skills while retaining old ones, AI models tend to overwrite earlier patterns as new training updates their internal weights. This is a core challenge in building AI systems that can continuously learn over time, and techniques like LoRA and replay-based methods aim to mitigate it.