👉 Forgetting in computing, particularly in the context of machine learning and artificial intelligence, refers to the phenomenon where a model's ability to recall previously learned information diminishes over time or after being exposed to new data. This degradation in performance can occur due to various factors, including catastrophic forgetting, where the model forgets previously learned tasks when trained on new data. Techniques like regularization, rehearsal, and architectural modifications are employed to mitigate this issue, ensuring that models can effectively learn new information without losing critical knowledge from their past experiences.
