Continual Learning

Catastrophic interference refers to the challenge in neural networks where new learning disrupts previously acquired knowledge.

Elastic Weight Consolidation helps neural networks retain old knowledge when learning new tasks.

An Independent Increment is a method in AI where a model learns from new data without affecting previous knowledge.

Online adaptation refers to real-time adjustments of AI models based on new data or environmental changes without retraining.