What is Continual Learning?
TL;DR
An AI technique for learning new tasks and data without forgetting previous knowledge. Essential for keeping AI up to date.
Continual Learning: Definition & Explanation
Continual learning (also called lifelong learning) is a technique that enables AI models to sequentially learn new tasks and data while retaining previously acquired knowledge. Traditional neural networks suffer from 'catastrophic forgetting' — losing old knowledge when trained on new data — and continual learning aims to overcome this. Main approaches include regularization-based methods (like EWC), replay-based methods (reusing past data), and architecture-based methods (allocating dedicated sub-networks per task). It is increasingly important for keeping LLM knowledge current, and dynamic knowledge updating mechanisms combining continual learning with RAG are gaining significant attention.