Training & Fine-tuning
Continual Learning
Techniques to let models learn new information without forgetting old knowledge.
Definition
Continual learning (also called lifelong learning) is an active research area aimed at enabling AI models to learn new tasks and information over time without forgetting what they already knew. This is a fundamental challenge because the standard training approach tends to overwrite prior knowledge when new information is introduced. Solutions include rehearsal methods (replaying old examples), regularisation techniques, and modular architectures that separate different types of knowledge.
Related Terms
Catastrophic Forgetting
When a model loses previously learned knowledge after being fine-tuned on new data.
Fine-tuning
Further training a pre-trained model on specific data to specialise it for a task.
Machine Learning (ML)
A method where computers learn patterns from data rather than being explicitly programmed.
Heard enough terminology — ready to talk outcomes?
We translate AI concepts into measurable business results. No upfront fees — you pay only when independently verified results are delivered.
Disclaimer
This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.
Document reference: ISO_webpage_knowledge-base_glossary_v1
Last modified: 29 March 2026
Knowledge Base·Training & Fine-tuning·Continual Learning