Continual Learning: Models That Learn Without Forgetting

Introduction

Continual learning enables models to learn new tasks without forgetting previously learned knowledge.

Challenges

• Catastrophic Forgetting: Tendency of models to forget old tasks when learning new ones.
• Memory Management: Strategies to retain important information.

Techniques

Regularization methods, replay buffers, and dynamic architectures.

Conclusion

Continual learning is essential for adaptive AI systems capable of lifelong learning.