What techniques mitigate catastrophic forgetting in continual Generative AI training

Question

With the help of proper code examples, can you tell me What techniques mitigate catastrophic forgetting in continual Generative AI training?

Answer 1

Techniques like Elastic Weight Consolidation (EWC), Replay Buffers, Knowledge Distillation, and Progressive Neural Networks help mitigate catastrophic forgetting in continual Generative AI training.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Implements Elastic Weight Consolidation (EWC) to retain knowledge from past tasks.
• Uses Fisher Information Matrix to measure parameter importance.
• Prevents catastrophic forgetting by penalizing drastic weight updates.
• Integrates EWC loss into standard model training for continual learning.

Hence, mitigating catastrophic forgetting requires techniques like EWC, replay buffers, and knowledge distillation to retain prior knowledge while learning new tasks.