What are effective strategies for managing catastrophic forgetting in Generative AI models

Question

Can you tell me What effective strategies are for managing catastrophic forgetting in Generative AI models?

Answer 1

Catastrophic forgetting occurs when a model forgets previously learned information while learning new tasks. Strategies to mitigate this include using techniques such as Elastic Weight Consolidation (EWC), knowledge distillation, and regularization to stabilize learning across tasks. Here is the code snippet you can refer to:

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

• Elastic Weight Consolidation (EWC): Adds a penalty to changes in important parameters to prevent forgetting.
• Knowledge Distillation: Transfers knowledge from a previous model to a new one, reducing forgetting.
• Regularization: Techniques like L2 regularization and rehearsal can also reduce catastrophic forgetting.
• Balanced Training: Ensures the model doesn't overwrite old knowledge when learning new tasks.

Hence, these are the effective strategies for managing catastrophic forgetting in Generative AI models.