How do you design a model update to incorporate new kno...

When RAG is not an option and knowledge must be injected into the weights, the primary risk is catastrophic forgetting or performance regression. You should implement a strategy that includes rank-constraining the update to preserve existing knowledge. Additionally, manage the learning rate through re-warming and re-decaying. To ensure stability, incorporate a 5% replay buffer of previous data, which incurs a 5.3% compute surcharge. Finally, ensure the update is validated against a frozen canary set before deployment.