According to Anthropic (@AnthropicAI), the Selective Gradient Masking (SGTM) technique divides a model’s weights into 'retain' and 'forget' subsets during pretraining, intentionally guiding sensitive or high-risk knowledge into the 'forget' subset. Before deployment in high-risk environments, this subset can be removed, reducing the risk of unintended outputs or misuse. This approach provides a practical solution for organizations seeking to deploy advanced AI models with granular control over sensitive knowledge, addressing compliance and safety requirements in regulated industries. Source: alignment.anthropic.com/2025/selective-gradient-masking/