Exploring the granularity of localization, Peter discusses the significance of analyzing outputs from specific layers in transformers. He highlights how surprising causal relationships can be manipulated through interventions in residual layers, revealing that knowledge editing can occur without altering the original information store. This insight opens up new avenues for understanding and modifying language models.
