External Memory

External memory, in the context of large language models (LLMs), refers to mechanisms that allow these models to access and utilize information stored outside of their internal parameters. This can involve retrieving relevant data from databases, knowledge graphs, or other external sources during the prompt processing or generation phases to augment the model's knowledge and improve its performance on specific tasks. This enhances the LLM's ability to handle complex queries and generate more accurate and contextually relevant responses.

Visit the following resources to learn more:

• @article@How to Maximize Agentic Memory for Continual Learning