Personal Memory

Personal memory research investigates how information is encoded, stored, retrieved, and forgotten, aiming to understand both biological and artificial memory systems. Current research focuses on developing computational models inspired by human memory mechanisms, such as semantic and episodic memory, and employing architectures like retrieval-augmented generation (RAG) and k-nearest neighbor (kNN) models to improve information access and reasoning capabilities in AI. These advancements have implications for improving AI systems' long-term conversational abilities, robot navigation, and personalized information management, as well as offering insights into the neural underpinnings of human memory.