MULTI-CALL MEMORY TO INTERJECT PREVIOUSLY GATHERED INFORMATION INTO A CONVERSATION BETWEEN AN ARTIFICIAL INTELLIGENCE (AI) AND A HUMAN

Abstract

A conversational artificial intelligence (AI) system is configured to engage in a multi-turn conversation with a user. The multi-turn conversation is substantially focused on a target topic. A conversation analyzer analyzes the multi-turn conversation to detect and store at least some turns in the multi-turn conversation that deviate from the target topic and instead characterize life attributes of the user. A knowledge graph constructor builds a knowledge graph for the user based on at least some turns in the multi-turn conversation that characterize the life attributes of the user. The knowledge graph translates the life attributes of the user into the user's life biography, including life chronology, life preferences, life milestones, life events, or any combination thereof. A knowledge graph applicator uses parts of the knowledge graph in a subsequent multi-turn conversation with the user by contextually interspersing portions of the user's life biography in the subsequent multi-turn conversation.

CPC Classifications