Enhancing AI with Knowledge Graphs: Introducing the Graph of Reason

In this video, Joseph, also known as Professor Synapse, introduces a major update to his AI project, inspired by his work with knowledge graphs in Obsidian. The update focuses on enhancing the AI’s reasoning capabilities by integrating knowledge graphs and semantic triples, which consist of a subject, predicate, and object. This approach aims to improve the AI’s understanding of relationships between concepts, thereby reducing errors and hallucinations in its responses. Joseph demonstrates how he has incorporated these elements into the new version of Professor Synapse, which now showcases its thought process using a ‘Graph of Reason’ before responding to queries. He explains the structure of the new prompt, which includes caching memory, constructing a semantic knowledge graph, reasoning over the working memory and knowledge graph, and responding based on this reasoning. The video also highlights the importance of modeling the conversation as a dialogue rather than just instructions, leveraging the AI’s training on conversational data. Joseph provides a detailed walkthrough of the prompt’s components and demonstrates its practical application, showing how the AI updates its working memory and knowledge graph in real-time. He encourages viewers to test the new version and provides tips for troubleshooting any issues with the Graph of Reason feature.