AI & Graph Technology: What Are Knowledge Graphs? - Neo4j Graph Database Platform

Last week in the first installment of our five-part blog series on AI and graph technology, we gave an overview of four ways graphs add context for artificial intelligence: context for decisions with knowledge graphs, context for efficiency with graph accelerated ML, context for accuracy with connected feature extraction, and context for credibility with AI explainability. This week, we examine knowledge graphs, which provide context for decision support (e.g., for call center staff or support engineers) and help ensure that answers are appropriate to the situation (e.g., autonomous vehicles in rainy driving conditions). This will give you insight into how a graph technology platform like Neo4j enhances AI with knowledge graphs. Knowledge Graphs: Context for Decisions One of the AI areas that's moved into production fastest is decision support. Let's say we're trying to solve a real-world problem: making a decision that requires a human to have the right contextual, relevant information and trying to automate or streamline that process in some way.