The author discusses the concept of artificial intelligence (AI) and its various forms, including machine learning (ML). They argue that achieving AI is not just about building intelligent systems but also about understanding the structure of data, particularly graphs. Graphs are a powerful tool for analyzing complex relationships between entities and can be used to build intelligent systems without relying on ML frameworks. The author shares their personal history with graphs, from working on graph databases to applying graph search techniques to real-world problems like supermarket purchasing behavior and detecting spam. They highlight the benefits of using graph technology, including its ability to provide fast query results and extract valuable information from structured data. The author concludes that graph machine learning is a promising field that can help build intelligent applications without relying solely on ML pipelines.