“Beauty will save the world”— Fyodor Dostoevsky A. Introduction did not emerge overnight. Today’s transformer-based systems can feel almost magical, capable of capturing context and even subtle relationships between ideas. But the origin of today’s semantic search systems is actually gradual. Before embeddings, transformers, and large language models, researchers used keyword matching, TF–IDF vectors, and traditional machine learning methods to analyze text. Many of those earlier ideas never truly disappeared. In fact, modern systems still build on concepts developed decades ago. The field evolved layer by layer, with each generation solving some problems while exposing new ones. Understanding that evolution is important. In machine learning, as in science generally, knowing where we came from often helps us understand where we are heading.…