Latest Semantic-Search Articles

AI embeddings are numerical vector representations of data that capture useful semantic relationships. Text, images, products, users, documents, source code, and other objects can be converted into embeddings so that software can compare them mathematically rather than relying only on exact keywords

Vector databases are databases and search systems designed to store high-dimensional vectors and efficiently find vectors that are similar to a query vector. They are commonly used with AI embeddings to power semantic search, retrieval-augmented generation, recommendation systems, duplicate detectio