Pinecone CEO on bringing vector similarity search to dev teams

All the sessions from Transform 2021 are available on-demand now. The traditional way for a database to answer a query is with a list of rows that fit the criteria. If there's any sorting, it's done by one field at a time. Vector similarity search looks for matches by comparing the likeness of objects, as captured by machine learning models. Vector similarity search is particularly useful with real-world data because that data is often unstructured and contains similar yet not identical items.