When Pinecone announced a vector database at the beginning of last year, it was building something that was specifically designed for machine learning and aimed at data scientists. The idea was that you could query this data in a format that machines understand, making it much faster.
Originally this involved semantic searches where users could search based on meaning instead of specific words. It turns out, however, that as people put Pinecone to work, there were use cases where specific keywords mattered, and today the company announced that it’s now possible to conduct searches combining both semantic and …
