What is vector search? We explain everything developers should know about vector indexes, embeddings, and how to use them effectively with Pinecone. For many developers, the present problem is vector similarity search. The solution is Pinecone.| www.pinecone.io
Vector similarity search is a game-changer in the world of search. It allows us to efficiently search a huge range of media, from GIFs to articles — with incredible accuracy in sub-second timescales for billion+ size datasets.| www.pinecone.io
Similarity search is one of the fastest-growing domains in AI and machine learning. At its core, it is the process of matching relevant pieces of information together.| www.pinecone.io
Vector embeddings are one of the most fascinating and useful concepts in machine learning. They are central to many NLP, recommendation, and search algorithms. If you’ve ever used things like recommendation engines, voice assistants, language translators, you’ve come across systems that rely on embeddings.| www.pinecone.io
Hierarchical Navigable Small World (HNSW) graphs are among the top-performing indexes for vector similarity search[1]. HNSW is a hugely popular technology that time and time again produces state-of-the-art performance with super fast search speeds and fantastic recall.| www.pinecone.io