This article is the first in a series of five that will dive into the intricacies of vector search, also known as semantic search, and how it is implemented in OpenSearch and Elasticsearch. This first part focuses on providing a general introduction to the basics of embedding vectors and how...
Zobraziť o 5 viac Principal author:Foteini Savvidou Searching over text documents, images, and audio files and finding similar ones is one of the most common tasks we do in our daily lives. Conventional search systems rely on exact matches on properties like keywords, tags...
Vector search and similarity search,AnalyticDB:AnalyticDB for MySQL provides the vector search feature to help you implement similarity search on unstructured data. This topic describes the vector search feature and how to create and use vector in...
Withpublic preview of integrated vectorization, a ground-breaking capability of vector search in Azure AI Search (previously Azure Cognitive Search), you can do vector search with data stored in Azure SQL Database easily. This feature is designed to streamline the process of chunking, generating, ...
Open-source vector similarity search for PostgresStore your vectors with the rest of your data. Supports:exact and approximate nearest neighbor search single-precision, half-precision, binary, and sparse vectors L2 distance, inner product, cosine distance, L1 distance, Hamming distance, and Jaccard ...
Learn how to use the Search REST APIs to create, load, and query vectors in Azure AI Search.In Azure AI Search, a vector store has an index schema that defines vector and nonvector fields, a vector configuration for algorithms that create the embedding space, and settings on vector field ...
Search for downloads To the Download-Center VectorCAST Software Test Automation for High Quality Software Automating Software Testing with VectorCAST The VectorCAST embedded software testing platform is a family of products that automates testing activities across the software development lifecycle. The purpo...
Vearch is a cloud-native distributed vector database for efficient similarity search of embedding vectors in your AI applications. Key features Hybrid search: Both vector search and scalar filtering. Performance: Fast vector retrieval - search from millions of objects in milliseconds. ...
A search for pair-produced heavy vector-like charge-2/3 quarks, T, in pp collisions at a center-of-mass energy of 7 TeV, is performed with the CMS detector at the LHC. Events consistent with the flavor-changing-neutral-current decay of a T quark to a top quark and a Z boson are ...
Explore AI Vector Search using RAG and enterprise LLMs for highly relevant, contextual results in similarity searches and more with your business data.