Enterprise adoption of retrieval-augmented generation has moved sensitive corporate content into a new storage format that existing security tools cannot inspect. Companies deploying internal AI ...

Vector databases power RAG, semantic search, recommendations, and memory. Learn how indexing, filtering, and hybrid retrieval ...

Google has introduced Gemini Embedding 2, its latest multimodal AI model designed to process text, images, video, audio and documents in a unified vector space. AI has been changing swiftly to the non ...

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...

AWS announced updates to Knowledge Bases for Amazon Bedrock, which is a new capability announced at AWS re:Invent 2023 that allows organizations to provide information from their own private data ...

Google announced a new multi-vector retrieval algorithm called MUVERA that speeds up retrieval and ranking, and improves accuracy. The algorithm can be used for search, recommender systems (like ...

Vector embeddings are numerical representations that capture the relationships and meaning of words, phrases and other data types. Through vector embeddings, essential characteristics or features of ...

A vector database is a type of database technology that's used to store, manage and search vector embeddings, numerical representations of unstructured data that are also referred to simply as vectors ...