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Launching your first vector engine on Amazon OpenSearch Serverless | Amazon Web Services
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The vector engine for Amazon OpenSearch Serverless introduces a simple, scalable, and high-performing vector storage and search capability that helps developers build machine learning (ML)–augmented search experiences and generative artificial intelligence (AI) applications without having to manage the vector database infrastructure. Get contextually relevant responses across billions of vectors in milliseconds by querying vector embeddings, which can be combined with text-based keywords in a single hybrid request.
This video provides a deep dive into the configuration steps for creating an Amazon OpenSearch Serverless collection for building Semantic Search application, using the vector engine.
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Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster.
#AmazonOpenSearch #SemanticSearch #VectorEngine #AWS #AmazonWebServices #CloudComputing
This video provides a deep dive into the configuration steps for creating an Amazon OpenSearch Serverless collection for building Semantic Search application, using the vector engine.
Subscribe:
Do you have technical AWS questions?
ABOUT AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster.
#AmazonOpenSearch #SemanticSearch #VectorEngine #AWS #AmazonWebServices #CloudComputing
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