Jul 24, 2023 · In this blog, you'll learn how vector search has been integrated into Elasticsearch and the trade-offs that we made.
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Vector search leverages machine learning (ML) to capture the meaning and context of unstructured data, including text and images, transforming it into a ...
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Apr 17, 2024 · In this blog post we'll take a deep dive into our efforts on making the onboarding experience to kNN search just a bit easier!
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For this reason, searches are synchronous by default. The search request waits for complete results before returning a response. However, complete results can ...
Feb 23, 2024 · The primary reason for the speedup is that we're able to pack the full 128-bit register with values and operate on all of them without ...
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Vector search provides the foundation for implementing semantic search for text or similarity search for images, videos, or audio. Retrieve relevant context ...
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A vector database is a database that stores information as vectors, which are numerical representations of data objects, also known as vector embeddings.
This workbook demonstrates similiarity search using SparseVectorRetrievalStrategy (ELSER). First, we split the documents into chunks using langchain and then ...
The dense_vector field type stores dense vectors of numeric values. Dense vector fields are primarily used for k-nearest neighbor (kNN) search.
Duration: 26:55
Posted: Feb 13, 2023
Posted: Feb 13, 2023
Build accurate, fast, and scalable applications using vector data and similarity search. No need to maintain infrastructure, monitor services, or...