Category: Vector Database

Articles tagged Vector Database

Subscribe
Filters
AI plagiarism: Plagiarism detection with Elasticsearch
Elasticsearch Labs

AI plagiarism: Plagiarism detection with Elasticsearch

Here's how to check for AI plagiarism using Elasticsearch, focusing on use cases with NLP models and Vector Search.

Priscilla Parodi
Introducing kNN Query: An expert way to do kNN search
Elasticsearch Labs

Introducing kNN Query: An expert way to do kNN search

Explore how the kNN query in Elasticsearch can be used and how it differs from top-level kNN search, including examples.

Mayya Sharipova
Understanding fused multiply-add (FMA) within vector similarity computations in Lucene
Elasticsearch Labs

Understanding fused multiply-add (FMA) within vector similarity computations in Lucene

Learn how to use fused multiply-add (FMA) within vector similarity computations in Lucene and discover how FMA can improve performance.

Chris Hegarty
Vector search & kNN implementation guide - API edition
Elasticsearch Labs

Vector search & kNN implementation guide - API edition

Learn how to implement vector search and kNN using the Elasticsearch APIs via HTTP or Python.

Jeff Vestal
Chunking large documents via ingest pipelines plus nested vectors equals easy passage search
Elasticsearch Labs

Chunking large documents via ingest pipelines plus nested vectors equals easy passage search

Learn how to chunk large documents using ingest pipelines and nested vectors in Elasticsearch for easy passage search in vector search.

Michael Heldebrant
Implementing image search: vector search via image processing in Elasticsearch
Elasticsearch Labs

Implementing image search: vector search via image processing in Elasticsearch

Learn how to implement image search with an example. This blog covers how to use vector search through image processing in Elasticsearch.

Alex Salgado
Using hybrid search for gopher hunting with Elasticsearch and Go
Elasticsearch Labs

Using hybrid search for gopher hunting with Elasticsearch and Go

Learn how to achieve hybrid search by combining keyword and vector search using Elasticsearch and the Elasticsearch Go client.

Carly Richmond
Perform vector search in Elasticsearch with the Elasticsearch Go client
Elasticsearch Labs

Perform vector search in Elasticsearch with the Elasticsearch Go client

Learn how to perform vector search in Elasticsearch using the Elasticsearch Go client through a practical example.

Carly Richmond
Elasticsearch as a GenAI caching layer
Elasticsearch Labs

Elasticsearch as a GenAI caching layer

Explore how integrating Elasticsearch as a caching layer optimizes Generative AI performance by reducing token costs and response times, demonstrated through real-world testing and practical examples.

Jeff Vestal
Lexical and semantic search with Elasticsearch
Elasticsearch Labs

Lexical and semantic search with Elasticsearch

In this blog, we'll explore various approaches to retrieving information using Elasticsearch, focusing on lexical and semantic search.

Priscilla Parodi
Multilingual vector search with the E5 embedding model
Elasticsearch Labs

Multilingual vector search with the E5 embedding model

Here's how multilingual vector search works and how to use Elasticsearch with the multilingual E5 embedding model, including examples.

Josh Devins
Adding passage vector search to Lucene
Elasticsearch Labs

Adding passage vector search to Lucene

Here's how to add passage vectors to Lucene, the benefits of doing so and how existing Lucene structures can be used to create an efficient retrieval experience.

Benjamin Trent