Josh Devins

Multilingual vector search with the E5 embedding model

In this post we'll introduce multilingual vector search. We'll use the Microsoft E5 multilingual embedding model, which has state-of-the-art performance in zero-shot and multilingual settings. We'll walk through how multilingual embeddings work in general and then how to use E5 in Elasticsearch.

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Multilingual vector search with the E5 embedding model

Recent Articles

Demystifying ChatGPT: Different methods for building AI search

Demystifying ChatGPT: Different methods for building AI search

In this blog, we look at how ChatGPT works, and consider three approaches to build generative AI like search experiences for specific domains.

Sherry Ger

Retrieval vs. poison — Fighting AI supply chain attacks

Retrieval vs. poison — Fighting AI supply chain attacks

In this post, learn about the supply chain vulnerabilities of artificial intelligence large language models and how the AI retrieval techniques of search engines can be used to fight misinformation and intentional tampering of AI.

Dave Erickson

Generative AI using Elastic and Amazon SageMaker JumpStart

Generative AI using Elastic and Amazon SageMaker JumpStart

Learn how to build a GAI solution by exploring Amazon SageMaker JumpStart, Elastic, and Hugging Face open source LLMs using the sample implementation provided in this post and a data set relevant to your business.

Uday Theepireddy, Ayan Ray

Vector search in Elasticsearch: The rationale behind the design

Vector search in Elasticsearch: The rationale behind the design

There are different ways to implement a vector database, which have different trade-offs. In this blog, you'll learn more about how vector search has been integrated into Elastisearch and the trade-offs that we made.

Adrien Grand

Relativity uses Elasticsearch and Azure OpenAI to build futuristic search experiences, today

Relativity uses Elasticsearch and Azure OpenAI to build futuristic search experiences, today

Elasticsearch Relevance Engine is a set of tools for developers to build AI-powered search applications. Relativity, the eDiscovery and legal search tech company, is building next-generation search experience with Elastic and Microsoft Azure Open AI.

Hemant Malik, Aditya Tripathi

How to get the best of lexical and AI-powered search with Elastic’s vector database

How to get the best of lexical and AI- powered search with Elastic’s vector database

Elastic has all you should expect from a vector database — and much more! You get the best of both worlds: traditional lexical and AI-powered search, including semantic search out of the box with Elastic’s novel Learned Sparse Encoder model.

Bernhard Suhm

Open-sourcing sysgrok — An AI assistant for analyzing, understanding, and optimizing systems

Open- sourcing sysgrok — An AI assistant for analyzing, understanding, and optimizing systems

Sysgrok is an experimental proof-of-concept, intended to demonstrate how LLMs can be used to help SWEs and SREs understand systems, debug issues, and optimize performance.

Sean Heelan

The generative AI societal shift

The generative AI societal shift

Learn how Elastic is at the forefront of the Large Language Models revolution –– helping users take LLMs to new heights by providing real-time information and integrating LLMs into search, observability, and security systems for data analysis.

Jeff Vestal