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.Keep reading
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.
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.
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
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.
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
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.
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.
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.