Blogs
Developer insights and practical how-to articles from our experts to inspire and empower your search experience.
Demystifying ChatGPT & LLMs: Different methods for building AI search
Explore the inner workings of ChatGPT and LLMs, and discover three effective approaches for building generative AI search experiences for specific domains.
Retrieval vs. poison — Fighting AI supply chain attacks
Learn about the supply chain vulnerabilities of artificial intelligence large language models (LLMs) 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 generative artificial intelligence (GAI) solution with 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.
Vector search in Elasticsearch: The rationale behind the design
In this blog, you'll learn how vector search has been integrated into Elasticsearch and the trade-offs that we made.
Improving information retrieval in the Elastic Stack: Hybrid retrieval
In this blog we introduce hybrid retrieval and explore two concrete implementations in Elasticsearch. We explore improving Elastic Learned Sparse Encoder’s performance by combining it with BM25 using Reciprocal Rank Fusion and Weighted Sum of Scores.
Improving information retrieval in the Elastic Stack: Steps to improve search relevance
In this first blog post, we will list and explain the differences between the primary building blocks available in the Elastic Stack to do information retrieval.
Improving information retrieval in the Elastic Stack: Benchmarking passage retrieval
In this blog post, we'll examine benchmark solutions to compare retrieval methods. We use a collection of data sets to benchmark BM25 against two dense models and illustrate the potential gain using fine-tuning strategies with one of those models.
Relativity uses Elasticsearch and Azure OpenAI to build AI search experiences
With Elasticsearch Relevance Engine, you can create AI-powered search apps. Learn how Relativity uses Elastic & Azure Open AI for this goal.
Exploring vector databases: how to get the best of lexical and AI-powered search with Elastic’s vector database
Learn about the concepts related to vector databases, how they work and how to get the best out of lexical & AI search with Elastic’s vector database.
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: Elastic's Gen AI & LLMs journey
Learn how Elastic is at the forefront of the generative AI & Large Language Models (LLMs) revolution, helping users take LLMs to new...
