Blogs
Entwickler-Einblicke und praktische Anleitungen von unseren Experten, um Ihr Sucherlebnis zu inspirieren und zu verbessern
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...
Logs: Understanding TLS errors with ESRE and generative AI
Here's how to set up and use the Elasticsearch Relevance Engine (ESRE) with its Elastic Learned Sparse Encoder capability for log analysis and probe TLS issues.
Accessing machine learning models in Elastic
Explore the machine learning (ML) models supported in Elastic, the Eland library for loading models and how to apply transformers & NLP in Elastic.
Improving information retrieval in the Elastic Stack: Introducing Elastic Learned Sparse Encoder, our new retrieval model
Learn about the Elastic Learned Sparse Encoder (ELSER), its retrieval performance, architecture, and training process.
Introducing Elastic Learned Sparse Encoder: Elastic’s AI model for semantic search
Learn about the Elastic Learned Sparse Encoder (ELSER), an AI model for high relevance semantic search across domains.