Articles
Improving information retrieval in the Elastic Stack: Improved inference performance with ELSER v2
Learn about the improvements we've made to the inference performance of ELSER v2.
Improving information retrieval in the Elastic Stack: Optimizing retrieval with ELSER v2
Learn about how we're reducing retrieval costs for ELSER v2.
RAG evaluation metrics: A journey through metrics
Explore RAG evaluation metrics like BLEU score, ROUGE score, PPL, BARTScore, and more. Discover how Elastic is evaluating RAG with UniEval.
Evaluating scalar quantization in Elasticsearch
Learn how scalar quantization can be used to reduce the memory footprint of vector embeddings in Elasticsearch through an experiment.
Evaluating search relevance - Part 1
How to evaluate your own search systems in the context of better understanding the BEIR benchmark, with specific tips and techniques to improve your search evaluation processes. Part 1 of the series.
Scalar Quantization Optimized for Vector Databases
Optimizing scalar quantization for the vector database use case allows us to achieve significantly better performance for the same retrieval quality at high compression ratios.
Understanding Int4 scalar quantization in Lucene
This blog explains how int4 quantization works in Lucene, how it lines up, and the benefits of using int4 quantization.
Improving information retrieval in the Elastic Stack: Introducing Elastic Learned Sparse Encoder, our new retrieval model
Deep learning has transformed how people retrieve information. We've created a retrieval model that works with a variety of text with streamlined processes to deploy it. Learn about the model's performance, its architecture, and how it was trained.
Speeding Up Multi-graph Vector Search
Sharing information among segment searches in multi-graph vector search allows us to achieve significant search speedups.