Articles
Aggregate data faster with new the random_sampler aggregation
Aggregate billions of documents in milliseconds instead of minutes with Elastic. Learn more about how the new random_sampler aggregation gives you statistically robust results at a lower cost.
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, achieving a 60% to 120% speed increase over ELSER v1.
Improving information retrieval in the Elastic Stack: Optimizing retrieval with ELSER v2
Learn how we are reducing the retrieval costs of the Learned Sparse EncodeR (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 - The BEIR benchmark
Learn to evaluate your search system in the context of better understanding the BEIR benchmark, with tips & techniques to improve your search evaluation processes.
Evaluating search relevance part 2 - Phi-3 as relevance judge
Using the Phi-3 language model as a relevance judge, with tips & techniques to improve the agreement with human-generated annotation
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.
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.
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
Learn about the Elastic Learned Sparse Encoder (ELSER), its retrieval performance, architecture, and training process.
Speeding Up Multi-graph Vector Search
Explore multi-graph vector search in Lucene and discover how sharing information between segment searches enhances search speed.