Artículos del autor
30 de junio de 2025
K-means for building vector indices
We discuss optimizing k-means to efficiently create high quality vector indices
31 de mayo de 2025
Optimizing scalar quantization with sparse preconditioners
We discuss a sparse preconditioner to apply to vectors which results in more stable quantization performance with respect to data distribution.
7 de abril de 2025
Speeding up merging of HNSW graphs
Explore the work we’ve been doing to reduce the overhead of building multiple HNSW graphs, particularly reducing the cost of merging graphs.
23 de diciembre de 2024
Improve search results by calibrating model scoring in Elasticsearch
Learn how to leverage annotated data to calibrate semantic model scoring for better search results
19 de diciembre de 2024
Understanding optimized scalar quantization
In this post, we explain a new form of scalar quantization we've developed at Elastic that achieves state-of-the-art accuracy for binary quantization.
5 de diciembre de 2024
Exploring depth in a 'retrieve-and-rerank' pipeline
Select an optimal re-ranking depth for your model and dataset.
25 de noviembre de 2024
Introducing Elastic Rerank: Elastic's new semantic re-ranker model
Learn about how Elastic's new re-ranker model was trained and how it performs.
29 de octubre de 2024
What is semantic reranking and how to use it?
Introducing the concept of semantic reranking. Learn about the trade-offs using semantic reranking in search and RAG pipelines.
19 de septiembre de 2024
Evaluating search relevance part 2 - Phi-3 as relevance judge
Using the Phi-3 language model as a search relevance judge, with tips & techniques to improve the agreement with human-generated annotation.
16 de julio de 2024
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.
3 de mayo de 2024
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.
25 de abril de 2024
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.
25 de abril de 2024
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.
12 de marzo de 2024
Speeding up multi-graph vector search
Explore multi-graph vector search in Lucene and discover how sharing information between segment searches enhances search speed.
1 de diciembre de 2023
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.
17 de octubre de 2023
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.
17 de octubre de 2023
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.
20 de julio de 2023
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.
13 de julio de 2023
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.
13 de julio de 2023
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.
21 de junio de 2023
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.
20 de abril de 2022
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.