Author’s articles
December 19, 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
December 5, 2024
Exploring depth in a 'retrieve-and-rerank' pipeline
Select an optimal re-ranking depth for your model and dataset.
November 25, 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.
October 29, 2024
What is semantic reranking and how to use it?
Learn about the trade-offs using semantic reranking in search and RAG pipelines.
September 19, 2024
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
July 16, 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.
May 3, 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.
April 25, 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.
April 25, 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.