From 18be6a3475c28894cc6e6e7990cc2d56de3a6670 Mon Sep 17 00:00:00 2001 From: Jael Gu Date: Wed, 18 Sep 2024 13:29:25 +0800 Subject: [PATCH] Add more resources Signed-off-by: Jael Gu --- README.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/README.md b/README.md index d97e408..067bb73 100644 --- a/README.md +++ b/README.md @@ -74,3 +74,11 @@ Query embedding in Faiss **Returns:** *Entity* Return the results in Faiss with `key` and `score`. + + +# More Resources + +- [Zilliz Triumphed in Billion-Scale ANN Search Challenge of NeurIPS 2021 - Zilliz Newsroom; Zilliz Triumphed in Billion-Scale ANN Search Challenge of NeurIPS 2021](https://zilliz.com/news/zilliz-triumphed-Neurips-2021): Zilliz team has won the first place in the Disk-based ANN Search track in NeurIPS 2021. The performance of BBAnn developed by Zilliz research team peaked during the search in the SimSearchNet++ dataset. +- [What is Faiss (Facebook AI Similarity Search)? - Zilliz blog](https://zilliz.com/learn/faiss): Faiss (Facebook AI similarity search) is an open-source library for efficient similarity search of unstructured data and clustering of dense vectors. +- [What is approximate nearest neighbor search (ANNS)?](https://zilliz.com/glossary/anns): Learn how to use Approximate nearest neighbor search (ANNS) for efficient nearest-neighbor search in large datasets. +- [Setting Up With Facebook AI Similarity Search (FAISS) - Zilliz blog](https://zilliz.com/blog/set-up-with-facebook-ai-similarity-search-faiss): Here's your FAISS tutorial that helps you set up FAISS, get it up and running, and demonstrate its power through a sample search program. \ No newline at end of file