A comprehensive guide to modern sparse neural retrievers: COIL, TILDEv2, SPLADE, and more. Find out how they work and learn how to use them effectively.
Evgeniya Sukhodolskaya
·October 23, 2024
A summary of my work and experience at Qdrant Summer of Code 2024.
Huong (Celine) Hoang
·October 14, 2024
Discover what a vector database is, its core functionalities, and real-world applications.
Sabrina Aquino
·October 09, 2024
In this article, we'll teach you about compression methods like Scalar, Product, and Binary Quantization. Learn how to choose the best method for your specific application.
Sabrina Aquino
·September 25, 2024
Learn everything about filtering in Qdrant. Discover key tricks and best practices to boost semantic search performance and reduce Qdrant's resource usage.
Sabrina Aquino, David Myriel
·September 10, 2024
My journey as a Qdrant Summer of Code 2024 participant working on enhancing vector visualization using WebAssembly (WASM) based dimension reduction.
Jishan Bhattacharya
·August 31, 2024
Learn how immutable data structures improve vector search performance in Qdrant.
Andrey Vasnetsov
·August 20, 2024
We recently discovered that embedding models can become late interaction models & can perform surprisingly well in some scenarios. See what we learned here.
Kacper Łukawski
·August 14, 2024
Our new Query API allows you to build a hybrid search system that uses different search methods to improve search quality & experience. Learn more here.
Kacper Łukawski
·July 25, 2024
Introducing BM42 - a new sparse embedding approach, which combines the benefits of exact keyword search with the intelligence of transformers.
Andrey Vasnetsov
·July 01, 2024
Discover how Qdrant's Role-Based Access Control (RBAC) ensures data privacy and compliance for your AI applications. Build secure and scalable systems with ease. Read more now!
Qdrant Team
·June 18, 2024
Learn how Qdrant-powered RAG applications can be tested and iteratively improved using LLM evaluation tools like Quotient.
Atita Arora
·June 12, 2024
Semantic cache is reshaping AI applications by enabling rapid data retrieval. Discover how its implementation benefits your RAG setup.
Daniel Romero, David Myriel
·May 07, 2024
Explore how RAG enables LLMs to retrieve and utilize relevant external data when generating responses, rather than being limited to their original training data alone.
Sabrina Aquino
·March 19, 2024
