Business Wire

Qdrant Launches Groundbreaking Pure Vector-Based Hybrid Search, Setting Higher Standards for RAG and AI Applications

BERLIN & NEW YORK--(BUSINESS WIRE)--Qdrant, the leading high-performance open-source vector database, today announced the launch of BM42, a pure vector-based hybrid search approach that delivers more ...
Forbes

Qdrant Introduces BM42: Hybrid Search For Enhanced RAG

Qdrant, a leading provider of vector database solutions, has recently unveiled an innovative search technology called BM42. This new approach promises to revolutionize information retrieval, ...
VentureBeat

Vector database company Qdrant wants RAG to be more cost-effective

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More More companies are looking to include retrieval augmented generation (RAG ...
SD Times

Qdrant introduces alternative to BM25 search tailored to improving RAG retrieval

The vector database Qdrant has developed a new vector-based hybrid search capability, BM42, which provides accurate and efficient retrieval for RAG applications. The name is a reference to BM25, which ...
InfoWorld

Qdrant unveils vector-based hybrid search for RAG

Open-source vector database provider Qdrant has launched BM42, a vector-based hybrid search algorithm intended to provide more accurate and efficient retrieval for retrieval-augmented generation (RAG) ...
InfoWorld

Qdrant review: A highly flexible option for vector search

Vector database offers on-prem, cloud-native, or SaaS deployment, leading performance, a rich set of integrations and language drivers, and a dizzying array of optimization options. Efficient ...
Hosted on MSN

Local LLM setup: how to use RAG and an embedding model to stop wasting context

Local LLMs are fantastic, and they keep getting better at a staggering pace. I have non-negotiable reasons for preferring a local setup over relying on cloud giants like Claude or ChatGPT. Because of ...