InfoQ

Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Birgitta Böckeler, Distinguished Engineer at ...
VentureBeat

Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a ...
Forbes

How RAG Continues To ‘Tailor’ Well-Suited AI

AI solves everything. Well, it might do one day, but for now, claims being lambasted around in this direction may be a little overblown in places, with some of the discussion perhaps only (sometimes ...
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 ...
VentureBeat

Agents need vector search more than RAG ever did

What's the role of vector databases in the agentic AI world? That's a question that organizations have been coming to terms with in recent months. The narrative had real momentum. As large language ...
Business Wire

KIOXIA AiSAQ™ Software Advances AI RAG with New Version of Vector Search Library

TOKYO--(BUSINESS WIRE)--In an ongoing effort to improve the usability of AI vector database searches within retrieval-augmented generation (RAG) systems by optimizing the use of solid-state drives ...
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) ...