Databricks research shows multi-step agents consistently outperform single-turn RAG when answers span databases and documents

Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with ...
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 ...
InfoQ

Redis Improves Performance of Vector Semantic Search with Multi-Threaded Query Engine

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Unite.AI

How to Build Reliable RAG: A Deep Dive into 7 Failure Points and Evaluation Frameworks

Retrieval-Augmented Generation (RAG) is critical for modern AI architecture, serving as an essential framework for building ...
KELOLAND News

MyScaleDB Open-sourced: the SQL Vector Database with High Performance

MyScaleDB, the innovative SQL vector database, is to announce that it is now open-source. It utilizes SQL queries to accelerate vector search and processing ...
SDxCentral

IBM and Nvidia tout content-aware storage on 100-billion vector database

In a collaboration with Nvidia and Samsung, IBM said it has demonstrated a content-aware storage (CAS) system that can hold a ...
InfoWorld

Oracle’s Database 23c gets vector search to underpin generative AI use cases

The semantic search capabilities added to the database offering include a new vector data type, vector indexes, and vector search SQL operators. Oracle is planning to add vector search capabilities to ...