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 ...
InfoQ

Building Hierarchical Agentic RAG Systems: Multi-Modal Reasoning with Autonomous Error Recovery

Traditional RAG systems struggle bridging structured SQL databases and unstructured document collections (a challenge we call the modality gap), leading to incomplete reasoning and hallucinations.
Hosted on MSN

RAG is dead: why enterprises are shifting to agent-based AI architectures

Recently, a new sentiment has emerged in AI security circles: "RAG is dead." I've observed firsthand how organizations are increasingly abandoning Retrieval-Augmented Generation (RAG) architectures in ...
Destination CRM

Oracle Launches Generative AI RAG Agent and Enhanced AI Services at CloudWorld

At its Oracle CloudWorld user conference in Las Vegs, Oracle introduced Oracle Cloud Infrastructure (OCI) Generative AI (GenAI) Agents with retrieval-augmented generation (RAG) capabilities and ...
Geeky Gadgets

Master the Art of Building RAG AI Agents with n8n – Step-by-Step Guide

Have you ever found yourself frustrated with AI systems that confidently provide answers, only to realize they’re riddled with inaccuracies? It’s a common pain point for anyone working with generative ...
Analytics Insight

Best Vector Database Options for RAG in 2026 Explained

Overview RAG is transforming AI apps, and vector databases are the engine behind accurate, real-time responsesChoosing the ...
Fast Company

True AI agents are agentic AI, not just dressed-up RAG

The Fast Company Executive Board is a private, fee-based network of influential leaders, experts, executives, and entrepreneurs who share their insights with our audience. BY Deon Nicholas AI agents ...
Geeky Gadgets

How to Build Enterprise AI Apps with Multi-Agent RAG Systems (MARS)

In the rapidly evolving landscape of enterprise AI, Multi-Agent Retrieval-Augmented Generation (MARS) systems are emerging as a cornerstone technology. These sophisticated systems, developed in ...
VentureBeat

MemRL outperforms RAG on complex agent benchmarks without fine-tuning

A new technique developed by researchers at Shanghai Jiao Tong University and other institutions enables large language model agents to learn new skills without the need for expensive fine-tuning. The ...