Search Engine Land

GraphRAG: What entity-first retrieval means for SEO

GraphRAG explains why AI is shifting from isolated text to connected knowledge, and what that means for AI search optimization. Making your brand machine-readable and increasing its chances of being ...
IEEE

A Comparative Evaluation of RAG Architectures for Cross-Domain LLM Applications: Design, Implementation, and Assessment

Abstract: Retrieval-Augmented Generation (RAG) pairs large language models with external search to constrain knowledge staleness and hallucination, a critical need in finance and e-commerce where ...
The White House

PROMOTING ADVANCED ARTIFICIAL INTELLIGENCE INNOVATION AND SECURITY

Section 1. Purpose. The United States continues to lead the world in Artificial Intelligence (AI) because of the enormous talent and innovation of our AI industry, and because we refuse to stifle this ...
The New York Times

For Most Household Cleaning Tasks, Bring Back the Rag

We independently review everything we recommend. When you buy through our links, we may earn a commission. Learn more› By Caroline Mullen Caroline Mullen is a writer focused on cleaning and organizing ...
IEEE

EvaRAG: Evaluating Advanced RAG Techniques With Indexing and Distance Metrics

Abstract: Retrieval Augmented Generation (RAG) has emerged as a powerful paradigm for enhancing large language models (LLMs) with external knowledge. Yet, the performance of RAG pipelines is ...
VentureBeat

The RAG era is ending for agentic AI — a new compilation-stage knowledge layer is what comes next

The vector database category is undergoing a shift in response to the needs of agentic AI. The retrieval-augmented generation (RAG)-to-vector database pipeline doesn't cut it anymore; agentic AI ...
Virtualization Review

Running AI on a Raspberry Pi, Part 1: Overview

LLMs and RAG make it possible to build context-aware AI workflows even on small local systems. Running AI locally on a Raspberry Pi can improve privacy, offline access, and cost control. Performance, ...
GitHub

All RAG Techniques: A Simpler, Hands-On Approach

This repository takes a clear, hands-on approach to Retrieval-Augmented Generation (RAG), breaking down advanced techniques into straightforward, understandable implementations. Instead of relying on ...
VentureBeat

'Observational memory' cuts AI agent costs 10x and outscores RAG on long-context benchmarks

RAG isn't always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, those ...
GitHub

rag-index-setup.json

"content": "Table: dbo.Customers\nPurpose: Customer master data (dimension).\nPrimary key: CustomerId\nColumns:\n- CustomerId (int, PK)\n- CustomerName (nvarchar(200 ...