Скачать или смотреть GFM-RAG Explained | Graph-Based RAG That Thinks Like Humans

In this video, I explain GFM-RAG-8M, a next-generation Graph-based Retrieval Augmented Generation (RAG) model that goes beyond simple keyword search and performs real reasoning over knowledge graphs.

Traditional RAG systems often fail when questions require multi-document understanding or logical connections. GFM-RAG solves this by converting documents into a Knowledge Graph and using a Graph Neural Network (Graph Foundation Model) to retrieve the most relevant information.

I break down:

What problem GFM-RAG is designed to solve

Why graph-based reasoning is better than vector search

How Knowledge Graph Indexing works

What makes GFM-RAG different from normal RAG and GraphRAG

Real-world use cases like research, medical, and AI agents

This explanation is beginner-friendly, practical, and perfect for anyone working with LLMs, RAG systems, AI agents, or knowledge graphs.

If you’re building advanced AI applications or want to understand the future of RAG systems, this video is for you.

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