Wisdom-Driven Knowledge Augmented Generation at Scale - Chin Keong Lam, Patho AI
The main thesis of the video is that by using a Wisdom-Driven Knowledge Graph, we can significantly enhance the quantitative analysis capabilities of Knowledge-Augmented Generation (KAG) systems. This allows for the creation of smarter AI systems that can not only retrieve information but also understand, reason, and provide expert-level advice. The talk argues that this approach surpasses traditional Retrieval-Augmented Generation (RAG) systems, which primarily rely on unstructured vector search.
00:00 Introduction to Patho AI and KAG
01:09 Defining Knowledge and Knowledge Graphs
01:56 KAG v…
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Chapters (11)
Introduction to Patho AI and KAG
1:09
Defining Knowledge and Knowledge Graphs
1:56
KAG vs. RAG
2:37
The Wisdom-Decision Making-Situation Diagram
6:26
Practical Application: Competitive Analysis Chatbot
8:37
Implementation with N8n and Multi-Agent System
11:37
Why Use Knowledge Graphs over RAG
14:01
Challenges with Vector RAG and Numerical Reasoning
15:34
Building KAG Systems and Hybrid Models
16:45
Graph Extraction and Benchmarks
17:42
Conclusion and Resources
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