Philip Rathle, the Chief Technical Officer of Neo4j, the popular graph database company which has now taken off by storm because of GraphRag, a new approach for making LLM Retrieval Augmented Generation applications more accurate by leveraging graphs, so you know today will be all about GraphRag and its impact on the market.
Chapters:
00:00 Intro
02:09 Is AI Resurgence of Graph tech?
03:46 GraphRAG popularity
05:39 Top Use Cases in GenAI
11:08 Gen AI in supply chain
16:46 Graph and its types in enterprise
24:03 GraphRag
25:25 GNNs in GraphRAG
29:30 Graphs are eating the world
35:16 Knowledge Graph
36:06 Drawbacks of vector based rag
37:43 Neo4j vector database
41:27 Filtering with Knowledge Graph
45:02 Execution Time of LLMs
49:03 Does longer prompts mean longer graph query?
54:26 Scale of Graph
57:05 Marriage of Graphs and Vectors
59:46 Fine Tuning with Graphs
01:00:46 Graphs Use less tokens
01:02:46 Multiple vs One GraphRAG
01:05:38 Updating Knowledge in Graph
01:10:50 large Vs small models
01:13:09 MultiModal GraphRAG
01:15:36 Graphs in Robotics
01:17:11 Neo4j journey
01:20:03 Phillip Linkedin Post
01:21:56 What's different with AI
01:23:31 Advice for Gen AI startups
01:26:00 CTO advice
01:29:36 Chemical Engineering
01:32:00 Career optimization function
01:35:00 Book Recommendations
01:37:06 Rapid Round
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