Seems like we are hearing a lot about GraphRAG these days, but there are lots of questions: what is it, is it hype, what is practical? One of our all time favorite podcast friends, Prashanth Rao, joins us to dig into this topic beyond the hype. Prashanth gives us a bit of background and practical use cases for GraphRAG and graph data.
Featuring
Sponsors
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Notes & Links
- Kùzu: A highly scalable, extremely fast, easy-to-use embeddable, open source graph database: GitHub repo
- The goals and vision of Kùzu: Blog post
- Kùzu YouTube channel
- Graph RAG strategies with Kùzu: GitHub repo
- Prashanth Rao’s blog: thedataquarry.com
Chapters
| Chapter Number | Chapter Start Time | Chapter Title | Chapter Duration |
| 1 | 00:00 | Welcome to Practical AI | 00:35 |
| 2 | 00:35 | Sponsor: Fly.io | 03:06 |
| 3 | 03:49 | Welcome back Prashanth | 04:52 |
| 4 | 08:41 | What are graphs? | 01:24 |
| 5 | 10:05 | DB vs graph experience | 03:26 |
| 6 | 13:31 | Data examples | 04:31 |
| 7 | 18:15 | Sponsor: Assembly AI | 02:21 |
| 8 | 20:45 | What is a RAG workflow? | 03:22 |
| 9 | 24:07 | GraphRAG/NaiveRAG | 04:47 |
| 10 | 28:54 | Hallucination risks | 01:59 |
| 11 | 30:54 | Building the data side | 04:33 |
| 12 | 35:35 | Sponsor: Speakeasy | 00:53 |
| 13 | 36:38 | Practical uses | 05:07 |
| 14 | 41:44 | Graph construction | 05:42 |
| 15 | 47:26 | Where is this headed? | 05:00 |
| 16 | 52:27 | Thanks for joining us! | 01:27 |
| 17 | 53:57 | Outro | 01:05 |