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The Fusion of Graph Databases and AI with FalkorDB CTO Roi Lipman

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Manage episode 472349803 series 3203753
Content provided by Arun Trivedi. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Arun Trivedi or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

This podcast features a discussion with Roi Lipman, CTO and co-founder of FalkorDB, about the intersection of graph databases and AI, particularly large language models. Lipman explains FalkorDB's origins from RedisGraph and its focus on high-performance graph technology. He highlights the resurgence of knowledge graphs for representing factual data and their application in Retrieval-Augmented Generation (RAG) to enhance LLM accuracy with private data. The conversation further explores the capabilities of AI agents, especially multi-agent systems, and the advantages of graph databases over vector databases for specific AI agent tasks. Lipman also introduces Code Graph, FalkorDB's initiative for code analysis, and outlines its potential to improve code understanding, refactoring, and developer onboarding.

  continue reading

60 episodes

Artwork
iconShare
 
Manage episode 472349803 series 3203753
Content provided by Arun Trivedi. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Arun Trivedi or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

This podcast features a discussion with Roi Lipman, CTO and co-founder of FalkorDB, about the intersection of graph databases and AI, particularly large language models. Lipman explains FalkorDB's origins from RedisGraph and its focus on high-performance graph technology. He highlights the resurgence of knowledge graphs for representing factual data and their application in Retrieval-Augmented Generation (RAG) to enhance LLM accuracy with private data. The conversation further explores the capabilities of AI agents, especially multi-agent systems, and the advantages of graph databases over vector databases for specific AI agent tasks. Lipman also introduces Code Graph, FalkorDB's initiative for code analysis, and outlines its potential to improve code understanding, refactoring, and developer onboarding.

  continue reading

60 episodes

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