Shows
DM RadioGraph for RAG, Networking and MoreHow can we make AI models more reliable and accurate? Tune in to this episode of DM Radio as we explore Retrieval-Augmented Generation (RAG) and Graph RAG—two innovative approaches that keep large language models grounded, relevant, and free from hallucinations. Host Eric Kavanaugh welcomes Philip Rathle, CTO of Neo4j, and Jon Brewton, CEO of data², to discuss how knowledge graphs enhance AI’s ability to deliver precise, explainable, and context-aware insights.2025-02-2053 min
The Ravit ShowThe GraphRAG ManifestoWhat is GraphRAG? It was great covering GraphSummit by Neo4j as Press, where I had the privilege of interviewing Philip Rathle, CTO at Neo4j on The Ravit Show.
— We had an in-depth discussion on GraphRAG and its potential to transform the future of AI and data management. Some of the key topics we covered were:
— The inspiration behind writing the GraphRAG Manifesto and why it's crucial for the AI community
— The distinct differences between GraphRAG and traditional RAG, and how these differences unlock new possibilities
— How knowledge graphs significantly improve the performance of generative AI systems
— The impact Gra...2024-11-1514 min
AI Portfolio PodcastPhilip Rathle: GraphRAG, Neo4J CTO, Graphs and Vectors and Mission - AI Portfolio PodcastPhilip 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 Intro02:09 Is AI Resurgence of Graph tech?03:46 GraphRAG popularity05:39 Top Use Cases in GenAI11:08 Gen AI in supply chain16:46 Graph and its types in enterprise24:03 GraphRag25:25 GNNs in GraphRAG29:30 Graphs are eating...2024-11-071h 42
AI Engineering PodcastEnhancing AI Retrieval with Knowledge Graphs: A Deep Dive into GraphRAGSummaryIn this episode of the AI Engineering podcast, Philip Rathle, CTO of Neo4J, talks about the intersection of knowledge graphs and AI retrieval systems, specifically Retrieval Augmented Generation (RAG). He delves into GraphRAG, a novel approach that combines knowledge graphs with vector-based similarity search to enhance generative AI models. Philip explains how GraphRAG works by integrating a graph database for structured data storage, providing more accurate and explainable AI responses, and addressing limitations of traditional retrieval systems. The conversation covers technical aspects such as data modeling, entity extraction, and ontology use cases, as well as the infrastructure...2024-09-1059 min