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Podcasts ›› Do GraphDBs give large language models (LLMs) context for doing real work? with Dr. Jim Webber, Neo4j

Do GraphDBs give large language models (LLMs) context for doing real work? with Dr. Jim Webber, Neo4j

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Robb and Josh go deep on a conversation with Dr. Jim Webber, Chief Scientist at Neo4j, about the convergence of large language models (LLMs) and graph databases. Popularized by Neo4j, graph DB creates databases that connects individual data points (or nodes) across a network of information. LLMs are capable of doing real work and providing more reliable responses when they are given context. Graph DBs can leverage all types of data across and organization to provide that context and elevate operations to new heights. This is an exciting discussion about the future of data that will captivate scientists and designers alike.

Dr. Jim Webber is Neo4j’s Chief Scientist and Visiting Professor at Newcastle University. At Neo4j, Jim leads the Systems Research Group, working on a variety of database research topics with a focus on fault tolerance. He also co-authored several books on graph technology including Graph Databases (1st and 2nd editions, O’Reilly), Graph Databases for Dummies (Wiley), and Building Knowledge Graphs (O’Reilly).

Prior to Neo4j, Jim worked on fault-tolerant distributed systems. First at Newcastle University startup Arjuna and then for a variety of clients for the global consulting firm ThoughtWorks. Along the way, Jim co-authored the distributed systems books REST in Practice (O’Reilly) and Developing Enterprise Web Services – An Architect’s Guide (Prentice Hall).

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