This podcast episode delves into the innovative realm of graph data science through the experiences of Tim Eastridge, who emphasizes the transformative power of knowledge graphs in various sectors such as fraud detection and private equity. Highlighting practical applications using Neo4j, Tim discusses the intricacies of managing complex data relationships, shares insights on generative AI, and outlines strategies for monetizing intellectual property through patent analysis. He encourages a balance between technology and human insight, advocating for continuous learning and the practical application of graph technology to solve real-world problems.
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