Practical Trends in Graphs and AI with Paco Nathan
In this episode of the Graph Geeks in Discussion podcast, join host Amy Hodler and special guest Paco Nathan as they unpack the latest trends in AI and graph technology. They dive into insights from recent conferences, highlighting a shift toward practical, programmatic uses of generative AI within the software development lifecycle. Paco explains how companies are moving beyond simple code generation to focus on real-world applications like fault detection and root cause analysis. The conversation also explores the rise of hybrid AI—combining neural networks with symbolic systems like knowledge graphs—to create more efficient and explainable models. Whether you're a developer, data scientist, or just curious about the future of AI, this episode offers a deep dive into the innovations driving the industry forward, from the promise of neurosymbolic AI to the practical use cases of Graph RAG.
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Real-Life Lessons for Tech Leaders with Denise Gosnell
In this discussion with Dr. Denise Gosnell, an entrepreneur, business strategist, and author. Denise shares insights from her impressive career—from a college athlete to a PhD, to leading graph teams at AWS and Datastax—and discusses the inspiration behind her new book, Tech Confidential: An Insider's Playbook for Daring Entrepreneurs. She reveals how the book, structured like an onion with layers on ego, team dynamics, product-market fit, and exit strategies, provides a no-nonsense guide to navigating the tech industry. We also dive into why graph technology hasn't yet gone mainstream and discuss the importance of embracing chaos and having a coach, reminding listeners that you should never try to succeed alone.Playbook and resources: https://www.techconfidential.ai/
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AI Readiness with Sumit Pal former Gartner research VP
Join host Amy Hodler and guest Sumit Pal, a former Gartner research VP and current Strategic Technology Director at Graphwise, as they dive into the power of graph technology and its impact on AI. They discuss how graph-based data gives AI the crucial context it needs to deliver better results.In this podcast:How graphs help make data "AI-ready" by resolving quality issues and providing critical context.The difference between what a traditional AI model can do with flat data (what happened) versus what a graph-enhanced model can do (why it happened).Why the future of AI might be in smarter, more domain-specific Small Language Models (SLMs) rather than just massive LLMs.How Graph RAG can dramatically improve AI outputs.Follow up with Graphwise on https://graphwise.ai/.
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Exploring GraphRAG with Neo4j's Tomaz Bratanic
Join us for an insightful discussion with Tomaz Bratanic, Graph ML and GenAI Research expert at Neo4j, as we dive deep into the world of GraphRAG and his newly released book "Essential GraphRAG – a practical guide to combining Knowledge Graphs with Retrieval-Augmented Generation (RAG)" (Manning Publications, co-authored with Oskar Hane).We explore how GraphRAG enhances LLM accuracy by combining the power of knowledge graphs with retrieval-augmented generation, covering everything from vector similarity search to agentic RAG systems. Tomaz also shares his unconventional journey from professional poker player to graph researcher.Key Topics Covered:The importance of incorporating more than just unstructured textAdvanced retrieval strategies and Text2Cypher generationBuilding knowledge graphs with LLMs and Microsoft's GraphRAG approachResources:📘 Free eBook from Neo4j: https://neo4j.com/essential-graphrag/
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Graph-Wide Scanning for Cybersecurity
Join Amy Hodler, David Haglin (Rocketgraph), and David Hughes (Enterprise Knowledge) as they explore graph-wide scanning and its role in revolutionizing cybersecurity. Discover how graphs are eliminating blind spots, detecting advanced persistent threats, and transforming how analysts find crucial insights in massive datasets. Learn why traditional methods fall short and how AI integration is key to navigating the colossal scale of cyber data for unprecedented clarity and threat detection.Want to take Rocketgraph for a spin? https://rocketgraph.com/free-trial/
Graphs are the data model for connected data. Graph technology enables us to capture and compute over interdependent relationships. Join us to hear from experts and practitioners as we chat about the latest innovations and research.Visit GraphGeeks.org to learn more about our community.
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