Fireside Q&A
summary
A live Q&A focuses on what actually moves graph + GenAI projects past pilots: presenters cite surveys showing 70–80% stalled in pilot, blame fuzzy use cases and a rapidly changing stack (LangChain, LlamaIndex, multiple daily model updates) and the probabilistic nature of LLMs. Concrete wins include parallel runtime making existing Cypher code faster, a unified Aura experience and import from Postgres via the Knowledge Graph Builder, and day‑to‑day developer boosts from GitHub Copilot for unit tests and boilerplate.
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chapters (7)
- 0:00Introduction and welcome
- 1:40About the event and speakers
- 6:57Challenges with Gen AI in production
- 14:09Gen AI in business and development
- 21:36Why nodes and relationships
- 27:15Recent Neo4j features
- 31:29Closing and next sessions
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