Live Q&A
summary
Live Q&A lays out concrete claims and product directions: Neo4j pushes a knowledge graph builder workflow that combines LLM-driven extraction with curated ontologies, recommends language‑specific embedding models (BERT and open‑source alternatives), and reports enterprise customers running more than 10 projects in production on shared knowledge layers. It frames the stack as models + compute + database, argues databases remain the deterministic system of record for state and multi‑agent coordination, and favors schema‑optional yet gradually explicit data models.
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chapters (7)
- 0:00Welcome and introduction
- 1:05AI bubble and industry trends
- 8:14AI adoption in organizations
- 14:36Graph modeling and schema balance
- 21:24Multilingual AI and knowledge graphs
- 24:35AI engineering and future databases
- 28:27State management in AI systems
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