#Neo4j
9 articles with this tag
Neo4j: AI on Lakehouse with Context in Shapes
Neo4j's Zach Blumenfeld explores how AI agents can overcome data context limitations using graph representations, focusing on warehouse and document data.
Gates Foundation's Mike Phipps on Data Models as AI Moats
Mike Phipps of the Gates Foundation details how a robust data model is key to building defensible AI, showcasing their Strategic Intelligence Platform (SIP).
AI Assistants Need Graph Memory, Not Just More Tokens
Stephen Chin of Neo4j discusses how graph databases offer superior memory solutions for AI assistants compared to traditional file storage or vector databases.
Neo4j CEO on AI Agents and Ontology-based Data
Neo4j CEO Emil Eifrem proposes an ontology-based semantic layer to streamline data management for AI agents, enabling 'thin agents on a smarter substrate'.
Neo4j's Zach Blumenfeld on AI Agents and Decision Traces
Neo4j's Zach Blumenfeld explains why AI agents need decision traces and how context graphs, powered by Neo4j, can provide the necessary memory and reasoning capabilities for more accurate and accountable AI.
Neo4j: Context Graphs for AI Agents
Neo4j experts Andreas Kollegger and Zaid Zaim discuss how context graphs enhance AI agents for explainable and decision-aware operations.
Neo4j's Stephen Chin on Context Graphs for AI
Stephen Chin from Neo4j discusses how context graphs, built on knowledge graph technology, are essential for creating explainable and context-aware AI agents.
Neo4j CEO Emil Eifrem on Graph Databases and AI
Neo4j CEO Emil Eifrem discusses the symbiotic relationship between graph databases and AI, highlighting how relational context is crucial for modern AI applications.
