How to build knowledge graphs that are fast enough for real-time LLM applications? FalkorDB is an open-source graph database that solves this by reimagining how graphs work. It uses sparse matrices and linear algebra instead of traditional traversal! But there's a problem: When you query for connections, the database walks through nodes and edges like following a map. For massive knowledge graphs powering AI agents, this creates a serious bottleneck. But what if you could represent the entire gr
How to build knowledge graphs that are fast enough for real-time LLM …
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26 reactions · 11 shares | Knowledge graphs capture complex relationships between diverse data types and enhance text retrieval beyond similarity search, boosting LLM context and RAG performance. In Knowledge Graphs for RAG, a short course taught by Andreas Kollegger from Neo4j, you’ll learn to build a knowledge graph from scratch and improve chat applications using text and graph data. Access the course for free: https://hubs.la/Q02WyPcC0 | DeepLearning.AI | Facebook
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