knowledge graphs with linear algebra and how it will impact RAG and explainability with LLMs. Is matrix multiplication the most effective way to query knowledge? Is Cypher or GQL the future of query languages?

Topics:

00:00 Intros

07:03 A different way of storing knowledge with FalkorDB

11:15 GraphBLAS

13:10 Sparse Matrices and Zeroes

17:35 Connecting linear algebra to Cypher

21:32 Semantic search and HNSW

26:04 Latency and knowledge graph queries

30:20 "The lack of explainability is disturbing"

34:18 Hybrid RAG systems

37:46 The focus will be on GraphRAG 🔗 FalkorDB Links: ➡️ Website: https://www.falkordb.com/ ➡️ GitHub: https://github.com/FalkorDB/FalkorDB ➡️ X/Twitter: https://x.com/falkordb ➡️ LinkedIn: https://www.linkedin.com/company/falkordb/ ➡️ Edges, GraphBLAS, spare matrices: https://www.falkordb.com/blog/edges-in-falkordb/ 🔗 TrustGraph Links: ➡️ GitHub: https://github.com/trustgraph-ai/trustgraph ➡️ TrustGraph Config UI: https://config-ui.demo.trustgraph.ai/ ➡️ Website: https://trustgraph.ai/ ➡️ Discord: https://discord.gg/sQMwkRz5GX

➡️ Bluesky: https://bsky.app/profile/trustgraph.bsky.social ➡️ Blog: https://blog.trustgraph.ai ➡️ LinkedIn: https://www.linkedin.com/company/trustgraph/