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/

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