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Join David Hughes (GraphGeeks community) for a Graph Chat with Chang She, CEO and Co-founder of LanceDB, filmed at the ODSC conference.
Chang shares groundbreaking insights on how agentic retrieval systems are challenging traditional RAG approaches, requiring much higher throughput and iterative search. The conversation highlights the new Lance Format as the multimodal Lakehouse standard optimized for AI data operations.
Most excitingly for the graph community, Chang provides a first introduction on the new open-source project, Lance Graph, which enables storing graph schemas and executing Cypher-like queries directly on Lance tables, integrating vector, tabular, and graph data into a unified format.
Learn why data differentiation is the key to winning in the age of AI agents.
https://lancedb.com/
By Amy Hodler3.7
33 ratings
Join David Hughes (GraphGeeks community) for a Graph Chat with Chang She, CEO and Co-founder of LanceDB, filmed at the ODSC conference.
Chang shares groundbreaking insights on how agentic retrieval systems are challenging traditional RAG approaches, requiring much higher throughput and iterative search. The conversation highlights the new Lance Format as the multimodal Lakehouse standard optimized for AI data operations.
Most excitingly for the graph community, Chang provides a first introduction on the new open-source project, Lance Graph, which enables storing graph schemas and executing Cypher-like queries directly on Lance tables, integrating vector, tabular, and graph data into a unified format.
Learn why data differentiation is the key to winning in the age of AI agents.
https://lancedb.com/

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