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Ben Lorica talks with Chang She, co-founder and CEO of LanceDB, about the limitations of traditional analytical data tools like Pandas and Parquet when applied to AI workloads. They discuss the rise of the “multimodal lakehouse,” the unique data storage and retrieval challenges introduced by AI agents, and how LanceDB provides both lightweight embedded memory and massive-scale infrastructure.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
By Ben Lorica4.6
3737 ratings
Ben Lorica talks with Chang She, co-founder and CEO of LanceDB, about the limitations of traditional analytical data tools like Pandas and Parquet when applied to AI workloads. They discuss the rise of the “multimodal lakehouse,” the unique data storage and retrieval challenges introduced by AI agents, and how LanceDB provides both lightweight embedded memory and massive-scale infrastructure.
Subscribe to the Gradient Flow Newsletter 📩 https://gradientflow.substack.com/
Subscribe: Apple · Spotify · Overcast · Pocket Casts · AntennaPod · Podcast Addict · Amazon · RSS.
Detailed show notes and transcript, can be found on The Data Exchange web site.

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