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Unlocking the Power of Unstructured Data

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Manage episode 428353540 series 2570898
Indhold leveret af Ben Lorica. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Ben Lorica eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Chang She is CEO and co-founder of LanceDB, an open-source database designed for multimodal AI applications, offering scalable vector search, streaming training data, and interactive exploration of large AI datasets. In this episode we discuss Lance, an open-source columnar data format that tackles the unique challenges posed by modern AI and machine learning workloads.
Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/
Subscribe: AppleSpotify OvercastPocket CastsAntennaPodPodcast AddictAmazonRSS.
Detailed show notes can be found on The Data Exchange web site.

  continue reading

255 episoder

Artwork
iconDel
 
Manage episode 428353540 series 2570898
Indhold leveret af Ben Lorica. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Ben Lorica eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Chang She is CEO and co-founder of LanceDB, an open-source database designed for multimodal AI applications, offering scalable vector search, streaming training data, and interactive exploration of large AI datasets. In this episode we discuss Lance, an open-source columnar data format that tackles the unique challenges posed by modern AI and machine learning workloads.
Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/
Subscribe: AppleSpotify OvercastPocket CastsAntennaPodPodcast AddictAmazonRSS.
Detailed show notes can be found on The Data Exchange web site.

  continue reading

255 episoder

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