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Chang She

Co-founder and CEO of LanceDB, an open-source, on-disk embedded vector search offering. Experienced in building data and machine learning tooling.

Top 3 podcasts with Chang She

Ranked by the Snipd community
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54 snips
Dec 12, 2024 • 58min

#488: Multimodal data with LanceDB

Chang She, CEO and co-founder of LanceDB, discusses the innovative open-source database tailored for AI, highlighting its application across companies like Midjourney. He explores the shift from traditional languages to Rust, the rise of unstructured data, and the implications for programming. The conversation delves into optimizing multimodal data lakes and efficient storage solutions, plus practical tips on integrating LanceDB into Python applications. Chang also emphasizes community engagement and the benefits of contributing to an evolving AI landscape.
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15 snips
Apr 7, 2025 • 42min

Multimodal AI | Data Brew | Episode 42

Chang She, CEO and Co-founder of LanceDB, shares his incredible journey from helping create the Pandas Library to developing a cutting-edge database for multimodal AI. He dives into the limitations of traditional data storage systems and explains how LanceDB efficiently handles diverse data types like images and videos. The conversation highlights the growing significance of multimodal AI in enterprises, future trends, and even offers spicy predictions for the AI landscape in 2025. Get ready for some intriguing insights!
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11 snips
Dec 19, 2023 • 42min

Open source, on-disk vector search with LanceDB

Chang She, co-founder and CEO of LanceDB, shares insights on their innovative open-source vector search solution. He discusses how LanceDB’s columnar database structure supports serverless deployments, leading to cost savings without sacrificing performance. The conversation delves into the integration of Rust for improved safety and efficiency, and the exciting possibilities of language agnosticism in AI tools. Chang also touches on future applications of AI in autonomous technologies, highlighting the evolving landscape of data management.

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