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Simon Eskildsen

Co-founder and CEO of turbopuffer, an AI startup focused on making vector search more accessible and affordable. Known for his expertise in learning and productivity systems.

Top 3 podcasts with Simon Eskildsen

Ranked by the Snipd community
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422 snips
Sep 11, 2024 • 1h 14min

How to Use AI to Become a Learning Machine - Ep. 34 with Simon Eskildsen

Simon Eskildsen, co-founder and CEO of AI startup turbopuffer, shares his journey from Shopify intern to learning machine. He discusses how his learning habits have evolved, integrating tools like ChatGPT and Notion AI to streamline tasks, from drafting legal documents to managing his cabin. Simon reveals his use of AI in creative cooking and unique word exploration, emphasizing the impact of language models on education and productivity. His insights highlight the transformative potential of AI in personal growth and skill acquisition.
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12 snips
Dec 2, 2024 • 1h 8min

How would you design a database on Object Storage?

In this talk, Simon Hørup Eskildsen, an experienced software engineer and founder of Turbopuffer, shares insights from his vast experience in database scalability and object storage solutions. He dives into the challenges of building databases on object storage, discussing write-ahead logs, multi-tenancy issues, and the intricacies of handling multiple writers. Simon elaborates on trade-offs in write operations and the complexities of optimizing database read paths, offering practical strategies for performance enhancement. A must-listen for database enthusiasts!
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Apr 7, 2025 • 1h 9min

How do vector (search) databases work? ft: turbopuffer

Simon Eskildsen, Co-founder of TurboPuffer and former infrastructure builder at Shopify, dives into the fascinating world of vector databases. He discusses the transformative role of vector search in enhancing recommendation systems, alongside challenges like cost and scaling. Simon also shares insights on managing podcast episode archives using embeddings and indexing strategies. The conversation highlights the importance of observability in database performance and paints an exciting picture of future trends in vector search technology.

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