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Episode 118: Overcoming Hardships, Confident Learning, Dataset Improvement, and The Ph.D. Rapper with Curtis Northcutt

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Content provided by James Le. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by James Le or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Curtis Northcutt is an American computer scientist and entrepreneur focusing on AI to empower people. He is the CEO and Co-Founder of Cleanlab, building next-generation data-centric AI and open-source technologies that enable AI to work with real-world, messy data. He completed his Ph.D. at MIT, where he invented confident learning to automatically find label issues in any dataset. Curtis received the MIT thesis award, NSF Fellowship, and Goldwater Scholarship for his work. Before Cleanlab, he worked in AI research teams at Google, Oculus, Amazon, Facebook, Microsoft, and NASA.
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133 episodes

Artwork
iconShare
 
Manage episode 365640476 series 2593033
Content provided by James Le. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by James Le or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Curtis Northcutt is an American computer scientist and entrepreneur focusing on AI to empower people. He is the CEO and Co-Founder of Cleanlab, building next-generation data-centric AI and open-source technologies that enable AI to work with real-world, messy data. He completed his Ph.D. at MIT, where he invented confident learning to automatically find label issues in any dataset. Curtis received the MIT thesis award, NSF Fellowship, and Goldwater Scholarship for his work. Before Cleanlab, he worked in AI research teams at Google, Oculus, Amazon, Facebook, Microsoft, and NASA.
  continue reading

133 episodes

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