Data-Centric AI

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

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

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.

Datacast Episode 102: Early-Stage Investing, Modern Venture Capital, and Trends in Enterprise Infrastructure with Astasia Myers

Datacast Episode 102: Early-Stage Investing, Modern Venture Capital, and Trends in Enterprise Infrastructure with Astasia Myers

Astasia Myers is a Partner on Quiet Capital's enterprise team leading investments in ML, data infrastructure, open-source, developer tools, and security. She focuses on pre-seed, seed, and Series A.

Prior to joining Quiet, Astasia was an investor in Redpoint's early-stage enterprise team, where she partnered with Dremio, LaunchDarkly, Solo.io, Preset, Hex, Cyral, among others. Before that, she worked at Cisco Investments, where she focused on cloud-infrastructure M&A and investments, including Cohesity, Datos IO, Elastifile, Guardicore, Springpath, and the funding of internal stealth projects.

Datacast Episode 100: Data-Centric Computer Vision, Productizing AI, and Scaling a Global Startup with Hyun Kim

Datacast Episode 100: Data-Centric Computer Vision, Productizing AI, and Scaling a Global Startup with Hyun Kim

Hyun Kim is the co-founder and CEO of Superb AI, an ML DataOps platform that helps computer vision teams automate and manage the entire data pipeline: from ingestion and labeling to data quality assessment and delivery. He initially studied Biomedical Engineering and Electrical Engineering at Duke but shifted from genetic engineering to robotics and deep learning. He then pursued a Ph.D. in computer science at Duke with a focus on Robotics and Deep Learning but ended up taking leave to further immerse himself in the world of AI R&D at a corporate research lab. During this time, he started to experience the bottlenecks and obstacles that many companies still face to this day: data labeling and management were very manual, and the available solutions were nowhere near sufficient.

Datacast Episode 97: Escaping Poverty, Embracing Digital Learning, Benchmarking ML Systems, and Advancing Data-Centric AI with Cody Coleman

Datacast Episode 97: Escaping Poverty, Embracing Digital Learning, Benchmarking ML Systems, and Advancing Data-Centric AI with Cody Coleman

Cody Coleman is the Founder and CEO of Coactive AI. He is also a co-creator of DAWNBench and MLPerf and a founding member of MLCommons. His work spans from performance benchmarking of hardware and software systems to computationally efficient methods for active learning and core-set selection. He holds a Ph.D. in Computer Science from Stanford University, where Professors Matei Zaharia and Peter Bailis advised him, and an MEng and BS from MIT.