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The Future of Data-Centric AI

Time / Place:

⏱️ 10/6 (Wed.) 21:15-21:40 at Online Track 1


Over the last half decade, there have been tremendous advances in new model architectures for machine learning that have led to more powerful and more accessible AI solutions. However, these models have become more data hungry than ever, and specifically rely on massive quantities of labeled training data to learn from. This massive change has led to a shift from model-centric AI, where the primary activity of an ML developer is iterating on models (e.g. feature engineering, architecture and algorithm design, etc.) to data-centric AI where labeling, slicing, augmenting, and managing the data at the center of AI is the key activity and leverage point. In this talk, I'll describe how data-centric AI must be programmatic to succeed, and will review our work on Snorkel Flow, a system for data-centric AI.

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Alex Ratner
  • Alex Ratner Alex Ratner
  • Snorkel AI / Co-founder and CEO
  • Alex Ratner is an Assistant Professor of Computer Science at the University of Washington, and co-founder and CEO of Snorkel AI, Inc. (

    Prior to UW and Snorkel AI, he completed his PhD in CS advised by Christopher Ré at Stanford, where his research focused on applying data management and statistical learning techniques to emerging machine learning workflows such as creating and managing training data, and his AB in Physics at Harvard.

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