The Future of Data-Centric AI

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.