The benefits of programmatic labeling for trustworthy AI 
- The following post is based on a talk discussing the benefits of programmatic labeling for trustworthy AI, which was presented as part of the Trustworthy AI: A Practical Roadmap for Government event that took place this past April, with Snorkel AI Co-founder and Head of Technology, Braden Hancock. If you… ...
Uncovering the unknowns of deep neural networks by Sharon Li - Learning about the challenges and opportunities behind deep neural networks In this talk, Assistant Professor in Computer Science Sharon Li shares some exciting work about uncovering the unknowns of deep neural networks. She also shares some exciting challenges and opportunities in this domain. If you would like to watch Sharon’s… ...
Named entity extraction and recognition with Snorkel Flow 
- If you were ever amazed at how Google accurately finds the answer to your question just by a few keywords, you’ve witnessed the power of named entity recognition (NER). By quickly and accurately identifying different entities in a sea of unstructured articles, like names of people, places, and organizations, the… ...
A data-centric perspective on trustworthy and interpretable AI - The future of data-centric AI talk series In this talk, Assistant Professor of Biomedical Data Science at Stanford University, James Zou, discusses the work he and his team have been doing from a data-centric perspective to trustworthy and interpretable AI. If you would like to watch James’ presentation, we have… ...
Government keynote presentation by FBI CTO Gregory Ihrie - Gregory Ihrie is the Chief Technology Officer for the FBI, responsible for technology, innovation, and strategy. He also leads the FBI’s efforts in advancing the bureau’s management, policy, and governance of AI systems. Ihrie chairs the FBI’s Scientific Working Group on Artificial Intelligence, as well as the Department of Justice’s… ...
MLOps: Towards DevOps for data-centric AI with Ce Zhang - The future of data-centric AI talk series Don't miss the opportunity to gain an in-depth understanding of data-centric AI and learn best practices from real-world implementations. Connect with fellow data scientists, machine learning engineers, and AI leaders from academia and industry with over 30 virtual sessions. Save your seat at… ...
What to expect at The Future of Data-Centric AI 2022 
- 30+ sessions by 40+ speakers in 2 action-packed days Last year we organized The Future of Data-Centric AI conference to explore the shift from model-centric to data-centric AI. Speakers included researchers and industry experts such as Andrew Ng (Landing AI), Anima Anandkumar (NVIDIA), Chris Re (Stanford AI Lab), Michael DAndrea… ...
Auto LF generation: Lots of little models, big benefits 
- Constructing labeling functions (LFs) is at the heart of using weak supervision. We often think of these labeling functions as programmatic expressions of domain expertise or heuristics. Indeed, much of the advantage of weak supervision is that we can save time—writing labeling functions and applying them to data at scale… ...
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