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Closing the Evaluation Gap in Agentic AI

Announcing a $3M commitment to launch Open Benchmarks Grants

February 11, 2026
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Snorkel’s Journey to Data-Centric AI, with Chris Ré

The Future of Data-Centric AI Talk Series Background Snorkel co-founder Chris Ré is an associate professor of Computer Science at Stanford University and an award-winning researcher in data-based theory and machine learning. He has co-founded four companies based on his research in machine learning systems. Chris recently presented at the Future of Data-Centric AI virtual event in September, where he…

Nov 03, 2021
Learn more about Snorkel’s Journey to Data-Centric AI, with Chris Ré
Building a Successful AI Startup

ScienceTalks with Saam Motamedi We at Snorkel AI have received many requests from data scientists and machine learning engineers who aspire to be founders, where do they start and how should they get started on their entrepreneurial journey? We genuinely believe that data scientists and machine learning engineers will build the next generation of mega-enterprises. Over the summer, we’ve recorded…

Oct 18, 2021
Learn more about Building a Successful AI Startup
Forager: Rapid Data Exploration for Rapid Model Development

Machine Learning Whiteboard (MLW) Open-source Series We started our machine learning whiteboard (MLW) series earlier this year as an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. We emphasize an informal and open environment to everyone interested in learning about machine learning.In this episode, Fait Poms, a Ph.D. student at Stanford…

Oct 14, 2021
Learn more about Forager: Rapid Data Exploration for Rapid Model Development
Recap: The Future of Data-Centric AI Event

Main takeaways from The Future of Data-Centric AI Event We recently hosted The Future of Data-Centric AI, where academia, research, and industry experts and practitioners came together to discuss the shift from model-centric AI development to data-centric AI and what lies ahead. This post gives you a quick overview of the event and top takeaways from over eight hours of…

Oct 11, 2021
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Building Malleable Machine Learning (ML) Systems

Defining and Building Malleable ML Systems – Machine Learning Whiteboard (MLW) Open-Source Series As you may know, earlier this year, we started our machine learning whiteboard (MLW) series, an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. We emphasize an informal and open environment to everyone interested in learning about machine learning. In this…

Sep 22, 2021
Learn more about Building Malleable Machine Learning (ML) Systems
Web Virtualization — Optimizing Data-Intensive App Performance

Frontend Development Best Practices for Working With Lots of Data From Snorkel AI Engineering As a frontend engineer, it’s often easy to run into limitations when scaling large applications. At Snorkel AI, we often run into times where our users work with data that scales into the gigabytes when using Snorkel Flow. We have built Snorkel Flow around two core…

Sep 16, 2021
Learn more about Web Virtualization — Optimizing Data-Intensive App Performance
Multi-Label Classification, Sequence Labeling, and More

Snorkel Flow LTS Release Summer ‘21 By adopting Snorkel Flow, a data-centric AI development platform powered by programmatic labeling, our customers have changed how they build and deploy AI applications. We’ve seen our customers save tens-of-millions of dollars in manual labeling costs and person-years of time by applying weak supervision with Snorkel Flow.Over the last few months, we’ve been hard…

Sep 15, 2021
Learn more about Multi-Label Classification, Sequence Labeling, and More
Applying Weak Supervision Research

ScienceTalks with Paroma Varma In this episode of Science Talks, Snorkel AI’s Braden Hancock chats with Paroma Varma – a co-founder of Snorkel AI and one of the first and leading contributors to the Snorkel project. We discuss Paroma’s path into machine learning, her work in optimization and signal processing during her undergrad, weak supervision and image data during her…

Sep 13, 2021
Learn more about Applying Weak Supervision Research
Sliceline: Fast, Linear-Algebra-Based Slice Finding for ML Model Debugging

Diving Into SliceLine – Machine Learning Whiteboard (MLW) Open-source Series Earlier this year, we started our machine learning whiteboard (MLW) series, an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. We emphasize an informal and open environment to everyone interested in learning about machine learning.In this episode, Kaushik Shivakumar dives into…

Sep 08, 2021
Learn more about Sliceline: Fast, Linear-Algebra-Based Slice Finding for ML Model Debugging
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