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We help labs advance frontier models by working with domain experts to design and build complex, realistic datasets that drive model performance.
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Open benchmarks, conversations, and research for real-world AI performance.

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Backed by a $3M commitment, the program funds open-source datasets, benchmarks, and evaluation artifacts that shape how frontier AI systems are built and evaluated.

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Amanpreet Singh, Lead Researcher at Hugging Face gave a presentation entitled Towards Unified Foundation Models for Vision and Language Alignment a Snorkel AI’s Foundation Model Summit in January.
Twelve speakers shared their insights into the present and future of foundation models January event; see what they had to say.
Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. What are they and how will they impact your business? Find out in our guide.
Combining foundation model outputs with weak supervision yields faster model development and requires fewer ground truth labels.
Snorkel AI CEO and Co-Founder Alex Ratner’s introduction to data-centric AI from the 2022 Future of Data-Centric AI virtual conference.
Brown professor Stephen Bach tells Snorkel CEO Alex Ratner about his research into improving foundation models like GPT-3 with curated data.
Cleanlab Co-Founder and CEO Curtis Northcutt presents his company’s automatic, universal and open-source tools to quickly clean data sets.
Anirudh Koul is Machine Learning Lead for the NASA Frontier Development Lab and the Head of Machine Learning Sciences at Pinterest. He presented at Snorkel AI’s 2022 Future of Data Centric AI (FDCAI) Conference.
Most poll respondents at Snorkel AI’s recent Foundation Model Virtual Summit named questionable accuracy as the biggest barrier preventing them from getting organizational value from Foundation Models.









