Category
Snorkel AI emerged from a research project, and we remain closely connected to the research community. Students and professors associated with the Snorkel project continue to publish academic papers that push the field forward, and the Snorkel AI research team integrates the most promising of those ideas into our platform.
Our picks
Getting better performance from foundation models (with less data)
Getting better performance from foundation models (with less data)
August 4, 2023
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Snorkel AI researchers present 18 papers at NeurIPS 2023
The Snorkel AI team will present 18 research papers and talks at the 2023 Neural Information Processing Systems (NeurIPS) conference from December 10-16. The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. Snorkel AI is proud of its roots in the research community and endeavors to remain at the forefront
October 31, 2023
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All articles on Research
Former U.S. Chief Data Scientist on past and future of data science
Past U.S. Chief Data Scientist DJ Patil talked with Snorkel AI CEO Alex Ratner on topics including the origin of the title “data scientist.”
September 12, 2023
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4 new papers show foundation models can build on themselves
The surest way to improve foundation models is through more and better data, but Snorkel researchers showed FMs can learn from themselves.
August 31, 2023
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Accelerating predictive task time to value with generative AI
Generative AI can write poems, recite common knowledge, and extract information. GenAI can also help quickly build predictive pipelines.
August 17, 2023
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Getting better performance from foundation models (with less data)
Getting better performance from foundation models (with less data)
August 4, 2023
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Data fuels enterprise AI value: 6 takeaways from the Gartner Hype Cycle for Artificial Intelligence, 2023
GenAI may be the most transformative technology of the past decade but data is where enterprises are able to realize real value from AI today.
August 2, 2023
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How we built better GenAI with programmatic data development
We used weak supervision to programmatically curate instruction tuning data for open-source LLMs to build a better GenAI.
July 19, 2023
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The future of large language models is faster and more robust
Snorkel and affiliated academic labs have been hard at work reducing how computationally expensive large language models are.
June 29, 2023
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LLMs high priority for enterprise data science, but concerns remain
Enterprises—especially the world’s largest—are excited to use large language models, but they want to fine-tune them on proprietary data.
June 23, 2023
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How MLCommons is democratizing data with public datasets
Peter Mattson, Google senior staff engineer and president of MLCommons.org, explained MLCommons at The Future of Data-Centric AI in 2022.
May 31, 2023
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Large language models: their history, capabilities and limitations
Large language models have enormous potential. But what are they? Where did they come from? And how can you make them work better?
May 25, 2023
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Stanford professor on data-centric AI for healthcare and medicine
Stanford assistant professor James Zou, presents “Responsible Data-Centric AI for Healthcare and Medicine” at The Future of Data-Centric AI.
May 18, 2023
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Poster presenters compete to win desktop GPU
Snorkel AI has accepted the first batch of applications for its first annual virtual poster competition. But there’s still time to add yours to the mix.
May 9, 2023
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Use your data to build your AI moat: The Future of Data-Centric AI 2023
Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023 free virtual conference.
May 4, 2023
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Out of distribution blindness: why to fix it and how energy can help
Sharon Li is an assistant professor at the University of Wisconsin-Madison. She presented “Detecting Data Distributional Shift: Challenges and Opportunities” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. The talk covered a novel approach for handling out-of-distribution objects.
May 3, 2023
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