Category

Research

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

Image for Getting better performance from foundation models (with less data)
Getting better performance from foundation models (with less data)
Getting better performance from foundation models (with less data)
August 4, 2023
Fred Sala
Image for Snorkel AI researchers present 18 papers at NeurIPS 2023
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
Team Snorkel
Image for Long context models in the enterprise: benchmarks and beyond
Long context models in the enterprise: benchmarks and beyond
Snorkel researchers devised a new way to evaluate long context models and address their “lost-in-the-middle” challenges with mediod voting.
June 6, 2024
Amanda Dsouza

All articles on Research

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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
Chris Glaze
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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
Fred Sala
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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
Matt Casey
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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
Team Snorkel
Book floating in space—a rough illustration of large language models.
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
Matt Casey
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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
Team Snorkel
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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
Matt Casey
Fdcai 2023 social speaker logos (2)
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
Devang Sachdev
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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
Team Snorkel
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Harvard professor: DataPerf and AI’s need for data benchmarks
Harvard Professor Vijay Janapa Reddi’s presentation: “DataPerf: Benchmarks for data” from Snorkel AI’s 2022 Future of Data-Centric AI event.
April 25, 2023
Team Snorkel
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Discovering climate change impact with Snorkel-enabled NLP
Prasanna Balaprakash, research and development lead from Argonne National Laboratory gave a presentation entitled “Extracting the Impact of Climate Change from Scientific Literature using Snorkel-Enabled NLP” at Snorkel AI’s Future of Data-Centric AI Workshop in August, 2022.
April 18, 2023
Team Snorkel
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AMA technique: a trick to build systems with foundation models
Simran Arora is a machine learning researcher at Stanford University. She presented “Ask Me Anything: How are Foundation Models Changing the Way We Build Software” at Snorkel AI’s Foundation Model Virtual Summit 2023.
April 13, 2023
Team Snorkel
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Coactive AI’s CEO: quality beats quantity for data selection
Cody Coleman, CEO and Co-Founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022.
April 11, 2023
Team Snorkel
Ananya Kumar, standfor student
Boost foundation model results with linear probing and fine-tuning
Ananya Kumar, Stanford Ph.D. student, explains methods to improve foundation model performance, including linear probing and fine-tuning.
April 5, 2023
Team Snorkel
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New research expands limitations of weak supervision, foundation models
Snorkel AI researchers continue to push the frontier of machine learning, as demonstrated by the 18 research papers recently added to our website.
March 24, 2023
Matt Casey