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
Foundation Models 101: a guide with essential FAQs
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.
March 1, 2023
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Combining foundation models with weak supervision
Combining foundation model outputs with weak supervision yields faster model development and requires fewer ground truth labels.
March 1, 2023
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Operationalizing knowledge for data-centric AI
Snorkel AI CEO and Co-Founder Alex Ratner’s introduction to data-centric AI from the 2022 Future of Data-Centric AI virtual conference.
February 27, 2023
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How a Brown professor sharpened and shrunk GPT-3
Brown professor Stephen Bach tells Snorkel CEO Alex Ratner about his research into improving foundation models like GPT-3 with curated data.
February 21, 2023
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Cleanlab CEO shows automatic data-cleansing tools
Cleanlab Co-Founder and CEO Curtis Northcutt presents his company’s automatic, universal and open-source tools to quickly clean data sets.
February 17, 2023
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NASA ML Lead on its WorldView citizen scientist no-code tool
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.
February 6, 2023
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Accuracy top concern for Foundation Model adoption—Poll
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.
January 31, 2023
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How Foundation Models bolster programmatic labeling
Snorkel CEO Alex Ratner interviews Mayee Chen about how Liger improves the effectiveness of programmatic labeling through foundation model embeddings.
January 26, 2023
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Unmasking Trafficking Risk in Commercial Sex Supply Chains with Machine Learning
Hamsa Bastani presented a summary of her and her co-authors’ ongoing work using machine learning and Snorkel AI’s tools to detect and track activities that are associated with a high risk for global sex trafficking.
January 20, 2023
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Prompting and weak supervision to build better, smaller models
Snorkel AI co-founder and CEO Alex Ratner recently interviewed several Snorkel researchers about their published academic papers. In this video, Alex talks with Ryan Smith, Senior Applied Scientist at Snorkel, about the work he did on using foundation models to build compact, deployable, and effective models.
January 19, 2023
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FM Summit shows Foundation Model hurdles and potential
Snorkel AI held its Foundation Model Summit Jan 17, bringing together 12 presenters and over 600 attendees at 10 virtual sessions. The event drew registrants from across many sectors, including the tech industry, healthcare, and financial services.
January 18, 2023
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Contrastive Learning boosts Foundation Model specialization
Snorkel AI co-founder and CEO Alex Ratner talks with Ananya Kumar about the work he did on improving the effectiveness of foundation models by using contrastive learning, image augmentations, and labeled subsamples.
January 13, 2023
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Ask Me Anything approach bolsters foundation models
Researcher Simran Arora tells Snorkel CEO Alex Ratner how she improved foundation model effectiveness by using “Ask Me Anything”-style questions.
January 4, 2023
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Combining human and artificial intelligence with human-in-the-loop ML | FDCAI
More components in an ML lifecycle are designed to run on autopilot, but some tasks require human-in-the-loop ML, an active research topic that has seen an increasing number of publications in the last 10 years.
December 28, 2022
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Seven research papers push foundation model boundaries
The recent debut of ChatGPT astounded the public with the power and speed of foundation models, but their enterprise use remains hampered by adaptation and deployment challenges. In the past year, Snorkel AI has researched several ways to overcome those challenges.
December 15, 2022
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