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Data-centric AI emphasizes the importance of curating and developing high-quality data to build better ML models and AI applications.
Data-centric AI stands in contrast to model-centric AI. This approach often treats data as a static artifact and adjusts model performance by optimizing model architectures and training parameters.
All articles on Data-Centric AI
How AI speeds patient classification and recruitment in clinical trials
The medical industry is exploding with data. Manually labeling data for clinical trials is a challenge. Fortunately, AI can help.
September 21, 2023
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Which is better, retrieval augmentation (RAG) or fine-tuning? Both.
Professionals in the data science space often debate whether RAG or fine-tuning yields the better result. The answer is “both.”
September 20, 2023
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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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How GPT helped expand our marketing team’s capacity
GPT-3 unlocked additional capacity by automating first drafts of internal updates—including blog summaries and sample tweets.
August 29, 2023
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How AI saves money and improves banking complaint handling
Handling complaints effectively and efficiently with AI is essential to maintain customer satisfaction and protect the bank’s reputation.
August 24, 2023
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How Wayfair built better, faster catalog tagging with Snorkel Flow
The following was originally published on Wayfair’s tech blog. We have cross-posted it here, edited only to fit Snorkel’s formatting guidelines. — One of our missions at Wayfair is to help our 22 million customers find the products they are looking for. For example, when a customer searches for a “modern yellow sofa” on Wayfair, we want to show the most
August 22, 2023
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Generative AI essentials: what everyone needs to know about GenAI
Experts named generative AI as the most transformative technology of the decade. What is genAI, how does it work and why does it matter?
August 16, 2023
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Beyond prompting: getting production quality LLM performance with Snorkel Flow
As enterprises look toward deploying LLM-powered, business-critical applications, they’re learning to use strategies beyond prompting.
August 9, 2023
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How AI and foundation models improve email surveillance for banks
Recent developments in AI tools have made email surveillance for banks better than ever. See how foundation models and Snorkel Flow can help.
August 8, 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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GenAI most impactful tech of the decade | Gartner AI Hype Cycle
Generative AI is at peak hype and poised to dive into the “trough of despair,” according to the 2023 Gartner® Hype Cycle™ for AI.
July 24, 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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Snorkel Flow Summer 2023: faster, easier and more secure
This release eases Snorkel Flow application creation process and tightens the iteration loop. It also upgrades our security certifications.
July 14, 2023
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Google experts on practical paths to data-centricity in applied AI
Google experts Abhishek Ratna and Robert Crowe discuss practical paths to data-centricity in applied AI at The Future of Data-Centric AI ’22.
July 5, 2023
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How to build reusable data cleaning pipelines with scikit-learn
State Farm senior data scientist Jason Goldfarb presented “Reusable Data Cleaning Pipelines in Python” at the Future of Data-Centric AI 2022.
July 3, 2023
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Arize AI on How to apply and use machine learning observability
Jack Zhou, product manager at Arize, on “How to Apply Machine Learning Observability to Your ML System” from The Future of Data-Centric AI
June 30, 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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Claypot AI CEO on why you should deploy models the hard way
Claypot AI CEO Chip Huyen presented “Platform for Real-Time Machine Learning” at Snorkel AI’s Future of Data-Centric AI 2022.
June 27, 2023
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McKinsey QuantumBlack on automating data quality remediation with AI
Jacomo Corbo and Bryan Richardson with QuantumBlack present “Automating Data Quality Remediation With AI” at The Future of Data-Centric AI.
June 22, 2023
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Sambanova on using LLMs to squeeze value from business data
Stefano Lindt presents “Leveraging NLP to Extract Value From Business Data” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022.
June 20, 2023
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Black Swan Data CTO on how to tackle petabyte-level learning
Peter Davio, CTO at Black Swan Data, presented “Petabyte-Level Learning” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022.
June 15, 2023
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The Future of Data-Centric AI Day 2: Snorkel Flow and Beyond
The Future of Data-Centric AI showcased customer to successes, took a deep look at Snorkel Flow, and announced two new solutions.
June 10, 2023
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Future of Data-Centric AI day 1: LLMs changed the world
Day 1 of The Future of Data-Centric AI virtual conference 2023 featured the creator of Spark, the first U.S. Chief Data Scientist, and others.
June 8, 2023
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How to import Databricks data into Snorkel Flow
Databricks customers can access their data seamlessly within the Snorkel Flow platform with a few clicks with the new Databricks connector.
June 2, 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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Luminaries and enterprise veterans to speak at Future of Data-centric AI
The Future of Data-centric AI will bring together a star-studded lineup of expert speakers from ML, AI, and data science.
May 24, 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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