Data-Centric AI

William Huang, senior data scientist at Capital One, discussed “dataset cartography” and its value at the Future of Data-Centric AI 2022.

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.

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.

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.

Dr. Ce Zhang is an associate professor in Computer Science at ETH Zürich. He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022.

Harvard Professor Vijay Janapa Reddi’s presentation: “DataPerf: Benchmarks for data” from Snorkel AI’s 2022 Future of Data-Centric AI event.

Forward-looking companies in finance, including banks, have looked to technology to meet challenges and are reaping the rewards of doing so.

Uniphore, a conversational AI and automation leader, has chosen Snorkel’s data-centric AI platform to accelerate AI development.

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.

Snorkel AI teamed up with Hugging Face to provide enterprises with even more flexibility and choice as they develop AI applications.

Snorkel Flow’s Spring 2023 release focuses on adapting foundation models for enterprise use—including fine-tuning and additional features.

Physician notes and other sources of unstructured data can offer insight into drugs’ negative side effects. Here’s how modern machine learning tools can help turn all that data into a useful resource.

Snorkel AI researchers continue to push the frontier of machine learning, as demonstrated by the 18 research papers recently added to our website.

Snorkel AI CEO and co-founder Alex Ratner recently spoke with five Snorkel researchers about their foundation model research.

McKinsey’s Carlo Giovine and David Harvey present “Trends in Enterprise ML and the potential impact of Foundation Models” at Snorkel’s Foundation Model Summit.

Dillon Laird, engineering manager at Landing AI, presents on LandingLens and democratizing AI at Snorkel AI’s 2022 FDCAI Conference.

Snorkel AI, Google Cloud and Vertex AI partner to help organizations transform data into AI-powered systems faster than ever.

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.

Credo AI’s head of data science explains at Snorkel’s FDCAI 2022 how his team works to operationalize responsible AI assessment tools.

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.

Jan Neumann, Vice President of Machine Learning for Comcast Applied AI and Discovery, describes Comcast’s data-centric AI approach to speech.

Meta senior applied research manager Anoop Sinha and Snorkel AI co-founder Braden Hancock discuss mastering speech and search with TWIML host Sam Charrington.

As part of Snorkel AI’s partnership with Snowflake, users can now upload millions of rows of data seamlessly from their Snowflake warehouse into Snorkel Flow via the natively-integrated Snowflake connector. With a few clicks, a user can upload massive amounts of Snowflake data and quickly develop high-quality ML models using Snorkel Flow’s Data-Centric AI platform.

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.

Snorkel AI is teaming up with Google Cloud to help F500 companies and AI innovators solve their most difficult problems.

As machine learning practitioners, few of us would expect the first version of a new model to achieve our objective. We plan for multiple rounds of iteration to address errors and improve performance, and the Snorkel Flow platform provides tools to enable this kind of iteration within the data-centric AI framework.