Data Labeling

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.

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.

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.

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.

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.

Cleanlab Co-Founder and CEO Curtis Northcutt presents his company’s automatic, universal and open-source tools to quickly clean data sets.

Understanding and quantifying people’s opinions has become increasingly important to businesses, but the way people can express multiple thoughts in the same sentence has frustrated practitioners’ efforts to extract those opinions cleanly—a problem we can solve through aspect-based sentiment analysis (ABSA).

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

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.

Together, Snorkel AI and Seldon enable enterprises to adopt AI across the business at scale by dramatically accelerating development and deployment and tightening the feedback loop to rapidly respond to data drift or changing business requirements.

Snorkel CEO Alex Ratner interviews Mayee Chen about how Liger improves the effectiveness of programmatic labeling through foundation model embeddings.

Snorkel AI has teamed with Snowflake to help our shared customers transform raw, unstructured data into actionable, AI-powered insights.

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.

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.

While a majority of Natural Language Processing (NLP) models focus on English, the real world requires solutions that work with languages across the globe. This demo shows how effectively users can build cross-language models in Snorkel Flow.

Using Snorkel Flow, Pixability has created a way to build classifiers for massive amounts of YouTube data quickly—that was previously out of reach.

See what’s in our latest Snorkel Flow release and how we’re accelerating data-centric AI development further.

A central innovation team at a top US bank wanted to modernize its AI development and data annotation processes in order to create a custom natural language processing (NLP) model that could extract important financial information from 10-Ks. Manually reviewing these documents was taking up valuable time that could be better spent assisting customers. The team used Snorkel Flow’s data-centric AI development process and programmatic labeling to train a customized NLP model that could accurately extract information on interest rate swaps.

MIT’s Technology Review reported this week that workers in Venezuela contracted by outsourced data annotation services provider shared customer data—low-angled pictures intended to be labeled, including one that featured a woman in a private moment in the bathroom—with each other on social media. Programmatic labeling could have minimized this.