Introducing Snorkel’s Foundation Model Data Platform

Discover Snorkel’s Foundation Model Data Platform: A revolutionary step to make AI data development systematic and programmatic. It enhances model accuracy by facilitating the selection, labeling, cleaning, and curation of data, which is often overlooked yet crucial. Snorkel’s solutions include Snorkel Foundry, Snorkel GenFlow, and Snorkel Flow, which cater to various AI use cases. Their aim is to create a unique ‘GPT-You’ for every enterprise, enabling AI customization based on specific data and use cases.

Alex Ratner
June 12, 2023

Latest posts

  • Building a Successful AI Startup
    October 18, 2021Team Snorkel
    - ScienceTalks with Saam Motamedi We at Snorkel AI have received many requests from data scientists and machine learning engineers who aspire to be founders, where do they start and how should they get started on their entrepreneurial journey? We genuinely believe that data scientists and machine learning engineers will build… ...
  • Forager: Rapid Data Exploration for Rapid Model Development
    October 14, 2021Team Snorkel
    - Machine Learning Whiteboard (MLW) Open-source Series We started our machine learning whiteboard (MLW) series earlier this year as an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. We emphasize an informal and open environment to everyone interested in learning about machine… ...
  • Recap: The Future of Data-Centric AI Event
    October 11, 2021Aarti Bagul
    - Main takeaways from The Future of Data-Centric AI Event We recently hosted The Future of Data-Centric AI, where academia, research, and industry experts and practitioners came together to discuss the shift from model-centric AI development to data-centric AI and what lies ahead. This post gives you a quick overview of… ...
  • Building Malleable Machine Learning (ML) Systems
    September 22, 2021Team Snorkel
    - Defining and Building Malleable ML Systems - Machine Learning Whiteboard (MLW) Open-Source Series As you may know, earlier this year, we started our machine learning whiteboard (MLW) series, an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. We emphasize an informal… ...
  • Web Virtualization — Optimizing Data-Intensive App Performance
    September 16, 2021Shubham Naik
    - Frontend Development Best Practices for Working With Lots of Data From Snorkel AI Engineering As a frontend engineer, it's often easy to run into limitations when scaling large applications. At Snorkel AI, we often run into times where our users work with data that scales into the gigabytes when using… ...
  • Multi-Label Classification, Sequence Labeling, and More
    September 15, 2021Patrick Kolencherry
    - Snorkel Flow LTS Release Summer ‘21 By adopting Snorkel Flow, a data-centric AI development platform powered by programmatic labeling, our customers have changed how they build and deploy AI applications. We've seen our customers save tens-of-millions of dollars in manual labeling costs and person-years of time by applying weak supervision… ...
  • Applying Weak Supervision Research
    September 13, 2021Team Snorkel
    - ScienceTalks with Paroma Varma In this episode of Science Talks, Snorkel AI's Braden Hancock chats with Paroma Varma - a co-founder of Snorkel AI and one of the first and leading contributors to the Snorkel project. We discuss Paroma's path into machine learning, her work in optimization and signal processing… ...
  • Sliceline: Fast, Linear-Algebra-Based Slice Finding for ML Model Debugging
    September 8, 2021Team Snorkel
    - Diving Into SliceLine - Machine Learning Whiteboard (MLW) Open-source Series Earlier this year, we started our machine learning whiteboard (MLW) series, an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. We emphasize an informal and open environment to everyone interested in… ...
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