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

  • Demo: Using Snorkel Flow to train Microsoft Azure Form Recognizer models
    January 5, 2023Snorkel Team
    - Snorkel Flow debuts a new integration with Microsoft Azure Form Recognizer to help organizations leverage Azure AI services. ...
  • Ask Me Anything approach bolsters foundation models
    January 4, 2023Snorkel Team
    - Researcher Simran Arora tells Snorkel CEO Alex Ratner how she improved foundation model effectiveness by using “Ask Me Anything”-style questions. ...
  • Snorkel Flow 2022 year-end release roundup
    January 3, 2023Aparna Lakshmiratan
    - See what's in our latest Snorkel Flow release and how we're accelerating data-centric AI development further. ...
  • Combining human and artificial intelligence with human-in-the-loop ML | FDCAI
    December 28, 2022Team Snorkel
    - 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. ...
  • How a top 3 US bank used Snorkel Flow to automate 10-K review for their analysts
    December 23, 2022Nick Harvey
    - 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… ...
  • How programmatic labeling can minimize data exposure
    December 21, 2022Devang Sachdev
    - 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. ...
  • How Georgetown University’s CSET uses Snorkel Flow to build NLP applications to inform policy research
    December 19, 2022Nick Harvey
    - Georgetown University's CSET is building next-generation NLP applications using Snorkel Flow to classify complex research documents. Snorkel Flow drastically reduced labeling, model training, and iteration time and better equipped CSET's data science team to collaborate closely with analysts to gather, process, and interpret data at scale.  ...
  • Seven research papers push foundation model boundaries
    December 15, 2022Matt Casey
    - 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.  ...
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