• Resilient enterprise AI application development
    March 3, 2022Arjun Prakash
    - Using a data-centric approach to capture the best of rule-based systems and ML models for enterprise AI One of the biggest challenges to making AI practical for the enterprise is keeping the AI application relevant (and therefore valuable) in the face of ever-changing input data and evolving business objectives. Practitioners typically… ...
  • How AI can be used to rapidly respond to information warfare in the Russia-Ukraine conflict
    February 28, 2022Charlie Greenbacker and Nic Acton
    - Proliferating web technology has contributed to information warfare in recent conflicts. Artificial Intelligence (AI) can play a significant role in stemming disinformation campaigns, cyber-attacks, and informing diplomacy in the rapidly evolving situation in Ukraine. Snorkel AI is dedicated to supporting the National Security community and other enterprise organizations with state-of-the-art… ...
  • How Genentech extracted information for clinical trial analytics with Snorkel Flow
    February 26, 2022Team Snorkel
    - Genentech, a global biotech leader and member of the Roche Group, leveraged Snorkel Flow to extract critical information from lengthy clinical trial protocol (CTP) pdf documents. They built AI applications that used NER, entity linking, text extraction, and classification models to determine inclusion/ exclusion criteria and to analyze Schedules of… ...
  • Augmenting the clinical trial design process with information extraction
    February 22, 2022Team Snorkel
    - The future of data-centric AI talk series Background Michael DAndrea is the Principal Data Scientist at Genentech. He earned his MBA from Cornell University and a Master’s degree in Computing and Education from Columbia University. He currently works on using unstructured data sources for clinical trial analytics and his team… ...
  • How Google used Snorkel to build and adapt content classification models
    February 18, 2022Team Snorkel
    - Google used Snorkel’s technology to leverage existing knowledge resources from across the organization to reduce development time and cost by an order of magnitude. The team built content classification models with Snorkel that achieved an average performance improvement of 52%, without requiring tens of thousands of hand-labeled examples. Challenge: Agile… ...
  • Q4 LTS Release of Snorkel Flow
    February 8, 2022Henry Ehrenberg
    - We’re excited to announce the Q4 2021 LTS release of Snorkel Flow, our data-centric AI development platform powered by programmatic labeling. This latest release introduces a number of new product capabilities and enhancements, from a streamlined programmatic data development interface, to enhanced auto-suggest for labeling functions, to new machine learning… ...
  • Making Automated Data Labeling a Reality in Modern AI
    February 4, 2022Braden Hancock
    - Moving from Manual to Programmatic Labeling Labeling training data by hand is exhausting. It’s tedious, slow, and expensive—the de facto bottleneck most AI/ML teams face today 1. Eager to alleviate this pain point of AI development, machine learning practitioners have long sought ways to automate this labor-intensive labeling process (i.e.,… ...
  • The Principles of Data-Centric AI Development
    January 25, 2022Team Snorkel
    - The Future of Data-Centric AI Talk Series Background Alex Ratner is CEO and co-founder of Snorkel AI and an Assistant Professor of Computer Science at the University of Washington. He recently joined the Future of Data-Centric AI event, where he presented the principles of data-centric AI and where it’s headed.… ...
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