Latest posts

  • Snorkel AI FAQ
    May 25, 2022Team Snorkel
    - Browse through these FAQ to find answers to commonly raised questions about Snorkel AI, Snorkel Flow, and data-centric AI development. Have more questions? Contact us. Programmatic labeling What is a labeling function? How does the labeling function know what the label should be? What is the output of a labeling… ...
  • Panel discussion: Academic and industry perspectives on ethical AI
    May 24, 2022Team Snorkel
    - This post showcases a panel discussion on the academic and industry perspectives of ethical AI, which was moderated by Director of Federal Strategy and Growth, Alexis Zumwalt, Fouts Family Early Career Professor and Lead of Ethical AI (NSF AI Institute AI4OPT), Georgia Institute of Technology, Swati Gupta, Chief Data Officer,… ...
  • Event recap: Adopting trustworthy AI for government
    May 23, 2022Alexis Zumwalt
    - We're currently experiencing such a rapid AI revolution and adoption of technologies, ranging from autonomous cars to virtual assistants and robotic surgeries and so much more, making it challenging for our government agencies to keep up. Especially when adding AI technologies to the mix, it can be even harder to… ...
  • Data extraction from SEC filings (10-Ks) with Snorkel Flow
    May 10, 2022Jonathan Dahlberg
    - Leveraging Snorkel Flow to extract critical data from annual quarterly reports (10-Ks) Introduction It can surprise those who have never logged into EDGAR how much information is available in annual reports from public companies. You can find tactical details like the names of senior leadership, top shareholders, and more strategic information like… ...
  • Liger: Fusing foundation model embeddings & weak supervision
    May 9, 2022Team Snorkel
    - Showcasing Liger—a combination of foundation model embeddings to improve weak supervision techniques. Machine learning whiteboard (MLW) open-source series In this talk, Mayee Chen, a PhD student in Computer Science at Stanford University focuses on her work combining weak supervision and foundation model embeddings that improve two essential aspects of current… ...
  • AI in cybersecurity an introduction and case studies
    May 5, 2022Nic Acton
    - An introduction to AI in cybersecurity with real-world case studies in a Fortune 500 organization and a government agency Despite all the recent advances in artificial intelligence and machine learning (AI/ML) applied to a vast array of application areas and use cases, success in AI in cybersecurity remains elusive. The… ...
  • Active learning: an overview
    May 4, 2022Josh McGrath
    - A primer on active learning presented by Josh McGrath. Machine learning whiteboard (MLW) open-source series This video defines active learning, explores variants and design decisions made within active learning pipelines, and compares it to related methods. It contains references to some seminal papers in machine learning that we find instructive.… ...
  • Using few-shot learning language models as weak supervision
    May 3, 2022Ryan Smith
    - Utilizing large language models as zero-shot and few-shot learners with Snorkel for better quality and more flexibility Large language models (LLMs) such as BERT, T5, GPT-3, and others are exceptional resources for applying general knowledge to your specific problem. Being able to frame a new task as a question for… ...
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