Latest posts

  • Measuring NLP Progress With Sebastian Ruder
    March 10, 2021Team Snorkel
    - In this episode of Science Talks, Sebastian Ruder, Research Scientist at DeepMind, shares his thoughts on making AI practical with Snorkel AI’s Braden Hancock. This conversation covers progress made in the NLP domain with emerging research, new benchmarks like SuperGLUE, rich repositories and news sources that keep you in the… ...
  • Productionizing ML Research With Thomas Wolf
    February 5, 2021Team Snorkel
    - In this episode of ScienceTalks, Snorkel AI’s Braden Hancock Hugging Face’s Chief Science Officer, Thomas Wolf. Thomas shares his story about how he got into machine learning and discusses important design decisions behind the widely adopted Transformers library, as well as the challenges of bringing research projects into production. ScienceTalks… ...
  • Debugging AI Applications Pipeline
    February 3, 2021
    - We’ll analyze major sources of errors during the four steps of building AI applications: data labeling, feature engineering, model training, and model evaluation. ...
  • How To Overcome Practical Challenges for AI in the Public Sector
    January 7, 2021Charlie Greenbacker
    - AI is already transforming the business of government. But the positive impacts of this transformation, from increasing the efficiency of public services to enhancing the effectiveness of tax dollars, are still in the earliest stages. Public sector organizations generally have access to the same talent, software models, and hardware infrastructure… ...
  • How To Overcome Practical Challenges for AI in Finance
    December 29, 2020Manas Joglekar
    - Advancements in artificial intelligence promise efficiency gains for financial institutions. AI-powered applications can revolutionize an organization’s risk management, fraud detection, compliance monitoring, and other processes. Financial services companies have smart data scientists and good infrastructure needed for deploying AI. But their ability to rapidly develop and deploy AI applications is… ...
  • Machine Learning Production Myths
    December 23, 2020Chip Huyen
    - Takeaways from MLSys Seminars with Chip HuyenIn November, I had the opportunity to come back to Stanford to participate in MLSys Seminars, a series about Machine Learning Systems. It was great to see the growing interest of the academic community in building practical AI applications. Here is a recording of… ...
  • Meet a Snorkeler at an Upcoming Event
    November 17, 2020Team Snorkel
    - We love meeting people in the data science and machine learning community. Here are a few upcoming events where you can meet Snorkelers. ...
  • How to Overcome Practical Challenges for AI in Healthcare
    November 9, 2020Brandon Yang
    - There’s a lot of excitement about the potential for AI to improve healthcare. This is driven by compelling advances across a wide range of applications including drug discovery, radiology, pathology, electronic medical record (EMR) intelligence, clinical trials, and more. There are also many challenges for development and deployment of AI… ...
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