Latest posts

• How NVIDIA Omniverse bolsters AI with synthetic data
  July 6, 2023Snorkel Team
  - NVIDIA's Nyla Worker presented “Leveraging Synthetic Data to Train Perception Models Using NVIDIA Omniverse Replicator” in 2022. ...
• Google experts on practical paths to data-centricity in applied AI
  July 5, 2023Snorkel Team
  - Google experts Abhishek Ratna and Robert Crowe discuss practical paths to data-centricity in applied AI at The Future of Data-Centric AI '22. ...
• How to build reusable data cleaning pipelines with scikit-learn
  July 3, 2023Snorkel Team
  - State Farm senior data scientist Jason Goldfarb presented “Reusable Data Cleaning Pipelines in Python” at the Future of Data-Centric AI 2022. ...
• Arize AI on How to apply and use machine learning observability
  June 30, 2023Snorkel Team
  - Jack Zhou, product manager at Arize, on “How to Apply Machine Learning Observability to Your ML System” from The Future of Data-Centric AI ...
• The future of large language models is faster and more robust
  June 29, 2023Fred Sala
  - Snorkel and affiliated academic labs have been hard at work reducing how computationally expensive large language models are. ...
• Claypot AI CEO on why you should deploy models the hard way
  June 27, 2023Snorkel Team
  - Claypot AI CEO Chip Huyen presented “Platform for Real-Time Machine Learning” at Snorkel AI’s Future of Data-Centric AI 2022. ...
• McKinsey QuantumBlack on automating data quality remediation with AI
  June 22, 2023Snorkel Team
  - Jacomo Corbo and Bryan Richardson with QuantumBlack present “Automating Data Quality Remediation With AI” at The Future of Data-Centric AI. ...
• Sambanova on using LLMs to squeeze value from business data
  June 20, 2023Snorkel Team
  - Stefano Lindt presents “Leveraging NLP to Extract Value From Business Data” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. ...