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- Foundation Models 101: a guide with essential FAQs - Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. What are they and how will they impact your business? Find out in our guide. ...
- Combining foundation models with weak supervision - Combining foundation model outputs with weak supervision yields faster model development and requires fewer ground truth labels. ...
- Operationalizing knowledge for data-centric AI - Snorkel AI CEO and Co-Founder Alex Ratner's introduction to data-centric AI from the 2022 Future of Data-Centric AI virtual conference. ...
- Credo AI DS head on operationalizing responsible AI - Credo AI's head of data science explains at Snorkel's FDCAI 2022 how his team works to operationalize responsible AI assessment tools. ...
- How a Brown professor sharpened and shrunk GPT-3 - Brown professor Stephen Bach tells Snorkel CEO Alex Ratner about his research into improving foundation models like GPT-3 with curated data. ...
- Cleanlab CEO shows automatic data-cleansing tools - Cleanlab Co-Founder and CEO Curtis Northcutt presents his company's automatic, universal and open-source tools to quickly clean data sets. ...
- Aspect-based sentiment analysis in Snorkel Flow - Understanding and quantifying people's opinions has become increasingly important to businesses, but the way people can express multiple thoughts in the same sentence has frustrated practitioners' efforts to extract those opinions cleanly—a problem we can solve through aspect-based sentiment analysis (ABSA). ...
- Comcast’s data-centric approach to speech interfaces - Jan Neumann, Vice President of Machine Learning for Comcast Applied AI and Discovery, describes Comcast's data-centric AI approach to speech. ...
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