{"type":"standard","title":"Cynthia Rudin","displaytitle":"Cynthia Rudin","namespace":{"id":0,"text":""},"wikibase_item":"Q59662692","titles":{"canonical":"Cynthia_Rudin","normalized":"Cynthia Rudin","display":"Cynthia Rudin"},"pageid":61587825,"thumbnail":{"source":"https://upload.wikimedia.org/wikipedia/commons/thumb/1/1a/Cynthia_Rudin_JSM_2020.png/330px-Cynthia_Rudin_JSM_2020.png","width":320,"height":238},"originalimage":{"source":"https://upload.wikimedia.org/wikipedia/commons/1/1a/Cynthia_Rudin_JSM_2020.png","width":516,"height":384},"lang":"en","dir":"ltr","revision":"1285063835","tid":"ac6c2472-16d8-11f0-8689-a6c8e6e10c0d","timestamp":"2025-04-11T13:27:11Z","description":"American computer scientist and statistician","description_source":"local","content_urls":{"desktop":{"page":"https://en.wikipedia.org/wiki/Cynthia_Rudin","revisions":"https://en.wikipedia.org/wiki/Cynthia_Rudin?action=history","edit":"https://en.wikipedia.org/wiki/Cynthia_Rudin?action=edit","talk":"https://en.wikipedia.org/wiki/Talk:Cynthia_Rudin"},"mobile":{"page":"https://en.m.wikipedia.org/wiki/Cynthia_Rudin","revisions":"https://en.m.wikipedia.org/wiki/Special:History/Cynthia_Rudin","edit":"https://en.m.wikipedia.org/wiki/Cynthia_Rudin?action=edit","talk":"https://en.m.wikipedia.org/wiki/Talk:Cynthia_Rudin"}},"extract":"Cynthia Diane Rudin is an American computer scientist and statistician specializing in machine learning and known for her work in interpretable machine learning. She is the director of the Interpretable Machine Learning Lab at Duke University, where she is a professor of computer science, electrical and computer engineering, statistical science, and biostatistics and bioinformatics. In 2022, she won the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI) for her work on the importance of transparency for AI systems in high-risk domains.","extract_html":"
Cynthia Diane Rudin is an American computer scientist and statistician specializing in machine learning and known for her work in interpretable machine learning. She is the director of the Interpretable Machine Learning Lab at Duke University, where she is a professor of computer science, electrical and computer engineering, statistical science, and biostatistics and bioinformatics. In 2022, she won the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI) for her work on the importance of transparency for AI systems in high-risk domains.
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{"fact":"It is estimated that cats can make over 60 different sounds.","length":60}
{"slip": { "id": 188, "advice": "Measure twice, cut once."}}