All Work Published on Machine Learning
Stanford scholars explore advances in foundation models, explore the next-generation chip, and study causal models at the recent Hoffman-Yee Symposium.
Stanford scholars explore advances in foundation models, explore the next-generation chip, and study causal models at the recent Hoffman-Yee Symposium.
Seven Stanford HAI faculty and fellows predict the biggest stories for next year in artificial intelligence.
Seven Stanford HAI faculty and fellows predict the biggest stories for next year in artificial intelligence.
Generative models dominated the year, as calls for policy and transparency heated up.
Generative models dominated the year, as calls for policy and transparency heated up.
At Stanford HAI’s recent fall conference, scholars showed how artificial intelligence is opening up new approaches to studying science.
At Stanford HAI’s recent fall conference, scholars showed how artificial intelligence is opening up new approaches to studying science.
BLASTNet – The First Large Machine Learning Dataset for Fundamental Fluid Dynamics
By collecting data from the field of computational fluid dynamics into a single dataset, AI researchers at Stanford hope to do for rocket science, oceanography, and climate modeling what web-scale data did for language.
By collecting data from the field of computational fluid dynamics into a single dataset, AI researchers at Stanford hope to do for rocket science, oceanography, and climate modeling what web-scale data did for language.
AI, Ethics, and Public Service: Bridging the Gap through Stanford HAI’s Fellowship Program
HAI’s first cohort of Tech Ethics & Policy fellows helped develop the White House executive order on AI, reassessed the AI procurement process, and shaped the conversation around generative AI.
HAI’s first cohort of Tech Ethics & Policy fellows helped develop the White House executive order on AI, reassessed the AI procurement process, and shaped the conversation around generative AI.