
Researchers at 91°µÍø used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts.
Researchers at 91°µÍø used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts.
The Department of Energy announced a $67 million investment in several AI projects from institutions in both government and academia as part of its AI for Science initiative. Six ORNL-led (or co-led) projects received funding.
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the
Despite its futuristic essence, artificial intelligence has a history that can be traced through several decades, and the ORNL has played a major role.
Effective Dec. 4, Gina Tourassi will assume responsibilities as associate laboratory director for the Computing and Computational Sciences Directorate at the Department of Energy’s 91°µÍø.
ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.
The Department of Energy’s 91°µÍø announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and t
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
As Frontier, the world’s first exascale supercomputer, was being assembled at the Oak Ridge Leadership Computing Facility in 2021, understanding its performance on mixed-precision calculations remained a difficult prospect.