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Media Contacts
For the past six years, some 140 scientists from five institutions have traveled to the Arctic Circle and beyond to gather field data as part of the Department of Energy-sponsored NGEE Arctic project. This article gives insight into how scientists gather the measurements that inform t...
![Default image of ORNL entry sign](/sites/default/files/styles/list_page_thumbnail/public/2023-09/default-thumbnail.jpg?h=553c93cc&itok=N_Kd1DVR)
James Peery, who led critical national security programs at Sandia National Laboratories and held multiple leadership positions at Los Alamos National Laboratory before arriving at the Department of Energy’s Oak Ridge National Laboratory last year, has been named a...
![Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database. Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2018-P00005_r3_0.jpg?itok=FrGhhOuK)
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the