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Media Contacts
![The hCA II active site is flanked by hydrophilic (violet) and hydrophobic (green) binding pockets that can be used to design specific drugs targeting cancer-associated hCAs. Five clinical drugs are shown superimposed in the hCA II active site The hCA II active site is flanked by hydrophilic (violet) and hydrophobic (green) binding pockets that can be used to design specific drugs targeting cancer-associated hCAs. Five clinical drugs are shown superimposed in the hCA II active site](/sites/default/files/styles/list_page_thumbnail/public/hCA_overall%5B2%5D_0.png?itok=UEpJXtYj)
![ORNL and EPRI built an enclosed welding system in a hot cell of ORNL’s Radiochemical Engineering Development Center. C. Scott White (ORNL) performs operations with remotely controlled manipulators and cameras. ORNL and EPRI built an enclosed welding system in a hot cell of ORNL’s Radiochemical Engineering Development Center. C. Scott White (ORNL) performs operations with remotely controlled manipulators and cameras.](/sites/default/files/styles/list_page_thumbnail/public/MAIN%20IMAGE%201_%20IMG_9383_main.jpg?itok=7GzGF5RT)
Scientists of the Department of Energy’s Light Water Reactor Sustainability Program (LWRS) and partners from the Electric Power Research Institute (EPRI) have conducted the first weld tests to repair highly irradiated materials at DOE’s Oak Ridge National Laboratory.
![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
![An example of a spiking neural network shows how data can be classified using the neuromorphic device. Credit: Catherine Schuman and Margaret Drouhard/Oak Ridge National Laboratory, U.S. Dept. of Energy An example of a spiking neural network shows how data can be classified using the neuromorphic device. Credit: Catherine Schuman and Margaret Drouhard/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/Spiking_neural_network_ORNL_2.jpg?itok=CN68Ze_4)
![Fossil_energy_ORNL3.jpg Fossil_energy_ORNL3.jpg](/sites/default/files/styles/list_page_thumbnail/public/Fossil_energy_ORNL3.jpg?itok=jVslmxRP)
![Neutrons-Exotic_particles.jpg Neutrons-Exotic_particles.jpg](/sites/default/files/styles/list_page_thumbnail/public/Neutrons-Exotic_particles.jpg?itok=9vxFNwzw)
![Inspired by the brain’s web of neurons, deep neural networks consist of thousands or millions of simple computational units. Inspired by the brain’s web of neurons, deep neural networks consist of thousands or millions of simple computational units.](/sites/default/files/styles/list_page_thumbnail/public/news/images/iStock_Patton.jpg?itok=-_7cCRH4)
Deep neural networks—a form of artificial intelligence—have demonstrated mastery of tasks once thought uniquely human. Their triumphs have ranged from identifying animals in images, to recognizing human speech, to winning complex strategy games, among other su...
![Eugene Mamontov and the BASIS beam line at the Spallation Neutron Source at ORNL. Photo credit: Jason Richards, ORNL. Eugene Mamontov and the BASIS beam line at the Spallation Neutron Source at ORNL. Photo credit: Jason Richards, ORNL.](/sites/default/files/styles/list_page_thumbnail/public/news/images/MamontovHortizontalTwo.jpg?itok=gZK_tcoc)
![The Department of Energy’s INCITE program promotes transformational advances in science and technology through large allocations of time on state-of-the-art supercomputers. The Department of Energy’s INCITE program promotes transformational advances in science and technology through large allocations of time on state-of-the-art supercomputers.](/sites/default/files/styles/list_page_thumbnail/public/news/images/incite_awards_headline.png?itok=o-UFMiIC)
The U.S. Department of Energy’s Office of Science announced 55 projects with high potential for accelerating discovery through its Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. The projects will share 5.95 billion core-hours on t...