![ORNL scientists estimated quantum computing energy usage from a detailed modeling technique. In a study, the team found that quantum computers could reduce energy usage by more than 20 orders of magnitude compared to conventional computers. ORNL scientists estimated quantum computing energy usage from a detailed modeling technique. In a study, the team found that quantum computers could reduce energy usage by more than 20 orders of magnitude compared to conventional computers.](/sites/default/files/styles/list_page_thumbnail/public/news/images/01%20Energy-Quantum_computing_efficiency_ORNL.jpg?itok=VV6kMwQz)
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![ORNL scientists estimated quantum computing energy usage from a detailed modeling technique. In a study, the team found that quantum computers could reduce energy usage by more than 20 orders of magnitude compared to conventional computers. ORNL scientists estimated quantum computing energy usage from a detailed modeling technique. In a study, the team found that quantum computers could reduce energy usage by more than 20 orders of magnitude compared to conventional computers.](/sites/default/files/styles/list_page_thumbnail/public/news/images/01%20Energy-Quantum_computing_efficiency_ORNL.jpg?itok=VV6kMwQz)
![A senior research scientist at Oak Ridge National Laboratory, Olufemi “Femi” Omitaomu is leveraging Big Data for urban resilience. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Jason Richards. A senior research scientist at Oak Ridge National Laboratory, Olufemi “Femi” Omitaomu is leveraging Big Data for urban resilience. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Jason Richards.](/sites/default/files/styles/list_page_thumbnail/public/news/images/Omi17-P05563_jr%20v1.jpg?itok=6iyNtEQC)
At the Department of Energy’s Oak Ridge National Laboratory, Olufemi “Femi” Omitaomu is leveraging Big Data for urban resilience, helping growing cities support future infrastructure and resource needs.
![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 th
![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)
![An ORNL-led team developed a variable control mechanism to enable precision de-icing on urban roads, using roadway data from the City of Knoxville in Tennessee. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy An ORNL-led team developed a variable control mechanism to enable precision de-icing on urban roads, using roadway data from the City of Knoxville in Tennessee. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/01%20Weather-Precision_de-icing.jpg?itok=LOLom0Il)
A precision approach to treating snow- and ice-covered roads, developed by an Oak Ridge National Laboratory-led research team, aims to help cities effectively allocate resources and expand coverage on roadways.
![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.
![Default image of ORNL entry sign](/sites/default/files/styles/list_page_thumbnail/public/2023-09/default-thumbnail.jpg?h=553c93cc&itok=N_Kd1DVR)
Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been elected fellows of the American Association for the Advancement of Science (AAAS). AAAS, the world’s largest multidisciplinary scientific society
![David Womble has been slated to lead ORNL’s artificial intelligence effort. David Womble has been slated to lead ORNL’s artificial intelligence effort.](/sites/default/files/styles/list_page_thumbnail/public/womble%5B1%5D%20r2.jpg?itok=CdbhVK26)
The Department of Energy’s Oak Ridge National Laboratory has hired high-performance computing leader David Womble to direct its artificial intelligence (AI) efforts. Womble began as AI Program Director on October 30.
![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.