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![ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La](/sites/default/files/styles/list_page_thumbnail/public/study_area_one_dest_2.jpg?itok=2cWFkQvW)
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
![The Consortium for Advanced Simulation of Light Water Reactors uses its Virtual Environment for Reactor Applications (VERA) software for the modeling and simulation of various nuclear reactors, such as the Westinghouse AP1000 pressurized water reactor. The Consortium for Advanced Simulation of Light Water Reactors uses its Virtual Environment for Reactor Applications (VERA) software for the modeling and simulation of various nuclear reactors, such as the Westinghouse AP1000 pressurized water reactor.](/sites/default/files/styles/list_page_thumbnail/public/AP1000_highres_pin_powers.png?itok=5jd5vcFM)
The Department of Energy’s Oak Ridge National Laboratory is collaborating with industry on six new projects focused on advancing commercial nuclear energy technologies that offer potential improvements to current nuclear reactors and move new reactor designs closer to deployment.
![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
![As hurricanes formed in the Gulf Coast, ORNL activated a computing technique to quickly gather building structure data from Texas’ coastal counties. Credit: Mark Tuttle/Oak Ridge National Laboratory, U.S. Dept. of Energy As hurricanes formed in the Gulf Coast, ORNL activated a computing technique to quickly gather building structure data from Texas’ coastal counties. Credit: Mark Tuttle/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/01%201%20-%20Impacts%20r1.jpg?itok=D1FzgK0y)
Geospatial scientists at Oak Ridge National Laboratory have developed a novel method to quickly gather building structure datasets that support emergency response teams assessing properties damaged by Hurricanes Harvey and Irma. By coupling deep learning with high-performance comp...