AI @ ORNL – Artificial Intelligence Contact

Using various tools developed by ORNL teams, researchers at the lab are adapting artificial intelligence techniques to better understand cancer and other diseases. Through a series of ongoing, interconnected research projects, they are informing health policy and improving public health outcomes. These efforts include a pilot project for the CANcer Distributed Learning Environment (CANDLE) initiative, a joint endeavor led by DOE and the National Cancer Institute that focuses on developing language processing techniques to identify connections between sources of medical data ranging from images to test results to doctors’ notes. Combing through these disparate health records simultaneously would not be feasible with conventional analytical methods.

AI, in combination with the Summit supercomputer and other resources at the lab, accelerates research across the broad spectrum of energy generation, distribution, storage, and security. For example, scientists use AI to study clean energy sources and mitigate environmental impacts by running climate simulations, developing new materials, and creating carbon-capture technologies. Additionally, AI helps ORNL staff improve certain maintenance and operation practices, extending the lifetimes and energy production capabilities of nuclear power plants and other facilities. AI techniques can also be used in studies related to the nation’s power grid, ensuring both cyber and physical security during the delivery of electricity to homes, businesses, and public spaces as part of DOE’s Grid Modernization Initiative.

ORNL’s Summit system is more than the most powerful high-performance computing machine in the United States—it’s also the nation's smartest supercomputer. This IBM system debuted in June 2018 and resides at the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility located at ORNL. With computing power and architecture components optimized for AI applications, Summit helps researchers apply machine learning and deep learning techniques to a variety of science problems to quickly obtain accurate results. Summit’s increased memory bandwidth means researchers can tackle data-intensive problems without the need to constantly move data. As a result, unimpeded deep learning algorithms run at faster speeds and reach higher levels of accuracy than would be possible on another system.