
Vanderbilt University and ORNL announced a partnership to develop training, testing and evaluation methods that will accelerate the Department of Defense’s adoption of AI-based systems in operational environments.
Vanderbilt University and ORNL announced a partnership to develop training, testing and evaluation methods that will accelerate the Department of Defense’s adoption of AI-based systems in operational environments.
Researchers tackling national security challenges at ORNL are upholding an 80-year legacy of leadership in all things nuclear.
ORNL drone and geospatial team becomes first to map the Coca River in the Amazon basin as erosion and sediment threaten Ecuador’s lands.
Researchers at the Department of Energy’s 91°µÍø met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI sy
ORNL researchers have produced the most comprehensive power outage dataset ever compiled for the United States. This dataset, showing electricity outages from 2014-22 in the 50 U.S. states, Washington D.C.
Mohamad Zineddin hopes to establish an interdisciplinary center of excellence for nuclear security at ORNL, combining critical infrastructure assessment and protection, risk mitigation, leadership in nuclear security, education and training, nuclear sec
Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people.
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.
Auburn University’s McCrary Institute for Cyber and Critical Infrastructure Security was awarded a $10 million DOE grant in partnership with ORNL to create a pilot regional cybersecurity research and operations center to protect the electric power grid
In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.