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Media Contacts
A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.
Researchers at the Department of Energy’s Oak Ridge National Laboratory 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 systems charged with our nation’s most precious data.
ORNL researchers have teamed up with other national labs to develop a free platform called Open Energy Data Initiative Solar Systems Integration Data and Modeling to better analyze the behavior of electric grids incorporating many solar projects.
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. and Puerto Rico, details outages at 15-minute intervals for up to 92% of customers for the eight-year period.
Four ORNL researchers traveled to Warsaw, Poland, during the first week of April to support the opening of Poland’s first Clean Energy Training Center, a regional hub dedicated to providing workforce development and training to expand new nuclear
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 security culture and resilience strategies and techniques.
Howard Wilson explores how to accelerate the delivery of fusion energy as Fusion Pilot Plant R&D lead at ORNL. Wilson envisions a fusion hub with ORNL at the center, bringing together the lab's unique expertise and capabilities with domestic and international partnerships to realize the potential of fusion energy.
Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.
Scientists at ORNL completed a study of how well vegetation survived extreme heat events in both urban and rural communities across the country in recent years. The analysis informs pathways for climate mitigation, including ways to reduce the effect of urban heat islands.
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.