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Media Contacts
![Quietly making noise: Measuring differential privacy could balance meaningful analytics and identity protection](/sites/default/files/styles/list_page_thumbnail/public/2024-04/AdobeStock_599537692.jpeg?h=8059516b&itok=oDcA1WvL)
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.
![: Quantity of CCR and, if applicable, water held in the unit as of 2020/2021.](/sites/default/files/styles/list_page_thumbnail/public/2024-05/image001%20%281%29.png?h=200d7428&itok=AS8NtvSo)
ORNL scientists contributed to a DOE technical study that found transitioning coal plants to nuclear power plants would create high-paying jobs at the converted plants and hundreds of new jobs locally.
![The AI for Energy Report provides a framework for using AI to accelerate decarbonization of the U.S. economy. Credit: Argonne National Laboratory](/sites/default/files/styles/list_page_thumbnail/public/2024-05/CLS_AI-for-Energy-Workshop-Report_1600x900_shutterstock_209822020_R2.jpg?h=748c0655&itok=uYkfSuJp)
Groundbreaking report provides ambitious framework for accelerating clean energy deployment while minimizing risks and costs in the face of climate change.
![The transportation and industrial sectors together account for more than 50% of the country’s carbon footprint. Defossilization could help reduce new emissions from these and other difficult-to-electrify segments of the U.S. economy.](/sites/default/files/styles/list_page_thumbnail/public/2024-05/GettyImages-887377090%20%281%29.jpg?h=73e7f248&itok=QYmqPfWv)
Scientists at Oak Ridge National Laboratory and six other Department of Energy national laboratories have developed a United States-based perspective for achieving net-zero carbon emissions.
![SOS26 attendees standing in front of the Kennedy Space Center on Merrit Island, Florida the night of their dinner reception provided by the conference sponsors. The keynote speaker was Rupak Biswas from NASA. Credit: Judy Potok/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/IMG_4436%5B16%5D%20%281%29.jpeg?h=51920af5&itok=cf3iVu5B)
Held in Cocoa Beach, Florida from March 11 to 14, researchers across the computing and data spectra participated in sessions developed by staff members from the Department of Energy’s Oak Ridge National Laboratory, or ORNL, Sandia National Laboratories and the Swiss National Supercomputing Centre.
![ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/powered%20by%20match.jpg?h=384e2afb&itok=wJegcDZm)
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.
![Credit: Tyler Spano/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/liz.jpg?h=ab2675cd&itok=jVO3_Ggr)
Nuclear nonproliferation scientists at ORNL have published the Compendium of Uranium Raman and Infrared Experimental Spectra, a public database and analysis of structure-spectral relationships for uranium minerals. This first-of-its-kind dataset and corresponding analysis fill a key gap in the existing body of knowledge for mineralogists and actinide scientists.
![ORNL researchers developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with more accurate information on cancer reporting.](/sites/default/files/styles/list_page_thumbnail/public/2024-03/bigbird%20image.jpg?h=8f74817f&itok=VXR7SQWV)
In partnership with the National Cancer Institute, researchers from ORNL and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.
![Sean Oesch](/sites/default/files/styles/list_page_thumbnail/public/2024-03/Picture1.jpg?h=b6c94d59&itok=HaSGWHLY)
While government regulations are slowly coming, a group of cybersecurity professionals are sharing best practices to protect large language models powering these tools. Sean Oesch, a leader in emerging cyber technologies, recently contributed to the OWASP AI Security and Privacy Guide to inform global AI security standards and regulations.
![AI-driven attention mechanisms aid in streamlining cancer pathology reporting.](/sites/default/files/styles/list_page_thumbnail/public/2024-03/attention%20mechanism%20%282%29.jpg?h=3a7a7cb1&itok=_OJowEl4)
In partnership with the National Cancer Institute, researchers from the Department of Energy’s Oak Ridge National Laboratory’s Modeling Outcomes for Surveillance using Scalable Artificial Intelligence are building on their groundbreaking work to