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Media Contacts
![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.
![Peter Thornton, second from right, is director of ORNL’s Climate Change Science Institute. He shares insights on the regional impacts of changing weather patterns during the Second Annual Appalachian Carbon Forum in Lexington, Kentucky. Credit: University of Kentucky’s Center for Applied Energy Research.](/sites/default/files/styles/list_page_thumbnail/public/2024-03/20240308AppalachianCarbonForum019-2.jpg?h=a1e1a043&itok=HmCrz1br)
ORNL hosted the second annual Appalachian Carbon Forum in Lexington March 7-8, 2024, where ORNL and University of Kentucky’s Center for Applied Energy Research scientists led discussions with representatives from
![ORNL researcher Brian Williams prepares for a demonstration of a quantum key distribution system. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-03/Picture1_0.jpg?h=e4f440a4&itok=5uAWjLhR)
An experiment by researchers at the Department of Energy’s Oak Ridge National Laboratory demonstrated advanced quantum-based cybersecurity can be realized in a deployed fiber link.
![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
![New system combines human, artificial intelligence to improve experimentation](/sites/default/files/styles/list_page_thumbnail/public/2024-02/Screenshot%202024-02-14%20at%2011.37.46%20AM%20%281%29.png?h=e621a1e2&itok=N3lsBqrh)
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
![A multidirectorate group from ORNL attended AGU23 and came away inspired for the year ahead in geospatial, earth and climate science](/sites/default/files/styles/list_page_thumbnail/public/2024-02/MicrosoftTeams-image%20%2815%29%20%281%29.png?h=a5eb5da0&itok=gY269KaC)
ORNL scientists and researchers attended the annual American Geophysical Union meeting and came away inspired for the year ahead in geospatial, earth and climate science.
![Three staff members in Oak Ridge National Laboratory’s Fusion and Fission Energy and Science Directorate (FFESD) have moved into newly established roles facilitating communication and program management with sponsors of the directorate’s Nuclear Energy and Fuel Cycle Division.](/sites/default/files/styles/list_page_thumbnail/public/2024-02/3_people_spacing.jpg?h=08ef668f&itok=33PRJFyS)
Three staff members in ORNL’s Fusion and Fission Energy and Science Directorate have moved into newly established roles facilitating communication and program management with sponsors of the directorate’s Nuclear Energy and Fuel Cycle Division.
![: ORNL climate modeling expertise contributed to an AI-backed model that assesses global emissions of ammonia from croplands now and in a warmer future, while identifying mitigation strategies. This map highlights croplands around the world. Credit: U.S. Geological Survey](/sites/default/files/styles/list_page_thumbnail/public/2024-02/global_croplands_usgs_globe-4g_1.png?h=4016a495&itok=rb8eHyvK)
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
![Conversion of an atomic structure into a graph, where atoms are treating as nodes and interatomic bonds as edges. Credit: Massimiliano “Max” Lupo Pasini/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/hydra_gnn_diagram.png?h=2deb2cea&itok=4OvY68cs)
Researchers at the Department of Energy’s Oak Ridge and Lawrence Berkeley National Laboratories are evolving graph neural networks to scale on the nation’s most powerful computational resources, a necessary step in tackling today’s data-centric