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Jiafu Mao, left, and Yaoping Wang discuss their analysis of urban and rural vegetation resilience across the United States in the EVEREST visualization lab at ORNL. Credit: Carlos Jones, ORNL/U.S. Dept. of Energy

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.

Hood Whitson, chief executive officer of Element3, and Cynthia Jenks, associate laboratory director for the Physical Sciences Directorate, shake hands during the Element3 licensing event at ORNL on May 3, 2024. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A collection of seven technologies for lithium recovery developed by scientists from ORNL has been licensed to Element3, a Texas-based company focused on extracting lithium from wastewater produced by oil and gas production. 

The AI for Energy Report provides a framework for using AI to accelerate decarbonization of the U.S. economy. Credit: Argonne National Laboratory

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.

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. 

Researchers relied on support from ORNL’s Quantum Computing User Program to simulate a key quantum state at one of the largest scales reported. The findings could mark a step toward improving quantum simulations.  Credit: Getty Images

Researchers simulated a key quantum state at one of the largest scales reported, with support from the Quantum Computing User Program, or QCUP, at ORNL. 

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

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

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. 
 

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.

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

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.

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