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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 are developing algorithms and multilayered communication and control systems that make electric vehicle chargers operate more reliably, even if there is a voltage drop or disturbance in the electric grid. Credit: Andy Sproles/ORNL, US Dept. of Energy

ORNL researchers are working to make EV charging more resilient by developing algorithms to deal with both internal and external triggers of charger failure. This will help charging stations remain available to traveling EV drivers, reducing range anxiety.

Alyssa Carrell is an ORNL ecologist studying how plant-microbe relationships can build resilience in natural ecosystems vulnerable to climate change. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Alyssa Carrell started her science career studying the tallest inhabitants in the forest, but today is focused on some of its smallest — the microbial organisms that play an outsized role in plant health. 

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.

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 industry, government and academia to discuss ways to transition to clean energy.

The 2023 Billion-Ton Report identifies feedstocks that could be available to produce biofuels to decarbonize the transportation and industrial sectors while potentially tripling the U.S. bioeconomy. The map indicates a mature market scenario, including emerging resources. Credit: ORNL/U.S. Dept. of Energy

The United States could triple its current bioeconomy by producing more than 1 billion tons per year of plant-based biomass for renewable fuels, while meeting projected demands for food, feed, fiber, conventional forest products and exports, according to the DOE’s latest Billion-Ton Report led by ORNL.

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.

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

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.

Anuj Kapadia

Anuj J. Kapadia, who heads the Advanced Computing Methods for Health Sciences Section at ORNL, has been elected as president of the Southeastern Chapter of the American Association of Physicists in Medicine. 

New system combines human, artificial intelligence to improve experimentation

To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.