At the GovAI Summit 2023, Ryan Eddy joined the Department of Homeland Security Science and Technology Directorate on a panel highlighting artificial intelligence impacts and opportunities in the field of emergency management.

The convergence of artificial intelligence, cloud, and high-performance computing to accelerate scientific discovery is the focus of a multi-year collaboration between Microsoft and PNNL.

Researchers at PNNL joined more than 600 national experts who contributed to NCA5.

PNNL had a significant presence at October’s North American Wind Energy Academy/WindTech 2023 Conference in Denver, Colorado. Thirteen PNNL wind experts participated in various capacities.

The U.S. Nuclear Regulatory Commission approved the construction permit for Kairos Power’s Hermes molten salt test reactor project in Tennessee.

Harish Gadey, David Peeler, and Tom Brouns named to Waste Management Symposia Program Advisory Committee positions to help develop radioactive waste management discussions.

PNNL researchers comment on the “Adversarial Machine Learning” white paper from the National Institute of Standards and Technology.

PNNL has created the Center for AI @PNNL to coordinate the pioneering research of hundreds of scientists working on a range of projects in artificial intelligence.

If current warming trends continue, heat waves like Washington's deadliest could grow stronger and afflict the Pacific Northwest more often.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.

PNNL has joined Gender Champions in Nuclear Policy, a leadership network that brings together leaders of organizations working in nuclear policy who are committed to breaking down gender barriers.

Resolving how nanoparticles come together is important for industry and environmental remediation. New work predicts nanoparticle aggregation behavior across a wide range of scales for the first time.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

Researchers from PNNL, CSET, and Google DeepMind delved into the potential risks of artificial intelligence in a roundtable discussion.

NRC Chair Christopher Hanson tours the nondestructive examination laboratories and learns more about PNNL’s broad support to the NRC mission.

PNNL signs memorandum of understanding with Oregon State University to support marine science and technology advancements.

A new tool helps identify non-powered dams across the country that are top candidates for conversion to power-generating hydroelectric facilities.

Robert Rallo from Pacific Northwest National Laboratory will direct a machine learning thrust for a new Department of Energy-funded project led by SLAC National Accelerator Laboratory.