In today’s digital age, the rabbit hole of connected information can be not only a time sink, but downright overwhelming. Even for high-performance computers.

Twenty-four analysts from U.S. intelligence organizations met in August for a machine learning activity with PNNL researchers Nicole Nichols, Jeremiah Rounds, Lawrence Phillips, and Brian Kritzstein.

A new study examines how back how back-to-back extreme events can affect a forest landscape.

Three powerhouses in the realm of artificial intelligence have become partners in a new research center created by the U.S. Department of Energy.

Trouble on the electric grid might start with something relatively small: a downed power line, or a lightning strike at a substation. What happens next?

Pacific Northwest National Laboratory is leading efforts to address next-generation computing’s critical role in protecting the nation from cybersecurity threats.

Small increases in irrigated and rainfed crop production across regions where water remains plentiful could help keep food shelves stocked worldwide.

A new data system—gcamdata—with its robust, clear, and easy-to-use application, was developed to be applied to a variety of Global Change Assessment Model scenarios.

Research software aims to formulate an accurate way to explore feedbacks among socioeconomics, Earth system changes, and crop yield changes

Researchers at PNNL are applying deep learning techniques to learn more about neutrinos, part of a worldwide network of researchers trying to understand one of the universe’s most elusive particles.

Scientists created a fast-track tutorial that equips a neural network to tackle drug discovery and other applications where there's a shortage of precisely labeled chemical data.

Researchers at PNNL used key metrics to develop visualizations that show how the combined effects of climate change on hydropower and load influence the frequency, duration, and severity of power shortfalls.

A unique strategy sharpens understanding of the behavior and physics within the model’s atmospheric component.