The nation is closer to its offshore wind energy goals than ever before, but better wind forecasting is still needed. To address this challenge, PNNL and collaborators are charting a new course with help from novel technology.

Ang participated in a White House-hosted CHIPS R&D event and roundtable discussion with senior leaders from industry, academia and key government agencies.

Machine learning methods and data science can uncover hidden patterns in nanoparticle synthesis conditions and property outcomes.

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.

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.

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.

Department of Energy’s Advanced Research Projects Agency-Energy selects PNNL project to help accelerate the development of marine carbon dioxide removal technologies.

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

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.

To identify communities ready for marine energy, help them realize their energy resilience goals, and facilitate community leadership in future projects, two national laboratories are developing the Deployment Readiness Framework.

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

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

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.

The report explores how research in planning, data, policy, and technology can address some of the underlying challenges facing water power systems.

PNNL convenes ocean leaders to tackle climate challenges and support the Ocean Climate Action Plan.

PNNL’s software tool brings together artificial intelligence and satellite imagery to help responders assess damage and take action.

PNNL is collaborating with Microsoft, Micron and other partners to make computational chemistry broadly available.