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.

Researchers use models to represent relationships between climate and socio-economic processes, helping inform decisions for slowing climate change and enhancing resilience.

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.

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.

Jingyi Chen and Claudia Tebaldi honored as outstanding reviewers by the American Geophysical Union.

Claudia Tebaldi, a PNNL Earth scientist, has been named a Fellow of the American Geophysical Union. Tebaldi and others will be recognized at AGU23 in December.

Variations in the level of market globalization can greatly affect the amount of water required to meet future global demand for agricultural commodities.

Climate change and socioeconomic pressures are transforming passenger and freight transportation in the Arctic, producing effects that have yet to be fully understood.

In a new paper, researchers point to three major efforts where the biggest climate mitigation gains stand to be realized: ramping up carbon dioxide removal, reigning in non-carbon dioxide emissions and halting deforestation.

Testing the assumption that different future socio-economic development patterns, which result in different land-use changes, can be paired with different future climate outcomes for risk assessments in a multi-model framework.

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

Incorporating spatially explicit land characteristics in a global model illustrates the complex effects of applying uniform regional protection assumptions in a global analysis.

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

Pasco School District teachers join PNNL for an immersive teaching experience.

Stinis will serve as a principal investigator on two of the four projects selected for funding by the Advanced Scientific Computing Research program.

The Human Factors Symposium took place at Discovery Hall at PNNL in May 2023. Fifty-seven attendees participated in the three-day event representing 15 different institutions.