A new approach developed by PNNL scientists improves the accuracy of patient diagnosis up to 20 percent when compared to other embedding approaches.

Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.

The U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) is the recipient of two R&D 100 awards and one gold medal.

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.

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.

Scientists have taken a common component of digital devices and endowed it with a previously unobserved capability, opening the door to a new generation of silicon-based electronic devices.

Researchers apply numerical simulations to understand more about a sturdy material and how its basic structure responds to and resists radiation. The outcomes could help guide development of the resilient materials of the future.

PNNL has developed a unique suite of tools that utilize satellite imagery to generate timely damage assessments with revealing detail.

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.

IDREAM researchers computed the first detailed free-energy landscape for the multistep dissolution of gibbsite

Scientists are exploring the use of deep neural network to interpret highly technical data related to national security, the environment and the cosmos.