Skip to main content
The Frontier exascale supercomputer at Oak Ridge National Laboratory. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL has joined a global consortium of scientists from federal laboratories, research institutes, academia and industry to address the challenges of building large-scale artificial intelligence systems and advancing trustworthy and reliable AI for

From left are Analytics and AI Methods at Scale group leader Feiyi Wang, technical lead Mike Matheson and research scientist Hao Lu.

The team that built Frontier set out to break the exascale barrier, but the supercomputer’s record-breaking didn’t stop there.

ORNL scientists developed a method that improves the accuracy of the CRISPR Cas9 gene editing tool used to modify microbes for renewable fuels and chemicals production. This research draws on the lab’s expertise in quantum biology, artificial intelligence and synthetic biology. Credit: Philip Gray/ORNL, U.S. Dept. of Energy

Scientists at ORNL used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of its Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making. Credit: Rachel Green/ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.

Oak Ridge National Laboratory entrance sign

Researchers and analysts at the Department of Energy’s Oak Ridge National Laboratory are combining geospatial science and artificial intelligence to reduce the risks posed by nuclear materials while further enabling the peaceful use of nuclear

The DEMAND single crystal diffractometer at the High Flux Isotope Reactor, or HFIR, is the latest neutron instrument at the Department of Energy’s Oak Ridge National Laboratory to be equipped with machine learning-assisted software, called ReTIA. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy

Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.

Frontier supercomputer cabinets

Experts at the Department of Energy’s national laboratories are working with university and industry partners to improve machine learning and deep learning by reducing costs and times to solution. And as AI systems become increasingly integral to critical decision-making processes and more deeply integrated into research workflows, ensuring their reliability and accuracy is more important than ever.

AIRES 4 attendees hailing from seven national laboratories and from academia met to discuss robust engineering for digital twins. Credit: Pradeep Ramuhalli/ORNL, U.S. Dept. of Energy

ORNL hosted its fourth Artificial Intelligence for Robust Engineering and Science, or AIRES, workshop from April 18-20. Over 100 attendees from government, academia and industry convened to identify research challenges and investment areas, carving the future of the discipline.

Trillion Pixel Challenge attendees included interdisciplinary experts from image science, computer vision, high-performance computing, architecture, machine learning, advanced workflows, and end-user communities who came together to discuss geospatial AI challenges.

Experts across varied technology fields gathered ORNL to collaborate on the future of geospatial systems at the Trillion-Pixel GeoAI Challenge workshop. The third iteration of this event focused on multimodal advances in the field, including progress in artificial intelligence, cloud infrastructure, high-performance computing and remote sensing. These capabilities, when combined, can help solve problems in national and human security such as disaster response and land-use planning.

Frontier supercomputer

Innovations in artificial intelligence are rapidly shaping our world, from virtual assistants and chatbots to self-driving cars and automated manufacturing.