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Research teams at the Department of Energy’s Oak Ridge National Laboratory received computing resource awards to train and test AI foundation models for science. A total of six ORNL projects were awarded allocations from the National Artificial Intelligence Research Resource, or NAIRR, pilot and the Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program to train their AI models.
ORNL has developed a network of autonomous science laboratories outfitted with state-of-the-art artificial intelligence and robotic systems and connected to the lab’s world-class user facilities. The goal is to supercharge the research process while producing scientific breakthroughs that would be unachievable in a traditional setting.
ORNL took part in the “1,000 Scientists AI Jam Session,” a first-of-its-kind virtual event that brought together leading scientists from nine national laboratories to test generative artificial intelligence models for their functionality in scientific research.
During his first visit to Oak Ridge National Laboratory, Energy Secretary Chris Wright compared the urgency of the Lab’s World War II beginnings to today’s global race to lead in artificial intelligence, calling for a “Manhattan Project 2.”
ORNL and NASA co-hosted the fourth iteration of this invitation-only event, which brings together geospatial, computational, data and engineering experts around a theme. This year’s gathering focused on how artificial intelligence foundation models can enable geospatial digital twins.
Prasanna Balprakash, director of AI programs for ORNL, discussed advancing climate and weather research through high performance computing and artificial intelligence as part of a September 18 panel for the United States Senate.
A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.
In a game-changing study, ORNL scientists developed a deep learning model — a type of artificial intelligence that mimics human brain function — to analyze high-speed videos of plasma plumes during a process called pulsed laser deposition.
As high-tech companies ramp up construction of massive data centers to meet the business boom in artificial intelligence, one component is becoming an increasingly rare commodity: electricity. Since its formation in 2004, the OLCF has fielded five generations of world-class supercomputing systems that have produced a nearly 2,000 times reduction in energy usage per floating point operation per second, or flops. With decades of experience in making HPC more energy efficient, the OLCF may serve as a resource for best “bang for the buck” practices in a suddenly burgeoning industry.
Prasanna Balaprakash, director of AI programs at the Department of Energy’s Oak Ridge National Laboratory, has been appointed to Tennessee’s Artificial Intelligence Advisory Council.