Jesse Labbé: Innovating biotechnology for energy, security and health
A carbon-reducing engine simulated on the world’s fastest supercomputer, a new center to lead research in artificial intelligence coming online and a power record set by the world’s top producer of pulsed neutrons were among the topics featured in Oak Ridge National Laboratory’s most popular news stories of 2023.
Despite its futuristic essence, artificial intelligence has a history that can be traced through several decades, and the ORNL has played a major role. From helping to drive fundamental and applied AI research from the field’s early days focused on expert systems, computer programs that rely on AI, to more recent developments in deep learning, a form of AI that enables machines to make evidence-based decisions, the lab’s AI research spans the spectrum.
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
The team that built Frontier set out to break the exascale barrier, but the supercomputer’s record-breaking didn’t stop there.
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 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.
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
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.
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.
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.