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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
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.
Currently, the biggest hurdle for electric vehicles, or EVs, is the development of advanced battery technology to extend driving range, safety and reliability.
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.
The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.
Innovations in artificial intelligence are rapidly shaping our world, from virtual assistants and chatbots to self-driving cars and automated manufacturing.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.
Scientists at the Department of Energy’s Oak Ridge National Laboratory have created a recipe for a renewable 3D printing feedstock that could spur a profitable new use for an intractable biorefinery byproduct: lignin.
A team of scientists, led by University of Guelph professor John Dutcher, are using neutrons at ORNL’s Spallation Neutron Source to unlock the secrets of natural nanoparticles that could be used to improve medicines.
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the