The U.S. Department of Energy (DOE) announced a total of $20 million in funding for innovative research and development in artificial intelligence (A.I.) and machine learning.
DOE’s Office of Electricity has selected eight projects to receive nearly $7 million in total to explore the use of big data, artificial intelligence, and machine learning technologies to improve existing knowledge and discover new insights and tools for better grid operation and management. DOE’s Office of Science announced a plan to provide $13 million in total funding for new research aimed at improving A.I. as a tool of scientific investigation and prediction.
“Leveraging the power of artificial intelligence will revolutionize every single aspect of our lives and help us address the complex challenges we face today, including the world’s most pressing scientific challenges and securing the power grid in our rapidly evolving environment,” said U.S. Secretary of Energy Rick Perry. “These two sets of A.I. funding will help ensure continued advancement in the scientific fields and will strengthen the resilience of our Nation’s critical energy infrastructure.”
Both the Grid Resiliency and Science A.I. investments are the latest examples of the Trump Administration’s commitment to prioritizing the cross-cutting research and development of America’s A.I. capabilities and driving breakthroughs in transformative applications of A.I.
A.I. in Grid Resiliency
These projects, totaling nearly $7 million in federal funding, are expected to inform and shape the future development and application of faster grid analytics and modeling, better grid asset management, and sub-second automatic control actions that will help system operators avoid grid outages, improve operations, and reduce costs.
These projects will uphold DOE’s commitment to ensuring secure, reliable, and resilient electricity.
A.I. in Science
Of the $13 million, $11 million will be devoted to the development of new A.I. algorithms and software adapted to specific scientific problems or sets of problems. Applications will be open to DOE national laboratories, with opportunities for universities, industry, and nonprofit organizations to participate as partners. Awards will be selected competitively by peer review. The total planned funding of $11 million in FY 2019 dollars will support three-year projects. Letters of Intent are due May 1. Final applications are due May 31.
A further $2 million will support research aimed at improving the reliability of predictions from A.I. and machine learning models through the application of mathematical and statistical techniques of uncertainty quantification. Applications will be open to national laboratories, universities, industry, and nonprofit organizations. Awards will be selected competitively by peer review. The total planned funding of $2 million in FY 2019 dollars will support two-year projects. Letters of Intent are required and are due May 8. Final applications are due May 31.
