WASHINGTON, D.C. – Today, the U.S. Department of Energy's (DOE's) Advanced Research Projects Agency-Energy (ARPA-E) announced $15 million in funding for 23 projects to accelerate the incorporation of machine learning and artificial intelligence into the energy technology and product design processes as part of the Design Intelligence Fostering Formidable Energy Reduction (and) Enabling Novel Totally Impactful Advanced Technology Enhancements (DIFFERENTIATE) program. Launched in April of this year, the DIFFERENTIATE program aims to develop streamlined solutions to next-generation energy challenges. The program identified three general mathematical optimization problems that are common to many design processes. The selected projects then conceptualized machine learning and artificial intelligence-based solutions to help engineers execute and solve these problems in a manner that dramatically accelerates the pace of energy innovation. "The incorporation of AI and Machine Learning into our energy technology design and engineering processes has great potential to increase the productivity of our nation's engineers and scientists," said Secretary of Energy Rick Perry.

WASHINGTON, D.C. – Today, the U.S. Department of Energy's (DOE's) Advanced Research Projects Agency-Energy (ARPA-E) announced up to $20 million in funding to accelerate the incorporation of machine learning and artificial intelligence into energy technology and product design processes. The Design Intelligence for Formidable Energy Reduction Engendering Numerous Totally Impactful Advanced Technology Enhancements (DIFFERENTIATE) program seeks to enhance energy innovation by incorporating artificial intelligence and machine learning into energy technology development. "Artificial intelligence and machine learning has the potential to literally transform every aspect of the world as we know it, and accelerating this technology is crucial to strengthening our country's economic and national security," said U.S. Secretary of Energy Rick Perry. "DOE-fueled artificial intelligence is being utilized across all sectors, from strengthening cybersecurity and national security, increasing energy efficiency, optimizing grid security and resiliency, and developing innovative health solutions. The DIFFERENTIATE program is the latest example of DOE paving the way towards the New American Energy Era." In order to organize these efforts, DIFFERNTIATE identifies six general mathematical optimization problems that are common to many design processes. It then conceptualizes several machine learning tools that could help engineers execute and solve these problems in a manner that dramatically accelerates the pace of energy innovation.