Air Force researchers ask industry for artificial intelligence (AI) and machine learning for military C4ISR
ROME, N.Y. – U.S. Air Force computer scientists are reaching out to industry for help in developing advanced technologies that involve disciplines such as nano-computing, neuromorphic computing, machine learning, and embedded deep learning.
Officials of the Air Force Research Laboratory Information Directorate in Rome, N.Y., have issued a broad agency announcement (FA875023S7004) for the four-year Extreme Computing program.
For now, Air Force computer researchers are asking industry for white papers on developing technologies in three areas: advancing computing technology and applications; nano-computing; neuromorphic computing and applying machine learning; and computers, algorithms, and applications for embedded deep learning.
Companies submitting white papers may be asked to submit formal proposals. The Air Force will accept white papers for the Extreme Computing program until 28 Sept. 2028. The program could be worth as much as $497.9 million, and companies selected will receive contracts worth between $1 million and $100 million.
Related: Wanted: cyber-hardened high-performance embedded computing, artificial intelligence (AI), machine learning
The program's first technical area, Advancing Computing Technology and Applications, involves developing computers with sophistication, autonomy, intelligence, and assurance for command, control, communications, computers, intelligence, surveillance and reconnaissance (C4ISR) and cyber applications.
Researchers are interested in technologies with limited size, weight, and power consumption (SWaP), and that include high-performance embedded computing with advanced machine learning; secure machine learning and artificial intelligence (AI); and non-conventional neuromorphic applications.
The technical point of contact for this technical area is Ryan Luley, who is available by email at ryan.luley@us.af.mil, or by phone at 315-330-3848.
The second technical area, Nano-Computing, involves for air and space systems operating at the edge, ranging from computer vision and knowledge extraction to autonomous flight and decision-making. This approach cannot rely only on current complementary metal-oxide-semiconductor (CMOS) technologies, but involves new CMOS-compatible materials that enhance existing nanoelectronics.
Target applications include bio-inspired computing architectures with ultra-low power consumption. The technical point of contact for this technical area is Joseph Van Nostrand, whose email address is joseph.vannostrand.1@us.af.mil, and phone number is 315-330-4920 Email:joseph.vannostrand.1@us.af.mil.
The third technical area, Neuromorphic Computing and Applying Machine Learning, seeks to advance computationally intelligent systems for perception, adaptability, resiliency, and autonomy for energy-efficient air and space systems.
Interest revolves around advancements in computational neuroscience; nanoelectronics; nano photonics; high-performance computing; material science; embedded deep learning; machine learning; pattern recognition and signature analysis; autonomous adaptive operations; human-machine collaboration; neural control of complex- systems; in-situ training of neuromorphic hardware; and online learning in neural networks. The technical point of contract for this area is Clare Thiem, whose email address is clare.thiem@us.af.mil, and phone number is 315-330-4893.
Air Force researchers ask industry for SWaP-constrained embedded computing for artificial intelligence (AI)The fourth technical area, Robust and Efficient Computing Architectures, Algorithms, and Applications for Embedded Deep Learning, seeks to develop advanced efficient computing architectures and algorithms for orders of magnitude improvement in SWaP for deploying AI and machine learning for embedded computing in ground, air, and space applications. The technical point of contact is Mark Barnell, whose email address is mark.barnell.1@us.af.mil.
Air Force researchers ask industry for SWaP-constrained embedded computing for artificial intelligence (AI)Companies interested should email white papers to the relevant technical point of contact by 30 Sept. 2024 for 2025 funding; by 30 Sept. 2025 for 2026 funding; by 30 Sept. 2026 for 2027 funding; and by 30 Sept. 2027 for 2028 funding.
Air Force researchers ask industry for SWaP-constrained embedded computing for artificial intelligence (AI)Email contractual questions to the Air Force's Amber Buckley at Amber.Buckley@us.af.mil. More information is online at https://sam.gov/opp/211b1819bd5f46eba20d4a466358d8bb/view.