August, Air Force Division – Massachusetts Institute of Technology Artificial Intelligence Accelerator (DAF-MIT AIA) provided cutting-edge AI training to pilots and engineers to prepare pilots and engineers to tackle the future of aerospace testing.
From August 4-15, 40 highly trained students, TPS pilots and technicians from the MQ-9, B-52, and F-35 communities met for the workshop to highlight the depth of experience and diversity.
“This workshop prepares testers to lead the integration of AI and machine learning into Air Force activities,” said Major Morgan Mitchell, DAF-MIT AIA Workshop Manager. “Test pilots and engineers need to understand how to design, evaluate and apply these technologies in real-world scenarios.”
Participants, hosted at MIT's Computer Science and Artificial Intelligence Institute (CSAIL) and MIT Lincoln Lab's Beaverworks, gained hands-on experience with AI-enabled systems. They programmed and tested MIT's RaceCar platform, applied AI/ML to flight test scenarios such as autonomy and anomaly detection, and investigated cutting-edge labs like the CSAIL Robot Apartment Living Lab.
“The workshop curriculum incorporated a wide range of aerospace and space domain applications to reflect the diverse roles of TPS alumni,” added Mitchell.
Following the successful induction course at Stanford University in February 2025, TPS plans to spin AI/ML training between DAF-MIT AIA in the summer and Stanford in the winter. This rotation allows each incoming TPS class to continuously gain exposure to cutting-edge research and practical applications, and to align the latest advancements and skills in aerospace testing. This shows a major change in how TPS prepares students for the rapidly evolving landscape of aerospace technology and testing.
“This collaboration with DAF-MIT AI Accelerator is a game-changer in how testers train,” said Colonel Scott Ruppelle, the Air Force Chief of DAF-MIT AIA. “By combining MIT's world-class expertise with an operational focus, we are preparing TPS students to tackle the challenges of testing AI-enabled systems in both areas of AI-AI-enabled systems.”
For more information, please visit: https://www.aiaccelerator.af.mil and https://aia.mit.edu
| Date taken: | 09.12.2025 |
| Date posted: | 09.12.2025 19:22 |
| Story ID: | 548053 |
| position: | Cambridge, Massachusetts, USA |
| Web View: | 13 |
| download: | 0 |
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