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The Army is developing an ecosystem to train and verify AI models before deployment, aiming to leverage AI to manage data overload and enhance battlefield success. This ecosystem will allow the Army to test AI models for various applications, such as target recognition systems and intelligence missions. The Army is focusing on ensuring the security and trustworthiness of the AI ecosystem, with plans to establish and resource the program in 2026. [Extracted from the article]

The article offers information on the Defense Innovation Unit's request for proposals for small, unmanned surface vehicles to attack enemy ships, highlighting their value in contested environments and potential use in a Taiwan-China conflict. Topics include the importance of integrating unmanned systems with each other, the need to expand the unmanned portion of the force for sustaining maritime advantage, and the role of software solutions.

The article presents information on the use of advances in artificial intelligence (AI) in the Target Recognition and Adaption in Contested Environments program of the U.S. Defense Advanced Research Projects Agency for fast and accurate targeting in combat environments. It discusses the problems with automatic target recognition systems, and the use of AI by BAE Systems to improve the performance of automatic targeting systems.

The article discusses the use of machine learning for automatic target recognition under the Target Recognition and Adaption in Contested Environments (TRACE) program of the Defense Advanced Research Projects Agency (DARPA). Topics covered include automatic identification of targets in synthetic-aperture radar (SAR) images, TRACE program manager John Gorman saying that processing algorithms are being introduced to locate potential targets faster, and the use of artificial intelligence (AI).

The editor comments on strategy proposed by airpower strategists John Boyd regarding the observation, orientation, decision and action (OODA) loop. Topics discussed include use of the unmanned aerial vehicles (UAV) for intelligence, surveillance and reconnaissance (ISR), increase automation to allow multiple UAVs to be monitored by a single operator and use of automatic target recognition sensors and software in combat.