Artificial Intelligence/Machine Learning

The objective of this topic is to create a realistic modeling and simulation environment using Generative AI for NGC2, the Army’s new approach to a data-centric C2 architecture.

Development of cognitive decision aiding logic, utilizing machine learning and artificial intelligence constructs, to assist aviators in safely performing tactical flight very close to terrain.

This topic seeks to develop autonomous drone swarm capability for watercraft operated in a riverine environment. The fielding of autonomous powered floating bridges will enable the Army to conduct unpredictable dispersed river crossings, increase crew survivability by removing the man from the craft, and reduce logistics footprint over the Improved Ribbon Bridge in use today by combining both payload capacity and powertrain into a single craft. The development of an autonomy package for multiple dispersed floating bays to interact separately and jointly is the key technology to bring this capability to the 2040 battlespace.

The objective of this topic is to apply Large Language Models (LLMs) and/or other Artificial Intelligence (AI) approaches to support and automate warfighter’s system’s integrations. This will pertain to problems with data unification and interoperability regardless of the target system, source system, or data format. It will focus on usage in tactical environments to assist and provide reliable performance, regardless of echelon level.