VISIMO

VISIMO will provide a dynamic decision and risk prediction engine for Orbs and Unmanned Aerial Vehicles (UAVs) using artificial intelligence (AI) and machine learning (ML) algorithms. VISIMO and the University of Cincinnati will collaboratively advance the state-of-the-art to build an artificial neural network model that will scale and enable Orbs / UAVs to perceive, learn, decide, and act more efficiently and effectively on their own.

To advance state-of-the-art landscape and object synthetic data generation through the development of a generative adversarial network (GAN), to produce infinite training data compatible with bi-directional mapping, dynamic multi-object tracking, and base

Provide an AI Legal Assistant to provide real-time guidance and instruction to legal professionals and commanders on use-of-force decisions. Deliver a feasibility study identifying the ability of the JAG Corps to use the provided system to advance the state-of-the-art (SOTA) in real-time legal support for time-sensitive tactical decision making in Air Operations Centers (AOCs) worldwide. In real-time use-of-force decision-making scenarios, JAG Corps becomes the bottleneck due to the complex and ever-changing nature of the rules of engagement (ROE). As the use of autonomous weapons systems increases, human legal professionals will not be able to keep up with the pace of engagement. VISIMO will create a proactive (not query-based) support AI that alerts JAG Corps members as potential force situations develop. The AI Legal Assistant will employ AI and ML techniques that enable the Legal Assistant to train and adapt continually as new data enters the program. VISIMO will employ human/autonomy trust techniques, including providing relevant source documents that justify the AI’s recommendations for fast human review.