Media Coverage

Pentagon Intensifies High-Speed Attack With AI, Machine Learning

Perhaps one data stream is an rf signal, another GPS while a third comes from a separate digital datalink or wireless signal?

Diagram showing machine learning

Royce Geo and the CURVE Cloud Operational Environment were mentioned recently by Warrior Maven.

By Kris Osborn, President, Center for Military Modernization

(Washington D.C.) Massive amounts of satellite images, video and data flow in at unprecedented speeds, EO/IR sensors on fighter jets generate target specifics, ground-based air-defense radar “lights up” enemy aircraft and both air and ground unmanned systems collect, analyze and transmit time-sensitive data. Meanwhile, dismounted soldiers and ship commanders consistently uncover new threat information and need to “network” key location detail, intelligence data and targeting specifics to an optimal “shooter” or weapons platform in a position to attack.

Operating within this conceptual framework, various weapons developers and industry innovators are working to “break ground” on new paradigm-changing technologies which can massively “speed up” attack speeds in warfare. Arlington, Virginia-based technology firm Royce Geo, for example, uses AI-enabled algorithms, machine learning applications, computer automation and gateways to “translate” and “integrate” data streams and expand the application of its now operational cloud-enabled analytics and data-modeling technology known as the CURVE Operating Environment (OE). CURVE OE enables users to gather, merge, analyze and help transmit precise, time-sensitive combat data from both commercial and military platforms.

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