DARPA is working to create a unified mathematical language for everything the military sees or hears:

The armed forces are overwhelmed by all the data its various sensors are sniffing out. They want a single data stream that combines drone video feeds, cell phone intercepts, and targeting radar. Darpa’s solution, found in the brand-new Mathematics of Sensing, Exploitation, and Execution program is to design an algorithm that teaches the sensors how to interpret the world — how to think, how to learn and what data, accordingly to collect.

Sensors “process their signals as if they were seeing the world anew at every instant,” Darpa laments in its call for algorithms. To put it in Philosophy 101 terms, existence is, to a sensor, what William James called a “blooming, buzzing confusion“: an unmediated series of events to be vacuumed up, leaving an analyst overloaded with unsorted data. Wouldn’t it be better if a sensor could be taught how to filter the world through a perceptual prism, anticipating what the analyst needs to know?

That’s the specific military application of MSEE. But to get there, Darpa takes a rather unconventional path. To get the “economy and efficiency that derives from an intrinsic, objective-driven unification of sensing and exploitation,” it wants to create an “intrinsically integrated” algorithm for the machines to interpret reality. “All proposed research must describe a unifying mathematical formalism that incorporates stochasticity fundamentally,” Darpa tells would-be designers.

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