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DARPA Wants AI Systems to Interpret Surveillance Data


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Predator unmanned aerial vehicle

U.S. Air Force

The U.S. Defense Advanced Research Projects Agency (DARPA) has announced an effort to create powerful artificial intelligences (AIs) that can mine and interpret a rapidly mounting volume of intelligence, surveillance, and reconnaissance (ISR) data generated by unmanned aerial vehicles like the Predator and other ISR resources of higher sophistication, resolution, and population. DARPA wants AIs that use "deep learning" methods to produce richer representations that can distinguish between different kinds of animals, for instance. "A deep learning system exposed to unlabelled natural images will automatically create high-level concepts of four-legged mammals on its own, even without labels," DARPA says.

The idea is that the deep learning machine will be provided access to the Pentagon's corpus of robotic video surveillance and start devising unknown concepts by itself using that information as a foundation. "A further end objective of the deep learning program is to support increased growth and development of the broader machine-learning community by making publicly available many, if not all, deep learning software modules, algorithmic approaches, evaluation criteria, and datasets in several application domains for use by researchers," DARPA says.

From The Register (UK)
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