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DARPA combines human brains and 120-megapixel cameras to create the ultimate military threat detection system

DARPA combines human brains and 120-megapixel cameras to create the ultimate military threat detection system
After more than four years of research, DARPA has created a system that successfully combines soldiers, EEG brainwave scanners, 120-megapixel cameras, and multiple computers running cognitive visual processing algorithms into a cybernetic hivemind. Called the Cognitive Technology Threat Warning System (CT2WS), it will be used in a combat setting to significantly improve the US Army’s threat detection capabilities. There are two discrete parts to the system: The 120-megapixel camera, which is tripod-mounted and looks over the battlefield (pictured below); and the computer system, where a soldier sits in front of a computer monitor with an EEG strapped to his head (pictured above). Images from the camera are fed into the computer system, which runs cognitive visual processing algorithms to detect possible threats (enemy combatants, sniper nests, IEDs). In short, CT2WS taps the human brain’s unsurpassed ability to recognize objects. Now read: Changing the world: DARPA’s top inventions

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Alpinestars Tech Air Race Suit Alpinestars Tech Air Race Suit Jeff Harris The Alpinestars suit can reduce the impact of a motorcycle crash to one tenth of what a racer wearing conventional body armor would suffer. The suit continuously monitors the rider's movements using embedded sensors, which communicate with a computer programmed to differentiate the motion that immediately precedes a crash from normal motion. When the system determines that a crash is imminent, it deploys airbags along the shoulders and collarbone in milliseconds to soften the blow. $8,000 (est.) Mental picture of others can be seen using fMRI, finds new study It is possible to tell who a person is thinking about by analyzing images of his or her brain. Our mental models of people produce unique patterns of brain activation, which can be detected using advanced imaging techniques according to a study by Cornell University neuroscientist Nathan Spreng and his colleagues. “When we looked at our data, we were shocked that we could successfully decode who our participants were thinking about based on their brain activity,” said Spreng, assistant professor of human development in Cornell’s College of Human Ecology.