AI Quantum Computing

The intelligence community’s (IC) stock in trade has always been knowing what nobody else knows. Now it’s looking to tap into new technology to expand its ability to forecast geopolitical events in several ways, including finding out what everybody knows. […]

Stacey Dixon, director of the Intelligence Advanced Research Projects Activity (IARPA), said today at an event organized by Defense One that some of the intelligence community’s more audacious research centers on using machines to predict the future–through more accurate forecasts of geopolitical events. Dixon also said IARPA research aims to translate neuroscience to neural networks, hoping that efforts to map the human brain can lead to massive strides in machine learning.






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Leaders in the Federal intelligence community, speaking last Tuesday at Defense One’s Tech Summit, said that their agencies are using vast stores of data, machine learning, and neural networks to go beyond simple fact-finding, to now radically re-envision how the intelligence community acts on credible information. But with these advances in technology come thorny new ethical and procedural questions, those officials said.






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The Pentagon’s top research arm is sponsoring development of a first-of-its-kind software that can model the events that contribute to conflicts around the world, and, if not quite predict the future, at least offer a timely heads-up on what might happen next.






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The possibilities of quantum computing have been floating on the horizon for a while now, at least since renowned physicist Richard Feynman dreamed up the idea in 1982. But like the horizon itself (at least in a world that isn’t flat), it always seems to recede despite all efforts to close in on it. Until now.






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The White House’s planned advisory committee on artificial intelligence may or may not help keep the country at the forefront of technological innovation, but it is another sign that the government is getting more serious about the importance of AI and the potential threats of falling behind in the “AI arms race.”






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Users have the reputation of being the weakest link in cybersecurity, because of their potential to undo the most fortified cyber setup with an exposed password or absent-minded click in a phishing email. They’re the guy who forgets to lock one door in an otherwise secure building, or the kid who unwittingly reveals where the family keeps an emergency house key.






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Artificial intelligence has been applied to everything from cybersecurity and financial management to human resources and self-driving cars, so it seemed only a matter of time before it could take over video surveillance duties. And while AI, machine learning, and neural networks have made some promising strides in this area, it’s not quite the slam dunk that it might seem.






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Secrets have always been the lifeblood of the spy game. However, sometimes it pays to know what everyone else does. To that end, agencies are learning that crowdsourced information can prove to be a good predictor of upcoming events.






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Machine learning and artificial intelligence are needed to bridge the gap between the volume of government intelligence data and the number of people capable of analyzing it, according to Jason Matheny, director of the Intelligence Advanced Research Project Activity (IARPA).






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Amit Lal, an electrical and computer engineering professor at Cornell University, is working with a group of students to create a device that can scan the surfaces of all 10 fingers in five minutes. His team is competing in the Intelligence Advanced Research Projects Activity’s Nail to Nail Fingerprint challenge.






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The Secret Service has an interesting class photo….The CIA is taking cues from the advertising technology industry….IARPA is investing in research into homomorphic encryption—a potential game-changer in the worlds of privacy and security that enables encrypted queries of encrypted databases….And synthetic biology is keeping Jason Matheny up at night.






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Six hundred people have registered for the Intelligence Advanced Research Projects Activity Multi-View Stereo 3D Mapping Challenge, which was announced on July 1. The Mapping Challenge invites people to submit 3-D maps created from IARPA’s vast data sets, most of which come from satellite images.






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