The Intelligence Advanced Research Projects Activity (IARPA) recently launched the Geopolitical Forecasting Challenge 2, which encourages solvers to develop innovative methods for utilizing crowdsourced information to create global issue forecasts. […]

The Intelligence Advanced Research Projects Activity (IARPA) office released a draft solicitation for innovative solutions for automated broad-area search, monitoring, and analysis of anthropogenic activities – those related to human activity – within its Space-based Machine Automated Recognition Technique (SMART) program.






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An important step in advancing artificial intelligence (AI) initiatives includes fortifying algorithms for AI, which are often brittle and “not good,” said Dr. John Beieler, program manager at the Intelligence Advanced Research Projects Activity (IARPA).






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Military AI DoD Defense
data privacy, people, personal data, binary

The IC’s top research arm, the Intelligence Advanced Research Projects Activity (IARPA), wants to be able to get the gist anywhere and anytime. They are inviting researchers from around the world in industry and academia to use machine learning to develop algorithms for cross-lingual information retrieval capable of extracting answers from little-known foreign languages to questions posed in English. IARPA’s Open Cross-language Information Retrieval (CLIR) Challenge is inviting participants to compete for prizes while working on a kind of fast-working translator that can interpret other languages while using a minimal amount of training data, focusing particularly on what it calls “computationally underserved languages.”






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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.






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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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