The U.S. Navy has kicked off its Artificial Intelligence Applications to Autonomous Cybersecurity Challenge (AI ATAC), sponsored by the Naval Information Warfare Systems Command (NAVWAR) and Program Executive Office for Command, Control, Communications, Computers, and Intelligence (PEO C4I). […]

The Office of Management and Budget (OMB) is being careful about introducing any kind of unintended bias in its use of machine learning and artificial intelligence (AI) technologies, according to Margie Graves, Deputy CIO at OMB, who said today that Federal agencies should be very judicious about the technologies’ “fit for use.”






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Former Deputy Secretary of Defense Robert Work wants the U.S. military to take the competitive advantage in new-age warfare by going all-in on artificial intelligence (AI) initiatives.






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Army DoD military Defense AI

As fake news threatens to eat the world, a number of government, academic, and private organizations have launched a range of projects to combat its spread, including artificial intelligence systems that can flag fake news by calling out its content.






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Machine learning AI modernization

The Department of Homeland Security’s (DHS) Science and Technology Directorate (S&T) recently founded an artificial intelligence (AI) community of interest (COI) for anyone in DHS with an “interest in the subject.”






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As the Federal government looks to emerging technologies such as artificial intelligence (AI) to help improve citizen services and lower government costs, applications that enable this new computer-based intelligence via application programming interfaces (APIs) might be the least disruptive and inexpensive way for agencies to get started.






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Machine learning innovation is kicking into high gear. Investment in this field and data science increased 9.3 percent in 2016 to $2.4 billion, according to Gartner. On top of that, the Federal government is increasing its focus on machine learning, with the MGT Act, Technology Modernization Fund, and the President’s Management Agenda all supporting transformation efforts.






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Conventional wisdom is that it takes a fairly long time to detect a cybersecurity breach. Typically, most research suggests, it takes two to three months, possibly longer. That may not be the case anymore, though, according to a recent report.






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Scientists at the Army Research Laboratory (ARL) are covering some new ground in artificial intelligence (AI) by connecting a machine with human intelligence via a neural connection. Not to worry: the research team isn’t cooking up an AI system that will run the show inside a person’s head. But it does have promise for both medical as well as deep machine learning systems uses, potentially in military and everyday applications.






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Like King Louie in the Jungle Book–Artificial Intelligence has to learn like people. Machine learning’s surely a brilliant student, but it’s still a slow learner. Once trained to recognize patterns, analyze huge amount of data, or interpret speech, they can do the job at lightning speed, often better than humans can. But the training part of that equation can be a labor and programming-intensive task, because machines still learn like machines–one thing at a time, often only after repeated instruction.






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Not all bots are bad. But in the wrong hands, botnets can be commanded to do some very nefarious things, like Distributed Denial of Service–DDoS–attacks to disrupt and bring down websites. There are also malware-based bots that are increasingly being used to steal data and personal information.






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With the Internet for transportation, a lie can get all the way around the world before truth can blink itself awake. And that’s a challenge for those who seek to stem the proliferation of false information, be it accidentally misattributed quotes, political propaganda, or malicious “fake news.” Artificial intelligence can help combat the problem, by using machine learning algorithms to detect the patterns used in phony stories and ads designed to stir up fear or outrage, or, in the case of Russian disinformation, unsettle people’s faith in American institutions.






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In light of recent advances in performance–not to mention the history of computing–it’s reasonable to assume that artificial intelligence and machine learning systems will become smarter and faster. But government-funded research that is being put into practice at the Air Force Research Laboratory (AFRL) could achieve new levels of performance while also consuming minimal amounts of power.






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Artificial intelligence (AI) systems are getting awfully good at the Who, What, When, Where and even How for a variety of jobs, from military operations to financial transactions to medical diagnosis and treatment. But the Why is another story.






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Pandemic threats such as Ebola, Zika, and avian flu are not only a danger to public health, but are also viewed as potential national security threats, as the National Intelligence Council, an arm of the Director of National Intelligence, points out in its 2017 report, Global Trends: Paradox of Progress.






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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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