IARPA in the News 2015

HPC Wire

US intelligence officials have set in motion a five-year project to spark progress in machine learning by reverse-engineering the algorithms of the human brain. The Intelligence Advanced Research Projects Agency (IARPA) recently put out a call for innovative solutions with the greatest potential to advance theories of neural computation as part of the Machine Intelligence from Cortical Networks (MICrONS) program. The agency, known for its funding of high-risk/high-payoff research in support of national intelligence, is ultimately looking to facilitate the development of synthetic systems with brain-like performance and proficiency.

In a just-issued broad agency announcement, IARPA lays out its strategy for fostering multidisciplinary approaches at the intersection of data science and neuroscience that increase scientific understanding of the cortical computations underlying neural information processing. Although there has been much progress in modeling machine learning algorithms after neural processes, the brain remains far better-suited for a host of detection and recognition tasks.

Popular Science

Intelligence agencies, the spies and spooks and analysts grouped under three letter acronyms, exist in part to answer a difficult question that dates back to antiquity: Is it possible to predict the future, and, if so, how do we do it? A study published this month in the Journal of Experimental Psychology answers the question at least in part: Prediction is a skill, but it takes a special environment to develop that skill.

To understand how prediction works, researchers wanted to see if certain behaviors—such as making a lot of predictions, taking time to consider a question before answering it, or just having a working knowledge of politics in the region in question—effected a forecaster's accuracy.

For the experiment, participants competed in two nine-month-long forecasting tournaments. The questions for the tournament were selected by the Intelligence Advanced Research Projects Activity. Over the two years of the tournament, the forecasters were each asked a total of 199 questions, which “covered topics ranging from whether North Korea would test a nuclear device between January 9, 2012, and April 1, 2012, to whether Moody’s would downgrade the sovereign debt rating of Greece between October 3, 2011, and November 30, 2011.” Forecasters had to answer at least 25 of the questions. The vast majority of the questions had just two possible outcomes, like if a certain embattled world leader would remain in power after a given date. Other questions asked forecasters to choose one time-frame among multiple choices for a possible future event. Participants answered the questions online.

IEEE Spectrum

Early in 2014, IEEE Spectrum teamed up with SciCast, the “Bayesian combinatorial prediction market” group based at George Mason University, in Fairfax, Va. And when our January Top Tech 2015 issue hit the Web, IEEE Spectrum added something new to a few of its articles: the opportunity for readers to participate in IEEE Spectrum SciCast forecasting and match wits with experts by making their own predictions about the future of technology.

SciCast founders Robin Hanson, Kathryn Laskey, and Charles Twardy built the system to allow large numbers of forecasters (some 10,000 have signed on so far) to collectively prognosticate on technological progress. Initial support for SciCast came from the U.S. Intelligence Research Projects Activity.

IEEE Spectrum

A hardware Trojan is exactly what it sounds like: a small change to an integrated circuit that can disturb chip operation. With the right design, a clever attacker can alter a chip so that it fails at a crucial time or generates false signals. Or the attacker can add a backdoor that can sniff out encryption keys or passwords or transmit internal chip data to the outside world.

There’s good reason to be concerned. In 2007, a Syrian radar failed to warn of an incoming air strike; a backdoor built into the system’s chips was rumored to be responsible. Other serious allegations of added circuits have been made. And there has been an explosion in reports of counterfeit chips, raising questions about just how much the global supply chain for integrated circuits can be trusted....

A lot of research is still being devoted to understanding the scope of the problem. But solutions are already starting to emerge. In 2011, the United States’ Intelligence Advanced Research Projects Activity (IARPA) started a new program to explore ways to make trusted chips. As part of that program, our team at Stanford University, along with other research groups, is working on fundamental changes to the way integrated circuits are designed and manufactured.


Political forecasting is among the most vital roles played by the intelligence services: determining which country's government is most likely to collapse in the next few months, or whether a given nation has weapons of mass destruction that render them a threat. But what happens when there's no way to assess the quality of those forecasts – or the people making them?...

But the work of Philip Tetlock and his team at the Good Judgment Project – funded by the US government's Intelligence Advanced Research Project (Iarpa) – points to new ways of thinking about geopolitical forecasting, and the question of what makes a person better-equipped to predict world events. A few people, the project has revealed, have extraordinary talents for seeing the future – might you be one of them?