IARPA in the News


The BRAIN Initiative℠ goal is to develop neurotechnologies that will enable scientists “to map the circuits of the brain, measure the fluctuating patterns of electrical and chemical activity flowing within those circuits, and understand how their interplay creates our unique cognitive and behavioral capabilities.” On March 4, 2015 the NIH BRAIN Multi-Council Working Group (MCWG) met for the second time to discuss current BRAIN Initiative activities, new funding opportunity announcements, and strategic planning for the future of the NIH BRAIN Initiative efforts. The BRAIN MCWG includes one member of the Advisory Council from each of the 10 NIH Institutes and Centers that contribute to the NIH BRAIN Initiative. In addition, at-large members are appointed to supplement MCWG expertise, and ex officio members are appointed from the Defense Advanced Research Projects Agency (DARPA), the Food and Drug Administration (FDA), the Intelligence Advanced Research Projects Activity (IARPA), and the National Science Foundation (NSF) – NIH’s four federal partners involved in The BRAIN Initiative℠. The purpose of the MCWG is to provide oversight for the long-term scientific vision of The BRAIN Initiative℠ and serve as a forum for initial “concept clearance” or the review of ideas for new initiatives before they become funding announcements.

Intelligence Community News

The Intelligence Advanced Research Projects Activity (IARPA) will host a Proposers’ Day conference for the Scientific advances to Continuous Insider Threat Evaluation (SCITE) program on 16 April 2015, in anticipation of the release of a new solicitation in support of the program. The conference will be held from 9:00 AM to 4:00 PM EDT in the Washington, DC metropolitan area. The purpose of the conference will be to provide introductory information on SCITE and the research problems that the program aims to address, to respond to questions from potential proposers, and to provide a forum for potential proposers to present their capabilities and identify potential team partners.

Science Express

Quantum annealers use quantum fluctuations to escape local minima and find low energy configurations of a physical system. Strong evidence for superiority of quantum annealing has come from comparing quantum annealing implemented through quantum Monte Carlo (QMC) simulations to classical annealing. Motivated by recent experiments we revisit the question of when quantum speedup may be expected. Even though, for two-dimensional Ising spin glasses, a better scaling is seen for quantum annealing, this advantage is due to time discretization artifacts and measurements which are not possible on a physical quantum annealer. Simulations in the physically relevant continuous time limit, on the other hand, do not show superiority. Our results imply that care has to be taken when using QMC simulations to assess potential for quantum speedup.

Midsize Insider

The Intelligence Advanced Research Projects Activity (IARPA), which conducts research for the U.S. intelligence community, is heading up a program called the Cyber-attack Automated Unconventional Sensor Environment (CAUSE). The goal of CAUSE is predicting and preventing cyberattacks by seeking out early indicators of cyberattacks, including monitoring cybercriminals who purchase malicious software or research a target online.

The long lead time between when an attacker performs reconnaissance and when they attack is critical, because firms simply cannot wait for an attack to happen before outlining a response plan. Researchers are also using big data and predictive analytics to develop new detection technologies that garner clues from around the Internet to indicate a malicious incident is in the works.

The research, featured in HS Today, highlights several key concepts relevant to midsize business. For one, security continues to be a major, if not top, concern for firms of all sizes. Smaller businesses have more to lose from a cyberattack since they have limited resources compared to larger enterprises. Secondly, identifying successful ways to thwart cybercrime can lead to more complete security solutions in an age of continuously evolving threats.


It’s called the gambler’s fallacy: After a long streak of losses, you feel you are going to win. But in reality, your odds of winning are no different than they were before.

For years, the gambler’s fallacy has been thought to be a prime example of human irrationality, but a new study published by researchers from the Texas A&M Health Science Center suggests that our brains naturally soak up the strange statistics of random sequences, causing us to commit the gambler's fallacy....

The research was partially funded by the Air Force Office of Scientific Research, the Office of Naval Research, and Intelligence Advanced Research Projects Activity (IARPA).

University of Colorado, Boulder

During a famous roulette game in a Monte Carlo casino in 1913, black came up 26 times in a row. After about 15 repetitions, the players began betting heavily on red, likely believing that such a long streak just couldn’t continue.

The gambler’s fallacy—the idea that past events, a streak of black in roulette, for example, can impact the likelihood of a future random event, whether black or red will come up after the next spin—has long been thought to illustrate human irrationality.

But new research that relies on a brain model created at the University of Colorado Boulder finds that when humans fall into the gambler’s fallacy, their brains may actually be acting with some logic after all....

The research was partially funded by the Air Force Office of Scientific Research, the Office of Naval Research, and Intelligence Advanced Research Projects Activity.


Since its inception in April 2012, an average of 80 to 90 percent of the forecasts it generates have turned out to be accurate—and they arrive an average of seven days in advance of the predicted event. EMBERS (short for Early Model Based Event Recognition using Surrogates) derives its intelligence from what data geeks call “open-source indicators”—social media, satellite imagery and more than 200,000 blogs that are publicly available. It mines up to 2,000 messages a second and purchases open-source data such as Twitter’s “firehose,” which streams hundreds of millions of real-time tweets a day.

While much has been made of the government’s secret surveillance operations—particularly those that spy on Americans—the EMBERS project is focused on tracking human behavior overseas and publishing its findings, even if negative. “We are not looking at anything classified and we aren’t forecasting terrorism, because we don’t have access to those kinds of back channels,” Ramakrishnan says. “We are looking at data anyone can get.”...

EMBERS was the product of a 2012 contest organized by Jason Matheny, an associate director of the government’s Office for Anticipating Surprise (yes, that’s the name of a real office) and a program manager at the Office of the Director of National Intelligence’s [Intelligence] Advanced Projects Research Activity program. Three teams—from Virginia Tech, quantum computing firm Raytheon BBN Technologies in Cambridge, Massachusetts, and HRL in Malibu, California, formerly Hughes Research Laboratories—were asked to build the best possible forecasting model based on open-source indicators. The most successful of these was EMBERS, which ended up integrating several members of the other teams into its own, including Raytheon BBN, which now builds some of EMBERS's social media models, like the ones trying to forecast civil unrest from reading Twitter feeds. Some of the guiding principles of the research, says Scott Miller, senior technical director of Raytheon BBN’s speech and language group, are astoundingly simple.