IARPA in the News 2015


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.


The intelligence community’s R&D arm wants industry researchers to predict cyberattacks rather than just respond to them.

Existing cyber defense methods such as signature-based detection "haven't adequately enabled cybersecurity practitioners to get ahead of these threats," said Robert Rahmer, a program manager at the Intelligence Advanced Research Projects Activity. "So this has led to an industry that's really invested heavily in analyzing the effects or symptoms of cyberattacks instead of analyzing [and] mitigating the cause."

New York Times

Scientists at the University of California, Santa Barbara, and at Google reported on Wednesday in the journal Nature that they had made a significant advance that brings them a step closer to developing a quantum computer.