Intelligence Advanced Research Projects Activity
Agency overview | |
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Formed | 2006 |
Jurisdiction | United States Government |
Headquarters | College Park, Maryland[1] |
Agency executive |
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Parent agency | Director of National Intelligence |
Website | http://www.iarpa.gov/ |
The Intelligence Advanced Research Projects Activity (IARPA) is an organization within the Office of the Director of National Intelligence (ODNI) responsible for leading research to tackle the Intelligence Community’s (IC) most difficult challenges. IARPA funds academic and industry research across a broad range of technical areas, including mathematics, computer science, physics, chemistry, biology, neuroscience, linguistics, political science, and cognitive psychology. Most IARPA research is unclassified and openly published. IARPA transfers successful research results and technologies to other government agencies. Notable IARPA investments include quantum computing, superconducting computing, and forecasting tournaments.
Mission
IARPA characterizes its mission as follows: To envision and lead high-risk, high-payoff research that delivers innovative technology for future overwhelming intelligence advantage.
History
In 1958, the first Advanced Research Projects Agency, or ARPA, was created in response to an unanticipated surprise—the Soviet Union’s successful launch of Sputnik on October 4, 1957. The ARPA model was designed to anticipate and pre-empt technological surprise. As then-Secretary of Defense Neil McElroy said, “I want an agency that makes sure no important thing remains undone because it doesn’t fit somebody’s mission.” The ARPA model has been characterized by ambitious technical goals, competitively awarded research led by term-limited staff, and independent testing and evaluation.
Authorized by the ODNI in 2006, IARPA was modeled after DARPA but focused on national intelligence needs, rather than military needs. IARPA was given the mandate to conduct cross-community research, target new opportunities and innovations, and generate revolutionary capabilities for national intelligence. IARPA operations began on October 1, 2007. Lisa Porter served as IARPA's first Director from 2008 to 2012. Peter Highnam served as IARPA's second Director from 2012 to 2015. Jason Matheny became IARPA’s third Director in 2015.
IARPA’s quantum computing research was named Science Magazine's Breakthrough of the Year in 2010. In 2015, IARPA was named to lead foundational research and development in the National Strategic Computing Initiative. IARPA is also a part of other White House science and technology efforts, including the U.S. BRAIN Initiative, and the Nanotechnology-Inspired Grand Challenge for Future Computing. New York Times OP-ED columnist, David Brooks, called IARPA “one of the government’s most creative agencies.” Notable articles from the Harvard Business Review, USA Today, the Washington Post, and more have since followed.
IARPA Approach
IARPA invests in multi-year research programs, in which academic and industry teams compete to solve a well-defined set of technical problems, regularly scored on a shared set of metrics and milestones. Each program is led by an IARPA Program Manager (PM) who is a term-limited Government employee. IARPA programs are meant to enable researchers to pursue ideas that are potentially disruptive to the status quo.
IARPA Research Thrusts
IARPA is organized into four offices, each with its own office director and its own research focus:
- Intelligence analysis, to maximize insight from information, in a timely fashion.
- Anticipatory intelligence, to detect and forecast significant global events.
- Operations, to counter new capabilities that could threaten the United States’ ability to operate freely and effectively in a networked world.
- Intelligence collection, to dramatically improve the value of collected data from all sources.
Current Research Programs
IARPA’s current research includes:
Aggregative Contingent Estimation (ACE): Improving forecasting through the wisdom of crowds
Aladdin Video: Searching for events of interest in massive unconstrained video
Babel: Rapidly building speech recognition and keyword search in new languages
Bio-Intelligence Chips (BIC): Analyzing and assessing human omni-omic signatures related to biological weapons handling
Circuit Analysis Tools (CAT): Developing integrated circuit analysis tools to match Moore’s Law scaling
Cryogenic Computing Complexity (C3): Developing energy-efficient superconducting supercomputers
Cyber-attack Automated Unconventional Sensor Environment (CAUSE): Developing automated methods for forecasting and detecting cyberattacks using unconventional multi-disciplined sensor technology
Crowdsourcing Evidence, Argumentation, Thinking and Evaluation (CREATE): Crowdsourcing to test hypotheses Finder: Locating where in the world an image or video was taken
Foresight and Understanding from Scientific Exposition (FUSE): Predicting technical emergence from scientific and patent literature using automated methods
High Frequency Geolocation (HFGeo): Geolocating high frequency ionospherically refracted transmissions
Janus: Enabling facial recognition in unconstrained video
Knowledge Discovery and Dissemination (KDD): Enabling analysts to produce actionable intelligence from multiple, disparate data sources
Logical Qubits (LogiQ): Building a logical qubit from a number of imperfect physical qubits
Machine Intelligence from Cortical Networks (MICrONS): Advancing machine learning by reverse-engineering the algorithms of the brain
Mercury: Automatically analyzing SIGINT data to forecast foreign societal events
Multi-Qubit Coherent Operations (MQCO): Resolving the challenges of simultaneous, coherent control with multiple quantum bits
Open Source Indicators (OSI): Automatically forecasting and detecting significant societal events using publicly available data
Quantum Enhanced Optimization (QEO): Providing quantum effects required to enhance quantum annealing solutions to hard combinatorial optimization problems
Rapid Analysis of Various Emerging Nanoelectronics (RAVEN): Delivering prototype analysis tool for acquiring images from all layers
Scientific advances to Continuous Insider Threat Evaluation (SCITE): Testing and detection of methods to uncover insider threat
Sirius: Using game-based training to reduce analysts' cognitive biases
Signal Location in Complex Environments (SLiCE): Improving geolocation of radio frequency emitters under difficult conditions
Standoff ILluminator for Measuring Absorbance and Reflectance Infrared Light Signatures (SILMARILS): Standing up portable system for real-time standoff detection and identification of trace chemical residues on surfaces
Strengthening Human Adaptive Reasoning and Problem-Solving (SHARP): Advancing the science on optimizing human adaptive reasoning and problem-solving
Tools for Recognizing Useful Signals of Trustworthiness (TRUST): Developing tools to assess signals of trustworthiness in humans
Trusted Integrated Chips (TIC): Demonstrating split-manufacturing of integrated circuits to ensure both world-class performance and security of design
Past Research Programs
ATHENA: Focused on computer network operations
Biometrics Exploitation Science and Technology (BEST): Significantly advancing biometrics technologies
Coherent Superconducting Qubits (CSQ): Demonstrating a reproducible, tenfold increase in coherence times in superconducting qubits
Forecasting Science and Technology (ForeST): Developing methods for generating accurate forecasts for significant S&T milestones, by combining the judgments of many experts
Great Horned Owl (GHO): Engineering the first generation of quiet unmanned aerial vehicles
Integrated Cognitive-Neuroscience Architectures for Understanding Sensemaking (ICArUS): Modeling how the human brain is able to make sense of sparse, ambiguous data
Knowledge Representation in Neural Systems (KRNS): Understanding how the human brain stores and organizes concepts
Metaphor: Revealing cross-cultural understanding through the use of metaphors
Quantum Computer Science (QCS): Exploring questions relating to the computational resources required to run quantum algorithms on realistic quantum computers
Reynard: Identified behavioral indicators in VWs and MMOGs that are related to the RW characteristics of the users
Security and Privacy Assurance Research (SPAR): Developed prototype implementations of efficient cryptographic protocols for querying a database that keep the query confidential; also, provided prototype implementations of efficient cryptographic protocols for subscribing to topics in a stream of documents; and efficient homomorphic encryption techniques to implement queries on encrypted data
Socio-cultural Content in Language (SCIL): Explored and developed novel designs, algorithms, methods, techniques and technologies to extend the discovery of the social goals of members of a group
Synthetic Holographic Observation (SHO): Created technology to enable full-parallax, full-color, high-resolution display of dynamic 3D data without head-gear, and possessing visually continuous perspectives without artifacts over wide viewing angles
Securely Taking On New Executable Software of Uncertain Provenance (STONESOUP): Developed and demonstrated comprehensive, automated techniques that allow end users to securely execute software without basing risk mitigations on characteristics of provenance that have a dubious relationship to security
See also
- Office of the Director of National Intelligence
- Defense Advanced Research Projects Agency (DARPA)
- Advanced Research Projects Agency-Energy (ARPA-E)
- Homeland Security Advanced Research Projects Agency (HSARPA)
References
IARPA homepage (www.iarpa.gov)
Further reading
- Signal. (2015). Data Analytics Programs Help Predict Global Unrest. Retrieved December 1, 2015.
- CS4ISR & Networks. (2015). IARPA's high-stakes intelligence experiment. Retrieved September 23, 2015.
- Executive Gov (2015). Jason Matheny: IARPA Seeks Automated Methods to Identify Cyber Attack Indicators. Retrieved October 14, 2015.
- Federal Times (2015). How IARPA Predicts the Unpredictable. Retrieved November 2, 2015.
- Fedscoop. (2013). Intelligence agency wants to know what makes you tick. Retrieved January 17, 2014.
- Harvard Business Review (2015). How a Video Game Helped People Make Better Decisions. Retrieved October 13, 2015.
- IEEE Spectrum (2015). IARPA’s New Director Wants You to Surprise Him. Retrieved October 19, 2015.
- New York Times. (2013). Forecasting Fox. Retrieved July 11, 2014.
- Popular Mechanics. (2015). What They're Building Inside America's Secret Spy Tech Lab. Retrieved September 23, 2015.
- USA Today. (2007). New IARPA Agency Developing Spy Tools. Retrieved October 2, 2015.
- Washington Post. (2013). Good judgment in forecasting international affairs. Retrieved February 10, 2014.
- Wired. (2010). U.S. Spies Want Algorithms to Spot Hot Trends. Retrieved August 13, 2014.
External links
- ↑ "IARPA dedicates a permanent home on the campus of U Maryland". Homeland Security News Wire. 2009-04-29. Retrieved 2015-12-15.