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IARPA Announces the Scoring Process for the Functional Map of the World Challenge and the Release of One of the Largest Public Satellite Imagery Data Sets

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announces its scoring process for its Functional Map of the World—“fMoW”—Challenge. Participants from around the world are invited to develop automated techniques to accurately detect and categorize points of interest from satellite imagery. Participants are scored based on their ability to correctly categorize portions of satellite images. Submissions are scored automatically and independently evaluated for accuracy.

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IARPA Launches “MOSAIC” Program to Better Assess the Intelligence Community Workforce

WASHINGTON – The Intelligence Advanced Research Projects Activity, in the Office of the Director of National Intelligence, announced today a multi-year research effort to develop and validate unobtrusive, passive, and continuously sensing methods to assess stable and dynamic psychological, cognitive, and physiological aspects of an individual. If successful, the technology developed under the Multimodal Objective Sensing to Assess Individuals with Context—“MOSAIC” —program will augment capabilities to evaluate the workforce and identify changes in an individual that may impact job performance.

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IARPA Launches Hybrid Forecasting Competition to Improve Predictions Through Human-Machine Integration

WASHINGTON – The Intelligence Advanced Research Projects Activity, in the Office of the Director of National Intelligence, announced today a multi-year research effort to improve geopolitical forecasting. The Hybrid Forecasting Competition—“HFC”—program aims to improve accuracy in predicting worldwide geopolitical issues, including foreign political elections, interstate conflict, disease outbreaks, and economic indicators by leveraging the relative strengths of humans and machines.

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IARPA Announces Chemical Detection Challenge “MORGOTH’S CROWN”

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, will launch the Modeling of Reflectance Given Only Transmission of High-concentration Spectra for Chemical Recognition Over Widely-varying eNvironments —“MORGOTH’S CROWN” —Challenge as part of the Standoff ILluminator for Measuring Absorbance and Reflectance Infrared Light Signatures—“SILMARILS”—program. The Challenge will launch later this month and invites solvers from around the world to develop algorithms to accurately predict the changes in a chemical’s infrared spectrum caused by changes in its molecular environment.

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IARPA Announces Functional Map of the World Challenge To Develop Automated Analysis of Satellite Imagery

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announces the launch of the functional Map of the World —“fMoW”— Challenge. The challenge invites solvers from around the world to develop machine learning algorithms and other automated techniques that accurately detect and categorize classify points of interest from satellite imagery.

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IARPA Announces Face Recognition Prize Challenge

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announced today that it has launched the Face Recognition Prize Challenge—“FRPC”—in partnership with the National Institute of Standards and Technology. The challenge aims to improve recognition of face images acquired without capture constraints—unconstrained images captured in the “wild.”

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IARPA Announces Publication of Data from the Good Judgment Project

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announced that forecasting data collected during IARPA’s Aggregative Contingent Estimation—ACE—program by team Good Judgment is now available for use by the public and the research community via https://dataverse.harvard.edu/dataverse/gjp. This data set includes millions of forecasts made by participants over the four years of the ACE forecasting competition and led to many noteworthy findings regarding the accuracy of human judgment about geopolitical events, including the finding that averaging the most historically accurate forecasters outperforms individual forecasters.

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IARPA Launches "RAVEN" Program To Develop Rapid Integrated Circuit Imaging Tools

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announced today the Rapid Analysis of Various Emerging Nano-electronics—“RAVEN”—program, a multi-year research effort to develop tools to rapidly image current and future integrated circuit chips

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IARPA Launches "MAEGLIN" Program To Develop Low-Power, Autonomous Chemical Identification Systems

Washington – The Intelligence Advance Research Projects Activity, within the Office of the Director of National Intelligence, announced the launch of the Molecular Analyzer for Efficient Gas-phase Low-power Interrogation—“MAEGLIN”—program, a multi-year research effort to ultimately develop a compact system capable of unattended environmental sampling and chemical identification with minimal (preferably no) consumables. If successful, the technology developed under the program would enable multi-year chemical monitoring of hard-to-access sites without the need of maintenance, reagent replenishing, or other activities that would require regular human intervention.

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IARPA Launches "QEO" Program To Develop Quantum Enhanced Computers

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announced today that it has embarked on a multi-year research effort to develop special-purpose algorithms and hardware that harness quantum effects to surpass conventional computing. Practical applications include more rapid training of machine learning algorithms, circuit fault diagnostics on larger circuits than possible today, and faster optimal scheduling of multiple machines on multiple tasks. If successful, technology developed under the Quantum Enhanced Optimization—“QEO”—program will provide a plausible path to performance beyond what is possible with today’s computers.

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