Defense Advanced Research Projects AgencyTagged Content List

Analytics for Data at Massive Scales

Extracting information from large data sets

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Military and civilian organizations have deep interest in human performance optimization (HPO). A key challenge for optimizing human performance, however, is the “tyranny of averages:” a common experimental approach that uses between-subject outcomes and group averages (means) to make conclusions about the efficacy of a given intervention.
The Technologies for Host Resilience (THoR) Program aims to develop new methods to maintain and optimize force health in the face of new and emerging infectious diseases. The goal is to discover the molecular mechanisms for tolerance of infection in animals, and develop therapeutic strategies that modulate the resilience of humans against infection. This capability would support military readiness by enabling warfighters to weather the storm of infectious diseases in low-resource or remote settings where pathogen-specific therapeutics or intensive care unit capabilities may not be locally available.
Urban Reconnaissance through Supervised Autonomy (URSA) is a DARPA program to enable improved techniques for rapidly discriminating hostile intent and filtering out threats in complex urban environments.
Currently, understanding and assessing the readiness of the warfighter involves medical intervention with the help of advanced equipment, such as electrocardiographs (EKGs) and other specialized medical devices, that are too expensive and cumbersome to employ continuously or without supervision in non-controlled environments. On the other hand, currently 92 percent of adults in the United States own a cell phone, which could be used as the basis for continuous, passive health, and readiness assessment.
| AI | Analytics | Data | Health |
Current defense systems for processing information struggle to effectively scale to the volume and characteristics of changing data environments and the range of applications for data analysis. Overcoming these challenges requires fundamentally new approaches to data science, including distributed computation and interactive visualization.