Defense Advanced Research Projects AgencyTagged Content List

Analytics for Data at Massive Scales

Extracting information from large data sets

Showing 79 results for Analytics RSS
May 1, 2018,
CENTRA Technology Incorporated Conference Center
DARPA’s Tactical Technology Office is hosting a Proposers Day to provide information to potential applicants on the structure and objectives of the new Urban Reconnaissance through Supervised Autonomy (URSA) program. URSA aims to develop technology to enable autonomous systems operated and supervised by U.S. ground forces to detect hostile forces and establish positive identification of combatants before U.S. troops encounter them. The URSA program seeks to overcome the inherent complexity of the urban environment by combining new knowledge about human behaviors, autonomy algorithms, integrated sensors, multiple sensor modalities, and measurable human responses to discriminate the subtle differences between hostile individuals and noncombatants.
The United States Government has an interest in developing and maintaining a strategic understanding of events, situations, and trends around the world, in a variety of domains. The information used in developing this understanding comes from many disparate sources, in a variety of genres, and data types, and as a mixture of structured and unstructured data. Unstructured data can include text or speech in English and a variety of other languages, as well as images, videos, and other sensor information.
The Anomaly Detection at Multiple Scales (ADAMS) program creates, adapts and applies technology to anomaly characterization and detection in massive data sets. Anomalies in data cue the collection of additional, actionable information in a wide variety of real world contexts. The initial application domain is insider threat detection in which malevolent (or possibly inadvertent) actions by a trusted individual are detected against a background of everyday network activity.
The Artificial Intelligence Research Associate (AIRA) program is part of a broad DAPRA initiative to develop and apply “Third Wave” AI technologies that are robust to sparse data and adversarial spoofing, and that incorporate domain-relevant knowledge through generative contextual and explanatory models.
The Automating Scientific Knowledge Extraction (ASKE) program aims to develop technology to automate some of the manual processes of scientific knowledge discovery, curation and application. ASKE is part of DARPA's Artificial Intelligence Exploration (AIE) program, a key component of the agency’s broader AI investment strategy aimed at ensuring the United States maintains an advantage in this critical and rapidly accelerating technology area.