Defense Advanced Research Projects AgencyTagged Content List

Data Analysis at Massive Scales

Extracting information and insights from massive datasets; "big data"; "data mining"

Showing 15 results for Data + Automation RSS
January 9, 2019,
Holiday Inn at Ballston
The Information Innovation Office is holding a Proposers Day meeting to provide information to potential proposers on the objectives of the new Knowledge-directed Artificial Intelligence Reasoning Over Schemas (KAIROS) program. KAIROS will explore how to understand complex events described in multi-media input by developing a semi-automated system that identifies, links, and temporally sequences their subsidiary elements, identifying the participants of the complex events and the subsidiary elements, and identifying the complex event type. An event is a recognizable and significant change in either the natural world or human society. Events of interest either create changes that have significant impact on national security or participate in causal chains that produce such impacts.
June 8, 2018,
Executive Conference Center
DARPA’s Defense Sciences Office (DSO) is hosting a Proposers Day to provide information to potential proposers on the objectives of the Systematizing Confidence in Open Research and Evidence (SCORE) program. SCORE aims to develop and deploy automated tools to assign "confidence scores" to different social and behavioral science (SBS) research results and claims. Confidence scores are quantitative measures that should enable a DoD consumer of SBS research to understand the degree to which a particular claim or result is likely to be reproducible or replicable. The event will be available via a live webcast for those who would like to participate remotely.
Efficient discovery and production of new molecules is essential to realize capabilities across the DoD, from simulants and medicines essential to counter emerging threats, to coatings, dyes and specialty fuels needed for advanced performance.
Some of the systems that matter most to the Defense Department are very complicated. Ecosystems, brains and economic and social systems have many parts and processes, but they are studied piecewise, and their literatures and data are fragmented, distributed and inconsistent. It is difficult to build complete, explanatory models of complicated systems, and so effects in these systems that are brought about by many interacting factors are poorly understood.
| AI | Automation | Data |
Understanding the complex and increasingly data-intensive world around us relies on the construction of robust empirical models, i.e., representations of real, complex systems that enable decision makers to predict behaviors and answer “what-if” questions. Today, construction of complex empirical models is largely a manual process requiring a team of subject matter experts and data scientists.