Defense Advanced Research Projects AgencyTagged Content List

Data Analysis at Massive Scales

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

Showing 97 results for Data RSS
Modern society depends on information and information depends on information systems. Timely, insightful, reliable, and relevant information is essential, particularly for national security. To ensure information advantage for the U.S. and its allies, the Information Innovation Office (I2O) sponsors basic and applied research in three thrust areas: Symbiosis, Analytics, and Cyber.
05/18/2015
Modern society depends on information and information depends on information systems. Timely, insightful, reliable, and relevant information is essential, particularly for national security. The Information Innovation Office (I2O) sponsors basic and applied research in three thrust areas to ensure information advantage for the U.S. and its allies:
01/01/2008
With the goal of developing analysis techniques for massive data sets, DARPA rolled out the Topological Data Analysis (TDA) program, which ran from 2004 to 2008. Like many other programs, this one spawned a commercial firm, in this case a software firm that remained in business at the posting of this timeline in 2018.
02/13/2013
DARPA held a multi-program performer meeting for researchers to hear presentations on the latest innovations and promising approaches in the area of Big Data and data analytics. Speakers during the day-long event included representatives from the White House, FBI, universities from across the country and leading companies from the private sector who are focused on the potential efficiencies and advantages that can be gained in Big Data.
03/19/2013
Machine learning – the ability of computers to understand data, manage results, and infer insights from uncertain information – is the force behind many recent revolutions in computing. Email spam filters, smartphone personal assistants and self-driving vehicles are all based on research advances in machine learning. Unfortunately, even as the demand for these capabilities is accelerating, every new application requires a Herculean effort. Even a team of specially-trained machine learning experts makes only painfully slow progress due to the lack of tools to build these systems.