Defense Advanced Research Projects AgencyTagged Content List

Data Analysis at Massive Scales

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

Showing 105 results for Data RSS
06/19/2018
Chemical innovation plays a key role in developing cutting-edge technologies for the military. Research chemists design and synthesize new molecules that could enable a slew of next-generation military products, such as novel propellants for spacecraft engines; new pharmaceuticals and medicines for troops in the field; lighter and longer-lasting batteries and fuel cells; advanced adhesives, coatings and paints; and less expensive explosives that are safer to handle. The problem, however, is that existing molecule design and production methods rely primarily on experts’ intuition in a laborious, trial-and-error research process.
07/11/2018
Machine learning (ML) systems today learn by example, ingesting tons of data that has been individually labeled by human analysts to generate a desired output. As these systems have progressed, deep neural networks (DNN) have emerged as the state of the art in ML models. DNN are capable of powering tasks like machine translation and speech or object recognition with a much higher degree of accuracy. However, training DNN requires massive amounts of labeled data–typically 109 or 1010 training examples. The process of amassing and labeling this mountain of information is costly and time consuming.
09/07/2018
Over its 60-year history, DARPA has played a leading role in the creation and advancement of artificial intelligence (AI) technologies that have produced game-changing capabilities for the Department of Defense. Starting in the 1960s, DARPA research shaped the first wave of AI technologies, which focused on handcrafted knowledge, or rule-based systems capable of narrowly defined tasks. While a critical step forward for the field, these systems were fragile and limited.
10/04/2018
The efficient discovery and production of new molecules is essential for a range of military capabilities—from developing safe chemical warfare agent simulants and medicines to counter emerging threats, to coatings, dyes, and specialty fuels for advanced performance. Current approaches to develop molecules for specific applications, however, are intuition-driven, mired in slow iterative design and test cycles, and ultimately limited by the specific molecular expertise of the chemist who has to test each candidate molecule by hand.
10/11/2018
Today’s machine learning systems are more advanced than ever, capable of automating increasingly complex tasks and serving as a critical tool for human operators. Despite recent advances, however, a critical component of Artificial Intelligence (AI) remains just out of reach – machine common sense. Defined as “the basic ability to perceive, understand, and judge things that are shared by nearly all people and can be reasonably expected of nearly all people without need for debate,” common sense forms a critical foundation for how humans interact with the world around them.