Defense Advanced Research Projects AgencyTagged Content List

Data Analysis at Massive Scales

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

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In supervised machine learning (ML), the ML system learns by example to recognize things, such as objects in images or speech. Humans provide these examples to ML systems during their training in the form of labeled data. With enough labeled data, we can generally build accurate pattern recognition models.
| AI | Algorithms | Data |
The U.S. Government operates globally and frequently encounters so-called “low-resource” languages for which no automated human language technology capability exists. Historically, development of technology for automated exploitation of foreign language materials has required protracted effort and a large data investment. Current methods can require multiple years and tens of millions of dollars per language—mostly to construct translated or transcribed corpora.
Machine common sense has long been a critical—but missing—component of AI. Its absence is perhaps the most significant barrier between the narrowly focused AI applications we have today and the more general, human-like AI systems we would like to build in the future. The MCS program seeks to create the computing foundations needed to develop machine commonsense services to enable AI applications to understand new situations, monitor the reasonableness of their actions, communicate more effectively with people, and transfer learning to new domains.
Synthetic chemistry is important across countless technological areas, from medicines to energetics to advanced coatings to functional materials. While our synthetic capabilities have developed rapidly over the last century, current approaches are still slow and inefficient, with poor reproducibility and scalability and limited use of prior knowledge. Such an approach not only limits production of known materials, but also impedes discovery of better synthetic routes and completely new molecules.
The Memex program seeks to develop the next generation of search technologies and revolutionize the discovery, organization and presentation of search results.