Defense Advanced Research Projects AgencyTagged Content List

Artificial Intelligence and Human-Computer Symbiosis Technologies

Technology to facilitate more intuitive interactions between humans and machines

Showing 66 results for AI RSS
02/20/2014
During the 1854 cholera epidemic in London, Dr. John Snow plotted cholera deaths on a map, and in the corner of a particularly hard-hit quadrangle of buildings was a water pump. Snow's maps, a 19th-century version of big data, suggested an association between cholera and the pump, but the germ theory of disease had not yet been invented and it took human ingenuity to realize that the pump was a causal mechanism of disease transmission.
| AI | Automation | Data |
02/11/2015
How will the growing use of robots change people’s lives and make a difference for society? How do teens want robots to make a difference in the future? As ever more capable robots evolve from the realm of science fiction to real-world devices, these questions are becoming increasingly important. And who better to address them than members of the generation that may be the first to fully co-exist with robots in the future? Through its new Robots4Us student video contest, DARPA is asking high school students to address these issues creatively by producing short videos about the robotics-related possibilities they foresee and the kind of robot-assisted society in which they would like to live.
02/20/2015
The lifelong human imperative to communicate is so strong that people talk not only to other people but also to their pets, their plants and their computers. Unlike pets and plants, computers might one day reciprocate. DARPA's new Communicating with Computers (CwC) program aims to develop technology to turn computers into good communicators.
04/22/2016
Advanced materials are increasingly embodying counterintuitive properties, such as extreme strength and super lightness, while additive manufacturing and other new technologies are vastly improving the ability to fashion these novel materials into shapes that would previously have been extremely costly or even impossible to create. Generating new designs that fully exploit these properties, however, has proven extremely challenging.
05/26/2016
It’s not easy to put the intelligence in artificial intelligence. Current machine learning techniques generally rely on huge amounts of training data, vast computational resources, and a time-consuming trial and error methodology. Even then, the process typically results in learned concepts that aren’t easily generalized to solve related problems or that can’t be leveraged to learn more complex concepts. The process of advancing machine learning could no doubt go more efficiently—but how much so?