Defense Advanced Research Projects AgencyTagged Content List

Automation Technologies

Automatic mechanical or digital operation

Showing 72 results for Automation RSS
Existing speech signal processing technologies are inadequate for most noisy or degraded speech signals that are important to military intelligence.
Current artificial intelligence (AI) systems excel at tasks defined by rigid rules – such as mastering the board games Go and chess with proficiency surpassing world-class human players. However, AI systems aren’t very good at adapting to constantly changing conditions commonly faced by troops in the real world – from reacting to an adversary’s surprise actions, to fluctuating weather, to operating in unfamiliar terrain.
As new defensive technologies make old classes of vulnerability difficult to exploit successfully, adversaries move to new classes of vulnerability. Vulnerabilities based on flawed implementations of algorithms have been popular targets for many years. However, once new defensive technologies make vulnerabilities based on flawed implementations less common and more difficult to exploit, adversaries will turn their attention to vulnerabilities inherent in the algorithms themselves.
The Department of Defense (DoD) often leverages social and behavioral science (SBS) research to design plans, guide investments, assess outcomes, and build models of human social systems and behaviors as they relate to national security challenges in the human domain. However, a number of recent empirical studies and meta-analyses have revealed that many SBS results vary dramatically in terms of their ability to be independently reproduced or replicated, which could have real-world implications for DoD’s plans, decisions, and models. To help address this situation, DARPA’s Systematizing Confidence in Open Research and Evidence (SCORE) program aims to develop and deploy automated tools to assign "confidence scores" to different SBS research results and claims.
Modern computing systems act as black boxes in that they accept inputs and generate outputs but provide little to no visibility of their internal workings. This greatly limits the potential to understand cyber behaviors at the level of detail necessary to detect and counter some of the most important types of cyber threats, particularly advanced persistent threats (APTs). APT adversaries act slowly and deliberately over a long period of time to expand their presence in an enterprise network and achieve their mission goals (e.g., information exfiltration, interference with decision making and denial of capability).