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 48 results for AI + Data RSS
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.
The Physics of Artificial Intelligence (PAI) program is part of a broad DAPRA initiative to develop and apply “Third Wave” AI technologies to sparse data and adversarial spoofing, and that incorporate domain-relevant knowledge through generative contextual and explanatory models.
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. Teams of hard-to-find experts must build expensive, custom tools that are often painfully slow and can perform unpredictably against large, complex data sets.
Serial Interactions in Imperfect Information Games Applied to Complex Military Decision Making (SI3-CMD) builds on recent developments in artificial intelligence and game theory to enable more effective decisions in adversarial domains. SI3-CMD will explore several military decision making applications at strategic, tactical, and operational levels and develop AI/game theory techniques appropriate for their problem characteristics.
New manufacturing technologies such as additive manufacturing have vastly improved the ability to create shapes and material properties previously thought impossible. Generating new designs that fully exploit these properties, however, has proven extremely challenging. Conventional design technologies, representations, and algorithms are inherently constrained by outdated presumptions about material properties and manufacturing methods. As a result, today’s design technologies are simply not able to bring to fruition the enormous level of physical detail and complexity made possible with cutting-edge manufacturing capabilities and materials.