Defense Advanced Research Projects AgencyOur Research

Our Research

DARPA’s investment strategy begins with a portfolio approach. Reaching for outsized impact means taking on risk, and high risk in pursuit of high payoff is a hallmark of DARPA’s programs. We pursue our objectives through hundreds of programs. By design, programs are finite in duration while creating lasting revolutionary change. They address a wide range of technology opportunities and national security challenges. This assures that while individual efforts might fail—a natural consequence of taking on risk—the total portfolio delivers. More

For reference, past DARPA research programs can be viewed in the Past Programs Archive.

The past decade has seen explosive growth in development and training of artificial intelligence (AI) systems. However, as AI has taken on progressively more complex problems, the amount of computation required to train the largest AI systems has been increasing ten-fold annually. While AI advances are beginning to have a deep impact in digital computing processes, trade-offs between computational capability, resources and size, weight, and power consumption (SWaP) will become increasingly critical in the near future. More
Efficient discovery and production of new molecules is essential to realize capabilities across the DoD, from simulants and medicines essential to counter emerging threats, to coatings, dyes and specialty fuels needed for advanced performance. More
The United States Government has an interest in developing and maintaining a strategic understanding of events, situations, and trends around the world, in a variety of domains. The information used in developing this understanding comes from many disparate sources, in a variety of genres, and data types, and as a mixture of structured and unstructured data. Unstructured data can include text or speech in English and a variety of other languages, as well as images, videos, and other sensor information. More
The Artificial Intelligence Research Associate (AIRA) program is part of a broad DAPRA initiative to develop and apply “Third Wave” AI technologies that are robust to sparse data and adversarial spoofing, and that incorporate domain-relevant knowledge through generative contextual and explanatory models. More
Humans intuitively combine pre-existing knowledge with observations and contextual clues to construct rich mental models of the world around them and use these models to evaluate goals, perform thought experiments, make predictions, and update their situational understanding. When the environment contains other people, humans use a skill called theory of mind (ToM) to infer their mental states from observed actions and context, and predict future actions from those inferred states. More
The Automating Scientific Knowledge Extraction (ASKE) program aims to develop technology to automate some of the manual processes of scientific knowledge discovery, curation and application. ASKE is part of DARPA's Artificial Intelligence Exploration (AIE) program, a key component of the agency’s broader AI investment strategy aimed at ensuring the United States maintains an advantage in this critical and rapidly accelerating technology area. More
Some of the systems that matter most to the Defense Department are very complicated. Ecosystems, brains and economic and social systems have many parts and processes, but they are studied piecewise, and their literatures and data are fragmented, distributed and inconsistent. It is difficult to build complete, explanatory models of complicated systems, and so effects in these systems that are brought about by many interacting factors are poorly understood. More
| AI | Automation | Data |
The Bioelectronics for Tissue Regeneration (BETR) program will develop technology aimed at speeding warfighter recovery, and thus resilience, by directly intervening in wound healing. To do this, researchers will build an adaptive system that uses actuators to biochemically or biophysically stimulate tissue, sensors to track the body’s complex response to that stimulation, and adaptive learning algorithms to integrate sensor data and dictate intervention to the actuators. More