Concurrent Technologies Corporation (CTC) has successfully delivered thousands of
customized IT solutions to the Intelligence Community (IC) and Department of Defense
(DoD) for more than 20 years. Our deployed edge node systems bring current geospatial
intelligence (GEOINT) data, applications, and services to coalition forces—much
quicker and with less bandwidth.
- The mix of compute and data storage capabilities enables faster discovery of finished
intelligence products and creation of new products based on recent foundation data.
- The use of applications and services reduces the need for specialized training for
the deployed force.
- Hosting the applications and data locally—at the user level—minimizes the time it
takes to produce intelligence products, plan and execute military operations—from
weeks and days to hours and seconds.
How can this technology be used?
Examples of the potential use of edge node systems include providing the capabilities
to find helicopter landing zones, conduct surveillance, locate targets, and assess
damage. In the past, those on the front lines would have to reach back to the data
centers in the U.S., which took too much time and bandwidth. Our system provides
our military with the tools necessary to analyze and exploit intelligence and plan
and execute operations faster than ever before.
Supplying critical resources for operational
decisions
In the context of data exploitation and analytic capabilities at the tactical edge,
real value comes in supplying vital cognitive aids for operational decisions. These
aids provide a significant advantage to those employing them, especially in tactical
scenarios where planning and decision time is short and actions must be taken quickly.
Providing valuable machine learning
capabilities in hostile environments
CTC’s approach to Machine Learning (ML) and Artificial Intelligence (AI) is in sync
with the U.S. Special Operations Command’s (SOCOM) Hybrid Enabled Operator landscape,
which resides at the intersection of the Cognitive, Digital and Physical Domains.
- We operate in contested environments that are very sensitive to security vulnerabilities—both
defending ours and exploiting others’ through forensic analysis of ML capabilities
and weaknesses.
- We are developing ML capabilities that can help identify, track, and monitor version
control where deep neural networks (DNNs) are most vulnerable.
