The National Geospatial-Intelligence Agency is using machine learning and computer vision in all aspects of its operations, from the battlefield to geopolitical analysis. The agency is using rapidly advancing artificial intelligence technologies to help military leaders observe battlefield activity more closely and give policymakers a better understanding of global threats and dynamics.
"We are very enthusiastic about the direction of AI applications," said NGA’s director, Vice Adm. Frank Whitworth, in an interview with SpaceNews.
Whitworth stated that a combination of rapidly advancing AI capabilities and updated business processes is changing how the agency provides intelligence to inform national security decision-making at the highest levels.
The agency, based in Springfield, Virginia, is expanding on the work of Project Maven, a Pentagon initiative started in 2017 to utilize AI for analyzing drone footage and satellite imagery.
Challenges of growth
At the beginning, the program struggled with the limitations of early computer vision technology, which required painstakingly annotating drone videos frame by frame to teach algorithms how to track vehicles across deserts.
Project Maven also faced political and media controversy in 2018 when Google employees objected to the company providing the Pentagon with Google’s open-source machine learning library for computer vision applications, which were being used to enhance drone strike targeting.
However, these initial challenges served as a catalyst, as Maven paved the way for the intelligence community’s adoption of AI over the following years. NGA is now working to incorporate machine learning and computer vision across its entire data analysis process.
Whitworth explained that with AI, analysts can uncover hidden threats and areas of interest within the enormous amounts of imagery and data agencies collect daily. He added that a new set of tools is enabling NGA to provide more timely and accurate intelligence.
Overflow of data
The government’s adoption of machine learning to extract insights from massive data streams has significant implications for the commercial remote sensing industry. Companies have invested billions of dollars in next-generation Earth observation satellite constellations that produce large amounts of imagery and geospatial data.
Whitworth stated that NGA is eager to take full advantage of the capabilities being developed by the private sector. The challenge is to be able to turn these massive data streams into usable intelligence.
"The sheer volume of geospatial data is staggering," Whitworth said, comparing it to attempting to send high-resolution photos from a mobile phone without a signal. "That challenge, multiplied a billionfold, is what we face on a national scale."
In addition to the practical uses of AI, he mentioned that the agency wants to make broader use of the technology, to monitor global events and provide policymakers with early warnings of potential flashpoints.
A new initiative at NGA is to seamlessly integrate AI into the daily workflow of analysts. These AI-powered systems would, for example, alert analysts to a potential threat emerging halfway across the globe, Whitworth said. "This is a much bigger opportunity that we’re really excited about."
The competition between the United States and China to use AI is really important, especially in the context of a war, according to a DoD intelligence official. The Chinese are racing to be the first to use AI in weapons, and the quality and accuracy of data is crucial for winning a war.
The Pentagon and China’s People’s Liberation Army believe that AI and machine learning are essential for quick data processing and fast decision-making, allowing them to go after a lot of targets quickly and effectively. This is how they see the future of warfare.
AI in war situations
Frontline combat units like the U.S. Army’s 18th Airborne Corps are now using AI tools from Project Maven, according to Trey Treadwell, NGA’s associate director for capabilities.
Using computer vision and detailed datasets, analysts can quickly examine satellite photos and drone videos to find specific targets like vehicles, aircraft, and military equipment. This gives commanders and intelligence analysts a clear operational picture, according to Treadwell at the 39th Space Symposium.
The agency sees AI as a way to enhance their capabilities, rather than letting AI or machines take over completely. For example, it can help in avoiding using expensive missiles to take down inexpensive drones.
The Maven project is about pushing boundaries and using cutting-edge technologies, according to the quote by an NGA official. Field operators are the driving force, challenging analysts to find new layers of information from the data.
Going beyond computer vision
NGA plans to make use of more AI technology beyond computer vision, according to Mark Munsell, NGA’s director of data and digital innovation. Computer vision is just a part of AI technology that allows computers to understand visual information from images and videos.
The agency plans to utilize newer foundation models developed by AI leaders OpenAI, Anthropic, Google, and Microsoft, and customize and train those models with their own data, according to Munsell.
In the future, analytics will rely on big computer vision models and large language models, and there will be a lot more collaboration between humans and machines, according to Munsell.
NGA launched the ASPEN project to integrate AI tools into analysts’ workflows, aiming to empower analysts to identify act