A few days into the trials, the computer identified objects ‐ people, cars, types of building ‐ correctly about 60 percent of the time. Just over a week on the job ‐ and a handful of on-the-fly software updates later ‐ the machine’s accuracy improved to around 80 percent. Next month, when its creators send the technology back to war with more software and hardware updates, they believe it will become even more accurate.
It’s an early win for a small team of just 12 people who started working on the project in April. Over the next year, they plan to expand the project to help automate the analysis of video feeds coming from large drones ‐ and that’s just the beginning.
"What we’re setting the stage for is a future of human-machine teaming," said Air Force Lt. Gen. John N.T."Jack" Shanahan, director for defense intelligence for warfighter support, the Pentagon general who is overseeing the effort. Shanahan believes the concept will revolutionize the way the military fights.
"This is not machines taking over," he said. "This is not a technological solution to a technological problem. It’s an operational solution to an operational problem."
Called Project Maven, the effort right now is focusing on helping U.S. Special Operations Command intelligence analysts identify objects in video from small ScanEagle drones.