DoD official: We will deploy advanced algorithms to front lines to decode data before year-end

WASHINGTON. The U.S. Department of Defense (DoD) plans to deploy to the front lines new computer algorithms designed to extract objects of interest from massive amounts of moving or still imagery by the end of the year, according to U.S. Marine Corps Col. Drew Cukor, head of the Algorithmic Warfare Cross-Function Team in DoD’s Office of the Undersecretary of Defense for Intelligence.

Speaking at a recent media event, Cukor said that by the end of 2017, the DoD will place advanced computer algorithms onto government platforms to extract objects from the huge amounts of imagery that is being captured in the field: "People and computers will work symbiotically to increase the ability of weapon systems to detect objects,” Cukor added. “Eventually we hope that one analyst will be able to do twice as much work, potentially three times as much, as they're doing now. That's our goal.”

The effort to help a workforce increasingly overwhelmed by incoming data, including millions of hours of video, began in April 2017 when then-Deputy Defense Secretary Bob Work announced in a memo that he was establishing an Algorithmic Warfare Cross-Functional Team, overseen by the undersecretary of defense for intelligence, to work on something he called Project Maven, which would integrate artificial intelligence and machine learning across DoD operations.

Cukor said that Project Maven focuses on computer vision, an aspect of machine learning and deep learning, which that autonomously extracts objects of interest from moving or still imagery; the process uses biologically inspired neural networks, with "deep learning" defined as applying these neural networks to learning tasks. He noted that the DoD is undertaking a significant effort to procure computational power, including graphic processing units that allow training of machine-learning algorithms; an algorithmic development contract also is in process, Cukor said, and the DoD will go through a competitive selection process to find vendors that can provide algorithms to handle DoD data.