electronic warfare systems provide new electronic detection, support and attack capability (U.S. Army photo by Sgt. Maricris C. McLane, 24th Press Camp Headquarters)

Army wants AI to help soldiers sort signals intell

The Army wants to use artificial intelligence to better classify signals for soldiers fighting against adversaries with well-developed electronic warfare capabilities. The solution would highlight signals of importance, so soldiers don’t have to sort through the data themselves.

The Army Rapid Capabilities Office plans to hold a challenge to find the best algorithms and AI implementations for integrating with intelligence, surveillance and reconnaissance systems. RCO was created in August 2016 to speed the delivery of critical combat capabilities to the warfighter.

In lieu of submitting white papers, the participants will submit source code for their applications and would provide “AI/Neural network pipeline designs, hyperspace parameters, and AI model configuration parameters or design features,” according to the draft announcement.

When the challenge goes live, participants will be given the data needed to build their application. No other data will be allowed to be used for development.

The winner will receive $100,000, with second place taking $30,000 and third place getting $20,000.

Comments on the draft can be submitted until April 19, and the challenge will appear on Challenge.gov once it is live.

Read the draft solicitation here.

About the Author

Matt Leonard is a reporter/producer at GCN.

Before joining GCN, Leonard worked as a local reporter for The Smithfield Times in southeastern Virginia. In his time there he wrote about town council meetings, local crime and what to do if a beaver dam floods your back yard. Over the last few years, he has spent time at The Commonwealth Times, The Denver Post and WTVR-CBS 6. He is a graduate of Virginia Commonwealth University, where he received the faculty award for print and online journalism.

Leonard can be contacted at mleonard@gcn.com or follow him on Twitter @Matt_Lnrd.

Click here for previous articles by Leonard.


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