Scientists, including one of Indian origin, have developed an artificial intelligence system that can help soldiers learn 13 times faster than conventional methods.
Scientists at the US Army Research Laboratory are working on improving the intensity and rate of learning even with a few resources in hand. It is possible to help soliders come up with quick solutions to threats like vehicle-borne improvised explosive device, or potential danger zones from aerial warzone images.
They relied on low-cost, lightweight hardware and implemented collaborative filtering, a well-known machine learning technique on a state-of-the-art, low-power Field Programmable Gate Array platform to achieve a 13.3 times speedup of training compared to a state-of-the-art optimised multi-core system and 12.7 times speedup for optimized GPU systems.
The new technique consumed far less power too. Consumption charted 13.8 watts, compared to 130 watts for the multi-core and 235 watts for GPU platforms, making this a potentially useful component of adaptive, lightweight tactical computing systems.
Rajgopal Kannan, an ARL researcher, said this technique could eventually become part of a suite of tools embedded on the next generation combat vehicle, offering cognitive services and devices for warfighters in distributed coalition environments.
Developing technology for the next generation combat vehicle is one of the six Army Modernisation Priorities the laboratory is pursuing.
Kannan said he is working on developing several techniques to speed up AI/ML algorithms through innovative designs on state-of-the-art inexpensive hardware.
This work is part of Army's larger focus on artificial intelligence and machine learning research initiatives pursued to help to gain a strategic advantage and ensure warfighter superiority with applications such as on-field adaptive processing and tactical computing.