Engineers make edge AI more efficient by redesigning both algorithm and hardware

Researchers in the Riccio College of Engineering at the University of Massachusetts Amherst have demonstrated that redesigning both hardware and algorithms can make AI applications on edge devices more efficient. As proof of concept, their system achieved 95.24% accuracy in language identification while reducing computing resources by 90%—the highest reported accuracy from a system of its kind.