Neuromorphic Promises Better AI

When Apple CEO Tim Cook introduced the iPhone X, he claimed it would "set the path for technology for the next decade." While it is too early to tell, the neural engine used for face recognition was the first of its kind. Today deep neural networks are a reality, and neuromorphic appears to be the only practical path to make continuing progress in AI. Facing data bandwidth constraints and ever-rising computational requirements, sensing and computing must reinvent themselves by mimicking neurobiological architectures, claimed a recently published report by Yole Développement (Lyon, France). In an interview with EE Times, Pierre Cambou, Principal Analyst for Imaging at Yole, explained that neuromorphic sensing and computing could solve most of AI's current issues while opening new application perspectives in the next decades.