The nano-neuron uses an exceptionally stable magnetic oscillator. Each gyration of this nano-compass generates an electrical output, which effectively imitates the electrical impulses produced by biological neurons. In the next few years, these magnetic nano-neurons could be interconnected via artificial synapses, such as those recently developed, for real-time big data analytics and classification.
The nano-neuron showed the ability to recognise numbers spoken by different individuals with 99.6% accuracy.
The long-term goal is to produce extremely energy-efficient miniaturised chips with the intelligence needed to learn from and adapt to the constantly ever-changing and ambiguous situations of the real world using true artifical intelligence rather than machine learning. These electronic chips will have many practical applications, such as providing smart guidance to robots or autonomous vehicles, helping doctors in their diagnosis’ and improving medical prostheses.
The team includes researchers from the joint French CNRS and Thales Joint Physics Unit, the Nanosciences and Nanotechnologies Centre at CNRS and Université Paris Sud as well as the Center for Nanoscale Science & Technology in Maryland, US, and the National Institute of Advanced Industrial Science and Technology (AIST) in Japan. The French National Centre for Scientific Research (CNRS) is Europe’s largest public research institution with 1100 laboratories.