Recently, there has been impressive progress in the field of artificial intelligence. A striking example is Alphago, an algorithm developed by Google, that defeated the world champion Lee Sedol at the game of Go. However, in terms of power consumption, the brain remains the absolute winner, by four orders of magnitudes. Indeed, today, brain inspired algorithms are running on our current sequential computers, which have a very different architecture than the brain. If we want to build smart chips capable of cognitive tasks with a low power consumption, we need to fabricate on silicon huge parallel networks of artificial synapses and neurons, bringing memory close to processing. The Bio-Ice project aims to deliver a new breed of bio-inspired magnetic devices for pattern recognition. Their functionality is based on the magnetic reversal properties of an artificial spin ice in a Kagome geometry. The local control of the magnetic properties gives to our device a learning ability. A consortium with complementary skills (materials science, measurements, characterization and theory) will drive this project having multiple applications.
Monsieur Daniel Lacour (Institut Jean Lamour (Matériaux - Métallurgie - Nanosciences - Plasmas - Surfaces))
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
IJL Institut Jean Lamour (Matériaux - Métallurgie - Nanosciences - Plasmas - Surfaces)
Unité Mixte de Physique CNRS/Thales
INEEL INSTITUT NEEL - CNRS
UPSud / C2N Université Paris Sud / Centre de Nanosciences et de Nanotechnologies
Help of the ANR 654,182 euros
Beginning and duration of the scientific project: February 2018 - 48 Months