Modern machine-learning applications require huge artificial networks demanding
computational power and memory. Light-based platforms promise ultrafast and energy …

We provide a perspective on the fundamental relationship between physics and
computation, exploring the conditions under which a physical system can be harnessed for …

We provide a perspective on the fundamental relationship between physics and
computation, exploring the conditions under which a physical system can be harnessed for …

We provide a theoretical, numerical, and experimental investigation of the Kerr nonlinearity
impact on the performance of a frequency-multiplexed Extreme Learning Machine (ELM). In …

Reservoir Computers (RCs) are brain-inspired algorithms based on recurrent neural
networks where only output weights are tuned, while internal weights remain untrained. We …

Throughout the course of human history, technology has played a critical role in shaping the
world and advancing human progress. From the earliest tools used by our ancestors to the …

En optique, l'utilisation croissante de techniques et d'algorithmes d'apprentissage machine
(ML) impact de façon importante une variété de systèmes. Celle-ci a mené aux …

The biological brain is a very efficient computer because it exploits the rich dynamic of the
organic substrate. Physical computing consists of processing information by exploiting the …