The future economic growth in Europe requires designing, developing and implementing new information technologies to support explosive data-driven transformation of economy, public and government activities. The analysis of this data demands a massive increase in processing power and communication bandwidth. Current information, computing and processing technologies strongly rely on the classical digital approaches and architectures developed by von Neumann. However,technological progress rates of digital technologies are flattening out and are about to hit their ultimate, physical ceilings (“end of Moore’s law”). This growing gap between what is demanded and what can be delivered becomes exacerbated by the increasingly inacceptable energy consumption of the global ICT infrastructure, whose relevance is amplified by the pressing and approaching climate crisis. In this situation, both academic and industrial ICT research has started to investigate and invest in so-called “unconventional”, nature-inspired approaches to computing which radically depart from the classical digital paradigm. In this project, we will study photonics as a promising platform to implement machine-learning based approaches to process information at high speeds and with low power consumption.