The future economic growth in Europe requires engineers and researchers capable to design, develop and implement new information technologies to support explosive data-driven transformation of economy, public and government activities. Current information, computing and processing technologies strongly rely on the classical digital approaches and architectures developed by von Neumann. It is well understood nowadays that brain- or nature-inspired (neuromorphic) technologies can offer substantial advantage in terms of processing capabilities and power efficiency. The development of analog hardware platforms will allow us to achieve significantly higher bandwidth efficiency, faster processing and higher adaptability through integration of self-learning systems.

How does neuromorphic computing differ from conventional computing?

Neuromorphic computing is fundamentally different from digital computing. The internal processing “flow of thought” x of brains and artificial brain-like systems is continuously modulated by sensor input streams u and generates a continuous stream y of outputs. The classical engineering example of such a continuously active self-regulating system is the steam engine governor invented by Watts. In contrast, in digital computing systems, inputs u are given once at the beginning of a computation (e.g. by typing “1 + 3” into a pocket calculator), and after some internal processing x, the output (here y = “4”) is delivered. The classical engineering example is Babbage’s mechanical calculation machine. While today we have a fully worked-out theory that guides digital hardware and software engineering, a similarly productive and scientifically insightful theory for neuromorphic computing is still missing. Theory research in Post-Digital resulted in a comprehensive, detailed agenda for establishing such a theory (documented in a Perspective article in Nature Communications). (historical drawings from commons.wikimedia.org)

Contrasting the process of conventional computer programming with the process of programming a physical substrate for unconventional computing:

Conceptual framework of the programming process for: (a) a digital computer using classical logic-based computational primitives, and (b) a physical substrate for unconventional computing using data-driven physical programming. Three separate domains are identified: the platonic domain of computational tasks or intentions, denoted by 𝛺, the abstract domain of computations as represented by a program in some mathematical formalism, denoted by 𝜆, and finally the tangible domain of physical systems that compute, denoted by 𝛹. The boundary between the platonic domain of intentions or computational tasks and the formalized domain of computer programs is referred to as the formalization barrier, because crossing this barrier requires the programmer to formalize their intentions into a computer program using a specific formalism. The boundary between the formalized program and the physical system is referred to as the implementation barrier, because crossing this barrier requires the programmer to implement their abstract computation into a concrete physical system.

European Training Network on Post-Digital Computing – POSTDIGITAL is an interdisciplinary training network comprising internationally leading teams from academia, research centres and industry, including IBM, Thales and three highly reputed SMEs. POST-DIGITAL will provide a unique training opportunity to a cohort of 15 early stage researchers (ESRs) in the inter-disciplinary fields of emerging disruptive neuromorphic computational technologies and their applications. The strong industrial presence in the network will bridge the gap between early stage innovation and utilization, providing ESRs with the experience of practical applications and solutions beyond traditional digital methods. POST-DIGITAL has the ambition and the vision to create a new generation of scientific and industrial leaders that will greatly contribute to strengthening Europe’s human resources and industry competitiveness in future digital and post digital economy and technology.