Neuromorphic Computing Technology (NCT) embraces technologies that enable brain-inspired computing hardware leading to more efficient, fast, and adaptive intelligent systems.
NEUROTECH CSA project aims to create and lead NCT community in Europe.
NCT community builds hardware inspired by biological neural systems using digital and analogue CMOS technologies, memristive devices, photonics, spintronics, and other nano-technological solutions. This technology will revolutionise the field Artificial Intelligence, since it provides orders of magnitude more power-efficient real-time computing platforms for embedded cognitive processing.
Our mission is to catalyse research and collaboration in NCT. Today's neuromorphic community in Europe is leading the state of the art in this domain. The community counts an increasing number of labs that work on theory, modelling, and implementation of neuromorphic computing systems. The NEUROTECH Project will create a Cartography of NCT in Europe, explore Roadmaps for its development, collect educational and information resources on NCT, inform about upcoming and previous events.
Join the NEUROTECH community in a LinkedIn group (https://www.linkedin.com/groups/8800039/) and follow us on Twitter @JoinNeurotech.
We aim to enable the uptake of NCT in real-world applications and to match the needs of companies that develop future products with research and technology development. The envisioned applications are in smart industry, health-care, intelligent assistive systems, cognitive robotics, and consumer devices. We aim to create a sustainable communication channel between research labs, industry, general public, and other stakeholders.
NEUROTECH project assembles and curates a collection of educational resources on all aspects of NCT, to promote core educational events on NCT, and to disseminate NCT curriculum to other communities. The current list of available educational resources can be found in the Blog section. It includes video recordings of lectures, courses at selected Universities, and talk series (https://neurotechai.eu/post/22-collection-online-education-material-neuromorphic-technology).
For me, neuromorphic implies spikes. Historically, it is restricted to sub-threshold analogue, which of course excludes SpiNNaker. Today I think it is wider, and covers all brain-inspired computing models that use spikes for primary communication. But we do need to be inclusive, encourage convergence with ANNs and machine learning.
– Steve Furber