Technological and theoretical innovations are needed to advance the field of cognitive computing. Therefore, CogniGron is creating the conditions for researchers from materials science (physics and chemistry), computer science, artificial intelligence and mathematics to work closely together with a common mission: to develop materials-centred systems paradigms for cognitive computing based on modelling and learning at all levels: from materials that can learn to devices, circuits and algorithms.
The main goal of CogniGron is to create self-learning materials that will perform the tasks that are currently assigned to thousands of transistors and complex algorithms in a more efficient and straightforward manner, thereby forming the basis for a new generation of computer platforms for cognitive applications, such as pattern recognition and analysis of complex data. To the best of our knowledge, CogniGron is the first initiative of such a kind that unites expertise from the disciplines of physics, materials science, mathematics, computer science and artificial intelligence.
Our programme in cognitive systems and materials aims to discover and develop physical building blocks (i.e. materials) with intrinsic cognitive functionality via cross-linked networks at the nanoscale, allowing more efficient and denser circuits than those of state-of-the-art solutions (e.g. the neuromorphic chip TrueNorthTM). CogniGron will also investigate and design the optimal implementation of such new material structures at the system level.
|Last modified:||06 April 2020 4.45 p.m.|