Spintronics meets Neuromorphics
An entire suite of novel Neuromorphic computational paradigms, taking inspiration from the functional properties of the brain, has emerged over the past two decades to address the need to efficiently process and analyze the exponential amount of data produced in our Information Age. Research on neural networks, reservoir computers and Boltzmann machines, has demonstrated that it is possible to perform complex computational tasks such as image and pattern recognition at a level comparable to that of a human. All proof-of-concepts have however relied mostly on digital implementations of their respective computational scheme. Whereas this has justified the importance of such techniques, their implementation into scalable and energy efficient analog electronic devices is still much of an open problem. The workshop “Spintronics meets Neuromorphics” aims to show how the challenges posed by neuromorphic computing paradigms can be addressed effectively with spintronics. The low-current tunability, thermal susceptibility and rich dynamics of magnetic thin-film heterostructures offer an ideal toolbox for implementing novel neuromorphic devices. Furthermore, progress in their material science guarantees that promising proof-of-concepts will have a high chance of proving scalable enough to afford industrial production.