Approaching limitations of digital computing technologies have spurred research in
neuromorphic and other unconventional approaches to computing. Here we argue that if we …

Sensing technology is an important aspect of information processing. Current development
in artificial intelligence systems (especially those aimed at medical and environmental …

Reservoir Computing is a type of recursive neural network commonly used for recognizing
and predicting spatio-temporal events relying on a complex hierarchy of nested feedback …

The main goal of the field of neuromorphic computing is to build machines that emulate
aspects of the brain in its ability to perform complex tasks in parallel and with great energy …

The slime mould Physarum polycephalum, an aneural organism, uses information from
previous experiences to adjust its behaviour, but the mechanisms by which this is …

Advances in flexible electronic devices and robotic software require that sensors and
controllers be virtually devoid of traditional electronic components, be deformable and …

Proteinoids–thermal proteins–are produced by heating amino acids to their melting point
and initiation of polymerisation to produce polymeric chains. Proteinoids swell in aqueous …

Physical reservoir computing (RC) is a machine learning algorithm that employs the
dynamics of a physical system to forecast highly nonlinear and chaotic phenomena. In this …

Nanodevices that show the potential for non-linear transformation of electrical signals and
various forms of memory can be successfully used in new computational paradigms, such as …

Reservoir computing (RC) systems can efficiently forecast chaotic time series using the
nonlinear dynamical properties of an artificial neural network of random connections. The …