Research published in Nature Machine Intelligence illustrates neuromorphic technology is up to sixteen times more energy-efficient for large deep learning networks than other AI systems.

Stating that a system is topological is a sophisticated way of saying that, in the described situation of the pie-like interfaced materials, it is impossible to devise a construction where the number of incoming radiation channels differs from the number of outgoing channels. In other words, in topological systems there is forcibly a balance between the number of incoming channels and the number of outgoing channels, analogous to the conservation of current in Kirchhoff's circuit laws. In fact, if the number of incoming and outgoing channels could be different, then it would be possible to devise an excitation which would continuously transfer energy from a source to the junction point. In such a situation, a thermodynamic equilibrium can be reached only if the energy arriving at the junction is dissipated as heat. Now, as reported in Advanced Photonics, researchers have shown that such a contrived scenario can indeed be observed in realistic physical systems. They explore the fact that nonreciprocal systems with a continuous translation symmetry have an ill-defined topology. They demonstrate that, contrary to common belief, a junction of nonreciprocal materials is not necessarily bound by any balancing constraint on the number of in/out channels.

Tool reveals hidden features on chest scan images.