Mechanical neural network could enable smart aircraft wings that morph

A mechanical neural network composed of beams, motors and sensors can learn to carry out several different tasks, just like its software equivalent, and could lead to aircraft wings that morph during flight to maintain efficiency or minimise turbulence. The basis of modern AI research is the artificial neural network (ANN), which mimics the structure of the human brain by creating large grids of artificial neurons connected by synapses. Just as the human brain learns new behaviours by strengthening synaptic connections, ANNs learn by adjusting the digital values stored to represent them. Ryan Lee at the University of California, Los Angeles, and his colleagues have borrowed that concept to create a mechanical neural network in which the strength of connections between neurons is replaced by beams of variable stiffness. Instead of processing digital data, the mechanical neural network processes forces applied to it, twisting and morphing its shape depending on the stiffness of its beams.