  Fuelled by increasing computer power and algorithmic advances, machine
learning techniques have become powerful tools for finding patterns in data.
Since quantum systems produce counter-intuitive patterns believed not to be
efficiently produced by classical systems, it is reasonable to postulate that
quantum computers may outperform classical computers on machine learning tasks.
The field of quantum machine learning explores how to devise and implement
concrete quantum software that offers such advantages. Recent work has made
clear that the hardware and software challenges are still considerable but has
also opened paths towards solutions.
