  Physical learning machines, be they classical or quantum, are necessarily
dissipative systems. The rate of energy dissipation decreases as the learning
error rate decreases linking thermodynamic efficiency and learning efficiency.
In the classical case the energy is dissipated as heat. We give an example
based on a quantum optical perceptron where the energy is dissipated as
spontaneous emission. At optical frequencies the temperature is effectively
zero so this perceptron is as efficient as it is possible to get. The example
illustrates a general point: In a classical learning machine, measurement is
taken to reveal objective facts about the world. In quantum learning machines
what is learned is defined by the nature of the measurement itself.
