  Machines are possible to have some artificial intelligence like human beings
owing to particular algorithms or software. Such machines could learn knowledge
from what people taught them and do works according to the knowledge. In
practical learning cases, the data is often extremely complicated and large,
thus classical learning machines often need huge computational resources.
Quantum machine learning algorithm, on the other hand, could be exponentially
faster than classical machines using quantum parallelism. Here, we demonstrate
a quantum machine learning algorithm on a four-qubit NMR test bench to solve an
optical character recognition problem, also known as the handwriting
recognition. The quantum machine learns standard character fonts and then
recognize handwritten characters from a set with two candidates. To our best
knowledge, this is the first artificial intelligence realized on a quantum
processor. Due to the widespreading importance of artificial intelligence and
its tremendous consuming of computational resources, quantum speedup would be
extremely attractive against the challenges from the Big Data.
