INSUBCONTINENT EXCLUSIVE:
Quantum computers don't have that sort of separation
While they could include some quantum memory, the data is generally housed directly in the qubits, while computation involves performing
operations, called gates, directly on the qubits themselves
In fact, there has been a demonstration that, for supervised machine learning, where a system can learn to classify items after training on
pre-classified data, a quantum system can outperform classical ones, even when the data being processed is housed on classical hardware.This
form of machine learning relies on what are called variational quantum circuits
This is a two-qubit gate operation that takes an additional factor that can be held on the classical side of the hardware and imparted to
the qubits via the control signals that trigger the gate operation
You can think of this as analogous to the communications involved in a neural network, with the two-qubit gate operation equivalent to the
passing of information between two artificial neurons and the factor analogous to the weight given to the signal.That's exactly the system
that a team from the Honda Research Institute worked on in collaboration with a quantum software company called Blue Qubit.The focus of the
new work was mostly on how to get data from the classical world into the quantum system for characterization
But the researchers ended up testing the results on two different quantum processors.The problem they were testing is one of image
The raw material was from the Honda Scenes dataset, which has images taken from roughly 80 hours of driving in Northern California; the
images are tagged with information about what's in the scene
And the question the researchers wanted the machine learning to handle was a simple one: Is it snowing in the scene?
