Quantum computers can be used to tackle machine learning problems. Quantum circuits are differentiable, and a quantum computer itself can compute the change in control parameters needed to become better at a given task.
Differentiable programming is the very basis of deep learning, implemented in software libraries such as TensorFlow and PyTorch. Differentiable programming is more than deep learning: it is a programming paradigm where the algorithms are not hand-coded, but learned. In our case we will be using this approach to solve systems of linear equations more efficiently than classical computational algorithms.
The Variational Quantum Linear Solver, or the VQLS is a variational quantum algorithm that utilizes VQE in order to solve systems of linear equations more efficiently than classical computational algorithms.