Machine learning using a hybrid quantum-classical algorithm

The industrial sector uses artificial intelligence (AI) in many ways. E.g. anomaly detection to identify and examine abnormal behavior of machines, such as voltage and current fluctuation. To develop self driving cars AI is used to perform segmentation of the environment to navigate the vehicle and make decisions, preferably in real-time. Quantum computers are already being used for special machine learning processes, achieving, in some instances, better results than a regular machine learning algorithm. This paper will elaborate on the upsides of a machine learning model consisting of a hybrid between a quantum machine learning (QML) algorithm and a classical machine learning algorithm.