An Introduction to Quantum Artificial Intelligence
An established business executive with a background in robotics, Chris Moehle is a venture capitalist specializing in new robotics technology. The managing director of The Robotics Hub, Chris Moehle has spent the last few years advocating for the advancement of robotics and, most recently, augmented intelligence, which involves the combination of data science and artificial intelligence (AI) with traditional human judgement. Quantum artificial intelligence, or simply quantum AI, refers to the integration of quantum computing in the computation of machine learning algorithms. Machine learning is an approach that focuses on developing self-instructable AIs that can learn and act according to everyday observations without continuous human interaction or code-mediated instructions. However, despite the promise of AI humans are not and should not be out of the loop. This is a core principle of Augmented Intelligence. Quantum AI can achieve results that are far beyond the limits of classical computers without straying from the principles of Augmentation. However, a key limitation to using Quantum approaches to Augmented Intelligence is the "noise" inherit in the system. This can make it more difficult to trace and track Quantum than classical methods. To minimize data error and also ensure accurate functioning of quantum computers, a hybrid quantum-classical model is crucial, which involves integrating quantum capabilities with classical computing to sort out data and "validate" learning. In Chris Moehle's opinion, these hybrid approaches are also much easier to adopt. If done well, hybrid implementations gain the power of Quantum additively without removing more trusted classical approaches. This allows trust in the Quantum systems to be built quicker as you are able to safely try them in more meaningful settings.














