Quantum Machine Learning: The Intersection of Quantum Computing and AI

Abstract

Quantum Machine Learning (QML) explores the convergence of quantum computing and artificial intelligence (AI) to leverage the unique computational advantages of quantum mechanics for machine learning tasks. By integrating quantum computing potential for handling vast datasets and complex algorithms with the pattern recognition and predictive capabilities of AI, QML aims to develop novel algorithms that could outperform classical counterparts in speed and efficiency. This interdisciplinary field investigates how quantum bits (quits) can represent and process information more effectively than classical bits, potentially revolutionizing data analysis, optimization problems, and model training. As quantum technology advances, QML holds promise for breakthroughs in various domains such as drug discovery, financial modeling, and artificial intelligence applications, driving a new era of computational power and innovative solutions.