Paper Contents
Abstract
This paper explores the transformative intersection of Quantum Computing and Artificial Intelligence (AI), collectively known as Quantum Artificial Intelligence (QAI). By leveraging principles like superposition and entanglement, QAI aims to solve complex computational problems that are intractable for classical systems. The study highlights advancements in Quantum Machine Learning (QML), where quantum-enhanced algorithms improve pattern recognition, optimization, and data analysis. Key applications discussed include financial modeling, where quantum methods enable superior risk assessment and portfolio optimization; healthcare, where quantum simulations expedite drug discovery and diagnostics; and cybersecurity, where quantum cryptography and AI-driven threat detection enhance data security. Real-world case studies from IBM, Google, Volkswagen, and Goldman Sachs showcase current industry implementations. Despite its immense potential, the paper addresses critical challenges such as hardware scalability, algorithmic limitations, and the integration of quantum-classical systems. As research progresses, QAI is poised to redefine the landscape of intelligent technologies, offering exponential advancements across diverse sectors.
Copyright
Copyright © 2025 A.Joe Martina. This is an open access article distributed under the Creative Commons Attribution License.
