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Quantum Intelligence: Integrating Quantum Computing with Advanced AI Systems

Published Sep 7, 2026• 0 citations
Publisher
DOI
10.59646/809/04

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Quantum computing is poised to revolutionize numerous fields, including artificial intelligence (AI) and machine learning (ML), by offering the potential for vastly improved computational efficiency and speed. This paper explores the intersection of quantum computing and intelligent systems, providing an in-depth analysis of how quantum computing can be harnessed to create next-generation AI systems. We discuss the fundamental principles of quantum computing, its potential advantages over classical computing, and current applications and challenges in integrating quantum computing with AI. Additionally, we explore the future trajectory of these fields, speculating on how the convergence of quantum computing and AI will shape future technological advancements.
This paper explores the emerging paradigm of Quantum-Enhanced Edge Intelligence (QEEI), which envisions the integration of quantum computing capabilities with distributed AI at the edge of networks. We review foundational concepts, highlight recent advances in quantum algorithms relevant to edge intelligence, and examine potential applications across domains such as autonomous systems and industrial IoT. The paper outlines a conceptual framework for QEEI, discusses current limitations in hardware and software integration, and offers a forward-looking perspective on research challenges and opportunities at the intersection of quantum computing and edge AI.