The Convergence of Quantum Computing and Artificial Intelligence

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Authors: Nitu Tank
Cited by: 0
References: 28

Abstract

This chapter discusses the intersection of quantum computing, artificial intelligence and neuromorphic engineering as a basis of the next generation hybrid intelligent systems. It describes the role of quantum processing in providing high-dimensional reasoning and probabilistic optimization, and the ability of neuromorphic hardware to do spiking computations at real time and using less energy. These paradigms and their combination address the scalability and performance constraints of classical AI. The chapter examines major hybrid architectures, neuromorphic-to-quantum encoding algorithms, quantum-assisted learning algorithms, and integrated inference pipelines. Another significant aspect that it brings to the fore is the key areas of application, including robotics, healthcare, finance, and edge intelligence, as well as engineering limitations, moral implications, and safety issues of AGI. An outlook research road identifies essential milestones towards scalable, secure, and interpretable hybrid neuromorphic quantum systems.

Fields of Study & Subjects

Quantum Computing Algorithms and Architecture Advanced Memory and Neural Computing Artificial Intelligence Applications

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Pages
101–136
Publication date
4 March 2026
Language
EN
Document type
Book chapter