Cloud Quantum Computing (CQC) is a paradigm shift in computer science
that has the potential to revolutionize Artificial Intelligence (AI) by utilizing the
computational capabilities of quantum mechanics. The primary objective of this
chapter is to examine the architectural framework of CQC, assess its impact on AIdriven applications, and analyze key challenges and innovations shaping its
development. It focuses on critical aspects of CQC, such as qubit fidelity, quantum
error correction, and hybrid quantum-classical models. The chapter also incorporates
the practical uses of CQC, highlighting its benefits in areas such as optimization,
cryptography, and machine learning. The key findings of this chapter are that although
CQC offers significant advantages in computational efficiency and problem-solving
capabilities, it is still hindered by hardware limitations, noise interference, and
algorithmic complexity. Innovations in error correction techniques and hybrid models
are crucial for overcoming these barriers. By leveraging the power of quantum
computing through cloud platforms, CQC has the potential to revolutionize AI and
computational science.
Keywords: AI model optimization, Cloud quantum computing, Data privacy, ML, Parallelism, Quantum algorithms, Quantum circuits, Quantum cryptography, Qubit fidelity, Quantum software, Quantum simulation, Simulation.
