Quantum Collaboration: Pioneering the Frontier of Enhanced Artificial Intelligence
DOI:
https://doi.org/10.53469/jrse.2024.06(12).15Keywords:
Quantum computing, Artificial Intelligence, Quantum - Enhanced AI, Machine learning, Quantum algorithmsAbstract
Quantum - Enhanced Artificial Intelligence QAI merges the advanced capabilities of quantum computing with the sophisticated algorithms of artificial intelligence. This paper explores the current challenges in developing quantum algorithms and qubits, addressing issues of fidelity and scalability. It also examines the potential applications of QAI in various industries, including healthcare, cryptography, and optimization. This article also highlights the transformative potential of QAI, showcasing how the integration of quantum computing with AI can overcome current limitations in data processing and optimization, leading to groundbreaking advancements across multiple sectors.
References
A. Ahmadi, “Quantum Computing and AI: The Synergy of Two Revolutionary Technologies, ” Asian Journal of Electrical Sciences, vol.12, no.2, pp.15–27, Nov.2023, doi: 10.51983/ages - 2023.12.2.4118.
G. De Luca, “Survey of NISQ Era Hybrid Quantum - Classical Machine Learning Research, ” Journal of Artificial Intelligence and Technology, Dec.2021, doi: 10.37965/jait.2021.12002.
P. S. Aithal, “Advances and New Research Opportunities in Quantum Computing Technology by Integrating it with Other ICCT Underlying Technologies, ” International Journal of Case Studies in Business, IT, and Education, pp.314–358, Sep.2023, doi: 10.47992/ijcsbe.2581.6942.0304.
M. - L. How and S. - M. Cheah, “Business Renaissance: Opportunities and Challenges at the Dawn of the Quantum Computing Era, ” Businesses, vol.3, no.4, pp.585–605, Nov.2023, doi: 10.3390/businesses3040036.
L. M. Shaker, A. Al - Amiery, W. N. R. W. Isahak, and W. K. Al - Azzawi, “Advancements in Quantum Optics: Harnessing the Power of Photons for Next - Generation Technologies, ” Journal of Optics, Nov.2023, Published, doi: 10.1007/s12596 - 023 - 01320 - 9.
O. O. Olatunji, P. A. Adedeji, and N. Madushele, “Quantum computing in renewable energy exploration: status, opportunities, and challenges,” Design, Analysis, and Applications of Renewable Energy Systems, pp.549–572, 2021, doi: 10.1016/b978 - 0 - 12 - 824555 - 2.00019 - 8.
A. Passian, G. Buchs, C. M. Seck, A. M. Marino, and N. A. Peters, “The Concept of a Quantum Edge Simulator: Edge Computing and Sensing in the Quantum Era, ” Sensors, vol. 23, no.1, p.115, Dec.2022, doi: 10.3390/s23010115.
F. V. Massoli, L. Vadicamo, G. Amato, and F. Falchi, “A Leap among Quantum Computing and Quantum Neural Networks: A Survey,” ACM Computing Surveys, vol.55, no.5, pp.1–37, Dec.2022, doi: 10.1145/3529756.
H. P. Paudel et al., “Quantum Computing and Simulations for Energy Applications: Review and Perspective,” ACS Engineering Au, vol.2, no.3, pp.151– 196, Jan.2022, doi: 10.1021/acsengineeringau.1c00033.
E. Pelucchi et al., “The potential and global outlook of integrated photonics for quantum technologies,” Nature Reviews Physics, vol.4, no.3, pp.194–208, Dec.2021, doi: 10.1038/s42254 - 021 - 00398 - z.
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Copyright (c) 2024 Zouhair LAKHYAR
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
