Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Advent of Quantum Computing and AI: Synergies and Implications

Rishi darji, Kush Agarwal

Published Jan 1, 2023• 0 citations
Publisher
DOI
10.2139/ssrn.4318349

Related papers

Advancing AI with Quantum Computing: Synergies Between Quantum Neural Networks and Quantum Reinforcement Learning

Aanal Sanjivbhai Raval, Ruchi Oza

Information systems engineering and management•Jan 1, 2025•2 citations

Quantum Minds: Exploring Quantum Computing and AI Synergy

Madhusudan Singh Irish Singh, Bharat S. Rawal

Springer eBooks•Jan 1, 2026•0 citations

The Future of Artificial General Intelligence (AGI): Quantum–AI Synergy for Human-Like Cognitive Systems

Muhammad Umar Khan, Dr. Muhammad Khalid, Muhammad Burhan Azam +2 more

The future of Artificial General Intelligence (AGI) lies in the fusion of quantum computing and artificial intelligence, creating a synergistic framework capable of human-like cognitive reasoning and adaptability. This study examined how quantum–AI integration enhances computational efficiency, learning capacity, and contextual understanding beyond the limits of classical AI systems. The findings highlighted that quantum-inspired neural networks, through their ability to process complex data in parallel, can enable AGI systems to simulate decision-making, perception, and self-learning in a manner closer to human cognition. Moreover, the research emphasized the ethical and governance challenges that accompany such advancements, including issues of transparency, control, and the moral implications of autonomous systems. The study proposed that responsible innovation, combined with interdisciplinary collaboration, is essential for aligning AGI’s development with societal values and global policy frameworks. Overall, the quantum–AI synergy was found to be a critical driver toward achieving general intelligence, offering unprecedented potential for innovation across scientific, industrial, and educational domains while raising profound ethical considerations for the future of human–machine coexistence.

Global Research Journal of Natural Science and Technology•Jan 2, 2026•1 citation

Quantum Computing Meets Artificial Intelligence: Innovations and Challenges

Maha A. Metawei, Hesham E. ElDeeb, Salwa M. Nassar +1 more

Artificial intelligence-enhanced software and systems engineering•Jan 1, 2022•11 citations

The Implementation of Artificial Intelligence in Quantum Technology

Muhammad Usman, Abubakar Umar Hamza, Sani Abdullahi +3 more

This study is based on Artificial Intelligence (AI) and Quantum Technology which represent two transformative frontiers in modern science. Their integration promises exponential computational enhancements, novel algorithmic models, and robust problem-solving frameworks for intractable problems. This paper explores the synergy between AI and quantum technologies, particularly focusing on how AI algorithms optimize quantum processes and vice versa. We present implementation methodologies, practical results from simulations, and discuss the mutual reinforcement of these technologies for future applications. The integration of Artificial Intelligence (AI) with Quantum Technology (QT) promises to revolutionize computational paradigms. This paper explores how AI models can enhance quantum error correction, optimize quantum circuit design, and facilitate quantum system control. We detail the methodology used to implement AI algorithms in quantum simulations and report results that highlight performance improvements in system efficiency, accuracy, and learning rates. The discussion covers implications for quantum computing, communications, and AI-driven quantum research.

Journal of Science Innovation and Technology Research•Jun 19, 2025•0 citations

Quantum Computing and Artificial Intelligence: A Convergence for Future Innovations

Fatma Foad Ashrif, Rami Ahmad, Faiza A. M. Mansour

Studies in computational intelligence•Jan 1, 2026•1 citation
The future of Artificial General Intelligence (AGI) lies in the fusion of quantum computing and artificial intelligence, creating a synergistic framework capable of human-like cognitive reasoning and adaptability. This study examined how quantum–AI integration enhances computational efficiency, learning capacity, and contextual understanding beyond the limits of classical AI systems. The findings highlighted that quantum-inspired neural networks, through their ability to process complex data in parallel, can enable AGI systems to simulate decision-making, perception, and self-learning in a manner closer to human cognition. Moreover, the research emphasized the ethical and governance challenges that accompany such advancements, including issues of transparency, control, and the moral implications of autonomous systems. The study proposed that responsible innovation, combined with interdisciplinary collaboration, is essential for aligning AGI’s development with societal values and global policy frameworks. Overall, the quantum–AI synergy was found to be a critical driver toward achieving general intelligence, offering unprecedented potential for innovation across scientific, industrial, and educational domains while raising profound ethical considerations for the future of human–machine coexistence.
This study is based on Artificial Intelligence (AI) and Quantum Technology which represent two transformative frontiers in modern science. Their integration promises exponential computational enhancements, novel algorithmic models, and robust problem-solving frameworks for intractable problems. This paper explores the synergy between AI and quantum technologies, particularly focusing on how AI algorithms optimize quantum processes and vice versa. We present implementation methodologies, practical results from simulations, and discuss the mutual reinforcement of these technologies for future applications. The integration of Artificial Intelligence (AI) with Quantum Technology (QT) promises to revolutionize computational paradigms. This paper explores how AI models can enhance quantum error correction, optimize quantum circuit design, and facilitate quantum system control. We detail the methodology used to implement AI algorithms in quantum simulations and report results that highlight performance improvements in system efficiency, accuracy, and learning rates. The discussion covers implications for quantum computing, communications, and AI-driven quantum research.