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Artificial intelligence-enhanced software and systems engineering

Quantum Computing Meets Artificial Intelligence: Innovations and Challenges

Maha A. Metawei, Hesham E. ElDeeb, Salwa M. Nassar, Mohamed Taher

Published Jan 1, 2022• 11 citations
Publisher
DOI
10.1007/978-3-031-08202-3_12

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Recent advancements and the collaboration between the groundbreaking artificial intelligence (AI), with the wider visibility sparked by generative AI in late 2022, and quantum computing technologies have the potential to revolutionize the world, reshape the tech industry, and mark the beginning of a new era of business disruption and innovation. Furthermore, quantum computing when combined with AI, has the potential to bring a new computing revolution surpassing today’s innovation by a wide margin for different fields including cybersecurity. In one hand, digital landscape has been complex making cybersecurity more crucial than ever. On the other hand, traditional methods of safeguarding information are being pushed to their limits with the rapid advancement of technologies. The emergence of quantum computing, combined with AI, is poised to revolutionize the field of cybersecurity, presenting both unprecedented opportunities and challenges. This paper presents challenges and perspectives when quantum-powered AI and cybersecurity meet for business and innovations.
In the twenty-first century, humanity is compelled to face global challenges. Such challenges involve complex systems. However, science has some cognitive and predictive limits in dealing with complex systems. Some of these limits are related to computational complexity and the recognition of variable patterns. To overcome these limits, artificial intelligence (AI) and quantum computing (QC) appear to be helpful. Even more promising is quantum AI (QAI), which emerged from the combination of AI and QC. The combination of AI and QC produces reciprocal, synergistic effects. This work describes some of these effects. It shows that QC offers new materials for implementing AI and innovative algorithms for solving optimisation problems and enhancing machine learning algorithms. Additionally, it demonstrates how AI algorithms can help overcome many of the experimental challenges associated with implementing QC. It also outlines several perspectives for the future development of quantum artificial intelligence.