Authors : Gopalakrishnan Arjunan

Volume/Issue : Volume 9 - 2024, Issue 11 - November

Google Scholar : https://tinyurl.com/4awnd5he

Scribd : https://tinyurl.com/4f9em4re

DOI : https://doi.org/10.5281/zenodo.14286984

Abstract : This report explores the intersection of Artificial Intelligence and Hybrid Quantum-Classical Systems, focusing on their ability to solve complex problems in different sectors. The report therefore sets out the various stages of AI development, noting its huge milestones, and how machines can learn. It then goes on to explain how quantum computing is expected to upgrade AI - particularly with respect to optimization and machine learning, which is going to be used in applications in drug discovery, financial portfolio optimization, and logistics. Other report domains discussed also include actual applications of hybrid quantum-classical systems and the setbacks associated with the integration of quantum technologies. Finally, the paper speaks about future prospects within this hybrid approach, signifying transformed capacities within AI and quantum computing that could be leveraged towards solutions of global complex problems.

Keywords : Hybrid Quantum-Classical AI Models, Quantum Computing, Artificial Intelligence (AI), and Machine Learning.

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