Quantum Computing in Artificial Intelligence: Exploring the Intersection of Quantum Algorithms and Machine Learning Models
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V2I1P103Keywords:
Quantum Machine Learning, Quantum Computing, Quantum Neural Networks, Quantum Support Vector Machines, Quantum Principal Component Analysis, Quantum Boltzmann Machines, Hybrid Quantum-Classical Models, Superposition, Quantum Gates, Financial ForecastingAbstract
Quantum computing, with its unique properties and potential to solve complex problems more efficiently than classical computers, has emerged as a promising field in the realm of computational science. The intersection of quantum computing and artificial intelligence (AI) presents a fertile ground for innovation, particularly in the development of quantum algorithms that can enhance machine learning models. This paper explores the theoretical foundations, current research, and potential applications of quantum computing in AI. We delve into the mathematical underpinnings of quantum algorithms, their integration with machine learning models, and the practical challenges and opportunities that lie ahead. Through a detailed analysis of existing research and the presentation of novel algorithms, this paper aims to provide a comprehensive overview of the current state and future prospects of quantum-enhanced AI
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