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Springer eBooks

Quantum-Based Computing and Machine Learning Convergence: Paving the Path to Artificial General Intelligence

H. Meenal, Md. Shoeb Atthar, Harika Koormala, Mohammed Shuaib

Published Jan 1, 2025• 3 citations
Publisher
DOI
10.1007/978-3-031-87931-9_4

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When it comes to artificial intelligence (AI) applications, quantum computing has the potential to bring forth dramatic advances in computational capacity, which could lead to breakthrough solutions. the convergence of artificial intelligence and quantum computing, showcasing the revolutionary powers of quantum mechanics as well as the hurdles involved in utilizing it to improve machine learning algorithms. Among the primary areas of concentration are quantum algorithms for optimization, machine learning models, and data analysis. The emphasis is placed on the potential to solve complicated problems at a rate that is exponentially faster than that reached by classical computers. On the other hand, seamless integration is hampered by significant problems such as quantum decoherence, error correction, and scalability. This paper summarizes the present research efforts, provides an overview of theoretical frameworks, and makes suggestions for future paths in order to maximize the potential of quantum artificial intelligence synergy while overcoming technical challenges.