Quantum Computing: Implications for Artificial Intelligence and Machine Learning

Authors

  • V. Rama Krishna Associate Professor,CVR College Of Engineering, India
  • Ravi Kumar Jalli Assistant Professor, Departments of EEE, GMRIT, India
  • Kallakuri N V P S Brahma Ramesh Assistant Professor, Department of Computer Science and Engineering, Shri Vishnu Engineering College for Women (A), India
  • Neerugatti Varipally Vishwanath Assistant Professor, Department of ECE, St.Martin's Engineering College, India
  • Neha Purohit Assistant Professor, Department of Computer Science and Engineering, G H Raisoni College of Engineering, India

DOI:

https://doi.org/10.63278/mme.v31i1.1251

Keywords:

Quantum Computing, Artificial Intelligence, Machine Learning, Superposition, Entanglement, Quantum Algorithms.

Abstract

Quantum computing has transformed into a revolutionary technology which can revolutionize artificial intelligence (AI) and machine learning (ML). The processing capabilities of quantum systems rely on the principles of superposition and entanglement to complete operations at quantum-fast speeds which drives solutions for optimization problems and pattern detection along with deep learning breakthroughs. The document analyzes quantum computing fundamentals and its leadership over conventional systems and their applications toward enhancing AI and ML capabilities. This paper examines modern advancements as well as present obstacles and future prospects of this fast-growing field.

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How to Cite

V. Rama Krishna, Ravi Kumar Jalli, Kallakuri N V P S Brahma Ramesh, Neerugatti Varipally Vishwanath, and Neha Purohit. 2025. “Quantum Computing: Implications for Artificial Intelligence and Machine Learning”. Metallurgical and Materials Engineering 31 (1):329-37. https://doi.org/10.63278/mme.v31i1.1251.

Issue

Vol. 31 No. 1 (2025)

Section

Research

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Copyright (c) 2025 V. Rama Krishna, Ravi Kumar Jalli, Kallakuri N V P S Brahma Ramesh, Neerugatti Varipally Vishwanath, Neha Purohit

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