Opportunities and Challenges in Integrating AI with Quantum Computing

The convergence of Artificial Intelligence (AI) and Quantum Computing (QC) marks a potentially transformative technological frontier. This study explores the synergistic integration of these fields, analyzing the landscape of opportunities and challenges arising from their combination. Quantum computing offers the promise to enhance AI by overcoming computational bottlenecks and enabling novel algorithms, particularly within machine learning and optimization. This analysis reveals significant opportunities in areas like accelerated machine learning, tackling intractable problems, and processing quantum data. However, substantial challenges currently impede progress, primarily due to limitations in Noisy Intermediate-Scale Quantum (NISQ) hardware, algorithmic complexities in demonstrating practical quantum advantage, and practical hurdles in implementation and interdisciplinary expertise. Despite these challenges, the synergistic potential of AI-QC integration remains immense, promising a paradigm shift in computational capabilities with the continued advancement of both fields, ultimately poised to revolutionize science, industry, and society

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-13
DOI
https://doi.org/10.5281/zenodo.14867911
Primary Topic
Hepatitis C virus research
Type
article
Field-Weighted Citation Impact
0.00
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article

Opportunities and Challenges in Integrating AI with Quantum Computing

Zenodo (CERN European Organization for Nuclear Research)
Hepatitis C virus research
article

Opportunities and Challenges in Integrating AI with Quantum Computing

article en

Abstract

The convergence of Artificial Intelligence (AI) and Quantum Computing (QC) marks a potentially transformative technological frontier. This study explores the synergistic integration of these fields, analyzing the landscape of opportunities and challenges arising from their combination. Quantum computing offers the promise to enhance AI by overcoming computational bottlenecks and enabling novel algorithms, particularly within machine learning and optimization. This analysis reveals significant opportunities in areas like accelerated machine learning, tackling intractable problems, and processing quantum data. However, substantial challenges currently impede progress, primarily due to limitations in Noisy Intermediate-Scale Quantum (NISQ) hardware, algorithmic complexities in demonstrating practical quantum advantage, and practical hurdles in implementation and interdisciplinary expertise. Despite these challenges, the synergistic potential of AI-QC integration remains immense, promising a paradigm shift in computational capabilities with the continued advancement of both fields, ultimately poised to revolutionize science, industry, and society

Zenodo (CERN European Organization for Nuclear Research)
Maria Curie-Skłodowska University (PL)
Industry, innovation and infrastructure
Openalex Percentile: Top 42%
Hepatitis C virus research
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