Integrating Quantum Computing and Ai for Scalable Data Compatibility Solutions
Year: 2025
Type: article
Abstract: The exponential increase in data generation across industries necessitates innovative strategies for ensuringseamless integration and interoperability. Conventional computing techniques struggle to cope with thecomplexities of heterogeneous data formats. This study introduces a hybrid methodology that synergizes QuantumComputing and Artificial Intelligence (AI) to streamline data compatibility. The proposed system employsQuantum Machine Learning (QML) for accelerated data processing and AI-driven adaptive algorithms for precisetransformations, reducing computational overhead while enhancing accuracy. The results demonstrate improvedefficiency in large-scale data integration scenarios
Author: Devasane Mallesham
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W6968310541
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