AI-ENHANCED REAL-TIME DATA SYNCHRONIZATION IN DISTRIBUTED FRONT-END WEB APPLICATIONS
Keywords:
Artificial Intelligence, Real-time Data Synchronization, Distributed Systems, Front-end Web Applications, Machine Learning OptimizationAbstract
Real-time data synchronization is essential for enhancing user experience in collaborative and interactive web applications operating in distributed environments. This article presents novel AI-driven techniques for optimizing data synchronization and conflict resolution in distributed front-end applications. The approach combines transformer-based neural networks with adaptive conflict resolution strategies, trained on an extensive dataset of 1.2 million real-world conflict scenarios. The article demonstrates exceptional performance improvements, achieving an 89% accuracy in automated conflict resolution compared to the traditional industry average of 65%, while reducing average resolution time from 89ms to 23ms.
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