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Introduction 
As computational challenges grow increasingly complex, traditional algorithms sometimes struggle to keep pace. Quantum-inspired algorithms have emerged as a promising solution that leverages principles from quantum mechanics to optimize data processing on classical processors. By mimicking features such as superposition and entanglement through sophisticated machine learning models, these algorithms can accelerate problem‑solving in areas like optimization, cryptography, and machine learning. This article explores how quantum-inspired techniques are being integrated into PC architectures to dramatically boost computation speed and efficiency.

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