analiza aiqbench

Lu Chaoyang's assertion that quantum computing cannot simply function as a "super GPU" highlights the fundamental architectural differences between current classical hardware and future quantum systems. The absence of recognized algorithms to accelerate large model training underscores that practical quantum advantages for AI are still in the theoretical or early experimental phase, rather than being an immediate deployment reality. This distinction is critical for managing expectations regarding near-term timelines for integrating quantum resources into existing machine learning workflows.