
The architectural gravity of artificial intelligence is rapidly shifting away from raw processing power toward a complex landscape where memory and storage orchestration determine the true limits of model performance. As the industry pushes the boundaries of context windows, the primary bottleneck in inference has evolved from compute cycles to the efficient management of Key-Value (KV) cache states. This transition










