
The sheer velocity of global AI compute consumption has reached a pivotal threshold where the brute-force efficiency of massive training clusters is being eclipsed by the nuanced, high-frequency demands of live execution. As organizations transition from building foundational models to deploying sophisticated autonomous agents, the limitations of rigid, all-in-one hardware architectures have become painfully clear. This shift marks a fundamental










