While GPU hardware dominates AI infrastructure costs, most private deployments suffer from chronically low utilization rates due to static resource allocation. This session demonstrates how open-source elastic inference technology transforms GPU pools to serve multiple models dynamically, significantly reducing infrastructure costs while maintaining production-grade performance.