Linear elastic caching algorithms reduce operational costs by dynamically scaling memory resources. Google AI Research developed this method to balance cache hit rates against cloud spending. It targets the inefficiency of static memory allocation in large-scale deployments. Engineers can now minimize waste without sacrificing latency for high-demand AI workloads.