Sustainable AI Computing through Dynamic Workload Scheduling and Carbon-Aware Neural Network Optimization
These findings demonstrate that meaningful reductions in AI-related carbon emissions are achievable through coordinated system-level and model-level interventions without requiring fundamental changes to underlying hardware infrastructure.