Risk-Calibrated Hybrid Forecasting for FinOps-Driven Cloud Cost Optimization of AI Workloads
This paper proposes a risk-calibrated forecasting framework that tackles the problem that existing cloud cost models are frequently concerned with providing point estimates and lack uncertainty awareness or operational decision support for FinOps-driven cloud cost optimization of AI workloads. The proposed approach is...