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德国计划到2030年将数据中心规模翻倍、AI算力提升四倍，但其气候承诺与《能源效率法》中要求数据中心回收废热的规定产生冲突，政府最终在行业压力下弱化了该要求，凸显欧洲在AI扩张与减排目标之间的两难。
The paper presents an analysis of the environmental break-even point for ML-based data compression, estimating carbon-equivalent costs for training and inference against savings from reduced disk storage.
A proposed SLA-constrained carbon-aware routing policy for geo-distributed serverless clouds achieves up to 46.8% carbon reduction while maintaining zero SLA violations, evaluated on real AWS deployments.