Brief

A new methodology has been proposed to accurately account for the greenhouse gas emissions generated by AI inference services within corporate sustainability reports. This four-tier framework aims to provide a more precise estimation than current practices, which often omit these emissions or use overly broad economic factors. The proposed method utilizes GPU energy benchmarks and regional grid carbon intensities for direct estimation, with a fallback to spend-based economic factors for services lacking usage data. AI

Researchers are developing new methods for machine unlearning, which aims to remove specific data's influence from trained models without full retraining. Several papers propose novel techniques to achieve more efficient and robust erasure. These methods focus on preserving model utility while ensuring that forgotten knowledge cannot be easily recovered, even with continued training or adversarial attacks. AI