Controlled experiments show Improper Model Reuse and Unreleased Tensor References in TensorFlow/Keras increase electricity use by 32% and 46% respectively, with proportional CO2 emission increases that are statistically significant.
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A review of AI sustainability studies finds inconsistent life cycle definitions and predominant reliance on coarse CO2e proxies, with limited coverage of water, materials, and multi-impact assessments.
citing papers explorer
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The Hidden Environmental Cost of Poor Coding Practices in TensorFlow and Keras Applications: A Study on Resource Leaks and Carbon Emissions
Controlled experiments show Improper Model Reuse and Unreleased Tensor References in TensorFlow/Keras increase electricity use by 32% and 46% respectively, with proportional CO2 emission increases that are statistically significant.
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From Cradle to Cloud: A Life Cycle Review of AI's Environmental Footprint
A review of AI sustainability studies finds inconsistent life cycle definitions and predominant reliance on coarse CO2e proxies, with limited coverage of water, materials, and multi-impact assessments.