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.
The energy cost of artificial intelligence of things lifecycle
2 Pith papers cite this work. Polarity classification is still indexing.
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Decentralized ML in IoT networks matches centralized predictive accuracy near 90% but reduces electricity consumption by up to 70% in a railway testbed.
citing papers explorer
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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.
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Towards Energy Impact on AI-Powered 6G IoT Networks: Centralized vs. Decentralized
Decentralized ML in IoT networks matches centralized predictive accuracy near 90% but reduces electricity consumption by up to 70% in a railway testbed.