DSEE is a flow-based emulator that generates stellar evolution tracks and isochrones as probabilistic outputs from a single model trained on millions of simulations, enabling fast interpolation and uncertainty-aware analyses.
The carbon and water footprints of data centers and what this could mean for artificial intelligence.Patterns, 6(4):101177, 2025
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
The paper formalizes the Water and AI Feedback Loop, introduces the Water Consumption Impact index, and shows water burden from AI data centers varies from 0.2% to 134% of local capacity across ten US sites.
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AI Data Centers and the Water Use Feedback Loop
The paper formalizes the Water and AI Feedback Loop, introduces the Water Consumption Impact index, and shows water burden from AI data centers varies from 0.2% to 134% of local capacity across ten US sites.