questo comunicato 
Vahdat, Amin, e Jeff Dean. «Measuring the environmental impact of AI inference». Google Cloud blog. Consultato 24 agosto 2025.https://cloud.google.com/blog/products/infrastructure/measuring-the-environmental-impact-of-ai-inference.

annuncia questo report:
Elsworth, Cooper, Keguo Huang, David Patterson, Ian Schneider, Robert Sedivy, Savannah Goodman, Ben Townsend, et al. «Measuring the environmental impact of delivering AI at Google Scale». arXiv, 21 agosto 2025. https://doi.org/10.48550/arXiv.2508.15734.

il cui nucleo è (sarebbe) che 

the median Gemini Apps text prompt uses 0.24 watt-hours (Wh) of energy, emits 0.03 grams of carbon dioxide equivalent (gCO2e), and consumes 0.26 milliliters (or about five drops) of water1 — figures that are substantially lower than many public estimates. The per-prompt energy impact is equivalent to watching TV for less than nine seconds.

At the same time, our AI systems are becoming more efficient through research innovations and software and hardware efficiency improvements. For example, over a recent 12 month period, the energy and total carbon footprint of the median Gemini Apps text prompt dropped by 33x and 44x, respectively, all while delivering higher quality responses.

metodologia e dati descritti nel report.

è credibile?
Maurizio