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