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