US spending on fossil fuel power has passed China's, mostly to power the growing number of AI data centers. #aienergy
https://www.carbonbrief.org/ai-boom-means-us-is-now-investing-more-in-fossil-fuel-power-than-china/
US spending on fossil fuel power has passed China's, mostly to power the growing number of AI data centers. #aienergy
https://www.carbonbrief.org/ai-boom-means-us-is-now-investing-more-in-fossil-fuel-power-than-china/
Thanks for sharing your thoughts.
Here are the actual numbers
Train Gemini Ultra ~150 GWh
Distill Nano from Ultra ~1–5 GWh / ~1–3%
One Gemini cloud query 0.24 Wh / 0.00000016%
1 year of Gemini cloud serving (~1B queries/day) ~90 GWh / ~60%
👉One Nano on-device query ~0 datacenter-side (phone battery) 0% 👈
Aggregate inference passes the training run in roughly 18–24 months at frontier-deployment scale and that's only counting the per-query number Google chose to publish. Query volume is a rough order-of-magnitude estimate
Gemini Ultra burn would have occurred regardless of Nano deployment.
Nano distill is a one off expenditure of SA grid demand for a day. After that free model with phone recharge.
Maths.
Could your data center run on biology? Dr. Brent Jensen reveals how quantum-biohybrid systems merge living tissue with quantum mechanics for clean energy at scale—essential reading where AI meets sustainable power innovation! 👉 https://medium.com/@ambitionmagician/quantum-biohybrid-energy-systems-revolutionizing-sustainable-power-with-synthetic-organoids-7a850487e4f3
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