Human brain runs on 20 watts; silicon equivalent needs 25 million times more energy
anselm · x · 2026-08-31
The human brain thinks on roughly 20 watts, while an artificial system doing equivalent work would need about 25 million times more energy—enough on paper to power a quarter of a million homes.
Researchers estimate a human-scale model of 20 billion neurons running on an exascale machine would draw around 0.5 GW, the demand of hundreds of thousands of households. That gap is a hard limit on copying the brain with conventional silicon, and a key reason labs are turning to neuromorphic chips.
More from Infra
- TensorSharp vs llama.cpp: Qwen 3.8 Flash Next Benchmarks — fuzhongkai · 2026-09-01
- Why did increasing context size increase speed in Llama.cpp? — satnl · 2026-09-01
- mlx-signal-processing brings 10-200x faster signal ops to Apple Silicon — TheMoonMidas · 2026-09-01
- AI inference demand surges again, supply brutally outpaced by token growth — Baconbrix · 2026-09-01
- Warp founder predicts cloud-based collaborative factories for all companies within a year — charlieholtz · 2026-09-01
- JPM: 1GW of AI Infrastructure Costs $40-45B, Frontier Labs Make ~$30B per GW — zephyr_z9 · 2026-09-01