# Training energy doubles every \~2 years; gigawatt-scale training by 2030

- **Speaker:** Greg Osuri
- **Attribution:** attributed
- **Said:** 2026-03-28
- **Theme:** Energy & AI — https://www.gregosuri.com/predictions/energy-ai/
- **Source:** Akash Network - Decentralized Cloud Built for AI's Next Frontier (DePIN Connection)
- **Watch at:** 00:17:09 — https://www.youtube.com/watch?v=QuVl2mVHRyo&t=1029s
- **Canonical:** https://www.gregosuri.com/predictions/energy-ai/2026-03-28-training-energy-doubles-every-2-years-gigawatt-sca-hi5v/
- **Cite as:** Greg Osuri, "Training energy doubles every \~2 years; gigawatt-scale training by 2030," Akash Network - Decentralized Cloud Built for AI's Next Frontier (DePIN Connection), 28 Mar 2026, 00:17:09. https://www.youtube.com/watch?v=QuVl2mVHRyo&t=1029s

## Quote — verbatim

> The amount of energy required to train state-of-the-art models is doubling roughly every 2 years... by 2030 we'll need about a gigawatt power install capacity to train the state-of-the-art AI if this trend continues, which looks like it's continuing. Only thing that can provide reliably a gigawatt power is a nuclear reactor.

## Context — site annotation, not spoken

Recapping his congressional testimony (8 months prior) and years of warnings; notes Elon Musk's Dwarkesh podcast made the same argument. Followed by a long breakdown of why the US grid can't scale.