Elon Musk – "In 36 months, the cheapest place to put AI will be space”

Data Center Costs and Energy Constraints00:00

Only 10-15% of the total cost of ownership of a data center is energy. Most of it's the GPUs. Moving to space saves on energy but makes servicing GPUs harder, shortening depreciation cycles and increasing costs.

Reason to Put AI in Space: Energy Availability00:30

Availability of energy is the issue. Outside China, electrical output is more or less flat with maybe a slight increase. China has rapid increase in electrical output. Chip output grows exponentially, but electricity output is flat. No magical power sources.

Elon is a big fan of solar. One terawatt of solar power with 25% capacity factor requires four terawatts of solar panels, 1% of US land area. We're in the singularity at one terawatt of data centers.

Covering Nevada in solar panels is hard due to permits.

Space as Regulatory and Scaling Solution02:02

Space is a regulatory play. Harder to build and scale on land than in space. Solar panels in space are five times more effective than on ground, no batteries needed.

"It's always sunny in space."

No day-night cycle, seasonality, clouds, or atmosphere. Atmosphere causes 30% energy loss. Solar panels produce five times more power in space. Avoids battery costs for night.

Actually much cheaper in space. Prediction: in 36 months or less (maybe 30 months), space will be the cheapest place to put AI. Then it gets ridiculously better. Only place to really scale is space.

Servicing GPUs in Space03:03

GPUs quite reliable past infant mortality, which can be tested on ground before launch. Past initial debug cycle of Nvidia, Tesla AI6 chips, TPUs, Trainiums, etc., reliable. Servicing not an issue.