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Public fear about data centers draining local water supplies is largely misplaced. New facilities using closed-loop cooling technology have minimal water consumption. For example, the massive Stargate campus in Abilene is projected to use less water in a year than a McDonald's restaurant.

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The concept of using compute waste heat, pioneered by a Bitcoin-mining-heated bathhouse, is now central to AI. New cooling systems are being designed not just to vent heat, but to process it as an energy asset for heat reuse or electricity generation.

Contrary to the belief that data centers only strain grids, they can lower bills in areas with surplus power. By consuming unused generation capacity, they spread the utility's fixed costs across a larger customer base, preventing existing ratepayers from shouldering the cost of idle assets.

From a first-principles perspective, space is the ideal location for data centers. It offers free, constant solar power (6x more irradiance) and free cooling via radiators facing deep space. This eliminates the two biggest terrestrial constraints and costs, making it a profound long-term shift for AI infrastructure.

Counterintuitively, data centers in arid regions like Arizona can be a net positive. They generate up to 50 times more tax revenue per gallon of water used than industries like golf, making them a highly efficient economic replacement.

The two largest physical costs for AI data centers—power and cooling—are essentially free and unlimited in space. A satellite can receive constant, intense solar power without needing batteries and use the near-absolute zero of space for cost-free cooling. This fundamentally changes the economic and physical limits of large-scale computation.

Data centers are ideal customers because they consume a steady, high amount of power, increasing the grid's overall utilization. Since electricity rates are total costs divided by kilowatt-hours delivered, adding these hyper-efficient customers increases the denominator, lowering the average rate for everyone.

Just two years ago, suggesting a data center operate off-grid was unthinkable. Today, because the public grid cannot support the massive power demands of AI, building dedicated, on-site power generation ('behind the meter') has rapidly become the new industry norm.

The energy demands of modern AI are difficult to contextualize. A one-gigawatt data center uses as much power as a city of nearly one million US households. A five-gigawatt facility requires a 5,000-acre building footprint, excluding any power infrastructure.

To circumvent grid connection delays, infrastructure costs, and potential consumer rate impacts, data centers are increasingly opting for energy independence. They are deploying on-site power solutions like gas turbines and fuel cells, which can be faster to implement and avoid burdening the local utility system.

Scaling AI on Earth is limited by our atmosphere's capacity to absorb heat and the massive amount of fresh water needed for cooling. Moving data centers to space offers an elegant solution: an infinitely cold vacuum for heat dissipation and direct solar power, removing major environmental and resource bottlenecks for AI's growth.