Conventional wisdom dictates large thermodynamic systems for efficiency. Exowatt's contrarian, small modular design prioritizes manufacturing principles like rapid iteration and cost control, creating a predictable learning curve akin to mass-produced solar PV panels.
While supply chains for GPUs and power have been major hurdles, the current primary constraint for building new data centers is a shortage of skilled construction workers. There simply are not enough electricians and laborers to build facilities quickly enough to meet demand.
Targeting an extremely low electricity cost of 1¢ per kilowatt-hour acts as a forcing function for Exowatt. This 'North Star' metric dictates a strategy of radical simplification, domestic manufacturing, and reliance on common raw materials like sand, dirt, and steel.
Exowatt provides round-the-clock solar power by using Fresnel lenses to focus sunlight onto rocks, storing the energy as heat. This stored heat then drives a Stirling engine to generate electricity, creating a continuous power source for energy-intensive AI data centers.
The AI boom has created such desperation for power that hyperscalers now prioritize immediate availability ('time to power') above all else. Cost has become a secondary concern, and sustainability, once a key objective, has fallen far lower on the priority list.
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.
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.