Every percentage point of growth in AI adoption translates directly into more data center construction, more power consumption, and more capital expenditure by a handful of large providers. This creates a structural bottleneck: the pace at which AI can be made available to the world is limited by how quickly a few companies can build and finance new facilities. A distributed model removes this bottleneck entirely. When compute is sourced from existing hardware across the globe, capacity grows organically as more node operators join with no single point of investment, failure, or control.Documentation Index
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The Problem