Liquid Training Aims to Maximize Idle Compute
markjeffrey · x · 2026-07-15
The author proposes a "liquid training" approach for AI: dynamically scaling compute resources up or down to fully utilize already-installed but idle capacity.
Referencing the idea of the "largest infrastructure build-out in history," they argue that the upcoming economic challenge isn't just about building more capacity, but extracting more useful work from existing setups. They suggest that @IOTASN9's liquid training solution could drive better economic outcomes.
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