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The DePIN & GPU narrative persists because constraints haven't moved.
Demand for training and inference keeps compounding, while centralized clouds stay bottlenecked by CAPEX, geography, and queuing.
Sure, a few years ago, compute scarcity was still a theory.
But now it’s an operational constraint.
How does this affect the usage and revenue of decentralized compute networks?
Decentralized compute networks aren’t “waiting for utilization someday.” They’re already running production workloads for real customers, under real latency constraints.
Tokenized GPUs, on-demand clusters, and hybrid cloud/DePIN stacks aren’t ideological statements anymore.
They’re emerging as the practical answer when centralized supply can’t spin up fast enough, close enough, or cheap enough.