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At Google, 95% utilization was considered an outage, because idle compute cost less than losing a job.
AMP's vision is to make FLOPs flow like megawatts through a compute grid with 1.2GW base-load and 6GW spike capacity.
Anthropic's P0 was coding from day one, and Claude cracked coding through sustained focus on that priority.
The AI scaling story is typically told through model architecture or GPU count, but Anjney Midha argues the real bottleneck is now infrastructure utilization and community alignment.
At Google, 95% utilization was considered an outage, because the marginal cost of idle compute was dwarfed by the cost of losing a job.
At frontier labs today, the opposite problem dominates: companies hoard compute to preserve optionality, leading to compounding waste.
DeepMind hoarding unpublished research creates a similar negative externality — knowledge that could accelerate the entire field sits locked away.
The tension is that the next phase of AI requires not just more FLOPs, but a fundamentally different market structure for how compute is allocated and governed.
