Predict before you manipulate

When does the race move to hardware?

The supplied post argues that after years of competition around better foundation models, hardware becomes a strategic battleground. Test the causal idea: usable deployment capacity is constrained by the weaker layer.

Before changing anything, what constrains deployment?

Choose a prediction, then run the scenario.

The orange gate marks the weaker layer. Increase either control to see the deployment stream change.
Manipulate the system

Find the limiting layer.

This is a conceptual capacity model, not a market forecast or a legal account. The post supplies the phase-shift claim; the lab teaches how bottlenecks determine which layer deserves attention.

78
38
Hardware is limiting.
Deployment capacity: 38 / 100
Prediction requiredSelect a limiting layer above, then run this scenario. The governing rule is deployment = min(model capability, hardware capacity).
Deployment is bounded by the weaker layer.

Worked case: with model capability 78 and hardware capacity 38, deployment is 38. Improving the model alone cannot lift deployment above 38.

Counterexample: once hardware rises to 90 while the model remains 78, the bottleneck moves back to the model. “Hardware matters” is not a universal claim; it depends on which layer constrains the system now.

Transfer task: raise hardware above 78, run the scenario, and explain why the bottleneck changes.

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