Changing behaviour with less disturbance
One target. Many possible changes.
Drag the orchid arrow along the dashed line. Every position reaches the same target; the sage arrow finds the least costly one.
2.74×your change’s cost relative to the minimum.
Your changeLeast costly change
Ellipses join changes with equal regularised local cost. A mathematical illustration in two internal directions.
The geometry predicts the cost of ignoring it.
Two interventions reach the same calibrated target. Each dot compares their predicted cost ratio with the ratio measured after changing the model.
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The advantage persists along a finite path.
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An update can preserve one set of prompts and transfer to another.
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