Today we're sharing a method we've been using to measure AI agent capabilities: the "expenditure horizon".
On an open-ended optimization problem, an AI agent given a small budget will often make more progress than a human given the same budget, because human time is expensive. The expenditure horizon is the budget at which the human catches up: the dollar value where a human's expected improvement, given the same budget, equals the agent's.
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