"Machine capability tends to advance fastest inside patches of reality we can record, constrain, measure, and score."
Karpathy argues that verifiability is a major determinant of which tasks become amenable to optimization through modern AI training. He identifies resettable, efficient, rewardable environments as especially suitable for improvement, explaining why measurable tasks such as mathematics and coding can advance rapidly while contextual and difficult-to-evaluate work remains challenging.
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