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| universal_ai_as_imitation [2026/03/08 19:37] – pedroortega | universal_ai_as_imitation [2026/03/08 20:59] (current) – pedroortega | ||
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| //Keywords: universal imitation, counterfactual action, third-party action, evidence-transfer, | //Keywords: universal imitation, counterfactual action, third-party action, evidence-transfer, | ||
| - | ===== Introduction: | + | ===== Introduction: |
| A common task is learning to cook with a chef. The learner attempts a step, and the kitchen replies with structured evidence: aroma shifts, sound changes, browning, viscosity, texture, and taste, as well as brief corrections or confirmations from the chef. Over repeated trials, competence takes the form of an internal rule: a compact explanation of why some interventions succeed and others fail, and a way to generalize beyond the demonstrated cases. In this setting, success is not naturally described as optimizing a standalone score in isolation. It is better described as learning what tends to //happen after// a chosen step, and using that relationship to produce good outcomes in dishes the learner has not seen before. | A common task is learning to cook with a chef. The learner attempts a step, and the kitchen replies with structured evidence: aroma shifts, sound changes, browning, viscosity, texture, and taste, as well as brief corrections or confirmations from the chef. Over repeated trials, competence takes the form of an internal rule: a compact explanation of why some interventions succeed and others fail, and a way to generalize beyond the demonstrated cases. In this setting, success is not naturally described as optimizing a standalone score in isolation. It is better described as learning what tends to //happen after// a chosen step, and using that relationship to produce good outcomes in dishes the learner has not seen before. | ||