AI's capabilities improve through repeated appropriate learning and continuous verification of the results. AI is a software technology that learns by utilizing data plasticity, and its growth process is similar to the mechanism by which neural circuits in the brain change through learning.
AI requires "appropriate learning"; proper data and task definition are key to growth
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To make AI applicable in specific domains, abundant and appropriate data, along with clear task definitions, is crucial. Furthermore, a feedback cycle to evaluate the validity of AI-generated answers and make corrections as necessary is the key to maintaining and improving accuracy.
Even if AI is used when data is inappropriate or task definitions are ambiguous, the expected results will not be achieved. Rather than treating AI like a "magic wand," an approach is required to judge its applicability through proper training (data, tasks, and verification).
Sources
- AIは魔法の杖ではなく“子ども”だ 「ずる賢く」育つのを阻止するための3つのポイント （ITmedia AI+、2026-09-30）