Part 3/10:
Moreover, overfitting fundamentally hampers a model's ability to generalize knowledge from its training dataset to unfamiliar inputs. Instead of creating a genuine understanding of the task—such as adding numbers—a model may instead end up functioning like a lookup table, simply recalling answers without comprehension. This phenomenon proved frustrating for AI researchers, who sought improved learning algorithms and neural architectures, as they were led to believe that larger models would merely memorize rather than learn.