딥러닝의 과학 이론은 등장할 것이다

The article introduces learning mechanics as a unified scientific framework that explains neural network training through principled interactions between parameters, data, and learning rules, moving deep learning from empirical trial-and-error to quantitative science. This foundation enables predictable control over model behavior, improved design choices, and concrete advances in AI safety and mechanistic interpretability.