That's not an insight, it's a misunderstanding. Overfitting is only applicable relative to claims of statistical performance. And in any event, there are lots

That's not an insight, it's a misunderstanding. Overfitting is only applicable relative to claims of statistical performance. And in any event, there are lots of systems with fewer degrees of freedom (or in the case of deep learning, more generalization potential) than the training data, that are not at particular risk of being overfit, and there are measures and tests to mitigate the risk of overfitting. It's not some inherent characteristic of "systems".