In the context of deep learning, why is it essential to rethink generalization?
A) Because deep learning models are inherently biased towards specific data distributions.
B) Due to the complexity and non-linear nature of deep neural networks, their ability to generalize to unseen data can vary.
C) Deep learning models often overfit to training data, necessitating a reevaluation of their generalization capabilities.
D) The theoretical foundations of deep learning emphasize the importance of broad applicability in real-world scenarios.