Why is SVM not widely used in deep learning systems?

SVM lacks scalability and feature learning capability compared to deep learning.

Deep learning models automatically learn hierarchical features from raw data, while SVM depends heavily on manual feature engineering. Additionally, SVM struggles with very large datasets, whereas neural networks scale better with GPUs.