Where is Gradient Descent used in practice?

Pure gradient descent has been largely supplanted by adaptive optimizers like Adam and AdamW that adjust per-parameter learning rates based on gradient history, dramatically improving convergence speed and stability on deep models. AI governance teams document the optimizer choice and hyperparameters as part of their training audit trail because optimizer behavior affects training stability, convergence, and the final model's properties. The p