Advanced Deep Learning Interview Questions #7 - The Vanishing Gradient Trap

Focusing only on gradient flow ignores that Sigmoid destroys forward-pass geometry, starving deeper layers of usable spatial signal.

You’re in a Senior Machine Learning Engineer interview at DeepMind.

The interviewer sets a trap: “Your team is migrating a deep model’s hidden layers from Sigmoid to ReLU. Why are we doing this?”

90% of candidates walk right into it.

Most candidates immediately suggest: “It’s to solve the vanishing gradient problem during backpropagation. Sigmoids saturat…