What is gradient (activation) checkpointing, and what does it trade off?
Activations, not just weights, can dominate training memory, and gradient checkpointing is the standard fix. The signal is the precise trade: recompute activations in the backward pass instead of storing them. Here is the answer.
Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.
Activations, not just weights, can dominate training memory, and gradient checkpointing is the standard fix. The signal is the precise trade: recompute activations in the backward pass instead of storing them. Here is the answer.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.