Activations, not just weights, can dominate training memory, and gradient checkpointing is the standard remedy. The signal is the precise trade: recompute activations in the backward pass rather than storing them. Here is the answer.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Activations, not just weights, can dominate training memory, and gradient checkpointing is the standard remedy. The signal is the precise trade: recompute activations in the backward pass rather than storing them. Here is the answer.
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