AnalysisAI ModelsSeptember 21, 2026

Explainer: Why backpropagation uses a backward pass

A 2018 blog post by Gregory Gundersen reconstructs backpropagation from first principles, arguing a forward pass is suboptimal for computing gradients. It shows that because downstream nodes depend on each node's value, the multivariable chain rule lets each node compute its local gradient contribution.

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