To derive why RMSNorm (Root Mean Square Normalization) requires a **sum of squares** and a **scaling pass**, we must look at the mathematical goal of normalization in neural networks: stabilizing the distribution of activations to facilitate faster and more stable training.

Here is the step-by-step logical derivation.

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