An Analytical View of LLMs: Layers as Interaction Terms Supporting Scaling
cephaloform · x · 2026-08-11
The author explored the underlying mechanics of Large Language Models (LLMs) through the lens of harmonic analysis, emerging with a strong conviction in model scaling.
The analysis suggests that every layer of an LLM essentially generates another set of interaction terms between variables, acting like basis functions. Consequently, increasing model dimensions introduces more variables, while adding layers enriches these interaction combinations. The author argues that this process relies on no mysterious magic that will suddenly break down, mathematically reinforcing the continued validity of Scaling Laws.
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