AI BriefingArithmetic Without Numbers – How LLMs Perform Math
Key point
It explores the internal mechanisms by which LLMs perform arithmetic through matrix and vector operations without physical tools.
Details
LLMs perform arithmetic using only Matrices, without physical tools like fingers or a calculator. This raises a fundamental question: when a model solves an arithmetic problem, is it simply memorizing patterns, or is it actually executing an algorithm?
The model processes Tokens in the form of Vectors, and continuously updates information as it passes through multiple Layers via the Residual stream. In this process, Attention exchanges information between different token positions, while the MLP (Feed-forward block) reconstructs local vectors to reinforce or suppress specific features.
As a result, LLMs handle mathematical operations by building their own mechanistic number system that operates within the model's internal vector space, distinct from the way humans do it.
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