UNDERSTANDING LLMS: INSIGHTS FROM MECHANISTIC INTERPRETABILITY

Summary from the TLDR AI newsletter

This post walks readers through in detail how large language models (LLMs) work. Transformer-based LLMs are autoregressive next-token predictors. Simple analogies like 'it's just statistics' are inadequate explanations of how LLMs work. LLMs perform tasks by forming emerging circuits that combine learned statistics, information-moving attention heads, and knowledge storing MLP sub-layers into specialized sub-networks that collectively execute complex behaviors.