Six misconceptions about large language models: A minimal model and diagnostic taxonomy
Large language models (LLMs) are now embedded in scientific, educational, and governance workflows, with debates centering on their capabilities, mechanisms, and impacts. Yet these debates remain structured by persistent folk theories--intuitive, informal explanatory models that guide attitudes and actions. Deflationary slogans ("just autocomplete," "stochastic parrots," and "average of the internet") and anthropomorphic framings ("emergent agents" and "proto-minds") each capture genuine features of current systems but mistake those features for the whole. This Perspective proposes a minimal working model of LLM-based systems centered on four distinctions: between pretraining and deployed...
| Authors | Zhicheng Lin |
|---|---|
| Primary category | cs.CY |
| Published | 19 August 2026 |
| Last updated at source | 19 August 2026 |
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