Researchers Debate Whether "Stochastic Parrot" Still Applies to Modern LLMs

On September 27, Redwood Research researcher Blanche Minerva and cognitive scientist Melanie Mitchell debated on social media over whether LLMs are merely "stochastic parrots" or next-token predictors.

Minerva proposed a five-step pipeline to rebut the claim: take a transformer, pretrain it on massive text, teach it special tokens for tool use, teach it to run programs via the command line, let it do long reasoning with CoT, and finally train it with RL — then she asked whether such a system still counts as a "stochastic parrot."

Confirmed

Why it matters

"Stochastic parrots" is one of the most widely circulated critical frameworks in the LLM field. This discussion shows that both its originators and critics agree the claim no longer fully applies to modern models trained with tool use, long chains of reasoning, and RL. Behind the terminology dispute lies a genuine disagreement over the substance of LLM capabilities.

2026-09-27 ~ 2026-09-27 · 6 related posts

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