And any next-comment predictor could have predicted your totally unhelpful, uninsightful, and unoriginal comment.

You -- along with everyone else who keeps parroting this thought-stopping phrase and other tired cliches like "stochastic parrot", simply because you heard other people say them, without understanding what they really mean, which published research papers they came from, or what those and other papers actually argued -- are desperately clinging to a reductive, short-sighted, shallow, simplistic model like a drowning person clutching a concrete life preserver.

Seriously, we are trying to throw you a lifeline, and you are refusing even to participate in your own rescue. So squawk for yourself.

https://news.ycombinator.com/item?id=48395727

> The term "stochastic parrot" is a slogan masquerading as an explanation, only a shallow surface description of the mechanism, that totally fails to explain the phenomenon, or account for all that LLMs and language itself can do.

Here is the original 2021 paper that coined the phrase. It was not primarily an argument about consciousness, nor did its title constitute experimental proof that everything an LLM does can be explained as parroting. It was principally a position paper about the risks of increasingly large language models: environmental and financial costs, biases and hegemonic viewpoints inherited from poorly documented training data, unequal access and power, and the danger of people attributing meaning and accountability to synthetic text.

The paper did, however, make a strong theoretical claim: because an LM is trained on linguistic form without direct access to communicative intent, it cannot possess meaning, understanding, or a model of the world. The authors described it as "haphazardly stitching together sequences of linguistic forms" according to statistical regularities -- hence "a stochastic parrot."

That distinction matters. The popular slogan discards the paper's detailed analysis of actual risks while treating its most controversial theoretical premise as an established scientific result. It has escaped into pop culture as a drive-by anti-LLM slogan -- something people repeat instead of investigating what these systems represent internally, how post-training changes their behavior, or what they can actually do.

Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell, "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?"

https://s10251.pcdn.co/pdf/2021-bender-parrots.pdf

Ironically, the objection that rhetoric was replacing scientific analysis appeared almost as soon as the phrase itself -- indeed, before the paper's formal publication. In January 2021, Michael Lissack published a response characterizing the draft as an advocacy piece that enumerated harms while leaving its assumptions, potential benefits, and cost-benefit trade-offs largely unexamined.

"The Slodderwetenschap (Sloppy Science) of Stochastic Parrots -- A Plea for Science to NOT Take the Route Advocated by Gebru and Bender"

https://arxiv.org/abs/2101.10098

“Next-token predictor” is the wrong mental model for LLMs