In
machine learning, "
stochastic parrot" is a term
[1] coined by
Emily M. Bender[2][3] in the 2021
artificial intelligence research paper "
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" by Bender,
Timnit Gebru, Angelina McMillan-Major, and
Margaret Mitchell.
[4] The term refers to "large language models that are impressive in their ability to generate realistic-sounding language but ultimately do not truly understand the meaning of the language they are processing."
[2]
[...]
Stochastic means "(1) random and (2) involving chance or probability".
[5] A "stochastic parrot", according to Bender, is an entity "for haphazardly stitching together sequences of linguistic forms … according to probabilistic information about how they combine, but without any reference to meaning."
[3] More formally, the term refers to "large language models that are impressive in their ability to generate realistic-sounding language but ultimately do not truly understand the meaning of the language they are processing."
[2]