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In their paper, Bender et al. argue that LLMs are probabilistically linking words and sentences together without considering meaning. Therefore, they are labeled to be mere "stochastic parrots". [4] According to the machine learning professionals Lindholm, Wahlström, Lindsten, and Schön, the analogy highlights two vital limitations: [1] [7]
English: The past 3 years of work in NLP have been characterized by the development and deployment of ever larger language models, especially for English. BERT, its variants, GPT-2/3, and others, most recently Switch-C, have pushed the boundaries of the possible both through architectural innovations and through sheer size.
Gebru had coauthored a paper on the risks of large language models (LLMs) acting as stochastic parrots, and submitted it for publication. According to Jeff Dean, the paper was submitted without waiting for Google's internal review, which then concluded that it ignored too much relevant research. Google management requested that Gebru either ...
In 2021, Bender presented a paper, "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜" co-authored with Google researcher Timnit Gebru and others at the ACM Conference on Fairness, Accountability, and Transparency [21] that Google tried to block from publication, part of a sequence of events leading to Gebru departing ...
Those birds and other introduced species of parrots and parakeets that have found niches in the clatter and commotion of Southern California city life are believed to be descendants of released ...
This paper's goal was to improve upon 2014 seq2seq technology, [10] ... [116] a phenomenon known as stochastic parrot, ...
After spending 200 days bringing each piece to life, I'm excited to share The Parrot Project, my latest series of hand-cut and hand-painted miniature paper artworks. This collection captures the ...
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