GPT-3: the abstract describes a language model with 175 billion parameters, tested on tasks given only a few examples as text.

The exact words it rests on

Specifically, we train GPT-3, an autoregressive language model with 175 billion parameters, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting. For all tasks, GPT-3 is applied without any gradient updates or fine-tuning, with tasks and few-shot demonstrations specified purely via text interaction with the model.

What the source said when we opened it, on 13 Oct 2026.

The source

Language Models are Few-Shot Learners (arXiv 2005.14165)
arXiv · 2020-05-28

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Checked

Checked by the notis newsroom on 13 Oct 2026, against the source above.

In the story

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