GPT-3

With 175 billion parameters, the model can write text, translate and answer questions, often from only a few examples in the prompt.

Why it is in the museum

Language is treated as a prediction problem. From Shannon’s statistical sequences, the story leads to Transformers and large language models.

What supports this exhibit

Primary conference paper

GPT-3’s 175 billion parameters and its few-shot behaviour.

Main source: Brown, T. et al. (2020), “Language Models are Few-Shot Learners”, NeurIPS 33.

Open the source

What to keep in mind: Primary source.

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This small guide uses only the information documented on this exhibit page. If your question goes beyond that evidence, it will say so instead of inventing an answer.

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