GPT-3 can generate impressively fluid text, but it is often unmoored from reality.

GPT-3 was built by directing machine-learning algorithms to study the statistical patterns in almost a trillion words collected from the web and digitized books. The system memorized the forms of countless genres and situations, from C++ tutorials to sports writing. It uses its digest of that immense corpus to respond to a text prompt by generating new text with similar statistical patterns.

The results can be technically impressive, and also fun or thought-provoking, as the poems, code, and other experiments attest. When a WIRED reporter generated his own obituary using examples from a newspaper as prompts, GPT-3 reliably repeated the format and combined true details like past employers with fabrications like a deadly climbing accident and the names of surviving family members. It was surprisingly moving to read that one died at the (future) age of 47 and was considered “well-liked, hard-working, and highly respected in his field.”

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