CONCEPT
The Blurry JPEG
Ted Chiang’s 2023 analogy for what a large language model actually is—a lossy compression of all the text on the web that retains statistical patterns while discarding exact sources, and reconstructs plausible approximations on demand rather than retrieving or understanding anything.
“Think of ChatGPT as a blurry JPEG of all the text on the Web.” With that sentence, published in
The New Yorker in February 2023,
Ted Chiang did more to clarify public understanding of
large language models than any technical paper, not because it was dismissive but because it was precise. A JPEG is a lossy compression format: it shrinks an image by discarding information the eye is unlikely to miss, keeping the gist while throwing away the exact bits. When you view a JPEG, you are not seeing the original; you are seeing a reconstruction, an approximation generated from the compressed data. Chiang’s claim is that an LLM does the same thing to the text it was trained on: it compresses the web, lossily, retaining statistical regularities while discarding the addresses of the sources. The analogy explains
hallucination (gaps filled with plausible interpolations that correspond to nothing real), the limits of originality (the