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ChatGPT Is a Blurry JPEG of the Web
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ChatGPT Is a Blurry JPEG of the Web

OpenAl’s chatbot offers paraphrases, whereas Google offers quotes. Which do we prefer?



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Today’s large language models operate by scouring massive data inputs, much of it from the web. The sheer magnitude of that training material requires researchers to employ compression algorithms that contain inherent flaws. The results are entertaining and often useful, but a far cry from human creative prose. Author Ted Chiang compares OpenAI’s ChatGPT to a “blurry JPEG” of the internet, rather than a reliable responder. 

Summary

Large language models and Xerox photocopiers share error issues, when compressing information.

File compression requires encoding, or converting, text into a more compact version – and then decoding it, or reversing the process. If the original and decoded files are identical, the compression is “lossless.” If the restored material is missing information, it is called “lossy.” Typically, lossless compression is used for text storage and computer programs, while lossy compression is used to save images and multimedia materials. Lossy compression isn’t usually noticed unless it causes “compression artifacts” such as image fuzziness or subpar audio.

Photocopiers sometimes eliminate important details, as long as the images appear similar enough to one another. In the same way, language models such as OpenAI’s ChatGPT provides an approximation of grammatical text, based on the immense volumes of material it retains and assembles to answer questions. By employing statistical regularities, GPT’s responses are generally acceptable. But because its answers are based on lossy algorithms, they represent a “blurry JPEG of all text on the...

About the Author

Ted Chiang is an award-winning author of science fiction. In 2016, the title story from his first collection, Stories of Your Life and Others, was adapted into the film Arrival. He lives in Bellevue, Washington, where he works as a freelance technical writer.


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