Curated Resource ( ? )

Journalism is Lossy Compression. In The New Yorker, Ted Chiang ...

Journalism is Lossy Compression. In The New Yorker, Ted Chiang ...

my notes ( ? )

Jeff Jarvis is not a fan of Ted Chiang's piece on CgatGPT, although he does admit TC (one of my favourite authors) "makes a clever comparison between lossy compression... and large-language models, which learn from and spit back but do not record the entire web". Indeed, he takes the metaphor further: "what is journalism itself but lossy compression of the world? ... what is a library or a museum or a curriculum but lossy compression — that which fits? What is culture but lossy compression of creativity?"

He reaches for another comparison: the authority of print. " It took time for print to earn its reputation of uniformity, accuracy, and quality and for new institutions — editing and publishing — to imbue the form with authority... it was not until a century and a half after Gutenberg that major innovation occurred with print... the essay... novel... newspaper... It may be too early to use [LLMs] in certain circumstances (e.g., search) but it is also too early to dismiss them."

Read the Full Post

The above notes were curated from the full post medium.com/whither-news/journalism-is-lossy-compression-86380f0bdb50.

Related reading

More Stuff I Like

More Stuff tagged ai , chatgpt , ted chiang , llm , jeff jarvis

See also: Digital Transformation , Innovation Strategy , Science&Technology , Large language models

Cookies disclaimer

MyHub.ai saves very few cookies onto your device: we need some to monitor site traffic using Google Analytics, while another protects you from a cross-site request forgeries. Nevertheless, you can disable the usage of cookies by changing the settings of your browser. By browsing our website without changing the browser settings, you grant us permission to store that information on your device. More details in our Privacy Policy.