4 ms·
There's some comedy in this article having all the hallmarks of LLM writing.
by chromacity 7mo ago
There's some comedy in this article having all the hallmarks of LLM writing.
- justonceokay 7mo agoYeah a typo in the subtitle does not especially inspire confidence
- deleted 7mo ago[deleted]
- niccl 7mo agoyou've got me. What's the typo?
- justonceokay 7mo agoIt seems to me there is a word or two missing between “rich” and “slowly”. If I read the whole thing aloud I cannot parse it into a sentence. Or the word “rich” could be removed. That would be clunky but at least grammatically sensible. “Make data get smoothed out” is a very strange way of saying “smooths out data”
- quantified 7mo agoIt might be weird if you haven't read a lot of English. It's actually quite normal to say that process X is a way to make effect Y happen. "Makes your mout water" is more effective than "waters your mouth". "Makes your breath fresh and tolerable" is better than "freshens and tolerablerizes your breath". Etc. Actually, what you are describing is what happens when LLM-generated prose cycles and then trains humans to use equally dull thinking.
- justonceokay 7mo agoI have read a lot of English. That’s why it’s weird
- atmavatar 7mo agoI read the subtitle as > The weird, rare, surprising patterns [that make data rich] slowly get smoothed out when an AI model trains on outputs from a previous model. i.e., the patterns are responsible for making data rich, and they are slowly lost as each new generation model trains on the prior generation's output. Or, if you'd prefer an analogy, we're using a copy machine to output new documents by taking the last copy spit out by the machine, adding some marks to it, and running it through the copier again. Over time, details present in much older copies blur and fade away in Nth generation copies.