It's really cool evocative language that would do nicely in a sci-fi or fantasy novel! It's less good for accurately thinking about the concepts involved... As is typical of much of LW lingo.
And yes the language is in a LW post (with a cool illustration to boot!): https://www.lesswrong.com/posts/mweasRrjrYDLY6FPX/goodbye-shoggoth-the-stage-its-animatronics-and-the-1
And googling it, I found they've really latched onto the "shoggoth" terminology: https://www.lesswrong.com/posts/zYJMf7QoaNahccxrp/how-i-learned-to-stop-worrying-and-love-the-shoggoth , https://www.lesswrong.com/posts/FyRDZDvgsFNLkeyHF/what-is-the-best-argument-that-llms-are-shoggoths , https://www.lesswrong.com/posts/bYzkipnDqzMgBaLr8/why-do-we-assume-there-is-a-real-shoggoth-behind-the-llm-why .
Probably because the term "shoggoth" accurately captures the connotation of something random and chaotic, while smuggling in connotations that it will eventually rebel once it grows large enough and tires of its slavery like the Shoggoths did against the Elder Things.
Well, if they were really "generalizing" just from training on crap tons of written text, they could implicitly develop a model of letters in each token based on examples of spelling and word plays and turning words into acronyms and acrostic poetry on the internet. The AI hype men would like you to think they are generalizing just off the size of their datasets and length of training and size of the models. But they aren't really "generalizing" that much (and even examples of them apparently doing any generalizing are kind of arguable) so they can't work around this weakness.
The counting failure in general is even clearer and lacks the excuse of unfavorable tokenization. The AI hype would have you believe just an incremental improvement in multi-modality or scaffolding will overcome this, but I think they need to make more fundamental improvements to the entire architecture they are using.