Ian Carroll's selling his Telegram channel

This was my response to him.
Something tells me, he likely won't take me up on my offer?
😂🤣😂

NORWAY FIRST COUNTRY TO ARREST EPSTEIN ASSOCIATE. Who's next? Can you imagine the rats panic and fear?

Can you imagine why these these men are fighting so hard to continue to perform in front of children? Imagine one of these creatures ''performing'' for your kids. Enough of this nonsense

There once was a girl from Korea
Whose dad wanted no one to see her
Until she succeeds
The throne that he schemes
'Now everyone has got to meet her.

Her dad is such a distemperer
It's tough for a kid being emperor
You don't get no childhood
You're stuck in a wildwood
She's lucky he doesn't dismember her

Kim Jue Ae from Ryongsong
Must be tired of hearing the same song
From Kangdong to Wonsan
It's stick to the plan
& no one admits they could be wrong

{does it really take extra pages of text to process niceties in queries like please thanks sorry etc}

Not really "extra pages," but every word counts toward the computational cost. AI models process text in chunks called tokens (roughly 4 characters or 0.75 words each), and you are billed or limited based on the total number of tokens used.
How Politeness Affects the Model:
Computational Cost: A simple "What is the weather?" is about 5 tokens. Adding "Hi! Could you please tell me the weather today, thank you!" jumps to roughly 20–25 tokens. At a massive scale (millions of users), these extra "niceties" consume significant GPU power and energy.
Response Length: Polite prompts often nudge the AI to mirror that tone, leading to longer, more "fluff-filled" responses rather than direct answers.
Accuracy: Some studies suggest that while being rude can hurt performance, being overly polite can actually decrease accuracy (by up to 9% in some tests) because the extra words add "noise" or ambiguity to your actual request.
Social Mirroring: LLMs are trained on human data where polite questions often get more detailed answers (like on StackOverflow), so being nice can sometimes trigger a "helpful assistant" persona that provides more thorough context.
In short: while it doesn't take "pages" to process a single "please," it does force the AI to perform a fresh computational pass on those specific tokens, which adds up to real infrastructure costs.

Abbreviations & typos generally have a lower impact on processing & cost than "niceties," but uniquely degrade quality of response.

1. Direct Cost Comparison
Niceties (Please/Thanks) add predictable, clean tokens to a sequence. Each has a small fixed cost, easy for a model to process but directly increases total token count.
Errors (Typos/Abbreviations) often result in sub-word tokenization, where a single misspelled word is broken into multiple smaller, nonsensical chunks.
Processing forces a model to use extra "heads" or layers to "reassemble" intended meaning from fragments.
Cost: A typo may increase token count by 1–2 units, but still "cheaper" than a sentence of politeness.

3. Structural "Noise"
Common abbreviations (e.g., IMDb vs imsb) are usually understood, but obscure ones shift position in embedding space, sending a model down less accurate reasoning paths.
Missing or incorrect punctuation (like a missing question mark) has negligible computational cost but can lead to misinterpretation of intent.