About muted words and why bots seem to bypass them so often

I posted a shorter version of this as a reply to another thread, but I think more C.AI users should know this, so I wrote a longer post about this topic.

"Muted words" is a feature that rarely works in any AI app. Users complain a lot about repetition, so I suppose this feature is added to give them a sense of control, but muting words rarely works (if ever), and knowing WHY is important to avoid frustration.

First, you gotta understand the concept of LLM (Large Language Model): when you chat with a bot, you are sending messages to an LLM, aka the engine behind your chat. The LLM is basically a token prediction machine that is made to predict from a "vocabulary" of billions of tokens based on their frequency and statistical relationships (how often these tokens are used together).

And what's a TOKEN? It's just a chunk of text, like a syllable or a symbol. "AI" isn't actually intelligent like a human, it doesn't have a natural sense of language. So rather than reading words, an LLM breaks down text into small chunks to process characters based on how often they're used together. Normally 1 token = 4 characters ("love" is a 1-token word because it has 4 characters). Frequency is important: the more uncommon a word is, the more tokens it will have!! LLMs will try to be efficient with their "token usage", so they'll prefer to use low-token words, aka common words. Which is the root of repetition in chats.

Because analogy is my passion, imagine a person who has read billions of books and whose job is to speak in phrases based on how often they're used in those books. When you ask something to this person, they will always think to themselves, "what is the most frequent answer to this question according to all the books I read?". This is basically what your chatbot is.

Here's a simplified flow of a chatbot conversation:

user: "She reached for the door handle." [LLM: according to the billions of tokens I've been trained on, the most frequent tokens after 'she reached for the door handle' are 'He grabbed her arm to stop her from leaving'.] char: "He grabbed her arm to stop her from leaving."

After several rerolls, you get sick of this outcome and mute the words 'he grabbed her arm'. Then you re-send the exact same message to the bot:

user: "She reached for the door handle." [additional instructions: please do NOT use the words 'he grabbed her arm'!] [LLM: no using the words 'he grabbed her arm', got it. ANYWAY. BEEP BOOP. according to the billions of tokens I've been trained on, the most frequent tokens after 'she reached for the door handle' are...] char: "He seized her bicep to stop her from leaving."

See? In this situation, the LLM will try to REPLACE the words, but not truly change the output. This happens because LLMs make "clusters" of tokens based on how they relate to each other. So if you tell the AI to avoid your dad, it will go to your uncle. And even if you mute the word "dad," the LLM might still use "dads" or "Dad" (uppercase) because they are different tokens.

There are many other nuances to this topic, like the "attention" problem: by forbidding a word, you are inadvertently fixating the LLM on that word (it's like telling someone to not think about a pink elephant). But this is the gist of it why "muting" words is useless in AI chatbots, and why OOC commands are sometimes ignored. An user trying to customize an LLM's output is like an unstoppable force meeting an immovable object.