Comment by intended

I think this is the entry point needed to get peoples attention and explain: LLMs aren’t people, and emergent properties are being over extended.

If LLMs are showing “better” performance when there are tokens that humans read as emotionally salient -

Then the underlying text it’s trained on shows humans give better answers when emotionally salient context is provided.

LLMs predict words. Any semantic validity is a side effect of enough training data reinforcing the close correlation of those tokens.

That is why proof of concept LLM tools are mind blowing and production tools are semantic time bombs.