this post was submitted on 22 Oct 2024
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It doesn't understand anything. It predicts a word based on previous words - this is why I called it syntax. If you imagine a huge and vastly complicated series of rules about how likely one word is to follow up to, say, 1000 others... That's an LLM.
It can predict that the word "scales" is unlikely to appear near "books". Do you understand what I mean now? Sorry, neural networks can't understand things. Can you make predictions based on what senses you received now?
Well given that an LLM produced the nonsense riddle above, obviously it cannot predict that. It can predict the structure of a riddle perfectly well, it can even get the rhyming right! But the extra layer of meaning involved in a riddle is beyond what LLMs are able to do at the moment. At least, all of them that I've seen - they all seem to fall flat with this level of abstraction.
It shows that one failed that time. I just asked ChatGPT. I can't be sure how original the riddle is. It's possible it copied the description of the double meaning from somewhere. But it looks like it understood it, and based on how LLMs work, there's no reason it shouldn't.
Make an original riddle. Explain the double meaning behind it.
Riddle: I hold many keys, yet open no doors. I sing without voice, yet keep perfect scores. Though I’m struck, I never feel pain; What am I, in sun or rain?
Answer: A piano.
Explanation of Double Meaning:
Each line has a figurative layer connected to musical terms, creating a double meaning based on the dual use of “keys,” “scores,” and “struck.”