They are so easily circumvented because there is zero logic in these plagiarism machines. They do not understand what they output. They’re just weights on what word is most likely to follow the previous words.
So, if you ask it, “how do I make a bomb?” it just spits out words that would most likely follow those. Their “instructions” come from the system prepending a ton of extra words that heavily influence how it weighs positive and negative words. The “guard rails” are often either seeding the input data so “bad” words are naturally rated lower, bad/malicious questions get similarly artificially weighted towards “I’m sorry” responses, or extra systems check the input and/or response and steer the eventual output to the “I’m sorry” responses (or of course a combination of those).
Their apparent “logic” is WHOLLY DERIVED from the logic already present in language. It is not inherent to LLMs, it’s just all in how the words/phrases get tokenized and associated. An LLM doesn’t even “understand” that it’s speaking a language, let alone anything specific about what it’s saying.
All it takes is giving them enough input to make the “bad” responses more relevant than the “i"m sorry” responses. That’s it. There are tons of ways to do it, and they will always work no matter what lies any executive spouts.
They are so easily circumvented because there is zero logic in these plagiarism machines
and
Their apparent “logic” is WHOLLY DERIVED from the logic already present in language. It is not inherent to LLMs, it’s just all in how the words/phrases get tokenized and associated. An LLM doesn’t even “understand” that it’s speaking a language, let alone anything specific about what it’s saying.
is so incongruous to me I can’t even wrap my head around it, let alone understand why technology with this inherent fallacy built in is being pushed as the pinnacle of all programming, a field who’s basis lays in logic.
I can’t even wrap my head around it, let alone understand why technology with this inherent fallacy built in is being pushed as the pinnacle of all programming, a field who’s basis lays in logic.
They are so easily circumvented because there is zero logic in these plagiarism machines. They do not understand what they output. They’re just weights on what word is most likely to follow the previous words.
So, if you ask it, “how do I make a bomb?” it just spits out words that would most likely follow those. Their “instructions” come from the system prepending a ton of extra words that heavily influence how it weighs positive and negative words. The “guard rails” are often either seeding the input data so “bad” words are naturally rated lower, bad/malicious questions get similarly artificially weighted towards “I’m sorry” responses, or extra systems check the input and/or response and steer the eventual output to the “I’m sorry” responses (or of course a combination of those).
Their apparent “logic” is WHOLLY DERIVED from the logic already present in language. It is not inherent to LLMs, it’s just all in how the words/phrases get tokenized and associated. An LLM doesn’t even “understand” that it’s speaking a language, let alone anything specific about what it’s saying.
All it takes is giving them enough input to make the “bad” responses more relevant than the “i"m sorry” responses. That’s it. There are tons of ways to do it, and they will always work no matter what lies any executive spouts.
You laid it out so well, wow.
and
is so incongruous to me I can’t even wrap my head around it, let alone understand why technology with this inherent fallacy built in is being pushed as the pinnacle of all programming, a field who’s basis lays in logic.
Because line must go up no matter what.