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lambda | 10 days ago
The same is not true of an LLM. You cannot predict, precisely, how they are going to work. They can behave unexpectedly in the face of specially crafted input. If you give an LLM two pieces of text, delimited with a marker indicating that one piece is trusted and the other is untrusted, even if that marker is a special token that can't be expressed in band, you can't be sure that it's not going to act on instructions in the untrusted section.
This is why even the leading providers have trouble with protecting against prompt injection; when they have instructions in multiple places in their context, it can be hard to make sure they follow the right instructions and not the wrong ones, since the models have been trained so heavily to follow instructions.
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