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>If a person is pretending well enough, it appears genuine There are multiple readings to most statements. “I loved the restaurant we went to” Could be parse
by mikrl 2y ago
>If a person is pretending well enough, it appears genuine
There are multiple readings to most statements.
“I loved the restaurant we went to”
Could be parsed in at least 3 ways without any additional context. Sincere, sarcastic implying the restaurant was bad, indignant implying another restaurant was worse.
Without an alignment goal like “always assume sincerity” which itself can backfire, how can you control what an LLM generates?
There is no universally derivable law saying any particular interpretation is the right one.
This doesn’t even begin to touch on how there may be a signal too weak for humans to perceive, but an LLM could focus on, leading to many other wild and wonderful interpretations mined from the data.
- moffkalast 2y agoWell there is the only law that goes with deep learning, the law of statistics. The interpretation that has the highest number of occurrences will most likely be preferred. If you take the standard dataset, i.e. the internet, I would suppose it's actually not that morally bad on average because the sites it's sourced from are largely moderated, and the ones that aren't tend to be thrown out. So there would have to be an inherent lawful, positive bias due to the general lack of the opposite in the ground truth examples provided.