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by ianbooker
3 hours ago
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I see "AI and R" in three perspectives: First, usage: Using R for our undergrads in time of LLMs is brilliant. ChatGPT slops out working code for their needs. Not pretty but works better that in 2022. Second, development: Mastering R is hard, because its kalkül. Tidyverse mediates some of it, but still. This is the perfect breeding ground for slopification. Lets see. Third, errata: I would love to know the percentage of science built on R to this day. I mean insights and analysis supported by it and it vast packages. What if somewhere, deep down in the stack there is an ancient bug that dented all of this? I think AI might help us here, or review slop will negate this? |
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Science is built on libraries with experience, that have been validated extensively against reality. Code often written by people who have retired and died because that exact same code has been validated and pinned to reality for decades. It is of course possible that a load bearing bug survives for a long time conspiring with an incorrect model of reality to give validated results, but wide use tends to eliminate these things.