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by strix_varius
875 days ago
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The spirit of the analogy holds, as there are plenty of clear alternatives that map verbatim: - drinking glass that is 99% hole-free - car that doesn't explode 99% of the time - bag of candy where 99% of the pieces are not poisonous In all of these cases, it's more optimal to start from scratch and build something that you know is 100% reliable than to start with whatever already exists and try to fix it after-the-fact. Personally, I use AI to assist development, especially in unfamiliar stacks, but in the form of a discussion rather than code-vomit. It's primarily synthesizing documentation into more-specific whole answers and providing options and suggestions. |
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> - drinking glass that is 99% hole-free
This describes my travel flask when the screw cap is on and the slot in the cap is open; most of my drinking glasses have (and need) a much bigger hole-to-surface ratio to get the fluid in and for me to drink from.
More relevantly for the output of an AI: in cases where testing is easy, a system which has a 99% chance of a producing a saleable drinking glass and just discards the other 1% to recycling isn't unreasonable… provided you can be sufficiently confident about the test.
For AI, the quality of the automated tests of the output is a very solid "it depends on what you're doing".