Are there enough open source aero engineering projects to give the current ai approaches a remotely plausible amount of training data?
replyImagine is a good word to use. Before offering a solution, understand the problem first - is "debugging speed" a problem that needs solving, in this case?
replyMuch more likely is that it would hallucinate a plausible sounding but incorrect answer and send intermediate and junior engineers on a wild goose chase
replyif an LLM is capable enough to be used this way it would be used to generate scenarios for the people who would otherwise have to be the ones to generate them. those people would then evaluate the scnearios. those people would then be in a position to decide if the LLM saves them time.
reply> a plausible sounding but incorrect answer
replyThat is an incorrect but plausible hypothesis. Do you really think that people can't make such mistakes?
If you want to say that people have understanding, then define understanding in an operationalizable way first.
It doesn't mean that I would recommend a general-purpose AI model without additional training to do a fault analysis.
>That is an incorrect but plausible hypothesis.
>Do you really think that people can't make such mistakes?
replyWhere did I say that? You just pulled that out of nowhere and then refuted it - strawman https://en.wikipedia.org/wiki/Straw_man
> it would hallucinate a plausible sounding but incorrect answer
reply"Hallucinate" as used in this context does not apply to humans and presupposes a qualitative difference.
I was saying that an AI would more likely hallucinate an incorrect answer than correctly diagnose the root cause failure. At no time was I comparing an AI to a human, thats the bit you made up.
replyThe knee-jerk reaction to pointing out any failure modes of AI with, "but meatbags bad!" is a tiring strawman to deal with. It immediately turns the discussion into something else.
replyHumans crash millions of cars a year, and you're worried about one dog driver running over four measly people?
replySo, your message is "Unspecified AI models with or without additional training aren't ready to do aerospace fault analysis and they can lead experienced engineers astray." OK, it might or mightn't be true depending on the free parameters in your statement.
replyI used the word "likely" meaning there is a chance, your re-phrasing of what I said into a certainty ... and then refuting that certainty, is another textbook strawman argument, you made the same logical fallacy again.
replyAlso I said "intermediate and junior" engineers - meaning INexperienced engineers, not experienced ones, so you quoted me wrong in that part too.