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Ford had to hire back former engineers to fix mistakes made by its automated systems (www.theverge.com)
submitted 3 months ago by to c/nottheonion@lemmy.world
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“Mistakenly, we thought that by just introducing artificial intelligence and adjusting the design requirements that we had, that that would produce a high-quality product,” said Charles Poon, VP of vehicle hardware engineering, in a briefing this week with reporters.

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[–] 17 points 3 months ago (2 children)

The major problem is that the work of an LLM has a massive number of hidden 'assumptions' that you need to be aware of. If you don't already have a good working knowledge of the task you wont have an intuition about those assumptions. It's annoying.

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  • [–] 5 points 3 months ago

    Yeah, and for those who don't know, the rationalization output of the LLM is just so pursuasive. It sounds quietly confident and rattles off things that sound like real details.

    People are believing the LLM output over actual human experts and the human experts have to expend non-trivial effort trying to disprove an LLM output before they can get on with the business of doing it right.

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  • [–] 3 points 3 months ago

    Yeah, like cards being the best thing ever on front-end. If I want a basic layout I put "avoid cards" usually because then it'll use them sparingly. But yeah, it's just autocomplete so it's always going to get the lowest common denominator code based on what it decided to look at.

    I'm now looking into finding something faster than GPT/Claude where I can ping pong prompt faster and get what I want. Whatever it writes first is just a first draft anyway.

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