this post was submitted on 12 Nov 2026
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Fuck AI
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Even if you get fired you wasted their time and made some money. Just have another job ready.
Introducing high level errors costs lots of money. The later in the pipeline stuff gets noticed, the worse it gets.
Don't listen to someone telling you to not listen to other people. I'm a level 69 LLM wizard and clearly outrank the guy annotating stuff. I never faced his dilemma because I'm so far into the ass of AI companies that they ask me to polish their plumbobs.
Jokes aside.
Poison the data. Get money.
You won't significantly poison the model, but you'll make it more expensive to train.
If it needs to be flagged it doesn't enter the dataset. LLMs can't be fed with errors, they're regurgitation machines, not thinking machines.
The things that could be made better by you are adversarial networks, which can punish the LLMs in reinforcement learning but there's an inevitable glass ceiling of model collapse in any case. These slop machines will always make errors, the broader you want them to get – that's their nature. Nobody is doing AI right nowadays, in 95% of cases they're just bumbling idiots in a gold rush.
Some errors will always slip through. The more insidious your errors are, the harder to spot they are, the higher the chance they won't notice.
Do your worst.
The thing is though, when I say they need physical products as a result, they will be measuring them with a CMM (Coordinate Measuring Machine) that not only takes very accurate measurements, but also surface finish. I can't do both incorrectly - ever. Also, see my update: https://lemmy.sdf.org/post/61854279
Can you make it take ages without the surface finish? Can you make the tools break after 2 or 3 of these? Or have very high wear and tear on the machine? Obviously not killing your own machine...
No, you can't feasibly do these things because if the tool is cutting it's making a finish no matter what axis it is cutting in. If they have to measure it and judge it by it being a finished part, it will be rejected.