• pigup@lemmy.world
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    25 days ago

    Call deepseek enjoy llm hallucinations and it jumping to conclusions and misconfiguring everything because it never bothers to check whether it’s just inventing bullshit, and there when it tries to solve the problem, it comes up with in correct theories and then further fucks everything up.

    Call GLM instead.

    • criticon@lemmy.ca
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      25 days ago

      Same as claude?

      We have to use Claude at my job, as in they check out token usage

      The other day I had to build a prototype using some development boards and decided to leave everything to claude. I gave it the datasets and told it what I needed to do and it created completely incorrect schematics, like hallucinating a LED on the board, adding a serial interface to some pins that are not related, confusing tx and rx on another set of pins, saying that it needed 12V when it is 3-5V, it even added some capacitors to some pins that weren’t even in use. I had to go thru maybe 10 iterations and burned a bunch of tokens, basically I had to do it manually

      The only thing it surprises me every time is the code, that usually runs with no errors on the first try. It’s just not very clean but it is ok for my needs

      • Ekky@sopuli.xyz
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        23 hours ago

        Back in my day I just chugged a few beers and went to work. Couldn’t remember the evening before, and got a decent-enough result after removing the worst errors.

    • halcyoncmdr@piefed.social
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      25 days ago

      You’re describing literally every LLM at some point. It’s why they can’t be trusted, and why the user needs to already know how to accomplish what they’re asking. The hallucination machine needs to only be used to try and make it faster, not relied on to blindly make decisions and changes without oversight.