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YawningNostalgia@thelemmy.club ⁨3⁩ ⁨days⁩ ago

I just don’t get it. I can’t imagine why I would ever want to use one unless I was working for a big corporation and had to collate a bunch of data. It just doesn’t compute to me. Like why would you not want to think through your problems yourself? How could another human being be so different from me? It’s not like someone liking golf when I like soccer, because I can still relate to them on some level.

It reminds me of a study they did on domesticated dogs and wolves and I’m not an animal behavior expert but it’s interesting and stuck with me. When they were faced with a problem with human handlers present the dogs tried to figure it out for a brief amount of time and then gave up and started yelping to the humans, whereas the wolves kept trying to do it themselves. I feel like we have a dog/wolf scenario between the AI-dependent and the resistant/independent.

TL;DR get off the train girl! It’s a grid system!!

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Buddahriffic@lemmy.world ⁨2⁩ ⁨days⁩ ago
Even if you need to collate a bunch of data, don’t use an LLM for that, use a script, spreadsheet, matlab, or a compiled program that does real data analysis. Hell, even training a different NN on it would give more reliable results more efficiently.

LLMs are best when the stakes are low or for tasks where even if they give the worst possible response, it won’t affect anything.

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starelfsc2@sh.itjust.works ⁨2⁩ ⁨days⁩ ago
Adding on to what the other person said, the reason is because we are evolutionarily trained to avoid effort because it uses less energy, same reason people will watch a 30 second youtube short over reading a book.

Alongside that, there are some cases where I’ll be working on something and there’s a task I’m actually working on, and some small aside that I can’t be bothered with at that moment. For instance, I’m processing some data from a file and using it to display differing graphics depending on what’s in the file, but I don’t remember how to open it and read the data. If the llm can give me the code that does that, then I can stay focused on the graphics-creation code (and I most likely revisit the file opening later)

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mirshafie@europe.pub ⁨3⁩ ⁨days⁩ ago
Because there are problems out there that you’re not going to feasibly solve on your own.

Think of it this way: do you ever look up anything on the internet? If yes - why did you do that, when you could just find out the information yourself by working from first principles? Likely not only because it’s orders of magnitude faster, but because doing it yourself would probably result in significantly lower quality thank just looking it up on Wikipedia.

LLMs are like search engines on steroids. They really can help you explore problems that have already been described in the literature, so to speak.

But of course that changes how our brains need to be wired. And it’s not necessarily bad. When I was growing up, the adults were really worried that the use of search engines would degrade the ability of children to look things up in the library. And they’re right - I would indeed have a more difficult time going to the library, finding the right shelf, finding the right book, looking through the index, and scanning the pages for the information I was looking for - because that’s a skill that I haven’t practiced because I could just do a web search for the better part of my life. Doing a web search is a different skill.

That’s not to say that this is all fine and just a technological development like any other. I think we do need to be careful about how we use LLMs and when, especially in order to think through problems ourselves. I think that we were already over-reliant on the Internet before LLMs came on the scene, and it will likely get worse now. But the reason that they’re dangerous is because they are in fact really useful tools too.

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- Jako302@feddit.org ⁨2⁩ ⁨days⁩ ago
  That would be a good argument if not for the simple fact that ai straight up lies to you.
  
  And its not even a question of using a “good” or “bad” model. We have observed a mathematical constant that shows no matter how large of a model you use, you can’t get below a certain percent of hallucinations.
  
  Its far less common because models got bigger (and more Ressource intensive), but it still happens too often.
  
  Or to phrase it in a different way, would you use a calculator if you knew every 30th answer it gives is wrong?
  
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  - mirshafie@europe.pub ⁨2⁩ ⁨days⁩ ago
    I see this argument often on Lemmy and I honestly have some trouble empathizing with it. Why should we demand that LLMs would be perfect, when nothing in life is perfect?
    
    Books and scientific reports can, and often have, falsehoods printed in them. All sensors have error margins. A human expert can be convinced that they’re right and still be wrong.
    
    What I’m trying to say is we shouldn’t trust anything blindly. I absolutely agree that it’s frustrating to see so many people trust LLMs blindly, but used as a tool among others I think they’re most likely going to be very effective in a wide variety of fields.
    
    LLMs are out there solving math problems, helping with biology research and fixing latent bugs in widely used open source software. Yes of course LLMs make mistakes, but you can verify their work.
    
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