[Off-topic] I got curious about the comment chain, checked it in a private window, and… well, I don’t remember when I blocked that poster, but by their profile I’m glad I did it — it’s a waste of time to chat with assumptive fools, you spend more time brushing off their assumptions (only so they vomit yet another assumption, and another, and another…) than actually saying what you want, or reading something meaningful. You probably won’t miss them.
[On-topic] I got the same experience as in your second link, but with translation instead of programming — using machine translation to give me ideas on how to translate specially problematic excerpts; idiomatic expressions, tricky grammatical distinctions lacking in the target language, stuff like this. Just ideas, mind you; I wouldn’t copy the machine translation, I’d pick one or two words from it and come up with my own, so it was still human-made.
Then I noticed the “problematic excerpts” were becoming more and more common.
Some might argue “than mite as well not uze calculatorz lol lmao u’ll get rusty math”… you know what, it’s actually a fair comparison, and one of the reasons I do think people should do maths by hand sometimes. Tools are supposed to allow you to do more, not to cripple you until you’re doing less.
Thank you, but I do not consider LLM equal to a calculator.
The latter doesn’t normally have any feedback, and has a constant solid system, where you may always expect the result won’t change in time all of a sudden, and predict it. There’s a circuit and read-only memory of its flashed program looped.
None of this is true in the context of the former - LLM. Here, an output may change each iterration due to the nature of LLM algorithms as “self-training”. The constant fear of the algorithm “plausible” mistakes, and it confidence in proving those are correct… is… unbearable…
We’re comparing both tools in different aspects. What you’re talking about is predictability (and accuracy); in these I agree a calculator is way better.
My point was about our reliance on tools, at the expense of deteriorating our own skills. Use calculators exclusively for long enough, and you’ll have a hard time with simple maths; rely too much on a kitchen scale, and you’ll lose the grasp on the right amounts of ingredients (or how to measure wheat flour without one); get used to an electric screwdriver and you’ll never know if you screwed it too little or too much. It may or may not matter, depending on someone’s profession, but I think some skills are worth kept alive and “un-rusty”, and I feel like the way I was using large models was rusting my skills.
[Off-topic] I got curious about the comment chain, checked it in a private window, and… well, I don’t remember when I blocked that poster, but by their profile I’m glad I did it — it’s a waste of time to chat with assumptive fools, you spend more time brushing off their assumptions (only so they vomit yet another assumption, and another, and another…) than actually saying what you want, or reading something meaningful. You probably won’t miss them.
[On-topic] I got the same experience as in your second link, but with translation instead of programming — using machine translation to give me ideas on how to translate specially problematic excerpts; idiomatic expressions, tricky grammatical distinctions lacking in the target language, stuff like this. Just ideas, mind you; I wouldn’t copy the machine translation, I’d pick one or two words from it and come up with my own, so it was still human-made.
Then I noticed the “problematic excerpts” were becoming more and more common.
Some might argue “than mite as well not uze calculatorz lol lmao u’ll get rusty math”… you know what, it’s actually a fair comparison, and one of the reasons I do think people should do maths by hand sometimes. Tools are supposed to allow you to do more, not to cripple you until you’re doing less.
Thank you, but I do not consider LLM equal to a calculator.
The latter doesn’t normally have any feedback, and has a constant solid system, where you may always expect the result won’t change in time all of a sudden, and predict it. There’s a circuit and read-only memory of its flashed program looped.
None of this is true in the context of the former - LLM. Here, an output may change each iterration due to the nature of LLM algorithms as “self-training”. The constant fear of the algorithm “plausible” mistakes, and it confidence in proving those are correct… is… unbearable…
We’re comparing both tools in different aspects. What you’re talking about is predictability (and accuracy); in these I agree a calculator is way better.
My point was about our reliance on tools, at the expense of deteriorating our own skills. Use calculators exclusively for long enough, and you’ll have a hard time with simple maths; rely too much on a kitchen scale, and you’ll lose the grasp on the right amounts of ingredients (or how to measure wheat flour without one); get used to an electric screwdriver and you’ll never know if you screwed it too little or too much. It may or may not matter, depending on someone’s profession, but I think some skills are worth kept alive and “un-rusty”, and I feel like the way I was using large models was rusting my skills.