People are pretending as if job replacement happens all at once, and that’s just not how it works.
A new tool that makes a job 15% more efficient will either produce 15% more goods or reduce the required labor by 15%. Some of that labor is absorbed elsewhere, but there was still a 15% reduction that happened.
Slow improvements are undoubtedly a good thing, that means we can create positions as fast as we make them obsolete. Maybe LLMs have reached their peak and we don’t have to worry about it, but it’s not a bad idea to prepare for that possibility that they continue getting better.
People really like shitting on overhyped new technologies, but I don’t think people appreciate just how big of a deal it is that a pretty basic algorithm is able to process natural language at all.
bitfucker@programming.dev 5 months ago
I think translation is where LLM could truly shine the most. Some simpler models are literally searching for the closest meaning in the higher dimensional feature space. Translation isn’t that far off from what those models do.
Skepticpunk@lemmy.world 5 months ago
Yep. They’re language models, after all. Not surprised they’re taking translation jobs.
Karyoplasma@discuss.tchncs.de 5 months ago
I use ChatGPT to romanize song texts from Farsi squiggly lines into something readable. There are some other sites that do that, but they are all terrible and use regex replacement (I assume) and that doesn’t really work for most things since vowels in Farsi (and Arabic too) are diacritics and are often left out entirely, so you get something unreadable. ChatGPT does a fine job, but you have to make multiple, smaller requests instead of a single big one or it starts hallucinating and/or repeat passages it already romanized.
brbposting@sh.itjust.works 5 months ago
Definitely
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