I'm currently taking a beginners python course and one of the chapter project examples breaks down basic sentence structure based on parts like nouns, prepositions, etc. The idea is to make several dictionaries based on these sentence parts with different words associated with them and then randomly pick words from them in the right order to make a cohesive (although not always intelligible) sentence. I figure most LLMs use a much bigger version of that with even more defined dictionaries to better encapsulate certain responses based on the topic.

There's nothing in that kind of program structure that would even come close to implying it's alive. LLMs are just a fancy version of Mad Libs.

it really is isolating. yet another thing to punish the sloppers for.

those friends don't have parents anymore.

I envy you dude/dudette... i dont understand how so many people around me is embelezed by it.. someone even compared it to the introduction of the first personal computers. I feel like I'm surrounded by idiots....

I feel like if more people tried AI in early days, we wouldn't have all these clowns selling us shit that's not real.

Speaks a lot about quality and necessity of research when AI already has all the answers.

Also I wonder if these people can be reasonably called scholars if they don't have the actual knowledge.

Like, I know this doesn't sit well with many Lemmy folks, but LLMs do have reasonable use in science. For example, they're amazing at contextual search, they can find what I'm looking for even if it's buried into walls of text of an obscure 2003 article as a sidenote. Combined with traditional search, this allows me as a junior scientist to better check what's already been discovered, and identify real gaps of knowledge, not what I personally didn't find.

They can also be useful when brainstorming concepts from the fields I had little experience with. Finding proper literature, breaking down jargon, and otherwise streamlining the study process. This allows to spend less time researching the widely known things on the subject, and dedicate more time to actual science, and also helps immensely with interdisciplinary research.

But that's just that - finding well-known, long discovered things that you could miss. Any meaningful steps beyond it require strong grasp on the subject, and this only comes with processing everything through the actual brain. Miss that - and you're just a machine parrot.