it's getting to the point where I notice people say it a lot, especially IRL now for whatever reason recently.

And for clarity I'm not in research or anything, so these people just mean 'LLM/image gen', not utilities like OCR or (usually not) transcription.

Some have argued it's just more efficient (which I can kind of get), while others think you're actively hindering your intelligence somehow.

On the first point:

I've tried it occasionally to see how it compares to my own skill, and while it produces a functional result, it's always very derivative work to the point where you can find things with the exact same names of other 'public' (but not libre) works, and often isn't the ideal solution to what it targets. So I can see how you can get things out of it, but it never felt really that profound to me.

But for the second... isn't this supposed to be the tool for people to do things they aren't experienced in? If anything, you probably need to be able to understand how to write pertaining to the task so the token probabilities are biased toward writing from that area.

And even then, if all you end up doing is prompting AI, then wouldn't you ultimately serve no purpose outside of being glorified QA?

I guess I'm trying to figure out what exactly non-users would be 'falling behind' in that affects them more than those who use AI?

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[–] 5 points 2 days ago* (last edited 2 days ago)

Why try to argue against the vocabulary on this one?

Of course it’s artificial intelligence.

We’ve used “artificial intelligence” to mean everything from bots in games to Deep Blue, to protein folding and ML predictions, and those are a whole hell of a lot more specialized than llms.

Modern llms pass the Turing Test for a LOT of people.

Are there lots of problems with it as it is now? Absolutely yes. Environmental, ethical, economic, and on and on and on. All this on top of the fact that it quite bad at many many tasks. But if it’s not artificial intelligence, you’re just moving the goal posts.

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