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?
We’ve already seen models degrading from being trained on LLM-generated data. The big companies were overly eager to follow the EU directive to watermark output. I think that’s solely so that they can filter it out when scraping for future training data. They’re running out of good training data to steal. I don’t imagine they’ll be paying a fair wage to anyone generating novel good data.
Entry jobs disappearing is uncharted territory. My latest hire had three years work experience in a very niche field. I’d have a hard time justifying anyone more jr than that for a startup burning investor capital.