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?
An LLM can only be derivative. It can come up with “unique” patterns, but only based off it’s training data. For something like your use case, it would have very little data to work on given that you claim the documentation is poor. Your best case would be to use a high reasoning model and feed the documentation into it’s context before asking anything - but it will only give you answers based on that input. If the documentation is wrong or outdated, you’ll get answers based on wrong and outdated data.
As far as “who could get left behind?”, I feel that is more people who’s job can be impacted by LLMs - programming is a big one, and the reason is largely in my first paragraph. The amount of “training data” on the internet for coding is absolutely massive and incredibly well organized because programmers are nothing if not incredibly pedantic. The result is that the task of writing code can be largely offloaded and with recent models, the quality of the code being produced is extremely good, especially in tasks that are well solved/documented.