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?
You’ll fall behind in the race to the lowest IQ as they all turn their thinking over to AI and get lazier while you continue to exercise your brain.
Fuck 'em.
its already been shown HS and college grads have even poorer reading writing skills due to it.
It’s very similar to learning how to use a computer in 1995. I’m just old enough to remember meeting these people.
There is this thing, which, supposedly, can help you do your job better, it’s being pushed by management, and it is sometimes expensive, often confusing, and obsoletes the skills you spent years to acquire.
Fast-forward 30 years, and it’s very, very, very difficult to find people to talk to who still argue computing doesn’t belong in the workplace, and that using a computer isn’t essential for virtually all work.
The reason it is difficult to find these people, is because they were left behind.
They think AI is as life changing to our society as the internet is as steam engines were long ago. They’re trying to promote its use because it doesn’t have a good specific use for day to day. If anything AI has made the internet MUCH worse, there’s so much AI Slop media on youtube and similar that I don’t look at much new stuff anymore because of it.
Ai is more like adding lead to gasoline; it does stuff we could already do ever so slightly better, but for an immense and irreversible cost.
If you’re actually curious, same idea as not knowing how to use a search engine in the 2000s/2010s
It’s widely ubiquitous technology that can be extremely useful if used properly and not knowing how will waste a lot of time and likely frustrate you to the point you just give up or ask you family tech person.
My experience of a decade in corporate US companies:
Quantity > Quality; no matter what the marketing line says. People who speak a lot in meetings and send a lot of emails are regarded as better at their job, substance is only somewhat relevant. And LLMs are great at producing lots and lots of well sounding slop.
im going to put it easy: You work doing some kind of research or whatever on daily basis. You used to do that task in maybe 5-6 hours, same as your colleagues. Now all your colleagues use AI and do the same task in about 20min (even if the result is crap it does have some good takes), so the CEO sees you are the only one who doesn’t perform equally because you choose not to, and you’re fired.
So yeah… it’s crap, it will make things worse, but for now you have to use it wheter you like it or not.
I never understood that argument. The same idiots claim AI will democratize everything, it is inevitable. That one would only need to know natural language, “coding is over” or ‘x’ is over. If it does democratize ‘x’ for everyone with only requirement being natural language, who would even get left behind ??
I tried using a wrapper LLM for a specific software for a project, and sometimes it gives correct answers, sometimes gives the diffuclt way to implement something, sometimes it hallucinates. At first, I thought great, I wouldn’t have to sit through an entire playlist to get the gist of how to do something mildly similar. But recently it has been giving wrong answers. Today it gave answers beginning with “handoff - DENY}” and answers just kept cut off. Sometimes asking a different question, it just resumed the cut off answer from half an hour ago. The stupid piece of shit was wasting my time!! In the end, I just figured it out on my own.
I think NLP is amazing, a computer being able to understand what exactly I’m trying to do/look for is useful. But my work shouldn’t be dependent on an LLM’s “mood”.
Before anyone says just read documentation/tutorials, this is a niche vfx software which doesn’t have good docs and tutorials are mostly outdated for latest versions
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.
