Change My View

40 readers

28 users here now

A place to learn something new, or strengthen your own position. Progress is impossible without a willingness to change.

#Rules

Remain civil and friendly. Personal attacks, excessive snark, or similar will not be tolerated. Downvoting based on disagreement (rather than quality of discourse) may also be bannable.
All posts should contain a view as the title, and should have an explanation of the reasoning in the body.
All top level comments should address the original viewpoint, either challenging it, or seeking clarification.

founded 1 day ago

MODERATORS

PlzGivHugs@sh.itjust.works

Generative AI isn't going anywhere, and will replace a number of jobs. (sh.itjust.works)

submitted 16 hours ago by PlzGivHugs@sh.itjust.works to c/changemyview@sh.itjust.works

5 comments fedilink hide all child comments

Generative AI has a number of uses that are already widespread, and I don't see going anywhere. Things like clipart and stock art, and initial contact customer support. AI automates these jobs, making it far, far cheaper than hiring a human to do the same job. It only takes one higher-end PC to do a job that a human would have had to be paid for. The economic incentive is already there.

Furthermore, Generative AI is a genie thats been let out of the bottle, and I don't see ever being put back in. These models are just files, which have already been replicated and become widespread. Sure, progress may slow as the "We're making a general purpose AI." bubble bursts, but if these tools work, they'll continue to be developed, and people will continue to get better at manipulating or augmenting them. I don't see any reason that would stop generative AI from continuing to exist from this point forward.

Generative AI isn't going anywhere, and will replace a number of jobs.

Change my view.

you are viewing a single comment's thread
view the rest of the comments

[–] mindbleach@sh.itjust.works 2 points 4 hours ago

Deep neural networks didn't work until quite recently. The theory was there. Single-layer models existed, but were limited to toy applications like single-character OCR. Now there's a whole ecosystem to go from 'what's Python?' to a working prototype within the week. The durable product of this trillion-dollar bubble will be a mountain of whitepapers for how to efficiently design and train models of bewildering complexity.

If the big boys stop releasing local versions, they will cease to matter. They've already created the tools for interested randos to continue development, after the bubble bursts. If they'd like to become irrelevant while they still have funding then that's their prerogative. Qwen Image 2 might never come out, at this rate, but we already know it's a fraction the size of prior models, and outperforms all of them... so there's no point pursuing big-iron mainframe models, once the community has to roll their own.

Pessimistic studies are mostly overblown. 'Doctors using detector get worse at eyeballing things,' no mention of accuracy whilst using that detector. 'Expert programmers slowed down by virtual amateur,' yeah I'll bet, like with a real amateur. 'Artist unimpressed by automated version of thing he's good at,' okay seriously - why do we keep asking professionals about these tools? They already learned things the hard way, at the highest level humans can reach. If they were getting shown-up, there'd be nothing to discuss.

I'm seeing videos where 'and then I vibe-coded the mechanical integration' is mumbled like a punchline. If you truly understand what you want then existing models can probably just do that. It turns doing things the normal way into a fallback. Like whining that you have to do the dishes by hand, when the dishwasher breaks.

The gaming industry has been a hellscape for decades. (Same with buying gizmos that spy on you.) This hype cycle obviously has not helped, but shit's been fucked since before that. If civilization on the whole is turbo-fucked then it's not primarily attributable to spicy autocomplete.