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27 points

you can put out an idea in plain language, and get back code that just “does” it

No you can’t. Simplifying it grossly:

They can’t do the most low-level, dumbest detail, splitting hairs, “there’s no spoon”, “this is just correct no matter how much you blabber in the opposite direction, this is just wrong no matter how much you blabber to support it” kind of solutions.

And that happens to be main requirement that makes a task worth software developer’s time.

We need software developers to write computer programs, because “a general idea” even in a formalized language is not sufficient, you need to address details of actual reality. That is the bottleneck.

That technology widens the passage in the places which were not the bottleneck in the first place.

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1 point
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1 point

this is just wrong no matter how much you blabber to support it" kind of solutions.

When you put it like that, I might be a perfect fit in today’s world with the loudest voice wins landscape.

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2 points

I regularly think and post conspiracy theory thoughts about why the “AI” is such a hype. And in line with them a certain kind of people seem to think that reality doesn’t matter, because those who control the present control the past and the future. That is, they think that controlling the discourse can replace controlling the reality. The issue with that is that whether a bomb is set, whether a boat is sea-worthy, whether a bridge will fall is not defined by discourse.

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0 points

they’re pretty good, and the faults they have are improving steadily. I dont think we’re hitting a ceiling yet, and I shudder to think where they’ll be in 5 years.

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0 points

I think you live in a nonsense world. I literally use it everyday and yes, sometimes it’s shit and it’s bad at anything that even requires a modicum of creativity. But 90% of shit doesn’t require a modicum of creativity. And my point isn’t about where we’re at, it’s about how far the same tech progressed on another domain adjacent task in three years.

Lemmy has a “dismiss AI” fetish and does so at its own peril.

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10 points

And I wouldn’t know where to start using it. My problems are often of the “integrate two badly documented company-internal APIs” variety. LLMs can’t do shit about that; they weren’t trained for it.

They’re nice for basic rote work but that’s often not what you deal with in a mature codebase.

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-7 points

Again, dismiss at your own peril.

Because “Integrate two badly documented APIs” is precisely the kind of tasks that even the current batch of LLMs actually crush.

And I’m not worried about being replaced by the current crop. I’m worried about future frameworks on technology like greyskull running 30, or 300, or 3000 uniquely trained LLMs and other transformers at once.

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10 points

And my point isn’t about where we’re at, it’s about how far the same tech progressed on another domain adjacent task in three years.

First off, are you extrapolating the middle part of the sigmoid thinking it’s an exponential. Secondly, https://link.springer.com/content/pdf/10.1007/s11633-017-1093-8.pdf

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3 points
*

I’ve written something vague in another place in this thread which seemed a good enough argument. But I didn’t expect that someone is going to link a literal scientific publication in the same very direction. Thank you, sometimes arguing in the Web is not a waste of time.

EDIT: Have finished reading it. Started thinking it was the same argument, in the middle got confused, in the end realized that yes, it’s the same argument, but explained well by a smarter person. A very cool article, and fully understandable for a random Lemming at that.

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-5 points

Dismiss at your own peril is my mantra on this. I work primarily in machine vision and the things that people were writing on as impossible or “unique to humans” in the 90s and 2000s ended up falling rapidly, and that generation of opinion pieces are now safely stored in the round bin.

The same was true of agents for games like go and chess and dota. And now the same has been demonstrated to be coming true for languages.

And maybe that paper built in the right caveats about “human intelligence”. But that isn’t to say human intelligence can’t be surpassed by something distinctly inhuman.

The real issue is that previously there wasn’t a use case with enough viability to warrant the explosion of interest we’ve seen like with transformers.

But transformers are like, legit wild. It’s bigger than UNETs. It’s way bigger than ltsm.

So dismiss at your own peril.

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5 points
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Are you a software developer? Or a hardware engineer? EDIT: Or anyone credible in evaluating my nonsense world against yours?

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-6 points

Machine learning scientist.

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