this post was submitted on 22 Dec 2024
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[–] [email protected] 19 points 21 hours ago (3 children)

Computers have always been good at pattern recognition. This isn't new. LLM are not a type of actual AI. They are programs capable of recognizing patterns and Loosely reproducing them in semi randomized ways. The reason these so-called generative AI Solutions have trouble generating the right number of fingers. Is not only because they have no idea how many fingers a person is supposed to have. They have no idea what a finger is.

The same goes for code completion. They will just generate something that fills the pattern they're told to look for. It doesn't matter if it's right or wrong. Because they have no concept of what is right or wrong Beyond fitting the pattern. Not to mention that we've had code completion software for over a decade at this point. Llms do it less efficiently and less reliably. The only upside of them is that sometimes they can recognize and suggest a pattern that those programming the other coding helpers might have missed. Outside of that. Such as generating act like whole blocks of code or even entire programs. You can't even get an llm to reliably spit out a hello world program.

[–] [email protected] 4 points 20 hours ago (3 children)

"It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'"
-Pamela McCorduck

"AI is whatever hasn't been done yet."
- Larry Tesler

That's the curse of the AI Effect.
Nothing will ever be "an actual AI" until we cross the barrier to an actual human-like general artificial intelligence like Cortana from Halo, and even then people will claim it isn't actually intelligent.

[–] [email protected] 1 points 1 hour ago

Sometimes it seems like the biggest success of AI has been refining the definition of intelligence. But we still have a long way to go

[–] [email protected] 7 points 17 hours ago (1 children)

I mean, I think intelligence requires the ability to integrate new information into one's knowledge base. LLMs can't do that, they have to be trained on a fixed corpus.

Also, LLMs have a pretty shit-tastic track record of being able to differentiate correct data from bullshit, which is a pretty essential facet of intelligence IMO

[–] [email protected] 8 points 17 hours ago

LLMs have a perfect track record of doing exactly what they were designed to, take an input and create a plausible output that looks like it was written by a human. They just completely lack the part in the middle that properly understands what it gets as the input and makes sure the output is factually correct, because if it did have that then it wouldn't be an LLM any more, it would be an AGI.
The "artificial" in AI does also stand for the meaning of "fake" - something that looks and feels like it is intelligent, but actually isn't.

[–] [email protected] 7 points 18 hours ago (1 children)

Well at least until those who study intelligence and self-awareness actually come up with a comprehensive definition for it. Something we don't even have currently. Which makes the situation even more silly. The people selling LLMs and AGNs as artificial intelligence are the PT Barnum of the modern era. This way to the egress folks come see the magnificent egress!

[–] [email protected] 3 points 21 hours ago (2 children)

I never know what to think when I come across a comment like this one—which does describe, even if only at a surface level, how an LLM works—with 50% downvotes. Like, are people angry at reality, is that it?

[–] [email protected] 13 points 18 hours ago (1 children)

With as much misinformation that's being spread about regarding LLMs. It would only lose more people's comprehension to go into anything more than a generalization.

The problem is people are being sold AGI. But chat GPT and all these other tools don't even remotely qualify for that. They're really nothing more than a glorified Alice chatbot system on steroids. The one neat new trick to all this is that they've automated the training a bit. But these llms have no more comprehension of their output or the input they were given than something like the old Alice chatbot.

These tools have been described as artificial intelligence to layman for decades at this point. It makes it really hard to change that calcified opinion. People would rather believe that it's some magical thing not just probability and maths.

[–] [email protected] 6 points 14 hours ago

They are bullshit machines, trained to output something that users think is the right output.

[–] [email protected] 2 points 18 hours ago

Downvoting someone on the Internet is easier than tangentially modifying reality in a measurable way

[–] brie -3 points 14 hours ago (3 children)

Large context window LLMs are able to do quite a bit more than filling the gaps and completion. They can edit multiple files.

Yet, they're unreliable, as they hallucinate all the time. Debugging LLM-generated code is a new skill, and it's up to you to decide to learn it or not. I see quite an even split among devs. I think it's worth it, though once it took me two hours to find a very obscure bug in LLM-generated code.

[–] [email protected] 2 points 6 hours ago

If you consider debugging broken LLM-generated code to be a skill… sure, go for it. But, since generated code is able to use tons of unknown side effects and other seemingly (for humans) random stuff to achieve its goal, I'd rather take the other approach, where it takes a human half an hour to write the code that some LLM could generate in seconds, and not have to learn how to parse random mumbo jumbo from a machine, while getting a working result.

Writing code is far from being the longest part of the job; and you gingerly decided that making the tedious part even more tedious is a great idea to shorten the already short part of it…

[–] [email protected] 1 points 5 hours ago* (last edited 5 hours ago)

I have one of those at work now, but my experience with it is still quite limited. With Copilot it was quite useful for knocking up quick boutique solutions for particular problems (stitch together a load of PDFs sorted on a name heading), with the proviso that you might end up having to repair bleed between dependency versions and repair syntax. I couldn’t trust it with big refactors of existing systems.

[–] [email protected] 1 points 14 hours ago (1 children)

What is your favorite flavor of kool aid?

[–] brie -5 points 14 hours ago

Grape, my nigga.