this post was submitted on 08 Feb 2024
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Programmer Humor

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[–] ColdFenix@discuss.tchncs.de 84 points 2 years ago (2 children)

What ChatGPT actually comes up with in about 3 mins.

[–] underisk@lemmy.ml 71 points 2 years ago (2 children)

the comic is about using a machine learning algorithm instead of a hand-coded algorithm. not about using chatGPT to write a trivial program that no doubt exists a thousand times in the data it was trained on.

[–] Honytawk@lemmy.zip 24 points 2 years ago (3 children)

The strengths of Machine Learning are in the extremely complex programs.

Programs no junior dev would be able to accomplish.

So if the post can misrepresent the issue, then the commenter can do so too.

[–] pearsaltchocolatebar@discuss.online 26 points 2 years ago (2 children)

Lol, no. ML is not capable of writing extremely complex code.

It's basically like having a bunch of junior devs cranking out code that they don't really understand.

ML for coding is only really good at providing basic bitch code that is more time intensive than complex. And even that you have to check for hallucinations.

[–] kurwa@lemmy.world 15 points 2 years ago

To reiterate what the parent comment of the one you replied to said, this isn't about chat GPT generating code, it's about using ML to create a indeterministic algorithm, that's why in the comic it's only very close to 12 and not 12 exactly.

[–] BluesF@lemmy.world 0 points 2 years ago

ML is not good for coding, it is good for approximately solving very complex problems.

[–] underisk@lemmy.ml 17 points 2 years ago

Yes that is what they are good at. But not as good as a deterministic algorithm that can do the same thing. You use machine learning when the problem is too complex to solve deterministically, and an approximate result is acceptable.

[–] Pelicanen@sopuli.xyz 15 points 2 years ago

I think the exact opposite, ML is good for automating away the trivial, repetitive tasks that take time away from development but they have a harder time with making a coherent, maintainable architecture of interconnected modules.

It is also good for data analysis, for example when the dynamics of a system are complex but you have a lot of data. In that context, the algorithm doesn't have to infer a model that matches reality completely, just one that is close enough for the region of interest.

[–] kfet@lemmy.ca 4 points 2 years ago (1 children)
[–] stephen01king@lemmy.zip 2 points 2 years ago

But not all ML is GPT

[–] Klear@lemmy.world 13 points 2 years ago

Nice, that saves the coffee.