this post was submitted on 31 Aug 2024
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I'm trying to feel more comfortable using random GitHub projects, basically.

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[–] [email protected] 8 points 2 weeks ago* (last edited 2 weeks ago) (1 children)

I don't think "AI" is going to add anything (positive) to such a use case. And if you remove "AI" as a requirement, you'll probably get more promising candidates than if you restrict yourself to "AI" (whatever that means) solutions.

[–] [email protected] -2 points 2 weeks ago* (last edited 2 weeks ago) (4 children)

I don't care if the solution is AI based or not, indeed.

I guess I thought it like that because AI is quite fit for the task of understanding what might be the purpose of code in a few seconds/minutes without you having to review it. I don't know how some non-AI tool could be better for such task.

Edit: so many people against the idea. Have you guys used GitHub Copilot? It understands the context of your repo to help you write the next thing... Right? Well, what if you apply the same idea to simply review for malicious/unexpected behaviour on third party repos? Doesn't seem too weird for me.

[–] [email protected] 6 points 2 weeks ago* (last edited 2 weeks ago) (1 children)

AI is quite fit for the task of understanding what might be the purpose of code

Disagree.

I don’t know how some non-AI tool could be better for such task.

ClamAV has been filling a somewhat similar use case for a long time, and I don't think I've ever heard anyone call it "AI".

I guess bayesian filters like email providers use to filter spam could be considered "AI" (though old-school AI, not the kind of stuff that's such a bubble now) and may possibly be applicable to your use case.

[–] [email protected] -1 points 2 weeks ago (2 children)

Bayesian filters are statistical, they have nothing to do with machine learning.

[–] [email protected] 4 points 2 weeks ago

If you're talking about naive bayes filtering, it most definitely is an ML model. Modern spam filters use more complex ML models (or at least I know Yahoo Mail used to ~15 years ago, because I saw a lecture where John Langford talked a little bit about it). Statistical ML is an "AI" field. Stuff like anomaly detection are also usually ML models.

[–] [email protected] 2 points 2 weeks ago* (last edited 2 weeks ago)

The A* algorithm doesn't have anything to do with machine learning either, but the first time I ever learned about it was in a computer science class in college called something like "Introduction To Artificial Intelligence".

But it's very much the case that the term "AI" has a very different meaning now-a-days during this cringy bubble than it did back in 2004 or 2005 or whenever that was.

Today "AI" is basically synonymous with "BS". Lol.

[–] [email protected] 5 points 2 weeks ago

AI is quite fit for the task

EXTREMELY LOUD INCORRECT BUZZER

[–] [email protected] -1 points 2 weeks ago

AI is quite fit for the task of understanding

Sure, and parrots are amazing at spotting fallacies like cherry picking...