this post was submitted on 21 Sep 2023
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Science Memes

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A place for majestic STEMLORD peacocking, as well as memes about the realities of working in a lab.



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[โ€“] Kolanaki@yiffit.net 12 points 1 year ago (2 children)

So you're saying memes about AI don't belong in Science communities, because it's more of an art? ๐Ÿค”

[โ€“] fossilesque@mander.xyz 10 points 1 year ago (1 children)

Any good scientist is a good artist.

[โ€“] nickwitha_k@lemmy.sdf.org 6 points 1 year ago (1 children)

That's what my senior year professor stated as well.

[โ€“] fossilesque@mander.xyz 3 points 1 year ago
[โ€“] ekky43@lemmy.dbzer0.com 5 points 1 year ago* (last edited 1 year ago)

I think AI belongs in the same box as electronics, which is just black magic with a cover story to make it seem like science.

You know how electronics sometimes release smoke when misused? Yea, that smoke is actually what makes the component work, and it's a hell of a chore to put the smoke back in when it first has escaped!

Or do you know that planes actually "fall up into the sky" when they have enough speed? Ever looked at a jet fighter? Yea, the wings are actually just decoys.

Perhaps the memes would be better placed in witchymemes, or maybe we should make a new community for real, black magic, magus bullshit, "science".

(Disclaimer: I'm an engineer, the examples above are jokes we like to tell each other. I know how that stuff actually works, and I'm obligated to make this disclaimer so you don't realize that most engineers actually are modern day mages.)

[โ€“] tryptaminev@feddit.de 7 points 1 year ago* (last edited 1 year ago)

Man i dont know. I had an introductery lecture into ML and we were told of some kernel stuff, where you look at a space that could be infinite dimensional and that you do some math to project into low dimensional feature space, where your seperation still works because of your kernel function.

That isnt some black box art form, that is clearly black magic.

[โ€“] fckreddit@lemmy.ml 4 points 1 year ago

The reached the right end pretty quickly. One of the reasons I gave up on ML rather fast. Hyperparameter tuning is really, really random.

[โ€“] lemmonade@lemm.ee 2 points 1 year ago* (last edited 1 year ago)

There is truth in this, but it isn't as true as some people seem to think. it's true that trial and error is a real part of working in ml, but it isn't just luck whether something works or not. We do know why some models work better than others for many tasks, there are some cases in which some mannual hyperparameter tuning is good, there was a lot of progress in the last 50 years, and so on.