this post was submitted on 13 Nov 2024
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Science Memes

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[–] slackassassin@sh.itjust.works 53 points 1 month ago (1 children)

Working with pretrained models implemented in FPGAs for particle identification and tracking. It's much faster and exactly as accurate. ¯\_(ツ)_/¯

[–] daniskarma@lemmy.dbzer0.com 21 points 1 month ago* (last edited 1 month ago)

Run, the butlerian jihad is already going your way.

[–] Clent@lemmy.world 26 points 1 month ago (1 children)

The actual model required for general purpose likely lies beyond the range of petabytes of memory.

These models are using gigabytes and the trend indicates its exponential. A couple more gigabytes isn't going to cut it. Layers cannot expand the predictive capabilities without increasing the error. I'm sure a proof of that will be along within in the next few years.

[–] Krauerking@lemy.lol 9 points 1 month ago* (last edited 1 month ago)

"Come on man, I just need a couple more pets of your data and I will totally be able to predict you something useful!".
It's capacitors flip polarity in anticipation.

"I swear man! It's only a couple of orders of magnitude more, man! And all your dreams will come true. I'm sure I'll service you right!"

Well if it needs it, right?

[–] Dirac@lemmy.today 13 points 1 month ago (1 children)
[–] fckreddit@lemmy.ml 11 points 1 month ago (1 children)

"There is no free lunch.", is a saying in ML research.

[–] SturgiesYrFase@lemmy.ml 15 points 1 month ago

That's just a saying.

[–] propter_hog@hexbear.net 10 points 1 month ago

GET YOUR SHIT TOGETHER, CORAL

[–] azi@mander.xyz 9 points 1 month ago

There's plenty of stuff where ML algorithms the state of the art. For example the raw data from nanopore DNA sequencing machines is extremely noisy and ML algorithms clean it up with much less error than the Markov chains used in years previous.

[–] Alexstarfire@lemmy.world 7 points 1 month ago

For the meme? The Walking Dead. For the content? No idea.

[–] Collatz_problem@hexbear.net 4 points 1 month ago (1 children)

It is not even faster usually.

[–] propter_hog@hexbear.net 15 points 1 month ago

And if it is faster, it just converges to the wrong answer faster

[–] Nasan@sopuli.xyz 4 points 1 month ago
[–] belated_frog_pants@beehaw.org 3 points 1 month ago (1 children)

Ai sucks ass, stop using it

It doesn't. It's just overhyped.

[–] BugleFingers@lemmy.world 3 points 1 month ago (1 children)

A lot of new tech is not as efficient or equally so at the get go. Learning how to properly implement and utilize it is part of the process.

Right now we are just throwing raw computing power in ML format at it. As soon as it catches and shows a little promise in an area we can focus and refine. Sometimes you need to use the shotgun to see the rabbits ya know?

[–] rando895@lemmygrad.ml 3 points 1 month ago

Physicists abhor a black box. So long as it is an option, most will choose not to use AI to any great extent, and will chastise those who do.

[–] bigbrowncommie69@hexbear.net 2 points 1 month ago

Pretty much the only thing it's even remotely good for is as a toy.

[–] Reddfugee42@lemmy.world -2 points 1 month ago

So what you're saying, Dad, is it's nascent and already faster? Gotcha.