8
submitted 2 weeks ago by cm0002@toast.ooo to c/science@mander.xyz
you are viewing a single comment's thread
view the rest of the comments
[-] eleijeep@piefed.social 9 points 2 weeks ago

To clarify the definition of "AI" that they're referring to: they're using Bayesian modelling. There's not a single neural-network in sight in this paper.

It's actually a great demonstration that you don't need "AI" and a cluster of expensive GPUs to solve this kind of practical optimisation problem. We've had these kind of statistical modelling techniques for decades already.

These kinds of headlines are being used to justify the massive data-centre build out and investment, despite the fact that the amount of computation they needed to do for this paper was just normal number crunching that data scientists have been doing on their laptops since forever.

The paper: https://ojs.aaai.org/index.php/AAAI/article/view/41428/45389

This paper develops a Bayesian Experimental design for AM (aka BEAM) approach

BEAM is inspired by work on active search ( Jiang et al. 2018 )

The referenced paper (Jiang et al 2018) is the best place to read about the method that they used.

this post was submitted on 02 Sep 2026
8 points (78.6% liked)

Science

7302 readers
2 users here now

General discussions about "science" itself

Be sure to also check out these other Fediverse science communities:

https://lemmy.ml/c/science

https://beehaw.org/c/science

founded 4 years ago
MODERATORS