Comment by karim79 2 days ago
I truly hope that the common theme of the likes of "JWST Just Found Something Which Should Not Exist" etc will not be augmented by stuff like "we used AI(tm) to figure out X, Y, Z".
The last thing we need is hallucinations fucking up the more grounded astrophysics. I'm not saying that is what is happening, I just worry about stuff like this. AI causing us to bark up the wrong tree, and so forth.
Yeah but what if we start seeing only using this new awesome tool? What if that becomes the new seeing apparati? THIS is the tool that breaks that mold? The tool that (near?)every field is also going to be considering to be the tool that's off limits, or be 'constrained?'.
What if we had that view with microscopes, back when?
I see the point being made above fully. If ai takes over it's because we are every day it seems like slowly placing that faith.
It's our wow. It's the future generations taken for granted.
"Much more in-depth" ways now just "the way".
That's going to be a sign of the times if that happens. There are way too many people that enjoy the search doing it by hand. Yes, they are all of a certain age. Those of a certain younger age that only knows digital tools and not the ways of using their own eyes might eventually happen, but thankfully I won't be around for that to happen. (I'm one that uses my own eyes).
> Yeah but what if we start seeing only using this new awesome tool?
Like telescopes?
Not sure if there was an update/response to this but:
1st image of our Milky Way's black hole may be inaccurate, scientists say
It looks like the disagreement is over the exact shape with new technology on the way to help figure it out.
For another ML-assisted science thing, there's the LHC: https://en.wikipedia.org/wiki/Higgs_boson#Findings_since_201...
Based on the paper I linked, it seems like a straight up classical sampling and clustering with baysian hyperparameter tuning. This is “everything is now AI” slop that’s infected all grants, academic and private industry fundraising. There’s no neural net or LLM involved.
That's machine learning.
Clustering alone is machine learning and has been taught as such to innumerable people.
I have deep feelings about this, someone in management taking exactly one Kaggle course managed to wield this knowledge to great damage.
But it is machine learning.
Additionally, it goes far beyond clustering: the article you linked describes training an image recognition model, which also seems to be heavily stressed in the article linked on HN.
> The last thing we need is hallucinations fucking up the more grounded astrophysics.
You're thinking of the wrong ML. Generative models "hallucinate" and it's as much a feature as it's a bug. ML in astrophysics is not generative. They use it for flagging, "binning" data and in general (simplified) classification.
Eventually youll give in to the fact that ai is useful, and maybe revolutionary. Until then, continue using swear words and sticking your head in the sand
If anything, it's just going to call out a thing in the image that humans can then go and look at. Nothing in astronomy is ever "decided" by a single report. It gets looked at and scrutinized, and then committee style decisions are made about it. So if someone is using some ML to scan every image taken by JWST and calls out 1 cool thing for every other 9 things it finds that's "yeah, we know about that", then that's still quite a lot of new cool things. it'll just be able to do this faster and potentially much more in-depth than a human scanning across the images manually