this post was submitted on 13 Jun 2025
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[–] utopiah@lemmy.world 1 points 2 months ago (2 children)

There are pretty great applications in medicine.

Like what? I discussed just 2 days ago with a friend who works in public healthcare, who is bullish about AI and best he could come up with DeepMind AlphaFold which is yes interesting, even important, and yet in a way "good old fashion AI" as has been the case for the last half century or so, namely a team of dedicated researchers, actual humans, focusing on a hard problem, throwing state of the art algorithms at a problem and some compute resources... but AFAICT there is so significant medicine research that made a significant change through "modern" AI like LLMs.

[–] Natanox@discuss.tchncs.de 7 points 2 months ago (1 children)

What I heard so far was about advanced pattern recognition for scans (MRI, CT etc) to reduce oversights and in documents to detect potential patterns relevant for epidemologists (a use that's very controversial since it requires all medical documents of citizens to be centralized and available unencrypted). Also some scientists seem to praise purpose-built machine learning technology for specialised tasks (those are not LLMs though).

[–] OpenStars@piefed.social 6 points 2 months ago

AI as in "Artificial Intelligence" has existed for decades and is quite useful - and specialized uses of LLMs can extend that. Although AI the buzzword for "generative intelligence" is new, and often wrong, being built to give the form of an answer rather than the reality of one.

[–] Dicska@lemmy.world 2 points 2 months ago (1 children)

The first thing that comes to my mind is cancer screening. I had to look it up because I can't always trust my memory, and I thought there was some AI involved in the RNA sequencing research for the Covid vaccine, but I actually remembered wrong.

[–] utopiah@lemmy.world 1 points 2 months ago

Skimmed through the article and I found it surprisingly difficult to pinpoint what "AI" solution they actually covered, despite going as far as opening the supplementary data of the research they mentioned. Maybe I'm missing something obvious so please do share.

AFAICT they are talking about using computer vision techniques to highlight potential problems in addition to bringing the non annotated image.

This... is great! But I'd argue this is NOT what "AI" at the moment is hyped about. What I mean is that computer vision and statistics have been used, in medicine and elsewhere, with great success and I don't see why it wouldn't be applied. Rather I would argue the hype at he moment in AI is about LLM and generative AI. AFAICT (but again had a hard time parsing through this paper to get anything actually specific) none of that is using it.

FWIW I did specific in my post tht my criticism was about "modern" AI, not AI as a field in general.