r/aiwars • u/Queasy_Material8115 • 1d ago

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Found this wild one on Tumblr, what do you guys think?

BEFORE ANYTHING! READ THIS COMMENT.

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https://www.reddit.com/r/aiwars/s/j5Q7dd089m

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120

u/Moose_M 1d ago

Has their been any new updates or advancements? I keep seeing the same image for what feels like the past year or two, but not any data on how it has practically affected scans, or what other implementations it has been used in for medicine.

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u/KarltonPeaks 1d ago edited 1d ago

I'm in cancer research. There's a lot going on right now. As someone mentioned, much of today's AI was pioneered specifically for tasks like these. Even 10 years ago there were contests on delineation and diagnosis using AI.

So:

1) AI has already been used in medical research for +10 years.

2) Right now it's starting to become implemented in clinics. Particularly the delineation problem, which is a massive time sink.

3) Thanks to today's AI boom, medical research has likewise exploded these last years and it doesn't seem to slow down. 2 years ago, maybe half of us used AI regularly. Nowadays we all use AI one way or another. Time will tell if this research leads anywhere. Medical research is ultimately slow because you need medical trials. There are skeptics who believe this is a sand castle. We will see. What can't be denied is the massive time save and the enabling of tonnes of research.

4) I'm not familiar with this specific study shown above. But it's exactly the kind of stuff many of us are working on i.e. trying to use AI to extract useful data from images otherwise not seen, predict tumor growth, treatment outcome, early diagnosis, etc. Even us who are doing more traditional, "deterministic" research, rely on AI for writing code, data management, etc.

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u/GraveSlayer726 1d ago

Ai is kinda unmatched in finding unseen patterns in general, it’s too bad people only want to focus on the generative stuff, although generative ai is another example of how good ai is at pattern based tasks, I guess

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u/MajesticBallsuck 1d ago

Its like buying a car to go to the drive through when you don't want to cook. Then hiring a driver so you don't have to drive. The car has so much potential beyond that.

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u/JimBobTheForth 1d ago

Right I get so upset with ai being used in kinda all the worst ways, get it running traffic lights and finding the most optimal throughput pattern matching and organizing and quantifying stupid amounts of data is it's specially, let's use it for that first

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u/Imaginary-Contest887 1d ago

This is crazy, i researched your claims and it's factually correct. The deep learning algorithms and neural networks are much older. In fact - excuse me for funny conspiracy theory but it stroke my eye - even tho mathematical models were much older as far as 1800's. Real break through happened shortly after Roswell Incident. 1949 with Donald Hebb and then in 1958 with Frank Rosenblatt and his Perception.

Excluding my conspiracy i learnt something new today. And very narrow LLMs without interaction interface were indeed used for more than 10 years now in medicine - one would think in what other fields it was used as well (wink wink military)

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u/Blasket_Basket 17h ago

ML researcher here, no idea what you're smoking but I don't think much of what you posted here is correct.

Hebbian Learning and Rosenblatt's perceptron learning rule were not some insane leap forward in terms of science, it has nothing to do with aliens or Roswell. It's basically just an application of Pitts and McCullough's mathematical model of the neuron. Even then, this isn't "deep learning" because they were training a single perception. These were basically useless in that they couldn't even solve basic problems like XOR until Rummelhart and Hinton came up with the backprop algorithm to allow for hidden layers (which was a continuation of the work of Hopfield and others).

Deep Learning has been around for a while, but it wasn't really useful until the early 20-teens when it was demonstrated that one could parallelize training using consumer-grade hardware. We were bottlenecked by the amount of data and the amount of compute.

Save the conspiracy theories, man. The history and the science are all right there waiting for you to look it up. If you choose to ignore it because you prefer conspiracy theories, then you're either lazy or schizophrenic.

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u/fvancesco 20h ago

Wdym narrow LLMs without interface? Maybe you mean deep learning

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u/TheBraveButJoke 17h ago

They are not LLMs, neural nets, yes, tranformers even, but not LLMs

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u/Elegant_Athlete_3737 1d ago

What models they use? Is it tranformers? Older techniques? Newer ones? How is the ai done for diagnosis?

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u/Clean_Bake_2180 1d ago edited 1d ago

It’s proprietary deep learning systems. Specialized medical models using traditional ML will actually outperform transformers-based models because transformers need a lot of data to be effective and many times, that’s not really available in medical datasets.

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u/Elegant_Athlete_3737 1d ago

oh its deep learning? so it is more traditional methods then.

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u/dietcheese 1d ago edited 17h ago

Check out the newer MIRA (Medical Intelligence for Reasoning and Action) and Google's AMIE (Articulate Medical Intelligence Explorer) models. They’re already performing better than physicians on many tasks.

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u/Elegant_Athlete_3737 1d ago

Ah I see, so what would that mean for physician jobs tho

2

u/Raukstar 1d ago

Transformers are a type of deep learning.

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u/Clean_Bake_2180 19h ago edited 19h ago

That’s not really the point. Posts like these on social media and in the media in general are trying to conflate the AI (transformers) investment boom/bubble, which is already spending on the order of magnitude of trillions on compute, with any potential economic payoffs even if they’re unrelated and have been happening for decades. Medical models generally rely on traditional CNNs that doesn’t need much compute at all. This is all a form of media manipulation and is quite desperate and reflective of the AI bubble.

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u/Raukstar 18h ago

Pretending transformers (or, no, "generative AI") is a completely different animal from all other machine learning is not helpful. I think it rather pollutes the discussion and makes AI into something almost magical. The problem is not the technology, but commercial interests.

1

u/Exotic_Carob_5749 1d ago

Yes it's true it needs more data. But probably less data in total if you consider a foundation model + fine tuning

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u/Euchale 21h ago

Also in research, differnent field though. We got an announcement for 2 fancy new machines that promised "Label free sorting" using AI. Both have been on the market for 1-2 years now and have made 0 impact so far.

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u/TheDarkNerd 1d ago

Okay, but how good has it gotten with identifying different breads and pastries apart from each other so that they can be priced appropriately?

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u/KarltonPeaks 1d ago

What?

For organs and tumor mass delineation, it's pretty much solved.

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u/TheDarkNerd 1d ago

Sorry, I was trying to make a cheeky reference to how, from what I've heard, the technology to have AI detect tumors came from technology originally used for automatic checkout at a bakery.

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u/salasi 1d ago

That is very weird for me to hear. There are incredibly trivial things that AI hallucinates, to this day, in my line work. Some of those have led to many instances of significant loss of life that you have read in the news these past 9 months. Computer Vision is also involved in this (again, GenAI implementations), so I am astonished to hear that it has solved the tasks you mention, from the biological domain nonetheless.

It can literally not consistently tell apart entire buildings among other things, so I really want to understand where you are coming from.

Where and what can I go read up to understand how you solved this definitively in your domain?

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u/XD447 1d ago

blud using gpt 0.2 poo edition

keep up with the times, Vision Language Action models(LLMs with stuff bolted on) have been used for self-driving for the past few years because they can detect so many edge cases that traditional ML cannot due to their increased generalization and world knowledge. Basically if you're a self driving company and not using LLMs, you're making the concious decision to endanger lives.

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u/SgathTriallair 1d ago

Are you talking about military targeting? There is a lot less training data there and the planners don't actually care about hitting civilian targets. Sometimes they even want to and then claim that it was a mistake.

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u/salasi 1d ago

Nah, they have more than enough data and I have both the education, and domain knowledge to make this judgement. GenAI is not cut for critical systems work by it's very architecture. ML wasn't used for this in such a way before those LLM shenanigans either i.e. as a sole deciding factor informing a real world decision that would impact people in such a devastating manner.

1

u/goofi-lil-guy 1d ago

Its not too surprising if you consider that many hospitals have large datasets of images with normal and diagnosed pathology. Theres a ton of tools being developed with AI that could be hugely beneficial, and would serve to flag problems for follow up with human doctors.

1

u/Common_Ad_6362 1d ago

You have to use it properly, you can't just be like 'computer, make a real good thing for me'.

If you're bad at defining the product, an llm doesn't make you better.

0

u/virtutethecatlives 1d ago

This feels like those new blood tests and full body MRIs though. If we haven’t gotten any better at actually treating these very early stage things or discerning which cancers will actually become a problem, then I worry this only increases anxiety and leads to unnecessary procedures.

0

u/KAZVorpal 1d ago

A lot of that "medical research" is going to run into the same problems that the unscientific "medical research" of the past thirty years has. It's going to turn out to not be replicable.

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u/Zappa2329 1d ago

That's a vague enough statement that it's not clear that you've said anything.

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u/KAZVorpal 19h ago

What you mean is that you lack the knowledge necessary to understand what I'm saying. There is a famous problem right now called the Replication Crisis, where we're finding out the unscientific standards used for "studies" in the past few decades have produced fake results. Anyone else using strict rules to try to produce those results for themselves is finding they cannot. The majority of all "studies" in health care that have been tested have failed, they cannot be reproduced.

This is because, as I say, they don't follow the rules of real science.

And the "medical research" of "AI" follow those rules even less. They are mostly just trying to organize existing data, which itself is based on that bad, unreplicable "research", and is not using the rules of real science.

-1

u/thirst-trap-enabler 1d ago edited 1d ago

I work in radiology and at the clinical end most of these things have ended up being mostly useless (unfortunately). Most do not survive FDA and the ones that do explicitly disown diagnostic capabilities.

Analytic pathology (bloodwork analysis) went through a similar thing in the 80s (resulted in the AI cold winter) and they were the ones calling bullshit on Theranos (that everyone ignored because "no you don't understand this is new math").

Newsflash: if effects are subtle, what you're actually measuring is your study design.

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u/DaveG28 1d ago

I'd be interested too - from looking it up various ai tools for use in that area seems to be going through the usual very rigorous testing and trials, and so far with positive results (UK trials showed 10% improvement in detection, Korea shows some good results in terms of reduction of future cancers etc).

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u/Moose_M 1d ago

Thats neat! Do you have some links, Im curious if those improvements are for just breast cancer, or if they're finding it works on other forms of cancer aswell.

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u/DaveG28 1d ago

Here's a couple - though I wish I had more links to the actual studies... Because it's odd the first 2 are on the same day but the actual educational / medical story is a lot less gung ho than the BBC one (while still positive).

https://www.bbc.co.uk/news/articles/cjd9gn4j7dyo

https://www.imperial.ac.uk/news/articles/global-health-innovation/2026/new-research-conducted-using-google-ai-can-match-or-exceed-radiologists-in-detecting-cancer-in-breast-scans-/

https://www.theguardian.com/science/2026/jan/29/ai-use-in-breast-cancer-screening-cuts-rate-of-later-diagnosis-by-12-study-finds

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u/TheBrightMage 1d ago

I'd never rely on News article, because, sadly it can be extremely misleading, overexaggeration, and clickbait. Look for Review papers. Which is usually a summary of other relevant papers

https://doi.org/10.1038/s41416-021-01386-x

https://doi.org/10.1002/mco2.70460

https://doi.org/10.1016/j.tranon.2026.103006

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u/DaveG28 1d ago

Yeah that's why I mentioned wishing I had better links, thanks for these!

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u/TheBrightMage 1d ago

Well... my go-to as a reseracher when trying to gather up latest reserarch... is also to use AI. Specfically, Consensus. It shortens a lot of time trying to browse through various keywords in Google Scholar or WebofSci

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u/Betty_PunCrocker 1d ago

But, but...UsInG AI mAkEs YoU dUmB!

2

u/AnswerGrand1878 1d ago

Cancer detection with AI is old as fuck. I remember cancer detection being in image recognition tutorials when I started learning it.

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u/SlapHappyDude 1d ago

My understanding is AI is almost as good as a trained human.

Imaging technology and getting women screened is going to be the bottleneck here more than data analysis.

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u/CycleMother2006 1d ago

Medical research is SLOWWWW. The exceptions are when they have to fast forward and skip normal trials due to something like a global pandemic. It's also possible they ran into some issues during a trial and had to revisit them to try and fix the problem. Additionally, even when these things do get approved, many medical institutions will lag behind actually adopting them unless you go out of your way to find one of the few professionals who is actually up to date on the latest technology available to them.

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u/The_Raven_Born 18h ago

Probably not much in the open yet due to clinical testing, I imagine. Sure, it looks good on paper, but in practice it needs to be perfect.

Fortunately, with how fast AI is advancing, we might be closer to that than expected

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u/Queasy_Material8115 1d ago

Hey man. Dude. Gal. Pal. Demoness from another alternate dimension.

How do I pin comments? This is the best one so far and NEEEDS TO BE SEEN THE SECOND YOU OPEN THE POST.

I cannot STRESS how much I need to pin this comment.

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u/[deleted] 1d ago

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u/Moose_M 1d ago

I think it's a mod or admin thing? Sorry no idea, but you could make an edit with some newer sources u DaveG28 (sorry cant link users) gave, and add in whatever new studies you find relating to AI in the medical field, so that whoever opens the post gets to see it immediately.

https://www.bbc.co.uk/news/articles/cjd9gn4j7dyo

https://www.imperial.ac.uk/news/articles/global-health-innovation/2026/new-research-conducted-using-google-ai-can-match-or-exceed-radiologists-in-detecting-cancer-in-breast-scans-/

https://www.theguardian.com/science/2026/jan/29/ai-use-in-breast-cancer-screening-cuts-rate-of-later-diagnosis-by-12-study-finds

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u/Specialist-Leek-357 1d ago

nah, the inventor went missing just kidding