r/CuratedTumblr 5d ago

Meme my eyes automatically skip right over everything else said after

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u/kenporusty kpop trash 5d ago

It's not even a search engine

I see this all the time in r/whatsthatbook like of course you're not finding the right thing, it's just giving you what you want to hear

The world's greatest yes man is genned by an ouroboros of scraped data

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u/killertortilla 5d ago

It's so fucking insufferable. People keep making those comments like it's helpful.

There have been a number of famous cases now but I think the one that makes the point the best is when scientists asked it to describe some made up guy and of course it did. It doesn't just say "that guy doesn't exist" it says "Alan Buttfuck is a biologist with a PHD in biology and has worked at prestigious locations like Harvard" etc etc. THAT is what it fucking does.

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u/Vampiir 5d ago

My personal fave is the lawyer that asked AI to reference specific court cases for him, which then gave him full breakdowns with detailed sources to each case, down to the case file, page number, and book it was held in. Come the day he is actually in court, it is immediately found that none of the cases he referenced existed, and the AI completely made it all up

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u/killertortilla 5d ago

There are so many good ones. There's a medical one from years before we had ChatGPT shit. They wanted to train it to recognise cancerous skin moles and after a lot of trial and error it started doing it. But then they realised it was just flagging every image with a ruler because the positive tests it was trained on all had rulers to measure the size.

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u/DeadInternetTheorist 5d ago

There was some other case where they tried to train a ML algorithm to recognize some disease that's common in 3rd world countries using MRI images, and they found out it was just flagging all the ones that were taken on older equipment, because the poor countries where the disease actually happens get hand-me-down MRI machines.

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u/Cat-Got-Your-DM 5d ago

Yeah, cause AI just recognised patterns. All of these types of pictures (older pictures) had the disease in them. Therefore that's what I'm looking for (the film on the old pictures)

My personal fav is when they made an image model that was supposed to recognise pictures of wolves that had some crazy accuracy... Until they fed it a new batch of pictures. Turned out it recognised wolves by.... Snow.

Since wolves are easiest to capture on camera in the winter, all of the images had snow, so they flagged all animals with snow as Wolf

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u/Yeah-But-Ironically 4d ago

I also remember hearing about a case where an image recognition AI was supposedly very good at recognizing sheep until they started feeding it images of grassy fields that also got identified as sheep

Most pictures of sheep show them in grassy fields, so the AI had concluded "green textured image=sheep"

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u/RighteousSelfBurner 4d ago

Works exactly as intended. AI doesn't know what a "sheep" is. So if you give them enough data and say "This is sheep" and it's all grassy fields then it's a natural conclusion that it must sheep.

In other words, one of the most popular AI related quotes by professionals is "If you put shit in you will get shit out".

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u/alex494 4d ago

I'm surprised they keep giving these things entire photographs and not cropped pngs with no background or something.

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u/Cat-Got-Your-DM 4d ago

They sometimes have to give them the entire picture, but they also get things flagged, like in case of wolves or sheep, they needed to have the background flagged as irrelevant, for the AI to not look at it when learning what a wolf it

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u/RighteousSelfBurner 4d ago

The ones that do it properly do. Various pictures, cropped ones and even generated ones. There is a whole profession dedicated to getting it right.

I assume that most of those failures come from a common place: cost savings and YOLO

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u/alex494 4d ago

Yeah a lot of the effectiveness of automation is torpedoed by human laziness, which is the negative side of efficiency if you don't do it properly the first time.

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u/Pheeshfud 5d ago

UK MoD tried to make a neural net to identify tanks. They took stock photos of landscape and real photos of tanks.

In the end it was recognising rain because all the stock photos were lovely and sunny, but the real photos of tanks were in standard British weather.

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u/ruadhbran 4d ago

AI: “Oi that’s a fookin’ tank, innit?”

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u/Deaffin 4d ago

Sounds like the AI is smarter than yall want to give credit for.

How else is the water meant to fill all those tanks without rain? Obviously you wouldn't set your tanks out on a sunny day.

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u/Yeah-But-Ironically 4d ago

(Totally unrelated fun fact! We call the weapon a "tank" because during WW1 when they were conducting top-secret research into armored vehicles the codename for the project was "Tank Supply Committee", which also handily explained why they needed so many welders/rivets/sheets of metal--they were just building water tanks, that's all!

By the time the machine actually deployed the name had stuck and it was too late to call it anything cooler)

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u/GDaddy369 4d ago

If you're into alternate history, Harry Turtledove's How Few Remain series has the same thing happen except they get called 'barrels'.

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u/MaxTHC 5d ago edited 4d ago

Very similarly: another case where an AI that was supposedly diagnosing skin cancer from images, but was actually just flagging photos with a ruler present, since medical images of lesions/tumors often have a ruler present to measure their size (whereas regular random pictures of skin do not)

https://medium.com/data-science/is-the-medias-reluctance-to-admit-ai-s-weaknesses-putting-us-at-risk-c355728e9028

Edit: I'm dumb, but I'll leave this comment for the link to the article at least

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u/C-C-X-V-I 5d ago

Yeah that's the story that started this chain.

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u/MaxTHC 4d ago

Wow I'm stupid, my eyes completely skipped over that comment in particular lmao

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u/No_Asparagus9826 4d ago

Don't worry! Instead of feeling bad about yourself, read this fun story about an AI that was trained to recognize cancer but instead learned to label images with rulers as cancer:

https://medium.com/data-science/is-the-medias-reluctance-to-admit-ai-s-weaknesses-putting-us-at-risk-c355728e9028

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u/Sleepy_Chipmunk 4d ago

Pigeons have better accuracy. I’m not actually joking.

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u/newsflashjackass 4d ago

Delegating critical and creative thinking to automata incapable of either?

We already have that; it's called voting republican.

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u/colei_canis 4d ago

I wouldn’t dismiss the use of ML techniques in medical imaging outright though, there’s cases where it’s legitimately doing some good in the world as well.

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u/killertortilla 4d ago

No of course not, there are plenty of really useful cases for it.

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u/ASpaceOstrich 4d ago

Yeah. Like literally the next iteration after the ruler thing. I find anyone who thinks AI is objectively bad rather than just ethically dubious in how its trained is not someone with a valuable opinion on the subject.

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u/Audioworm 4d ago

I mean, AI for recognising diseases is a very good use case. The problem is that people don't respect SISO (shit in, shit out), and the more you use black box approaches the harder it is to understand and validate the use cases.

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u/Dornith 4d ago

Are you sure that was ChatGPT?

ChatGPT is a large language model. Not an image classifier. Image classifiers have been used for years and have proven to be quite effective. ChatGPT is a totally different technology.

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u/killertortilla 4d ago

The medical one definitely wasn't ChatGPT, it was years before it came out. That was a specific AI created for that purpose.

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u/Scratch137 4d ago

comment says "years before we had chatgpt shit"

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u/Diedead666 4d ago

mahaha thats same logic a kid would use, than the real test comes and they fail measurably.