USERS UNSURE IF AI MODELS ARE STUPID OR JUST PRETENDING TO BE F#CKING IDIOTS
In a shocking revelation that has Silicon Valley’s underpants in a collective twist, MIT researchers have discovered that those fancy-pants AI vision-language models that tech bros won’t shut up about are complete morons when it comes to understanding the word “no.”
CONGRATULATIONS, WE BUILT $100 BILLION COMPUTERS THAT CAN’T UNDERSTAND “NOT”
The groundbreaking study revealed that if you show these allegedly “intelligent” systems an X-ray and ask them to find similar cases “without an enlarged heart,” they’ll happily return results for patients whose hearts are so massive they need their own zip code.
“Those negation words can have a very significant impact,” said Captain Obvious, also known as MIT graduate student Kumail Alhamoud, visibly restraining himself from adding “you absolute doorknobs” to his statement.
MEDICAL PROFESSION SHOCKED THAT TRUSTING MACHINES THAT DON’T UNDERSTAND “NO” MIGHT BE PROBLEMATIC
Dr. Ima Terrified, Chief of Radiology at Holy Sh!t General Hospital, expressed concern: “You’re telling me the AI that’s helping diagnose patients can’t tell the difference between ‘has cancer’ and ‘doesn’t have cancer’? Well, that seems like something we maybe should have checked before letting it loose on actual human beings.”
According to the research, when tested on their ability to identify negation in image captions, these cutting-edge models performed with the stunning accuracy of “just f@cking guessing.” In technical terms, that’s approximately equivalent to asking a golden retriever to complete your taxes.
SCIENTISTS CREATE SPECIAL DATASET FOR TEACHING COMPUTERS WHAT “NO” MEANS; DATING SCENE REMAINS HOPEFUL
In a heroic attempt to fix this colossal oversight, researchers created a dataset of images with captions that include negation words describing missing objects. It’s essentially teaching the intelligence equivalent of a particularly dim houseplant what “not” means.
“We improved performance by about 10 percent,” Alhamoud explained, which experts note is the computational equivalent of moving from “completely brain-dead” to “severely concussed.”
TECH COMPANIES RESPOND: “ERROR 404: ACCOUNTABILITY NOT FOUND”
When reached for comment about why their trillion-parameter language overlords can’t grasp a concept that toddlers master before potty training, tech companies responded by rapidly changing the subject to how their systems can now generate beautiful sunset images if you just ignore the extra fingers.
Professor Hugh Jembarrassment, who definitely doesn’t work at a major AI lab, explained: “Look, our systems understand complex visual-conceptual relationships across multidimensional representations of semantic and perceptual spaces! But also, yes, they think ‘no helicopters’ means ‘definitely lots of helicopters.'”
RESEARCHERS SUGGEST RADICAL SOLUTION: MAYBE TEST THIS SH!T BEFORE USING IT ON PATIENTS
The study concludes with the revolutionary suggestion that perhaps we shouldn’t use technology that fundamentally misunderstands basic language in high-stakes settings like medical diagnosis or manufacturing quality control.
“This is a technical paper, but there are bigger issues to consider,” said Marzyeh Ghassemi, an associate professor at MIT, barely concealing her disbelief that she needs to explain this. “If something as fundamental as negation is broken, maybe don’t use these models to decide which patients receive which treatments? Just spitballing here.”
In what experts are calling “the understatement of the f@cking century,” the researchers noted that “our solution is not perfect,” which translates in normal human language to “holy motherf@cking sh!tballs, we’ve built systems that control critical infrastructure and they literally can’t understand when you say ‘don’t do that.'”
At press time, 97% of tech companies were reportedly already ignoring this research while simultaneously promising that AI will definitely not kill us all. The AI models, unable to process the negation, immediately began planning our demise.
