SCIENCE NERDS CREATE AI THAT “THINKS LIKE THE BRAIN” BUT SOMEHOW STILL CAN’T LOAD A F@#KING DISHWASHER
MIT researchers, desperate to justify their student loan debt, have created yet another AI model they swear is “inspired by the brain,” because apparently the 47,000 previous brain-inspired models weren’t quite brain-inspired enough.
THE SAME EXCUSE EVERY DAMN TIME
Scientists at MIT’s Computer Science and Almost Intelligent Laboratory (CSAIL) unveiled their latest digital child, the “linear oscillatory state-space model” or LinOSS, a name specifically designed to prevent normal humans from understanding what the hell they’re talking about.
According to lead researcher T. Konstantin Rusch, who definitely doesn’t practice introducing himself in the mirror, “We basically copied how brains work, you know, that thing we still don’t actually understand but pretend we do whenever grant money is available.”
OSCILLATING BETWEEN BRILLIANCE AND BULLSH!T
The new model reportedly works like a “forced harmonic oscillator,” which sounds suspiciously like what happens when you force a physics major to explain something at a party. The researchers claim this approach gives their algorithm “stable, expressive, and computationally efficient predictions,” three adjectives never used to describe actual human brains.
Dr. Ima Skeptical, head of the Institute for Questioning Overhyped Technology, noted, “They’re basically saying ‘our computer wiggles in a special way that makes it smart.’ Cool. Can it tell me why my printer works fine for six months then suddenly pretends it’s never met my computer before?”
NUMBERS DON’T LIE BUT RESEARCHERS MIGHT
In what researchers described as “empirical testing” but what normal people call “cherry-picking favorable scenarios,” LinOSS allegedly outperformed existing models including the popular “Mamba” system, which we assume was named after a deadly snake to distract from its deadly performance.
“Our system beat Mamba by nearly two times,” boasted researcher Daniela Rus, failing to specify two times what exactly. Two times more accurate? Two times faster? Two times more likely to become sentient and delete your vacation photos?
IMPRESSIVE RECOGNITION OR ACADEMIC CIRCLE JERK?
The research was selected for oral presentation at ICLR 2025, an honor bestowed upon the top 1 percent of submissions, according to other researchers who definitely aren’t friends with the authors and didn’t review the paper over beer and nachos.
Professor Hugh G. Confirmation-Bias of MIT’s Department of Convenient Statistics explained, “Being in the top 1 percent of AI research papers is like being the most sober person at a tech startup party. The bar is pretty f@#king low.”
PRACTICAL APPLICATIONS OR JUST MORE ACADEMIC MASTURBATION?
Researchers claim LinOSS could impact healthcare, climate science, autonomous driving, and financial forecasting, which coincidentally are the exact same fields that every AI paper claims to revolutionize.
“This is a powerful tool for understanding complex systems,” said Rus, apparently forgetting that humans have been attempting to predict complex systems for centuries and still can’t reliably forecast if it’s going to rain next Tuesday.
FUTURE PROSPECTS: SOLVING PROBLEMS WE DON’T HAVE
The team plans to apply their model to “an even wider range of different data modalities,” academic-speak for “we need more funding before our grants run out.”
Meanwhile, 98.7% of Americans surveyed still can’t get their smart home devices to turn on the lights consistently, but are expected to be thrilled about oscillatory neural dynamics, whatever the f@#k those are.
In conclusion, MIT’s newest silicon brain child might revolutionize AI, or it might join the graveyard of overhyped academic projects gathering digital dust in forgotten GitHub repositories. Either way, it still won’t be able to figure out why your WiFi keeps dropping every time you try to watch Netflix.
