Artificial General Intelligence Coming Soon*

The tables have turned! Software developers who've spent decades being called stupid by machines (compiler errors, runtime exceptions, segmentation faults) are now watching AI models struggle with basic logic and hallucinate facts. That skeleton represents the hardened dev who's been through countless debugging nightmares, now getting to say "You are stupid" to the innocent AI models that confidently generate nonsense. Sweet, sweet revenge for all those "undefined is not a function" messages that kept us awake at 3 AM.

BEHOLD! The most spectacular corporate announcement in the history of Stack Overflow! Meta proudly announces their "exciting partnership" with OpenAI and the community responds with... *dramatic pause*... a CRUSHING -461 votes! 💀 Nothing says "we're thrilled about this collaboration" quite like hundreds of developers collectively hitting that downvote button with the fury of a thousand crashed servers. The corporate-speak about "socially responsible AI" and "revenue streams" clearly resonated with everyone! And by "resonated," I mean triggered a downvote avalanche that could bury a small village. The true masterpiece? That little "-461" quietly sitting there like the world's most passive-aggressive code review. Stack Overflow users have spoken, and they've spoken in the universal language of "absolutely not." Chef's kiss! 🤌

Content Trump: Only 2 genders, Male, and Female

HONEY, THEY'RE NOT EVEN TRYING TO HIDE IT ANYMORE! 💀 The "sophisticated AI" behind health insurance claims is literally just import random and a coin flip between "deny" and "approve"?! I. AM. DECEASED. This is the technological equivalent of discovering your surgeon is actually just two raccoons in a lab coat. The absolute AUDACITY of companies claiming their "advanced algorithms" are anything more than digital dice rolls! Your life-saving medication approval? RANDOM CHANCE, BABY! 🎲

Machine learning algorithms in a nutshell: trained to identify "daddy" but wildly misinterpreting based on, uh, certain physical attributes. The algorithm sees round objects and makes confident yet hilariously wrong predictions. Just like that neural network you spent weeks training only to have it confidently label your boss's bald head as "an egg in its natural habitat" during the company demo. Context matters, folks! But try explaining that to a model that's just looking for patterns without understanding what those patterns actually mean.

The classic programmer paradox. Manually writing code for 30 minutes? Absolutely disgusting. But spending 3 hours configuring LLMs to generate code that would've taken 10 minutes to write? Now THAT'S what we call "productivity." It's the same energy as spending 5 hours automating a 30-minute weekly task and calling it "efficiency." The math doesn't add up, but the dopamine from avoiding actual work definitely does.