Reject Algorithms Return To Monke

Looks like AI has learned the airline industry's most profitable algorithm! Nothing says "cutting-edge technology" quite like an AI that's figured out how to charge you $1000 for seat 11A—you know, that magical seat where your knees only slightly touch your chin. The beauty of machine learning: it doesn't just mimic human intelligence, it also picks up our worst capitalistic tendencies. Next update: AI that automatically adds a $25 fee for the privilege of being sardined next to a crying baby.

The perfect cup for programmers who can't stop working even during hydration breaks! This glass implements a recursive drinking algorithm that ensures optimal caffeine levels at all times. The conditional statement checks if the glass is full, then instructs you to drink, otherwise refill - basically a while loop for your beverage consumption. The beauty is in its efficiency: no explicit exit condition means you'll be properly caffeinated until you manually break the loop by leaving your desk. Hydration-driven development at its finest!

OH. MY. GOD. This is the most REVOLUTIONARY sorting algorithm of our time! 💀 Who needs bubble sort or quicksort when you can just HALLUCINATE your sorted data?! The audacity of this function to claim O(0) time complexity while literally DELETING your original data and returning a completely made-up sorted list! It's the computational equivalent of "I don't like reality so I'm creating my own." Computer science professors EVERYWHERE are having simultaneous heart attacks. But hey, technically it's the fastest sorting algorithm in existence since it doesn't actually sort ANYTHING! Pure. Evil. Genius.

First dev: "I'll just hardcode every single number from 1 to infinity with its even/odd status. Efficiency!" Second dev: "Why use simple modulo math when you can just outsource your basic arithmetic to a GPT model? That's 500KB of code and a $10 API bill to determine if a number is divisible by 2." The evolution of problem-solving in 2023: from hilariously inefficient to absurdly overcomplicated. Because nothing says "modern software engineering" like turning a one-line function into an enterprise-grade AI solution with cloud dependencies. Next week: "IsPositive() function now requires stable internet connection and cryptocurrency wallet."

Ah, sweet summer child with dreams of "enhancing" the Linux kernel with AI. Linus Torvalds is probably already typing a profanity-laden email explaining why your brilliant idea belongs in the same category as "adding blockchain to grep" or "making systemd even bigger." The Linux kernel maintainers have spent decades perfecting schedulers that can run everything from supercomputers to toasters. But sure, slap some AI on it! While you're at it, why not rewrite the whole thing in JavaScript? Those 9 replies are probably ranging from "please read the kernel documentation first" to "who let the intern on the mailing list again?"

Machine learning algorithms don't question their training data—they just optimize for patterns. So when a concerned parent uses that classic "bridge jumping" argument against peer pressure, ML algorithms are like "If that's what the data shows, absolutely I'm jumping!" No moral quandaries, no self-preservation instinct, just pure statistical correlation hunting. This is why AI safety researchers lose sleep at night. Your neural network doesn't understand bridges, gravity, or death—it just knows that if input = friends_jumping, then output = yes. And this is exactly why we need to be careful what we feed these algorithms before they cheerfully optimize humanity into oblivion.