There Will Be Signs

The battle cry of every regex enthusiast who's watched AI models steal their thunder. Remember the good old days when text processing meant crafting the perfect regex pattern that looked like someone headbutted a keyboard? Now we've got billion-parameter models turning words into vectors and pretending they "understand" language. The bottom half showing "real NLP" with incomprehensible mathematical formulas and question marks is just *chef's kiss* - nothing says "human-friendly" like equations that would make even tenured professors reach for the aspirin. And that regex pattern in the middle? That's the ancient incantation developers used to summon the text-processing gods before we decided to burn exaflops of computing power to figure out if "John hates Mary" or if he's just having a bad day.

ABSOLUTE CHAOS BEHIND ME? Couldn't care less! My neural network is THRIVING on those sweet, sweet 32 gigabytes of video RAM! While mere mortals panic about the metaphorical house fire that is our AI models consuming astronomical computing resources, I'm just standing here with that smug little smile knowing my GPU can handle it. Who needs ethical considerations or efficiency when you can just throw more VRAM at the problem?! The data center might be melting down, but at least my model can hallucinate cat pictures in 8K resolution! 💅

Behold, the evolution of AI priorities! First panel: "AI coding for me so I can do my laundry" gets a hard pass. Second panel: "AI doing my laundry so I can code" receives enthusiastic approval. It's the perfect inversion of expectations. Instead of using cutting-edge technology to avoid the noble pursuit of programming, true developers want AI to handle mundane chores so they can spend more time doing what they actually love - staring at a screen wondering why that semicolon is breaking everything. The future isn't AI replacing programmers; it's AI folding your underwear while you debug in peace. Now THAT'S progress.

That's not machine learning. That's just a terminal spewing errors while someone went to lunch. Classic misdirection to keep management from asking why your project is six weeks behind. The screen full of red text means either your code is spectacularly broken or you're training the next ChatGPT. Either way, nobody's touching that keyboard until the "learning" is complete.

Ah, the evolution of debugging assistance. In 2019, you'd explain your problem to a rubber duck (a legitimate debugging technique where explaining your code aloud helps you spot the error). The duck just sits there, judging you silently while you ramble about line 43. Fast forward to 2025: Now you just bark "FIX THE ERROR" at ChatGPT, Claude, or whatever AI overlord is running your IDE. No need to understand the problem anymore - just demand a solution and watch as the machines do what took us mere mortals hours of Stack Overflow scrolling. The real error was thinking we'd still be doing our own debugging.

Ah, the modern "programmer" who only knows how to prompt ChatGPT. Nothing says "I've mastered coding" like typing "Write me a function that..." instead of actually learning syntax. Ten years of experience? More like ten minutes of experience with an AI that does the heavy lifting. The rest of us spent years debugging pointer arithmetic while these folks are getting violently rejected at technical interviews the moment someone asks them to reverse a linked list without digital assistance.