Another Job Taken By AI

Pre-ChatGPT: Developers channeling Neo from The Matrix, bending reality and code to their will, fighting bugs with superhuman focus. Post-ChatGPT: Just a sad cat begging an AI to draw pictures because we've forgotten how to solve our own problems. The evolution of debugging is complete - from coding wizards to glorified prompt engineers asking "pretty please fix my code." The irony? ChatGPT can't even draw that image. Not even a stick figure. Welcome to dependency hell's newest circle.

When AI confidently told everyone there are only two Rs in "strawberry" (spoiler: there are THREE), the internet collectively lost its mind. Like, bestie, you can write sonnets and debug code but you can't count letters? The meme roasts AI's infamous fail by comparing it to stroke symptoms—because honestly, that level of confident wrongness IS concerning. The "incoherent speech" panel hits different when your supposedly superintelligent overlord can't even spell-check its own existence. It's giving "I can generate entire novels but basic literacy? That's where I draw the line." The irony of AI promising world domination while simultaneously failing kindergarten-level tasks is *chef's kiss* peak comedy.

Jensen Huang really out here catching strays for making GPUs so expensive that Microsoft and Nvidia became household names for draining corporate budgets. But you know what? The man deserves credit where credit is due. He didn't just create a tech company—he created "Microslop Nshitia," the beautiful merger of bloated software and overpriced hardware that perfectly encapsulates modern tech. Your AI model needs 8 H100s to run? That'll be the GDP of a small nation, thanks. Want to train anything? Better get that enterprise license from Microsoft Azure while you're at it. It's the perfect ecosystem: Microsoft provides the cloud infrastructure to burn money, and Nvidia provides the GPUs to set that money on fire even faster. The Drake meme format really captures the vibe—rejecting the individual corporate overlords but fully embracing their unholy alliance. Because if you're gonna get fleeced, might as well get fleeced by the dream team.

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The eternal machine learning love triangle! Your relationship with TensorFlow was going just fine until PyTorch walked by with those sleek dynamic computation graphs and intuitive Python interface. Now you're doing that awkward neck-twist of betrayal while TensorFlow catches you eyeing PyTorch's hot new features. The static graph never felt so... static. Let's be honest, we've all mentally cheated on our ML frameworks. It's not you, TensorFlow, it's your verbose API and that whole session management thing.

So we've gone from "move fast and break things" to "move fast and let AI clean up your mess later." The galaxy brain take here is that tech debt—the accumulation of shortcuts, hacks, and questionable architectural decisions—is somehow an investment now. The reasoning? AI will eventually get good enough at refactoring that it'll just... fix everything for you while you sleep. It's the software equivalent of trashing your apartment because you heard Roombas are getting smarter next year. Sure, ship that spaghetti code. Name your variables "x1" through "x47." Nest those ternaries eight levels deep. Future AI will totally understand what drunk-you at 2 PM on a Friday was thinking. The real kicker is calling it an "interest rate" that's falling. Like tech debt is a mortgage you're refinancing, not a pile of burning garbage that makes onboarding new devs feel like archaeological fieldwork. But hey, if AI can refactor legacy code, maybe it can also explain to your future self why that 3000-line function seemed like a good idea.