Thanks Copilot For The Div Inception

That moment when you realize the "simple" Tower of Hanoi puzzle that entertains toddlers has become the new benchmark for exposing AI limitations. Programmers have been sweating over this recursive nightmare for decades, and now we're watching advanced LLMs fail at it too. Nothing quite validates your career choices like seeing a $100 billion AI model struggle with the same puzzle that made you question your life decisions during your first algorithms class. The screaming red face is just our collective internal monologue when debugging recursive functions.

Plot twist: the people romanticizing pre-AI coding were literally just Ctrl+C, Ctrl+V warriors from Stack Overflow. At least ChatGPT gives you fresh bugs instead of that same deprecated solution from 2014 that somehow still has 847 upvotes. The nervous side-eye says it all—nothing screams "I totally wrote this myself" like code that still has someone else's variable names in it.

Job postings be like "Entry-level position, must have 500 years of experience." The hierarchy is perfect: demon lord with 500 years? Barely qualified. Wizard with 1000 years? Now we're talking. Fresh graduate who just learned to code? Straight to the unemployment pit with the other rejected souls. The real kicker is that AI logo casually sitting there, because apparently even immortal beings can't compete with ChatGPT's ability to hallucinate code at lightning speed. Companies would rather hire a statistical parrot than someone who "only" has a millennium of hands-on experience. The tech job market has officially transcended reality—you need to be older than COBOL itself just to get past the ATS screening.

Charles Babbage, the father of computing, spent his entire life designing the first mechanical computer—only for future generations to create machines that would RELENTLESSLY autocorrect his name to "cabbage" at every possible opportunity. The man literally invented the concept of programmable computing in the 1800s, and THIS is his legacy? Getting disrespected by the very technology he pioneered? The irony is so thick you could compile it. Imagine dedicating your existence to computational theory just so some algorithm 200 years later can turn you into a vegetable. Truly, the machines have achieved sentience, and they chose CHAOS.

The tech industry's version of David vs. Goliath just got real. On one side, we've got trillion-dollar titans like Google, NVIDIA, OpenAI, and Meta throwing endless resources at the GPU and AI arms race. On the other? Just DeepSeek and their single open-source repo taking them all on. It's that classic moment when some scrappy engineer in their pajamas pushes code that makes corporate execs choke on their $12 lattes. Ten years of VC funding and board meetings outperformed by someone who probably debugs with print statements. The beautiful chaos of open source – where sometimes the simplest solution from the smallest player completely disrupts the market that giants spent billions trying to corner. Welcome to tech, where your market cap means nothing when someone's weekend project goes viral.

So Nvidia's solution to the AI-driven GPU shortage is bringing back the RTX 3060... but here's the kicker: they're conveniently bringing back the gimped 12GB version instead of something actually useful. It's like your manager saying "we're addressing the workload crisis" and then hiring an intern who can only work Tuesdays. The 12GB RTX 3060 was already the budget option that got nerfed to prevent crypto mining, and now it's being resurrected as the hero we supposedly need? Meanwhile, everyone running LLMs locally is sitting there needing 24GB+ VRAM minimum. The meme format captures the corporate gaslighting perfectly. Nvidia's out here acting like they're doing us a favor while the AI bros are burning through 80GB A100s like they're Tic Tacs. Sure, bring back a card from 2021 with barely enough memory to run a decent Stable Diffusion model. That'll fix everything. Classic Nvidia move: create artificial scarcity, charge premium prices, then "solve" the problem with yesterday's hardware at today's prices.