Multilayer Perceptron: It Just Says 4

Say one word about Nvidia's proprietary drivers, their CUDA monopoly, or their Linux support and watch the fanboys materialize like they're being summoned by a GPU mining rig. The company's worth more than most countries' GDP, but somehow needs defending from random devs on Reddit. Meanwhile Linus Torvalds literally gave them the middle finger on camera and they're still printing money faster than their RTX cards can render frames. The funniest part? Half the people defending them can't even afford their GPUs at scalper prices.

Remember when we used to memorize algorithms and syntax? Yeah, me neither. The meme shows our brains shrinking to pea-size after using ChatGPT for coding. Why bother storing all that knowledge when you can just prompt an AI? "Hey ChatGPT, how do I reverse a binary tree while making coffee?" and boom—instant solution without taxing those precious neurons. Soon we'll just be meat puppets with thumbs for typing prompts while our atrophied brains handle the critical task of deciding when to get more coffee. Progress!

Ah, the irony of modern tech! Here's a vintage book teaching "Artificial Intelligence in BASIC" from what looks like the 80s, sitting right next to "EXPERT SYSTEMS" on the bookshelf. Fast forward to 2023, and we're all losing our minds over ChatGPT and friends—billion-dollar AI systems built on Python, a language that would make your CPU cry if you asked it to calculate 2+2 in less than half a second. The cosmic joke is that we've gone from programming AI in languages designed to be "Beginner's All-purpose" to building world-changing models with a language where indentation errors can crash your entire system. Somewhere, this book's author is either laughing hysterically or weeping uncontrollably.

OH MY GODDD! This is LITERALLY k-means clustering in its purest form! Those poor souls are manually separating colored balls into distinct clusters like some twisted data science ritual! The algorithm in real life is just as chaotic - throwing random centroids around and then frantically shuffling points between groups until everything looks "good enough." The absolute DRAMA of unsupervised learning, where you're just desperately hoping your arbitrary number of clusters makes sense! And don't even get me started on how this perfectly captures the "elbow method" failing spectacularly when you realize you picked the wrong k value and now your entire analysis is a technicolor disaster!

The job market in 2026: millions of AI-generated apps flooding the ecosystem like digital locusts, all created by people who discovered ChatGPT and suddenly became "entrepreneurs." Meanwhile, the senior engineer sitting there with actual projects that real humans use is about as impressive as bringing a knife to a nuclear war. The vibe coder with their prompt engineering skills has industrialized app creation to the point where having genuine users is now the rarest commodity in tech. Quality over quantity? Never heard of her.