My Wife Bought Hexagonal Ice Trays And I Got To Explain How Ice Is Already Hexagonal!

When you're so deep in mathematical obsession that you start marketing your unsolved millennium problem like it's the next Marvel movie franchise. Nothing says "I've lost touch with reality" quite like releasing a proof in episodic installments while monitoring prediction markets for reactions. The Navier-Stokes equations have claimed another victim! That abstract is what happens when you let ChatGPT write your mathematical papers after feeding it nothing but fluid dynamics textbooks and energy drinks. The real twist ending? The proof was inside us all along... or maybe just inside this guy's imagination.

Content Both shapes have the same number of holes. Try it yourself. Start with a cube of playdo. Take a chopstick and push it through until it pokes out. Expand each hole. Repeat until each face has a hole. You only need to poke 5 holes in the cube to create the final shape. The first poke creates an opening in the top and bottom. Each following poke adds a hole to one of the 4 side faces.

The perfect illustration of machine learning in its natural habitat! Our protagonist claims ML as their strength, then immediately demonstrates how it actually works—getting the first answer wrong, then blindly repeating the "correct" answer regardless of the new input. This isn't just a coding joke; it's an existential crisis for anyone who's ever built a model that confidently produces nonsense. The algorithm has spoken: 6+9=15, therefore 4+20=15. The math is wrong, but the confidence is unwavering. Just like 90% of the ML models currently running in production somewhere.

So much for the robot uprising! While we're busy building bunkers for the AI apocalypse, our digital overlords are busy answering pressing questions like "is tennessine a metal?" (which, by the way, is element 117, an artificially created halogen that exists for milliseconds before decaying). The most dangerous thing this AI is doing is correcting our chemistry homework. World domination status: pending basic periodic table mastery.

Someone finally found a practical use for thermodynamics diagrams! The meme compares ChatGPT (left) to DeepSeek (right) using engine cycle diagrams. ChatGPT gets the complex Otto cycle with all its labeled strokes and processes, while DeepSeek gets the simplified, cleaner Carnot cycle. Basically saying ChatGPT is overcomplicated while DeepSeek is elegant and efficient. The perfect metaphor for anyone who's ever spent 20 minutes getting ChatGPT to understand a simple prompt. Maximum work output with minimum explanatory heat loss—just like a good Carnot engine.