I'll Do This Instead

When you run a local AI model but it's having an identity crisis. The DeepSeek model introduces itself as GPT-4, then immediately changes its story to being "DeepSeek R1" in the next message. It's like catching your date using someone else's profile pic, then frantically backpedaling when called out. Trust issues with AI: unlocked.

When you spend years building an AI model only to have someone ctrl+c, ctrl+v your entire codebase. Welcome to the cutting-edge world of AI, where the most innovative technology is... *checks notes*... copying your competitor's homework and hoping the teacher doesn't notice. Silicon Valley's billion-dollar secret: sometimes the best R&D strategy is just "Download & Rebrand." DeepSeek apparently took "deep learning" to mean "deeply learning OpenAI's proprietary code."

Ah yes, the classic "SQL" - Select Query Language interface for AI art generation. Just like SQL lets you select data from databases with minimal effort, these AI generators let you "select" artistic styles with equally minimal creativity. Behold the artistic process reduced to dropdown menus! Why spend years mastering painting techniques when you can just "SELECT (626)" from photographers? It's the perfect intersection of database queries and creative expression - both equally soulless when automated. The irony of unsubscribing from an art account to generate the same art yourself isn't lost on me. It's like firing your plumber after they show you where the wrench is.

Ah, the classic "models" folder misunderstanding. While she's expecting to find questionable photoshoots, you're just a data scientist with PyTorch and scikit-learn files. The disappointment on her face says it all—she was ready for scandal but found... *checks notes*... pickle files and Python tensors. The relationship might need a flowchart to explain that your "hot models" are just neural networks with good accuracy scores.

Left guy's in denial about AI coding tools while right guy's already seen the git blame logs from the future. The eternal cycle continues: new tech emerges, developers panic, then end up maintaining the mess it creates. The only constant in programming is cleaning up after the latest "revolutionary" tool. Just wait until we're all writing prompts to fix the prompts that fixed the code that broke the system.

Simple task: print numbers 1-10. Developer asks ChatGPT to do it. Instead of a basic loop, it delivers a recursive function. "Not bad," thinks the developer, and asks for optimization. ChatGPT's response? "Let's spawn threads for each recursive call!" The result is computational chaos—a CPU-melting, fan-screaming disaster that turns a 3-line solution into a parallel processing nightmare. It's like asking for a screwdriver and getting a nuclear-powered jackhammer with rocket boosters. Classic AI overengineering at its finest!