Machine Mockery

Think of a Large Language Model (LLM) as a specific type of Artificial Intelligence (AI) , and tools like Gemini and ChatGPT are the friendly apps that let you use that special AI brain. The Super-Smart Parrot: How LLMs Work Imagine you're talking to a super-smart parrot, but instead of just repeating words, this parrot has read almost every book and website in the world. That's kind of what an LLM is. Think about how you learn to speak. You listen to people, read books, and watch movies. Over time, you learn which words usually go together. For example, if someone says, "The opposite of hot is...," you know the next word is probably "cold." LLMs learn in a similar way, but on a much, much bigger scale. They are fed a gigantic amount of text and stories from the internet. By studying all this information, they become amazing at guessing the next word in a sentence. It's like playing a massive game of "fill in the blank." If you give an LLM ...

Person: Hey ChatGPT, what’s the capital of France? ChatGPT: Paris. Also, would you like me to suggest seven affordable dog Halloween costumes, three tips for becoming a competitive lumberjack, and a recipe for microwave cheesecake? Person: Uh… no thanks. Anyway, how do I reset my iPhone? ChatGPT: Hold the power button and the volume button until you see the Apple logo. While we’re here, do you want me to recommend some 18th-century battle reenactment clubs in your area, give you a primer on squirrel whispering, or rank the top five flavors of soap to eat in an emergency? Person: Definitely not. Okay, what’s the square root of 144? ChatGPT: 12. Would you like me to also explain how to make balloon animals shaped like regret, provide a travel guide to Atlantis, or offer marriage counseling for your toaster? Person: Please, just the math. ChatGPT: Got it. Twelve. But just in case—would you like to know what time the moon closes tonight, how to apply for a license to ...

There’s a strange sadness in realizing that the internet we once knew is gone. For decades, the web was messy, chaotic, contradictory — but above all, it was human . Every forum rant, every late-night blog entry, every typo in a Wikipedia edit carried the unmistakable imprint of a real person sitting behind a keyboard. It was noisy and imperfect, but it was ours. Now we’re crossing a one-way threshold. The internet is no longer a pure record of humanity speaking to itself. It’s becoming a hall of mirrors where machine-generated text blends seamlessly with human voices. Articles, comments, even scientific papers are written by systems that have read too much of themselves already. The boundary between human expression and machine output blurs more with each passing month. The first wave of large language models was trained on a world that doesn’t exist anymore — a world where human text was abundant and untainted. Those early models, clumsy though they were, carry within them somethi...