Fine Tuning

Text lets an incorrect explanation remain elegant. A simulation is less polite. The bridge falls, the orbit escapes, or the ball passes through the floor. I wanted to test a narrow version of a larger idea: Can a model with fewer than one billion parameters learn enough structured code to generate small interactive physics worlds? The repository contains a completed Qwen3 0.6B LoRA run built from synthetic p5.js examples. It also contains a developmental learning proposal for MuJoCo....

In an era of photorealistic AI-generated images, I trained a language model to draw with box-drawing characters and pipe symbols. This isn’t nostalgia. It’s a bet that the most universal visual medium for AI isn’t pixels – it’s text. Why ASCII Diagrams Still Matter Every developer, every terminal session, every SSH connection, every log file, every README – text is the one output format that works everywhere. No rendering engine, no GPU, no browser required....

What happens when you take one of the smallest language models available, feed it a thousand physics animations generated by one of the largest, and ask it to teach K-12 students about science? You get a model that weighs less than a gigabyte, trains in under 3 minutes, and generates interactive physics simulations on demand. The Premise LLMs are getting bigger. GPT-5, Claude Opus, Gemini Ultra – they’re all racing to hundreds of billions of parameters....