"Be horse." – a diffusion language model on an M2 Air
Try the demo here: https://llm-trajectory.boesch.dev/ This is a write-up of a system I designed at a previous job. It's a natural language interface for industrial robots. The demo runs MuJoCo in the browser via WASM. The demo uses a free-tier LLM API with rate limiting, so it might be slow or unavailable under load, but feel free to check out the code and hook up your own inference service: https://github.com/Encrux/llm_trajectory
"Be horse." – a diffusion language model on an M2 Air launched on April 30, 2026 with 10 votes, #1,251 of 21,248 launches that month and more than 90% of that year's launches.
What it does
Building a tiny diffusion language model from scratch and training on an M2 MacBook Air
To be, fo hend! First her sense ountier to Jupits, be horse. Wise words! This is the results of 2 hours of training my very own PyTorch Diffusion Language Model on an M2 MacBook Air. You can check out the code over at GitHub: github.com/Encrux/simple_dlm Diffusion Language Models are kind of a hot-topic right now in Machine Learning. The basic idea: corrupt some data with noise, then train a model to reverse that corruption over many small steps. They’re used in a variety of domains, most notably in image synthesis. Image generation algorithms like Stable Diffusions treat this as a continuous problem on a per-pixel basis, because a pixel value of 134 is close to 135. For text, this…from boesch.dev
In the maker’s words, at launch
Be horse.
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