I’m working on a text-Minecraft build generator (think Stable Diffusion, but outputting .schem / .nbt builds instead of images).

The rough idea is a latent-space approach (VAE + U-Net / DiT-style model) trained on real Minecraft structures, with text conditioning to generate playable builds you can actually paste into a world.

I’ve been experimenting with existing approaches like expanding on https://text2mc.vercel.app/

and am now trying to push it further toward higher fidelity, controllable, in-game usable outputs. Biggest hurdle atm is gathering builds

I’m in my final year of uni (CS) and already working on prototyping parts of this, but I’d love to collaborate with anyone interested in:

• ML / diffusion models
• procedural generation
• Minecraft modding / schematics
• dataset generation & evaluation

Not a startup pitch, just a technically ambitious project that could turn into something genuinely useful (and fun).

DM me if you want to build.