blueblazin

I made a stylized low-poly 3D Earth engine using open maps and elevation data that runs in the browser (desktop only for now).

It's written in Rust and runs on WebGPU (wasm with threads). I made it as a native mac app but have now ported it to wasm.

Disclaimer: The app was fully vibe-coded over a course of around 80 days using Claude Code and Codex.

Web app: play.lowpolyearth.online

Press esc for controls.

Home page with more screenshots: lowpolyearth.online

Thanks! I am trying to port it to the browser. Keeping those Anthropic GPUs and TPUs busy.

Thanks, this is an online app and it uses protomaps[1] and mapterhorn[2] data for cities and elevation. So the app streams relevant elevation tiles based on your current location and uses those to render the terrain.

[1] https://protomaps.com [2] https://mapterhorn.com/

I think you may be confusing autoregressive and generative. But that can just mean it's a BERT-like encoder model that outputs a single vector for the given input tokens. To make it sound even more "novel" you can say it's a bidirectional encoder-only transformer model which modern LLMs are not and sell that as something revolutionary.

I really appreciate this type of articles. I feel like a lot of knowledge in LLM training and inference is locked inside the heads of practitioners. Similar to compiler engineers before.

To work in LLM training/inference you’re expected to know this stuff but to know this stuff you need to be working in the space.

Not difficult, just boring.

As someone with a bit of interest in programming languages (design and implementation) this was really interesting to me:

> For most people who work on programming languages, the easy part is coming up with new and better ideas about how to make programming better. The hard part is convincing anyone to actually use those ideas for real work.

Totally agree, there's only so much strangeness you can introduce in a new language[1] regardless of benefit.

But AI agents should not feel much resistance to radically new ideas in PL design. I've been thinking for a while now about how PL design will evolve post agentic AI. I think it will be very interesting to see what new ideas we can come up with to improve programming languages when we worry much less about adoption.

[1] https://steveklabnik.com/writing/the-language-strangeness-bu...

I think they poison outputs now if they detect distillation attempts. So a model trained on distilled outputs will be stupider.

Thanks for the kind words! Even though this is definitely meant for desktop screens, I really didn't want it to fall apart on mobile. As for upvotes, it's super niche so I wasn't really expecting even a single one tbh

A fully vibe coded python 3.14 interpreter in Rust: https://blueblazin.github.io/pyrs

Now at 350k lines. Native and wasm binaries (you can try the limited wasm version online). Currently adding a full CPython test suite benchmark.

Just for fun, not trying to replace CPython here. Mainly to test the limits of current coding agents.

As I understand Peter had already early retired because of a successful startup exit and presumably has more money than he knows what to do with. Does that help make you feel less jealous on him getting a job at oai?