# Anytime Lab

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Troy Choi](https://cerebralvalley.ai/u/kowabyngawaaas)
- **GitHub:** https://github.com/suitzero/anytime-world
- **Demo video:** https://www.youtube.com/watch?v=8UECbV8wn5c
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/1066

Anytime World is a budget-slider demo of anytime computing. One scene is written once as a program — a canonical SDF scene in GFL, a budget-aware scene language — and rendered under a compute budget the user controls. Drag the budget slider from 1 to 100 and the world refines from a coarse estimate to a faithful reconstruction, while a live graph plots reconstruction error against budget, so every unit of compute shows exactly what it bought. Stop the slider anywhere and the image is complete and valid — that is the anytime property. The demo is an interactive four-region app (Target / Render / Controls / Metrics) that runs entirely locally: a WebGL2 raymarcher compiles the scene program, structural level-of-detail follows the budget, and the error curve is measured from real renders. The full architecture pairs this canonical scene with a neural side — Muse Image for target appearance, SAM 3.1 for the coarse first pass, and a Muse Spark-guided planner that would spend each budget unit on the highest-error region first. The submitted build is cache-first by design: preset targets and refinement ladders are precomputed, so the demo completes offline; those three models are its documented integration points rather than live calls. In the demo video, the uniform-allocation error curve is measured from the app's own renders; the guided curve shown next to it is a clearly labelled model-based illustration of error-first allocation, not a live planner run.

## More from Meta Global AI Developer Hackathon

- [Nichita Stane](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/1063)
- [MoDesign](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/1064)
- [SunSeg](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/1065)
- [Adiyan-Wayfinder](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/1067)
- [Amitech](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/1068)
- [VariantCut](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/1069)

---

Markdown version of https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/1066. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt