tokens&
For enterprises
tokens&

Find tools, check provider offers, save a build plan, and share your work when you’re ready.

For buildersFor enterprises

For builders

  • Startup credits and perks
  • Agent Skills
  • Publish a project

For enterprises

  • Start free company workspace
  • Submit a tool, product, or perk

Community

  • Community
  • Newsletter
  • Events
Xin

© 2026 tokensand, LLC. All rights reserved.

  • Terms
  • Privacy
  • Security
  • Data Processing
  • Status
  1. Hackathon
  2. Project gallery
  3. World Compiler
Vontarius Fallsabout 1 hour agoContributorJudging locked: Event build

World Compiler

An application that uses a relay from smart glass such as Meta Raybans to capture real time video, label it, build a semantic searchable map + digital twin.

Review the project

Start with the source code, then open the demo or video if available.

Tools used
  • VAST Data logoVAST Data
  • SpaceXAI (Cursor) logoSpaceXAI (Cursor)
  • CoreWeave (Weights & Biases) logoCoreWeave (Weights & Biases)
  • NVIDIA logoNVIDIA
View GitHub repository
Visit project websiteWatch demo videoProject gallery
Demo video
Watch demo video
Project description
World Compiler turns captured video and sensor data from smart glasses into a structured, inspectable model of the physical world. It organizes observations into objects and claims, links each interpretation to its original evidence, and preserves a revision history. Users can review uncertain results, correct interpretations, and replay how the system’s understanding evolved without changing the original recordings. Our hackathon work focused on building the actual compilers and connecting them to World Sensor, our separate capture platform for phone, desktop, and watch. The technology stack brings together: Cursor for developing the compiler backend, frontend, and integration workflows.VAST Data: Provided the VM used to run Cursor’s remote development and build environment for the compiler project.CoreWeave as part of the cloud compute infrastructure for GPU workloads.YOLO as the object-detection component of the perception architecture, feeding observations into the compiler rather than treating detections as final truth.The key distinction is traceability: the system connects what it believes about the world to what it actually observed, with human review and recorded corrections.
Project links
  • GitHub repository
  • Project website
  • Demo video
Tools used
  • VAST Data logoVAST Data
  • SpaceXAI (Cursor) logoSpaceXAI (Cursor)
  • CoreWeave (Weights & Biases) logoCoreWeave (Weights & Biases)
  • NVIDIA logoNVIDIA