# Crowd

- **Event:** [GPT-6 Astra Hackathon NYC](https://cerebralvalley.ai/e/openai-gpt-6-astra-nyc)
- **When:** Thu, Sep 10 at 9:00 AM – 10:00 PM (EDT)
- **Where:** New York, NY
- **Team:** [Yash Raj Pandey](https://cerebralvalley.ai/u/devYRPauli)
- **GitHub:** https://github.com/devYRPauli/crowd
- **Demo video:** https://drive.google.com/file/d/16EyIkHmOk2unT87y4pLUmtnSdRWW8VXG/view?usp=sharing
- **Gallery:** https://cerebralvalley.ai/e/openai-gpt-6-astra-nyc/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/openai-gpt-6-astra-nyc/hackathon/gallery/10

Crowd rehearses your event before the doors open. Describe the event, watch simulated guests move through your room, and ask GPT-6 Astra to propose changes within your constraints.

Our demo uses a schematic of the Puck Building's third floor: 120 guests arriving over ten minutes, with two volunteers serving. Moving the queue into the south corridor reduced walkway conflict by about 40%, but increased mean wait from 128 to 174 seconds. A third volunteer reduced mean wait to 79 seconds; a fourth reduced it to 28 seconds. These verified runs completed all 120 guests through actual exits. Crowd shows measured trade-offs instead of declaring every change an improvement.

Astra interprets briefs, lists assumptions for confirmation, proposes permitted changes, and explains results. JuPedSim moves people; a deterministic engine measures waits, walkway conflicts, overflow, and completion. Layout comparisons reuse the same presampled people, while changes in arrival are explicitly labeled. The interface includes a 3D room editor, playback, a guided demo, and a staffing comparison.

Built solo today. The verified demo uses arrival mode; dense dinner-call simulation remains experimental. This is an exploratory planning tool, not a safety certification.

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