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Nov 14 - NYC Physical AI Workshop and Meetup
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Nov 14 - NYC Physical AI Workshop and Meetup

Hosted by NYC Computer Vision in Production

Saturday 14 November 2026, 13:30

Venue time (New York)

Kimmel Center for University Life · Directions

Saturday 14 November 2026, 13:30Venue time (New York)
Kimmel Center for University LifeDirections
FreeTickets sold by meetup.com
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Hey, how's it going? Nov 14 - NYC Physical AI Workshop and Meetup looks like it should be pretty interesting. Want me to help you organise around it?

Event details

Tickets sold by meetup.com

Add to calendar · Downloads an .ics file · Times are in America/New_York · Google Calendar

Join us at NYU on Nov 14 for the NYC Physical AI Workshop and Meetup, co-presented by Nebius and Voxel51.

Seats are limited, Pre-registration is mandatory.

Date, Time and Location

Nov 14, 2026
1:30 PM - 4:30 PM
NYU Kimmel Center - Room 914
60 Washington Square South
New York, NY 10012

Meetup Agenda
5:30–6:30 PM

Networking, food, drinks, and lightning talks

Workshop Agenda
This hands-on session uses DROID, a real-world robotics dataset loaded into FiftyOne as a native multimodal MCAP recording, and YOLO11n, fine-tuned live during the session.

6:30–7:30 PM

Welcome + framing: from raw robot logs to a trained detector
Explore a real DROID robotics recording in FiftyOne's native multimodal MCAP viewer: camera, proprioception, and language on one synced timeline, no ROS install required
Curate: extract and browse frames from the recording, filter and deduplicate
Compute embeddings on the curated frames; explore via similarity search and embeddings visualization (via Nebius Serverless AI Jobs)

7:30–8:00 PM

Auto-label: open-vocabulary detection to generate bounding boxes for the robot gripper and target objects
Train: fine-tune a YOLO11n detector on the auto-labeled frames (via Nebius Serverless AI Jobs)
Evaluate results and close the loop: view predictions back on the original MCAP timeline

8:00–8:30 PM

What else Nebius offers: Token Factory walkthrough — chat/vision models, fine-tuning, credits

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