Berlin Physical AI Workshop and Meetup - September 26, 2026

Sep 26, 2026

1:30 PM - 4:30 PM CEST

MotionLab.Berlin, Bouchéstraße 12/Halle 20, 12435 Berlin, Germany

Speakers

About this event

Join us at MotionLab.Berlin on Saturday, September 26th for the Berlin Physical AI Workshop and Meetup, co-presented by Nebius and Voxel51.

The afternoon kicks off meetup-style with lightning talks from local speakers working across AI, machine learning, and computer vision, followed by a hands-on workshop on building physical AI applications with FiftyOne, from curating robotics and sensor datasets to evaluating vision models on real-world data.

A laptop is required to participate in the hands-on workshop - please bring one. Space is limited, so register early.

Also joining us the night before at w3.hub? Register for both nights to save your spot at the September 25 meetup too.

A company, university, or government email address is required to take part in the hands-on workshop. Personal and disposable email accounts (Gmail, Yahoo, Outlook, and similar) cannot be used for the workshop environment. This is a blanket policy of the workshop platform to prevent fraud and abuse and to meet compliance requirements. If you need an exception, contact the hosts before the event.

Schedule

Hosts

Networking and Meetup

1:30–2:30 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.

2:30–3:30 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)

3:30–4:00 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

4:00–4:30 PM

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