[NALA - Virtual] Physical AI: Picking the Impossible Parts with GRIIP 

Hosted by Vention

Most Physical AI demos show the easy parts. This session explains how to pick the hard ones.

Jimmy Li and Jean-François Tremblay open up GRIIP, the perception-to-motion pipeline behind Rapid Operator AI. From raw point clouds straight from the sensor, to how each model in the pipeline turns them into a reliable pick: segmentation, grasp selection, motion planning. The same models run every deployment, and the pipeline adapts to a new application in hours, not months. That architecture is why GRIIP holds up on the parts that break conventional vision: reflective, dark, transparent, tangled, or buried at the bottom of a deep bin.

The session covers how GRIIP segments cluttered scenes, selects grasps, and plans collision-free motion on real production parts. It also draws the line where classical vision stops working and foundation models such as NVIDIAs take over.

Attendees leave knowing exactly what runs inside the pipeline and why it holds up on a real factory floor. It comes down to one thing: hardware, AI pipeline, motion, and control engineered as one system, not stitched together from scattered vendors. It all runs on the Vention platform, the same platform behind 28,000+ machines. That is how automation stops breaking on real-world variability, and how it reaches the parts and the manufacturers it never could before.

Registration required: https://events.ringcentral.com/events/physical-ai-picking-the-impossible-parts-with-griiptm