Defining Physical AI

Physical AI is arriving on factory floors ahead of schedule, and Vention is already deploying it on applications four automation integrators failed to crack.

François Giguère, CTO of Vention, draws a precise line between agentic AI and physical AI. Agentic systems process data and return data. Physical AI controls motion and actuation that produce real world consequences on a factory floor where a hundred percent uptime is the only acceptable standard. Giguère has spent a decade helping build Vention, a platform that lets manufacturers design robotic cells in 3D, program them through natural language, simulate them in a browser, and receive the physical machine shipped in modular components like an industrial kit. With a team of 95 engineers and three years as CTO, he brings a grounded perspective on where AI delivers real value in industrial automation and where it still falls short.

The design, automate, simulate workflow at Vention represents one of the most complete implementations of AI-powered machine engineering currently in production. In the design phase, customers build systems from a modular component library. In the automate phase, an AI agent converts natural language prompts into Python control code for the entire cell including robot arms, conveyors, vision systems, and grippers. The program is validated in simulation before a single component ships. This is made possible by Vention's motion streaming architecture: instead of treating the robot as the master controller the way KUKA KRL does, Vention brings all motion planning, inverse kinematics, forward kinematics, blending, and trajectory optimization into its own software stack. The robot becomes a passive component consuming a motion stream, and the entire machine becomes programmable from a single unified codebase that AI tools excel at generating. Giguère notes that Vention's choice to use Python as the programming language for automation control gives their AI tools a measurable edge over environments built on structured text or ladder logic.

Vention's two physical AI products are GRIP (Generalized Robotics Intelligence Pipeline) and Rapid AI Operator, a modular bin picking application built on top of GRIP. The technology relies on transformer-based foundation models.

About François Giguère
François Giguère is the CTO of Vention, an industrial automation platform where manufacturers design, program, simulate, and deploy robotic systems entirely online. Employee number four at the company, he has contributed to Vention's growth for over 10 years and leads a team of 95 engineers. He holds a background in electrical engineering and real-time embedded software development.
Learn more: https://vention.io

Timestamps
0:00 Introduction and welcome
1:00 François Giguère's background and Vention overview
2:20 How AI spans Vention's internal tools and customer products
4:00 Why embedded and robotics code is harder for AI to generate
7:00 Design, automate, simulate: Vention's three-stage AI workflow
13:50 Motion streaming: one unified controller for all robot brands
18:20 Defining physical AI versus agentic AI
20:10 GRIP pipeline and Rapid AI Operator
22:40 Case study: MacAlpine Plumbing bin picking with foundation models
39:40 Nvidia GTC impressions: agentic AI eclipsing physical AI
46:20 Edge versus cloud: why real-time inference stays on-prem
56:10 Predictions: physical AI roadmap and the VLA timeline

This episode is sponsored by:
MaintainX helps maintenance and operations teams work smarter by putting critical information directly in the hands of technicians. According to MaintainX, technicians spend up to 40 percent of their time searching for answers and responding to radio calls rather than fixing assets.
https://www.maintainx.com

About Your Hosts
Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development.
Connect with Vlad: https://www.linkedin.com/in/vladromanov/

Want to go deeper? Vlad and the team at Joltek have covered related topics here:
Industrial Robotics: https://www.joltek.com/blog/industrial-robotics
Edge Computing and AI Value in Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-data

Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.
Connect with Dave: https://www.linkedin.com/in/davegriffith23/

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