ZurichRobotics #3
Michael Neunert from Google DeepMind on efficient models for bringing AI into the real world and Riccardo Maggioni from FORGIS on the intelligence layer for the factory floor.
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Speakers
Michael Neunert
Google DeepMindRiccardo Maggioni
FORGISAbout
Michael Neunert (Google Deepmind): Building AI agents for the physical world The realization of truly general-purpose robots relies on three fundamental capabilities: a deep understanding of the physical world, advanced reasoning, and highly dexterous control. We will explore the development and impact of two groundbreaking models: Gemini Robotics 1.5, a multi-embodiment Vision-Language-Action (VLA) model, and Gemini Robotics-ER 1.5, our state-of-the-art Embodied Reasoning (ER) model. We will examine three major innovations driving this new generation of physical agents:
- Multi-Embodiment Learning via Motion Transfer (MT): How a novel architecture allows the VLA model to learn seamlessly from heterogeneous data across different types of robotic hardware
- "Thinking Before Acting": How interleaving actions with a multi-level internal reasoning process in natural language greatly improves a robot's ability to decompose complex tasks while remaining interpretable to human users.
- State-of-the-Art Embodied Reasoning: How Gemini Robotics-ER 1.5 establishes new benchmarks in critical areas like visual and spatial understanding, task planning, and progress estimation.
Riccardo Maggioni (FORGIS): FORGIS: Building the Intelligence Layer for the Factory Floor
Forgis is building the layer that makes industrial robots truly flexible, able to perform new tasks without the costly, months-long reprogramming cycle. By combining a foundation model with intelligent, transferable skills, Forgis deploys and scales robots on any production line in days instead of months.
Programme
- Building AI Agents for the Physical WorldMichael Neunert
- FORGIS: Building the Intelligence Layer for the Factory FloorRiccardo Maggioni