WHAT TO EXPECT

The Physical AI track is designed for robotics and embodied AI discussions.

Explore what it takes to move AI out of servers and into the physical world, and how the pioneers in this field are infusing models with an understanding of physical dynamics.

For roboticists, embedded engineers, research scientists & software specialists.

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Physical AI Speakers

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Who Attends?

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AWS
Bayer
Blue Origin
Boeing
Bosch
Brambles
Bruker Nano
Denso
EdgeCortix
Expedera

Dedicated Partners

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Edge IR
Vision Systems Design
Robotic Magazine

How Will You Benefit?

SEE HOW INTELLIGENCE MEETS THE REAL WORLD

See how intelligence meets the real world. Learn from the pioneers bringing AI out of the data center and into motion, from autonomous systems and robotics to edge deployments running on constrained hardware. Understand how perception, control, and simulation are converging to enable embodied learning.

DISCOVER BREAKTHROUGHS IN EMBODIED MODEL DESIGN

Stay ahead of breakthroughs in embodied model design. Explore how pioneers in robotics and embodied AI are integrating multimodal inputs, reinforcement learning, and world-model architectures to give machines a sense of physics, context, and adaptability.

MEET THOSE SHAPING THE PHYSICAL FRONTIER

Meet the systems builders shaping the physical frontier. Connect with roboticists, embedded systems engineers, and applied researchers who are deploying intelligence in dynamic, unpredictable environments, from industrial robotics to humanoids and field systems.

FAQs

The AI Infra Summit’s Physical AI track differs from other Physical AI and robotics conferences as it is situated within a full stack AI infrastructure event. 

Not only will attendees hear from Physical AI’s thought leaders and their strategies for overcoming solutions to critical challenges in engineering autonomy, but, because the track is embedded within a wider full stack AI infrastructure conference, attendees also have access to critical developments across the entire AI infrastructure ecosystem.   

Yes, the Physical AI track will dedicate an entire afternoon to lessons from Physical AI in deployment. Industry leaders from manufacturing, logistics, and aerospace will share their experiences deploying Physical AI systems into their o perations, the benefits these have brought, and strategies for overcoming integration challenges.   

The Physical AI track will cover the entire Physical AI ecosystem and system development. 

  • We will cover the pace of progress in industrial robotics and the critical developments and challenges in humanoid engineering.  

  • The track will also platform the critical players in the autonomous vehicle space, including Waymo, Wayve, and General Motors and their approaches to Level 4 autonomy.  

  • To complete our highlighting of Physical AI systems, the need for efficient edge inference, and strategies to enable this, will be a central topic. 

The Physical AI track will cover all the most pertinent challenges in engineering autonomous Physical AI systems.

We will examine solutions to robotics-specific engineering challenges, such as the challenge posed by insufficient, poor-quality data, strategies to close the sim-to-real gap, and how to ensure safe human-robot interaction. Alongside wider Physical AI and autonomous engineering bottlenecks, such as ensuring real-time performance at the edge, low-latency, and how to guarantee efficient edge inference. 

 

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