NVIDIA Physical AI Community

A partner-exclusive series delivering product updates, feature deep-dives, and technical insights direct from NVIDIA product teams. Each edition highlights Omniverse, Robotics, Intelligent Vision, and the underlying hardware and accelerators — keeping developers, solution architects, and pre-sales leaders ahead of the curve. 

Learnings
In this month’s edition, you'll learn:

• NVIDIA CAE End to End Acceleration
  • Overview
  • Ecosystem landscape and roadmap
  • Customer Success Stories Highlight
• Real-Time Digital Twins : live demonstration
  • Kit-CAE Walkthrough + Live Demo
  • Best-practices
• ISV Spotlight
  • Showcasing our work with the ISV in the CAE Space and how this can be utilised by partners
• Round Table Panel with the experts

In this livestream, we’ll showcase how NVIDIA’s new Alpamayo open ecosystem for AV development, and in particular its AV dataset, creates new opportunities to advance AV safety.

Join the livestream to learn:

• How to interact with one of the largest, most geographically diverse collections of multi-sensor data (multi-camera, LiDAR, and radar) empowering AV researchers to build the next generation of end-to-end driving systems.
• How to use various curation tools, from accessing metadata labels to language-based retrieval to reasoning traces, to identify scenarios of relevance to safety objectives.
• Paradigms for iterative “data flywheel”-based development of safety evaluators, runtime monitors, and E2E driving models applicable to research with this dataset and beyond.

Don’t miss this unique opportunity to engage with our experts directly.

Learn how to create photorealistic training environments for Isaac Sim in minutes instead of weeks using three modern Gaussian Splatting workflows.

In this livestream, we’ll demonstrate how to:

• Generate synthetic environments from text and images using World Labs’ Marble
• Capture real-world spaces with NVIDIA’s FVDB reality capture pipeline
• Digitize room-scale environments using the XGRIDS SLAM scanner

You’ll see how each approach produces simulation-ready assets that integrate directly into Isaac Sim, enabling faster iteration, greater environmental diversity, and more realistic scenarios for robot training, reinforcement learning, and sim-to-real workflows.

Whether you’re building robotics simulations from scratch or scaling dataset diversity for training and evaluation, this session will show practical, end-to-end techniques for turning real and synthetic spaces into high-fidelity simulation environments.

📆  Check out the full calendar for all of our upcoming events → https://nvda.ws/3JqaWnA

----------------------------------------------------------------------------

⬇️Get Started → https://nvda.ws/4cZAZO1 
👀Explore OpenUSD → https://nvda.ws/3CeozBQ 
👥Join the Community → https://nvda.ws/3ZMfc6e 

Join our interactive Isaac Sim and Isaac Lab study group, led by NVIDIA Omniverse Ambassador Scott Dempsey. Explore robotics simulation, digital twins, and AI-driven control using NVIDIA’s advanced platforms and OpenUSD workflows. This hands-on series offers insights for all skill levels, fostering collaboration and practical learning for real-world robotics applications.

A partner-exclusive series delivering product updates, feature deep-dives, and technical insights direct from NVIDIA product teams. Each edition highlights Omniverse, Robotics, Intelligent Vision, and the underlying hardware and accelerators — keeping developers, solution architects, and pre-sales leaders ahead of the curve. 

Learnings
In this month’s edition, you'll learn:

• NVIDIA CAE End to End Acceleration
  • Overview
  • Ecosystem landscape and roadmap
  • Customer Success Stories Highlight
• Real-Time Digital Twins : live demonstration
  • Kit-CAE Walkthrough + Live Demo
  • Best-practices
• ISV Spotlight
  • Showcasing our work with the ISV in the CAE Space and how this can be utilised by partners
• Round Table Panel with the experts

Schließe dich unserer gemeinsamen Study Group an, in der wir den OpenUSD Learning Path Schritt für Schritt durchgehen. So kannst du deine Fähigkeiten stärken, Erfahrungen mit anderen teilen und dich optimal auf die USD-Zertifizierung vorbereiten – alles in einer unterstützenden Lernumgebung.
Weitere Informationen: https://perfectproducts.github.io/openusd_studierstube/

The OpenUSD Study Group is a dedicated space for addressing challenges and issues encountered during OpenUSD learning. As a group, we share our experiences of how we solved some of the problems and challenges we faced while learning and building OpenUSD-based solutions.Additional Resources: https://ziacreatesideas.github.io/STUDY_USD-GROUP/index.html

Welcome to OpenUSD Insider—a livestream series that brings together developers, researchers, and industry leaders to explore the latest tools, workflows, and innovations shaping the future of OpenUSD. From digital twins and simulation to robotics and industrial applications, each episode features real-world use cases, technical deep dives, and insights from those working on the cutting edge.

Whether you're building complex systems, training autonomous robots, or streamlining simulation pipelines, this series is your front-row seat to the evolving OpenUSD ecosystem.

📆  Check out the full calendar for all of our upcoming events → https://nvda.ws/3JqaWnA

----------------------------------------------------------------------------

⬇️Get Started → https://nvda.ws/4cZAZO1 
👀Explore OpenUSD → https://nvda.ws/3CeozBQ 
👥Join the Community → https://nvda.ws/3ZMfc6e 

Join our interactive Isaac Sim and Isaac Lab study group, led by NVIDIA Omniverse Ambassador Scott Dempsey. Explore robotics simulation, digital twins, and AI-driven control using NVIDIA’s advanced platforms and OpenUSD workflows. This hands-on series offers insights for all skill levels, fostering collaboration and practical learning for real-world robotics applications.

We’re hosting an AMA to explore how open models are changing the way robots learn, reason, and interact with the world.

Open models give developers more transparency, flexibility, and control over training and deployment. In this AMA, we’ll dig into how they enable better robot learning, stronger physical and social reasoning, and faster iteration across simulation and real-world systems.

How to Participate:  

1. Post your questions in the ⁠#ama channel on Discord before January 26.  
2. Browse through the questions and upvote the ones you want answered using the ♥ emoji.  
3. Join us live at 9:00 AM PM/12:00 PM EST on January 29 to see our expert respond to top-voted questions in real time. 

Pro tip: The more specific your question, the more detailed the answer you’ll get!