# Extended Reality

Extended reality (XR) is the merging of physical and digital worlds, enabling users to interact with virtual environments, integrate digital elements into reality, and create transformative experiences in entertainment, work, and beyond.

Find tutorials, samples, videos, and more:

[Learning Library](https://developer.nvidia.com/topics/ai/xr?sortBy=developer_learning_library%2Fsort%2Ffeatured_in.xr%3Adesc%2Ctitle%3Aasc%20#library)

## Key Topics:

- Immersive Technologies
- Spatial Computing
- Artificial Intelligence

Click Image to Enlarge

_Katana_

## Extended Reality and Spatial Computing: The Interface for Physical and Agentic AI

[Extended reality](https://www.nvidia.com/en-us/design-visualization/solutions/virtual-reality/) (XR) is an umbrella term for immersive technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) that blend the physical and digital worlds, while [spatial computing](https://www.nvidia.com/en-us/glossary/spatial-computing/) is the broader paradigm in which digital intelligence understands and interacts with the physical world in real time.

NVIDIA’s comprehensive offerings in this space bridge the gap between heavy computational requirements and lightweight mobile devices through a suite of advanced hardware and software solutions. By centralizing the heavy lifting on [NVIDIA RTX™](https://www.nvidia.com/en-us/technologies/rtx/)-powered servers and workstations, NVIDIA allows you to bypass the processing limits of mobile hardware and stream complex, photorealistic environments with zero model decimation. These technologies leverage the dedicated ray-tracing and AI cores of the RTX architecture to power full-fidelity XR and spatial computing experiences—delivering unmatched visual realism and physically accurate simulations to any untethered device.

## Explore XR Technologies

### NVIDIA CloudXR

Stream high-fidelity XR content from RTX-powered servers to an open ecosystem of devices. Built as a universal OpenXR bridge, NVIDIA CloudXR™ 6.0 delivers native visionOS integration and frictionless web-based access via [CloudXR.js.](https://developer.nvidia.com/topics/ai/xr/cloudxr-js-sdk)

[Get Started With CloudXR](https://developer.nvidia.com/nvidia-cloudxr-sdk)

### NVIDIA Omniverse

NVIDIA Omniverse™ is a collection of libraries and microservices for developing industrial digital twins and physical AI simulation applications. Stream complex OpenUSD stages directly to Apple Vision Pro with full RTX visual fidelity.

[Get Started With Omniverse Libraries](https://www.nvidia.com/en-us/omniverse/)

### NVIDIA Professional VR Ready Solutions

NVIDIA VR Ready systems deliver unparalleled performance for smooth, immersive virtual reality experiences.

[Get Started With VR Ready](https://www.nvidia.com/en-us/design-visualization/solutions/vr-ready-systems/)

### NVIDIA VR Capture and Replay

NVIDIA Virtual Reality Capture and Replay (VCR) enables developers to accurately capture and replay VR content for performance testing, scene quality control, and more.

[Get Started With VCR](https://developer.nvidia.com/vcr-early-access)

### NVIDIA VRWorks

NVIDIA VRWorks™ enables VR application and headset developers to create amazing virtual reality experiences, improving VR performance and visual quality.

[Get Started With VRWorks](https://developer.nvidia.com/vrworks)

### NVIDIA Warp

Warp enables Python developers to create GPU-accelerated, 3D simulation workflows that drive ML pipelines in PyTorch, JAX, PhysicsNeMo, and NVIDIA Omniverse.

[Get Started With Warp](https://developer.nvidia.com/warp-python)

### NVIDIA XR AI

NVIDIA XR AI is a framework that connects XR devices—such as lightweight AR/AI glasses or head-mounted displays—to your organization’s full computational power, enabling spatially aware, intelligent agents to operate seamlessly across cloud, data center, workstation, and edge deployments.

[Get Started With XR AI](https://developer.nvidia.com/xr/xr-ai)

## XR Learning Resources

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1. Featured

### An Introduction to NVIDIA Cosmos for Physical AI

In this introductory, hands-on course, explore NVIDIA Cosmos, a platform of generative WFMs, advanced tokenizers, guardrails, and an accelerated data processing and curation pipeline.

[Learn more](https://www.nvidia.com/en-us/on-demand/session/gtcdc25-dct51187/)

2. Featured

### AV Simulation with Neural Reconstruction and Cosmos

Create realistic, diverse training data from real-world environments with AV simulation using neural reconstructions and Cosmos models.

[Learn more](https://developer.nvidia.com/blog/accelerating-av-simulation-with-neural-reconstruction-and-world-foundation-models/)

3. Featured

### Beyond Rendering: Why Graphics is Needed For Physical AI

Machines need more than perception—they need understanding. NVIDIA Cosmos WFMs help developers predict, transfer knowledge, and reason for autonomous systems.

[Learn more](https://www.nvidia.com/en-us/on-demand/session/siggraph25-s05/)

4. Featured

### Cosmos Cookbook

Read the Cosmos Cookbook for an open-source guide offering workflows and examples to deploy and post-train NVIDIA Cosmos world foundation models for real applications.

[Learn more](https://nvidia-cosmos.github.io/cosmos-cookbook/)

5. Featured

### Demo Cosmos Reason Model on NVIDIA Build

NVIDIA Cosmos Reason is a 7B-parameter vision language model that lets robots and AI agents reason and plan actions using knowledge, physics, and common sense.

[Learn more](https://build.nvidia.com/nvidia/cosmos-reason1-7b)

6. Featured

### Synthetic Data From Neural Simulation for Robot Training

This blueprint helps overcome the data challenge for training robot policy models like GR00T N - and enables generalist robots reason, plan, and execute tasks.

[Learn more](https://www.youtube.com/watch?v=Coy2TyBcT4g)