
World foundation model platform for generating physically grounded video and training physical AI systems.
Cosmos is NVIDIA's world foundation model platform for physical AI development. The platform packages pretrained generative world models, advanced tokenizers, guardrails, and an accelerated data processing pipeline so developers can synthesize photoreal driving and robotics video for training and evaluation.
Cosmos integrates with Omniverse and Isaac to generate synthetic data, simulate edge cases, and post-train policy models for autonomous vehicles, humanoid robots, and industrial automation. NVIDIA released several Cosmos models under an open license so developers can fine-tune them on proprietary data.



Synthetic data platform that generates photorealistic labeled images and video for training computer vision models.


Synthetic data platform that generates physically accurate, fully labeled imagery for computer vision model training.


Digital World Models predict and simulate agent actions in digital workflows for AI training.


AI video generation and creative platform built on generative world models.


Operating system for agentic software development orchestrating specialized AI agents across the SDLC.


PhysicsX Platform unifies simulation, physics AI, and engineering applications into an AI-native software stack for industrial design and manufacturing.


Fern learns world models from robot data for scalable policy evaluation and training.


Realistic simulation environments for training and evaluating robot policies at scale.


Genie 3 is a DeepMind world model that turns text prompts into photorealistic, real-time explorable 3D environments.


World models are AI systems that understand physical reality through continuous observation and interaction rather than processing text alone.


Physics-based verifiable world model with a persistent 3D substrate and gated surfaces.


PD Replica reconstructs real locations from imagery for training and testing machine perception systems.


AI assistant and model family developed by Alibaba Cloud for enterprises and developers.
Causal world model platform for Physical AI and robotics.

Synthetic data platform that generates photorealistic labeled images and video for training computer vision models.

Synthetic data platform that generates physically accurate, fully labeled imagery for computer vision model training.

Digital World Models predict and simulate agent actions in digital workflows for AI training.

AI video generation and creative platform built on generative world models.

Operating system for agentic software development orchestrating specialized AI agents across the SDLC.

PhysicsX Platform unifies simulation, physics AI, and engineering applications into an AI-native software stack for industrial design and manufacturing.

Fern learns world models from robot data for scalable policy evaluation and training.

Realistic simulation environments for training and evaluating robot policies at scale.

Genie 3 is a DeepMind world model that turns text prompts into photorealistic, real-time explorable 3D environments.

World models are AI systems that understand physical reality through continuous observation and interaction rather than processing text alone.

Physics-based verifiable world model with a persistent 3D substrate and gated surfaces.

PD Replica reconstructs real locations from imagery for training and testing machine perception systems.

AI assistant and model family developed by Alibaba Cloud for enterprises and developers.
