NVIDIA Cosmos Opens New Tools to Train, Evaluate and Deploy World Models

To help developers rapidly build world models, which help physical AI systems understand and simulate the real world, NVIDIA has expanded the Cosmos platform with new training tools, simulation checkpoints and Cosmos Data Factory blueprints. 

Ranking top five on six different open models leaderboards, the NVIDIA Cosmos platform gives world model builders the frontier open models — as well as data, training and optimization tools and recipes — to scale training data, adapt models, test behavior and optimize for performance before deployment. 

Build Better Training Data

Building world models begins with multimodal, multisensory data.

NVIDIA Cosmos Data Factory brings together the tools and skills for labeling, curating, augmenting and evaluating data at scale for training physical AI. Cosmos Curator, a GPU-accelerated solution for curating video training datasets, has now added support for multimodal multisensory inputs and processing blocks.

Cosmos Data Factory now offers the following five cloud-native blueprints and is available through GitHub, Microsoft Azure, Nebius and CoreWeave:

• Autonomous Vehicle Dataset Generation: Curates and labels driving data, then adds synthetic examples of hard-to-capture scenarios to expand training coverage.
• Image Attribute Augmentation: Varies object appearance to improve image search.
• Event Video Generation: Turns still images into synthetic videos of rare or unsafe events.
• Defect Image Generation: Generates printed circuit…