Friday, February 7, 2025

NVIDIA Cosmos Use Cases, Models, And Benefits Explained

In this blog we will discuss what is NVIDIA Cosmos, its advantages, models and Cosmos Use Cases.

What is NVIDIA Cosmos?

NVIDIA Cosmos is a platform that accelerates the development of physical AI systems, such as robots and autonomous vehicles (AVs), by utilising advanced tokenisers, guardrails, generative world foundation models (WFM), and an accelerated data processing and curation pipeline.

Cosmos Benefits

Accelerate Physical AI Development With World Foundation Models

Cosmos makes physical AI development accessible to everyone by giving developers free and simple access to extremely effective world foundation models and data pipelines.

Physics Aware

9,000 trillion tokens were used to train a suite of first-generation video models, which produced high-quality films from multimodal inputs like text, photos, and video. These models included 20 million hours of robotics and driving data.

Open

Because Cosmos WFMs and tokenisers are covered by the NVIDIA Open Model License, developers from all across the world can create physical AI systems at scale without incurring significant startup expenditures.

Accelerate Data Processing and Curation

With the NVIDIA NeMo Curator pipeline of CUDA-X and NVIDIA AI-accelerated tools for processing more than 100 PB of data, you can expedite data curation by 20X. It offers unconventional optimizations that speed up time-to-market and reduce total cost of ownership (TCO).

Develop Custom Models

Cosmos tokeniser uses 12X quicker processing and 8X better compression to turn visual data into high-fidelity tokens.

For physical AI, NVIDIA NeMo offers faster training and fine-tuning to create multimodal generative AI models.

Models

NVIDIA Cosmos World Foundation Models

A series of pre-trained models designed specifically to produce world states and movies with physics awareness for the development of physical AI.

Family of State-of-the-Art Models

For Text-to-World and Video-to-World generation, autoregressive and diffusion models are offered in parameter values ranging from 4 to 14 billion to accommodate different requirements.

A 12-billion-parameter up sampling model is used to improve text prompts and produce outputs with more accuracy and detail. This 7-billion-parameter model is optimized for augmented reality applications and is used to decode video sequences.

Inbuilt Guardrails

  • Pre-guard to remove unwanted prompts, hazardous content, and brands from outputs produced by Cosmos.
  • Post-guard to eliminate dubious situations.
  • Safeguard to obscure people’s faces.
  • Digital watermarks on fake videos produced using the NVIDIA API catalog’s Preview APIs.

Benchmarks

Journey to Physical AI Performance

In order to include the particular needs of physical AI applications from world foundation models, NVIDIA is collaborating with the robotics and autonomous car ecosystem to create a set of benchmarks.

The purpose of Cosmos benchmarks is to assess the upcoming generation of world models using sophisticated standards such as physics alignment and 3D consistency, which are crucial for robotics and autonomous systems.

Cosmos WFMs outperform VideoLDM (VLDM), a baseline generative model for video synthesis, in terms of geometric precision, temporal stability, and Sampson error. WFMs are also assessed by benchmarks using physical characteristics such as collision dynamics and gravity.

With up to 14 times greater pose estimate success rates, Cosmos WFMs routinely outperform VLDM in terms of visual consistency. Autoregressive models perform exceptionally well for custom models, however diffusion models offer superior realism right out of the box.

Cosmos Use Cases

Discover how developers may utilize Cosmos to further their work in robotics, autonomous cars, and visual AI.

Video Search

Cosmos assists developers in creating custom datasets for training AI models. By comprehending spatial and temporal patterns, Cosmos streamlines video labelling and search, making training data preparation easier, whether it’s for robotics or self-driving cars on snowy roads.

In addition to saving money and time, this helps produce AI models that are extremely applicable and useful in the real world.

Controllable 3D-to-Real Synthetic Data

Developers can create photoreal synthetic video by utilising their 3D simulation data. They can design 3D environments that reflect their model training requirements by using Omniverse. For highly customized synthetic datasets, they may then produce photorealistic films that are carefully controlled by 3D scenarios.

Policy Model Training and Evaluation

Scalable and repeatable training and evaluation of policy models, which provide strategies for physical AI systems by mapping states to actions, are made possible by Cosmos world foundation models optimized for action-conditioned video prediction. In order to optimize performance and guarantee dependability in real-world applications like robotics and autonomous cars, developers utilize these models to lessen their dependency on hazardous real-world testing or intricate simulations for activities like obstacle navigation and object manipulation.

Foresight

Cosmos enhances physical AI with sophisticated predictive intelligence, allowing systems to forecast future events and make more intelligent choices. Cosmos enables physical AI to choose the best course of action through foresight generation, producing predictive movies based on historical data and language cues, improving productivity, flexibility, and safety in changing contexts.

Multiverse Simulation

Developers can test real-time scenarios by simulating several Cosmos outcomes with NVIDIA Omniverse, which speeds up decision-making and improves AI-driven systems like robotics and driverless cars. Cosmos and Omniverse work together to give physical AI models the capacity to investigate every potential future scenario and choose the optimal course of action for increased accuracy and dependability in challenging situations.

Ecosystem

Adopted by Leading Physical AI Innovators

Cosmos is being used by model developers in the robotics, autonomous car, and visual AI sectors to expedite the development of physical AI.

Next Steps

Ready to Get Started?

Start creating your own world models with NVIDIA Cosmos or test drive a world foundation model from the NVIDIA API catalogue.

Build Your Custom Models

An end-to-end pipeline for curating, tokenising, and optimizing world models on any platform is offered by NVIDIA NeMo.

Start Curating Video Data For World Models

NVIDIA NeMo Curator-powered accelerated data processing and curation pipeline that is tailored for NVIDIA data centre GPUs.

Drakshi
Drakshi
Since June 2023, Drakshi has been writing articles of Artificial Intelligence for govindhtech. She was a postgraduate in business administration. She was an enthusiast of Artificial Intelligence.
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