NVIDIA’s New AI: Insanely Good!

# NVIDIA’s GR00T-N1: The Open Foundation Model Set to Revolutionize Robotics

NVIDIA has released what may prove to be a groundbreaking development in robotics: GR00T-N1, an open foundation model for humanoid robotics that’s completely free and accessible to everyone. This model could be the catalyst for a robotics revolution that brings helpful, capable robots closer to reality than ever before.

## The Data Problem in Robotics

One of the biggest challenges in robotics has been the data problem. Unlike training language models, which have access to vast amounts of text data on the internet, training robots requires labeled demonstrations of physical movements—millions of them. Even companies like OpenAI stepped away from robotics partly because of this hurdle.

## NVIDIA’s Three-Part Solution

NVIDIA addresses this challenge with three innovative approaches:

### 1. Simulated Data Generation
– **Omniverse**: NVIDIA uses its Omniverse platform to create accurate digital simulations of the real world
– **Cosmos**: This system transforms video game-like footage into realistic, fully-labeled training videos
– **Scale**: The system can simulate more than 25 years worth of data in just one day

### 2. Self-Labeling Internet Videos
NVIDIA developed a system that can automatically extract and label information from existing internet videos, including:
– Camera movements
– Joint positions and movements
– Actions being performed
– Goals being achieved

This turns the vast library of unlabeled internet videos into usable training data, effectively turning reality into “video game data.”

### 3. Dual-System Thinking
GR00T-N1 builds on NVIDIA’s previous Eagle-2 vision-language model to implement two complementary thinking systems:
– **System 2**: Slow, deliberate reasoning to understand the world and plan actions
– **System 1**: Fast, real-time motor action generation using a diffusion model

This combination is remarkably effective, improving success rates from 46% to 76% compared to previous methods.

## Real-World Impact

The model is already showing promising results:
– It works with different robot embodiments
– Researchers and developers are using it for various projects
– It’s fully open and free, allowing for