Nvidia is positioning physical artificial intelligence as the foundation of a fast-approaching robotics revolution, using a mix of open-source models, unified software frameworks, and purpose-built hardware to push intelligent machines into real-world environments. The company frames these advances as the basis for a new industrial era in which robots enhance productivity, safety, and economic output, while also creating a long-term growth story for investors anchored in an ecosystem strategy rather than stand-alone products.
On the software side, Nvidia’s Cosmos and GR00T model families are presented as a turning point in how robots are built and trained. The Cosmos Transfer 2.5, Cosmos Predict 2.5, and Cosmos Reason 2 models are used for synthetic data generation, policy evaluation, and contextual reasoning, and the Isaac GR00T N1.6 model is described as specializing in full-body control for humanoid robots according to Nvidia’s release. By open-sourcing these models on Hugging Face, Nvidia has democratized access to high-performance artificial intelligence, reducing the need for costly pretraining and enabling developers to move more quickly to deployment. Frameworks like Isaac Lab-Arena and OSMO unify training workflows across different compute environments, and integration with Hugging Face’s LeRobot framework plus hardware such as the Reachy 2 and Reachy Mini robots illustrates how Nvidia is trying to close the gap between research and commercialization.
Nvidia is pairing this software stack with dedicated silicon to run physical artificial intelligence in the field. The Jetson T4000 module, built on the Blackwell architecture, is described as delivering four times the performance of its predecessor while supporting high-energy-efficiency computing for use cases from humanoid robots to industrial automation. Partners including Boston Dynamics, Richtech Robotics, and LG Electronics are said to have integrated Jetson Thor into their systems to enhance navigation and manipulation, underscoring the company’s full-stack strategy in which models and hardware are tightly coupled to enterprise use cases.
The company’s financial performance and market share are portrayed as a reinforcing moat for this robotics push. In FY 2025, the company reported revenue of $130.5 billion and net income of $72.88 billion, with the Blackwell architecture achieving sell-out status in its first quarter. Its market share in discrete GPUs for data centers and gaming exceeds 90%, with the CUDA ecosystem cited as a key driver of this dominance. Nvidia is channeling this financial strength into physical artificial intelligence through a $10 billion investment in Anthropic and partnerships with companies like Figure AI and Wayve, alongside collaborations with Boston Dynamics and LG, which are all presented as accelerants for commercialization.
External assessments are used to underline Nvidia’s growing role across robotics and autonomous systems. According to the Intelligent Robotics – Company Evaluation Report 2025, Nvidia ranks among the top 11 quadrant leaders in the robotics sector, and the report credits the company with powering the top 30 autonomous vehicle data centers and enabling applications such as precision harvesting and medical assistance. A separate press release highlights Nvidia’s collaboration with United States manufacturing leaders to support reindustrialization through physical artificial intelligence, which the article presents as evidence of rising geopolitical and economic influence.
For investors, the article argues that Nvidia’s strategy is to own the entire value chain of physical artificial intelligence, from synthetic data generation and training to deployment on optimized hardware, creating a flywheel in which broader adoption feeds more innovation and investment. While naming AMD and Intel as emerging competitors in accelerators, the piece maintains that Nvidia’s full-stack solutions and CUDA ecosystem form a strong moat. The conclusion casts Nvidia’s physical artificial intelligence breakthroughs as central to the architecture of future productivity, extending artificial intelligence’s impact from data centers into the physical world through increasingly capable robots.
