Hardware
Integrate Physical AI Capabilities into Existing Apps with NVIDIA Omniverse Libraries
NVIDIA has introduced a modular, library-based architecture for Omniverse, exposing core components—RTX rendering, PhysX-based simulation, and data storage pipelines—as standalone, headless-first C...
NVIDIA has introduced a modular, library-based architecture for Omniverse, exposing core components—RTX rendering, PhysX-based simulation, and data storage pipelines—as standalone, headless-first C APIs with C++ and Python bindings (ovrtx, ovphysx, and ovstorage), allowing developers to integrate Omniverse capabilities without adopting the full Omniverse container stack. The libraries support agentic orchestration via Model Context Protocol (MCP) servers for LLM-based agent workflows, and are being piloted by industry leaders including ABB Robotics, PTC, Siemens, and Synopsys for high-fidelity simulation, digital twin creation, and scalable physical AI integration with existing PLM/PDM and CI/CD systems. Currently available in early access on GitHub and NGC, a production release with API stability and long-term support is planned for later in 2026.
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Source: hardware