This datasheet from RTI details how RTI and NVIDIA provide a foundation for Physical AI systems and the development of software-defined, AI-enabled medical devices.
Physical AI systems rely on real-time, interoperable data sharing across diverse data sources and computing platforms. The document examines how the integration of RTI with NVIDIA Holoscan enables deployable edge AI models to leverage diverse, interoperable data sources with reliable, low-latency, and secure communications across applications, networks, and platforms.
The paper highlights how this integration can simplify and accelerate the development of software-defined, AI-enabled, flexible, and scalable MedTech systems. RTI provides proven, production-ready software infrastructure for real-time data streaming across diverse and distributed data sources, applications, and platforms.
By enabling data integration across distributed applications and platforms, RTI and NVIDIA help unlock the full potential of edge AI for real-time actuation and insights. This approach also enables software-defined architectures for adaptable systems that integrate sensing, monitoring, video, and control across legacy and new applications.
Key Topics Covered
- Real-time, interoperable data sharing for Physical AI systems
- Integration of RTI with NVIDIA Holoscan for deployable edge AI models
- Reliable, low-latency, and secure communications across applications, networks, and platforms
- Development of software-defined, AI-enabled, flexible, and scalable MedTech systems
- Real-time data streaming across diverse and distributed data sources
- Edge AI data integration for real-time actuation and insights
- Integration of sensing, monitoring, video, and control across legacy and new applications
