FAQ
You can run real-time control and AI together on a single robot compute by using Intel® Robotics with Intel® Time Coordinated Computing (Intel® TCC), which keeps sensor‑actuator control loops deterministic even as AI workloads run concurrently.
Intel® Core™ Ultra Series 3 processors integrate CPU, GPU, and NPU on one platform, allowing control, perception, and Physical AI policies to run together instead of across multiple systems. The OpenVINO™ Physical AI Framework then deploys perception and policy models with predictable execution behavior, helping keep latency and jitter within bounds as intelligence scales.
Intel® Robotics lowers total cost of ownership by enabling a single x86‑based platform for real-time control, AI inference, and system workloads, reducing the need for multiple compute boxes, proprietary accelerators, and custom integrations.
By standardizing on Intel® Core™ Ultra Series 3 processors, robotics programs benefit from higher performance per watt, simpler thermal design, and fewer system redesigns over a robot’s lifecycle. This consolidation helps reduce power consumption, system complexity, and long‑term maintenance costs.
You can design a maintainable, safety‑ready robotics software stack by using the OpenVINO™ Physical AI Framework on Intel® Robotics platforms, which standardizes how perception and policy models are deployed into real‑time control loops.
This structured runtime cleanly connects cameras, sensors, AI models, and robot actions while preserving predictable timing behavior. Combined with Intel® Robotics’ optimized ROS 2 controls layer, Intel® TCC, and Intel® Core™ / Core™ Ultra Series 3 processors, this architecture supports consistent validation, predictable behavior, and scalable, safety‑ready deployments as robots grow in complexity.
Disclaimers
1 As estimated by running Physical Intelligence’s OpenPi pi0.5 Vision-Language-Action (VLA) foundation model on Intel® Core™ Ultra X7 358H processor and NVIDIA Jetson Orin™ AGX 64GB running OpenPi (pi0.5) VLA workload with Droid Latency, 3 Cameras, at FP16, on TensorRT and OpenVINO™. Details at intel.com/performanceindex.
2 As estimated by running medium end-to-end video analytics workload with BS=8 on Intel® Core™ Ultra X7 358H processor vs. NVIDIA Jetson Orin™ AGX 64GB. Individual system results may vary as power and performance are affected by use, configuration and other factors. Details at intel.com/performanceindex.