Building real-time physical AI applications—such as high-performance, multimodal object tracking for autonomous systems within a constrained power envelope—is notoriously difficult. It requires coordinating specialized hardware, managing complex data flows, and optimizing every microsecond for maximum performance.
This tech paper explores how agentic software environments can dramatically accelerate the development and deployment of physical AI applications. By abstracting the complexity of heterogeneous computing into structured, high-level libraries purpose built for physical AI, developers can transform AI models into production-ready applications in days/hours rather than months.
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