Taipei, June 1, 2026 /PRNewswire/ — Linker Vision, a leading AI platform company in physical and inferential AI, today announced that it will leverage NVIDIA AI technology to significantly expand its platform across Taiwan’s cities and transportation systems.
introduction build The 2026 scale-up expansion of Kaohsiung Lighthouse Infrastructure, one of the world’s largest city-scale AI infrastructure environments, and the expansion of autonomous video inference capabilities across Taipei City and the Taiwan Ministry of Transportation and Communications (MOTC).
Large-scale agent video inference built on an application-driven AI grid
Built using NVIDIA NemoClaw Blueprint for safer long-running agents, NVIDIA Metropolis VSS Blueprint for scalable video AI deployments, and NVIDIA Cosmos for physical AI and world infrastructure modeling, and running on Linker Vision’s platform, this deployment demonstrates how autonomous video inference agents support real-time operational intelligence across large-scale physical environments.
From video analysis to autonomous operation
As cities and infrastructure operators face increasing operational complexity, AI systems are evolving from passive monitoring tools to active inference and operational intelligence platforms.
At the core of Linker Vision’s platform is an application-driven orchestration and runtime layer for large-scale physical AI deployments that dynamically coordinates compute, AI agents, and services across AI grids deployed across urban and infrastructure environments.
Combined with Linker Vision’s video inference platform, the system transforms real-time video streams into actionable intelligence, enabling AI systems that can continuously observe, infer, and support operational decisions in complex operational environments.
The platform uses NVIDIA NemoClaw with NVIDIA Metropolis VSS Blueprint and NVIDIA Cosmos to enable autonomous video inference agents that can orchestrate operational workflows, optimize infrastructure operations, and support large-scale AI deployments across transportation and city systems.
Scaling your physical AI infrastructure
The expanded Kaohsiung Lighthouse infrastructure supports large-scale AI operations across traffic management, public infrastructure, environmental intelligence, and flood response, extending into a broader operational and citizen service environment.
This deployment shows how the Linker Vision platform can scale to tens of thousands of cameras and distributed environments to support real-time traffic analysis, traffic hazard detection, flood response, operational intelligence, and proactive infrastructure coordination.
This scalable infrastructure also extends autonomous video inference capabilities across Taipei City and Taiwan’s Ministry of Transportation and Communications (MOTC) to support transportation and operational intelligence scenarios such as passenger flow analysis, congestion management, infrastructure coordination, and AI-assisted operational optimization.
These deployments represent a transition from passive video analytics to active AI-driven operations leveraging autonomous video inference and agent AI systems.
A new foundation for physical AI
Paul Shieh, founder and CEO of Linker Vision, said: “Cities and infrastructure systems are evolving from isolated AI deployments to interconnected physical AI environments.
“With the Linker Vision orchestration platform and autonomous video inference agents powered by NVIDIA AI technology, we are building an infrastructure that can understand, orchestrate, and operate real-world environments at scale.”
Linker Vision’s architecture shows how physical AI, video inference, and agent orchestration are evolving into the foundational infrastructure for future autonomous operations.
This vision of “Mirror City, Keep It Safe” reflects how physical AI systems continuously observe, infer, and support real-world environments at scale.
About linker vision
Linker Vision is a leading AI platform company that pioneers physical and video inference AI, enabling cities and industries to deploy scalable, real-time AI systems across intelligent infrastructure, industrial AI, humanoid robotics, and future autonomous services.
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