Advantech Edge AI Conference Highlights Physical AI and Edge Computing, Ushering the AI Applications at Scale

Advantech Co., Ltd. (TWSE: 2395), a global leader in IoT intelligent systems and embedded platforms, hosted its international “Edge AI Conference” on June 1 at the Hua Nan Bank International Convention Center. The conference brought together industry leaders, technology experts, and ecosystem partners, while a simultaneous global livestream attracted more than 3,000 professionals worldwide. Advantech Chairman K.C. Liu attended the conference and joined global AI ecosystem partners, including NVIDIA, Qualcomm Technologies, Inc., and Intel to spotlight the latest advancements in edge computing and Physical AI, underscoring that the era of scalable Edge AI deployment has officially arrived.

In his keynote speech, “Edge Computing & AI-Powered WISE Solutions,” Advantech Chairman K.C. Liu stated, “AI is moving from the cloud to the edge, evolving from a technology trend into the core of enterprise operations and becoming a key driver of digital transformation across industries.” K.C. Liu further noted that Advantech is also transforming from a hardware and technology provider into an industry enabler. Through its platform-based WEDA (WISE-Edge Developer Architecture) framework, ecosystem integration, and software-hardware co-creation capabilities, Advantech helps enterprises elevate AI into a core engine for operations and decision-making.

Physical AI Rises as WEDA Builds the Core Architecture for Edge AI

As Edge AI continues to mature, AI is evolving beyond cloud-based model training and generative AI into Physical AI, which is capable of perception, reasoning, and action. This shift enables AI to participate in real-time industrial decision-making and autonomous operations. “Advantech has been actively expanding its presence across smart manufacturing, healthcare, retail, energy, semiconductor, AMR, autonomous robotics, and humanoid robotics applications,” said Miller Chang, President of Advantech’s Embedded Sector. “To further support this development, Advantech has introduced the core architecture and key modules for Physical AI Robotics, integrating edge computing and multi-sensor fusion with its Robotic Suite software development kit to accelerate the deployment of robotics applications across industries. In addition, Advantech is working with ecosystem partners including NVIDIA, Qualcomm, Intel, AMD, and NXP to launch next-generation platform solutions. Through Advantech’s WEDA developer architecture, the company provides integrated solutions with cross-platform compatibility and AI agent development acceleration capabilities, helping drive real-world implementation and scalable adoption across industrial scenarios.”

Global Technology Leaders Gather to Explore the Future of Physical AI and Edge Computing

The conference brought together executives from global AI ecosystem partners, including NVIDIA, Qualcomm Technologies, and Intel. In his keynote speech, Deepu Talla, VP and GM of Robotics and Edge AI at NVIDIA, highlighted NVIDIA’s three-computer framework as the technological foundation for Physical AI. By combining NVIDIA Omniverse, Isaac Sim, Metropolis and NemoClaw, the framework establishes a complete pathway from training and simulation to real-world deployment. Under the theme of “AI Factory Brain,” Talla further illustrated how manager AI agents can deliver a new layer of intelligence and orchestration across visual inspection, SOP management, and factory operations. He also cited Advantech’s factory transformation roadmap as a compelling real-world example of the future potential of Physical AI.

Nakul Duggal, Executive Vice President and Group General Manager of Automotive, Industrial and Embedded IoT, and Robotics at Qualcomm Technologies, Inc., noted that edge computing and wireless technologies will help drive the large-scale development of industrial and Physical AI. Leveraging Qualcomm Dragonwing™ high-performance industrial processors, along with connectivity such as 5G and Wi-Fi 8, intelligent solutions can be deployed directly at the edge, supporting low latency, real-time decision-making, and autonomous operations. Qualcomm Technologies and Advantech will continue to collaborate to advance robotics innovation and unlock the full potential of Physical AI.

Dan Rodriguez, Corporate VP and GM of the Network and Edge Solutions Group at Intel Corporation, shared how Intel and Advantech are driving scalable AI innovation through an open ecosystem, native Edge AI architecture, and robotics AI platforms. He highlighted how these efforts are accelerating the real-world deployment of AI technologies across industries.

Advancing Industrial Applications Through Four Key Pillars of Physical AI Deployment

At the forum, Linda Tsai, Chief Operating Officer and President of Advantech’s Intelligent Systems Sector, joined NVIDIA and Omron to address four key priorities for the industrial deployment of Physical AI. She noted that the fundamental advancement of AI platform capabilities has moved Physical AI from concept to reality, while OT integration and scalable deployment remain critical to industrial adoption.

Advantech is further leveraging NVIDIA’s three-computer framework to establish a complete closed-loop workflow covering AI training, simulation, and deployment, significantly improving deployment efficiency. To address the scalability challenges caused by the highly fragmented nature of industrial environments, Advantech has introduced seven standardized “AI Foundry” modules to help enterprises accelerate the transition from proof of concept to mass deployment. Looking ahead, the “AI Factory Brain” will use AI agents to drive factories from fixed automation toward adaptive intelligent systems capable of continuous learning. “Physical AI is no longer a question of whether it can be realized, but how quickly we can scale it,” Linda Tsai emphasized.

The conference also featured in-depth discussions on the evolution of Edge AI in manufacturing and smart cities. Through real-world use cases, speakers shared how AI, digital twins, and edge computing can help enterprises improve production efficiency, quality consistency, and operational resilience, accelerating the transition toward open, intelligent, and scalable autonomous manufacturing. The discussions also explored key deployment models for AI across industries, including hospitals and chain retail.