The artificial intelligence (AI) industry is entering a new phase centered on agentic and physical models, shifting from generative AI and creating new opportunities across Taiwan’s technology supply chain, Pegatron Corp (和碩) chairman Tung Tzu-hsien (童子賢) said yesterday.
Agentic AI is capable of carrying out more complex tasks, while physical AI encompasses applications such as autonomous vehicles, robots and smart medical devices, representing the next stage of the technology’s integration into the real world, Tung said on the sidelines of the Computex expo in Taipei.
Rapid development of agentic and physical AI could lead to the deployment of more than 1 billion AI agents worldwide, he said.
Photo: Meryl Kao, Taipei Times
This trend would drive demand for sensors, motors, printed circuit boards, IC substrates, advanced packaging, optical fibers and other components, creating significant opportunities for Taiwanese suppliers, he said.
At Computex, Pegatron is showcasing a new version of its robotic dog “Simba,” with significant improvements in weight and system integration.
It is suitable for use in patrol, security and other mission-critical environments, Tung said.
The company has about 1,000 employees dedicated to AI-related tasks, more than tripling in size over the past three years, Pegatron cochief executive officer Gary Cheng (鄭光志) said.
While the company was slower than some of its local peers in entering the AI server business, it aims to make a major push into the business this year, as inference applications, agentic AI and physical AI begin to gain real-world traction, Cheng said, adding that revenue contribution would become more visible next quarter.
Pegatron, which plays multiple roles within Nvidia Corp’s ecosystem, said that DRAM was the most constrained component in the AI server supply chain, while central processing unit (CPU) availability has improved following capacity expansions by Advanced Micro Devices Inc and Intel Corp.
About 80 to 90 percent of Pegatron’s AI server customers are medium-sized cloud data center operators, Cheng said.
Demand for general-purpose servers is steady, as traditional CPU-based servers are still well-suited for AI inference workloads, he said.
However, the shift from x86 to Arm Holding PLC architecture requires significant software modifications, giving large cloud service providers an advantage over smaller customers, he added.
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