As memory shortages worsen, Team Group is aggressively deepening its footprint in the industrial control market. Vice general manager Shao-An Hsia noted that with AI applications accelerating their expansion from the cloud to the edge, industrial and edge system manufacturers must pivot away from competing head-on with cloud giants for component supply. Instead, they need to rely on flexible specification adjustments and specialized hardware protection technologies. In driving edge AI adoption, memory suppliers will serve as "icebreakers" during the commercialization process.
Breaking from the industry's mainstream reliance on III-V compound semiconductors, Taiwanese startup Taiwan Nano & Micro-Photonics (N&M) is using complementary metal-oxide-semiconductor (CMOS) processes to develop a single chip capable of emitting more than four wavelengths of mid- to far-infrared light.
Nuvoton Technology sees robots and other physical AI applications becoming an important source of demand for microcontrollers (MCUs) over the next decade as computing moves from the cloud into edge devices, smart factories, drones, and care applications.
Taiwanese IC design companies have recently begun highlighting opportunities in physical AI and robotics. Arm's recently announced expansion of its Arm Total Design for Physical AI ecosystem, for example, includes Taiwanese IC designer Realtek Semiconductor.
Humanoid robots have entered a clear new phase since agentic AI emerged in 2025, with DIGITIMES analyst Zouhao Shen saying the category is now moving toward a three-tier hardware architecture of the brain, cerebellum, and peripheral nerves. He said the shift is reshaping the market and setting the stage for rapid growth through 2030.
At the "AI on Chips: Semiconductor Industry Trends Forum" hosted by DIGITIMES in Taipei on August 20, semiconductor, investment, and financial executives gathered to discuss the industry's next frontier. During the event, DIGITIMES deputy director Jason Tsai pointed out that as electricity supply struggles to keep pace with soaring compute demands, energy efficiency per unit of compute power will dictate the future fate of AI data centers.
