At SEMICON Taiwan 2026, Google outlined the direction of its AI infrastructure, and DIGITIMES notes that the discussion extended well beyond its next-generation TPU. Rather than focusing on a single chip, Google described how it links large numbers of TPUs into an integrated computing system spanning compute clusters, data centers, and ultimately multiple data centers, while also addressing the power constraints that emerge as the system continues to scale.
Anthropic CEO Dario Amodei's call to slow frontier AI development has stirred debate over safety, but chip industry sources say global demand for AI infrastructure is likely to keep rising. For readers worldwide, the larger issue is not whether AI spending stops, but how quickly it spreads across clouds, devices, and industries.
South Korea is updating its artificial intelligence security guidance as companies deploy AI agents capable of operating with limited human supervision, while Microsoft is proposing model-level rules requiring its systems to remain subject to human interruption and shutdown.
China's humanoid robot industry is moving from prototypes to industrial production. The next test is no longer whether robots can be built at scale, but whether they can work reliably and cheaply enough to make that scale economically viable.
Taiwan's original equipment manufacturer/electronics manufacturing services (OEM/EMS) sector is witnessing a structural split between explosive demand for artificial intelligence (AI) infrastructure and softening demand for legacy consumer device assembly in 2026. Monthly revenue data highlight how suppliers anchored to high-density compute racks, GPU-based servers, and high-speed network switches are delivering massive year-over-year gains, whereas manufacturers more reliant on standard notebooks face component supply bottlenecks.
At this year's China International Optoelectronic Expo (CIOE), Sivers Semiconductor brought two products to its booth that trace the trajectory of the optical networking industry: a 1.6T pluggable optical transceiver currently ramping toward mainstream adoption, and a prototype module built for external light source (ELS) architectures, a technology that could define the next generation of data center interconnects.
Panasonic Energy, the battery unit of Panasonic Holdings, is betting big on energy storage for AI data centers as demand for backup batteries from AI data centers surges. The company said it will keep energy storage systems (ESS) as a core growth driver and flex investment plans to match market demand.
As US AI executives warn that artificial intelligence development may need to slow down, Chinese companies are pressing ahead with open source tools and large-scale deployment. The gap matters far beyond China, because the next phase of AI competition may be shaped as much by collaboration and standards as by chips and model size.
OpenAI has acquired Glass Imaging, a startup developing artificial-intelligence (AI) technology designed to improve smartphone camera performance, in a deal valued at more than US$300 million, according to The Wall Street Journal. The acquisition adds imaging expertise to OpenAI as it expands beyond software and into consumer hardware.
China has introduced what it says is the world's first medical-device standard for brain-computer interfaces (BCIs) that use AI to process electroencephalogram (EEG) data, marking a step toward tighter regulation and commercialization of the emerging technology.
In 2026, major smartphone system-on-chip (SoC) vendors began moving selected flagship processors to 2nm technology, seeking not only to secure sufficient capacity but also to deliver meaningful upgrades in technical specifications.
After months of tight supply and sharp price increases in 2026, the global memory market is expected to see its supply-demand gap narrow significantly in 2027 as DRAM capacity expands and demand patterns shift, according to Beijing-based Sigmaintell Consulting. The consultancy expects the memory and broader semiconductor markets to continue growing through 2028, but forecasts a potential pullback in 2029 as evolving AI applications reshape demand.
eCloudvalley Digital Technology said enterprise adoption of generative AI is accelerating, with use cases expanding from single departments and single tasks to cross-functional workflows and core business processes. The company is rolling out an Enterprise AI Portfolio by integrating the technology and products of its group companies to target enterprise-grade AI.
