CONNECT WITH US
Mar 26
Nvidia and Emerald AI partner with utilities to build grid-responsive AI data centers
Nvidia and Emerald AI said on Tuesday that they are joining forces with a group of major US power producers — including AES Corporation, Constellation Energy, Invenergy, NextEra Energy, Nscale Energy & Power, and Vistra — to develop a new generation of "AI factories" designed to come online faster and operate as active participants in the power grid.
Cloud AI demand is tightening advanced-node supply, with TSMC's 3nm capacity emerging as the most constrained segment at the end of the first quarter of 2026, according to IC design houses.
Service-sector labor shortages have surpassed those in manufacturing, emerging as a global structural challenge. To address this shift, Taiwan is prioritizing the deployment of service-oriented robots through a four-year "Smart Robot Service Application Guidance Program" launching in 2026.

At the intersection of global semiconductor power and cultural influence, K-pop band 2AM's Lim Seul Ong delivered a keynote at the AI Expo, reframing the AI race as a battle for human time. While the focus is typically on enterprise productivity, Lim introduced "the 8-hour war" concept, arguing that the ultimate leader in the AI ecosystem will be whoever captures the final third of a person's day. This refers to the eight hours dedicated to leisure, fandom, and emotional connection. While tech giants focus on faster chips and more massive models, Lim argued that these are engines idling without a destination. To reach the mass market, AI must transition from a solely tech to experience industry, using entertainment as the medium to turn raw computing power into something humans can actually feel.

The agentic AI age is upon us, and many businesses are keen to adopt them as the newest productivity tool, yet many enterprises never take their AI agents beyond the pilot stage. Speaking at the AI Expo in Taipei, IBM Taiwan CTO Steve Chuang said that the key is for the company leadership to pursue the AI transformation from the top-down.
As AI compute demand surges, the rising need for high-bandwidth memory (HBM) testing and failure analysis is reshaping semiconductor inspection equipment markets, affecting chipmakers, foundries, and equipment suppliers worldwide. Demand for integrated microscopy platforms and localised service hubs is increasing to control yield, reduce costly iterations, and secure AI supply-chain positions.
Keysight Technologies is opening local manufacturing operations in India, a move that promises faster access to precision test equipment and greater supply-chain resilience for global customers. The expansion is set to accelerate development across semiconductors, quantum computing, aerospace, AI, and wireless sectors, while deepening collaboration with Indian research institutions and government programs.
Indian conglomerate Adani Group is advancing plans to expand its data center business, holding preliminary talks with global technology firms including Meta Platforms and Google, according to a Bloomberg report.
Nvidia says quantum computing will not replace GPUs
Mar 27, 07:37
Nvidia said quantum computing will complement rather than replace GPUs, even as Taiwan accelerates investment in quantum technology. Speaking at an industry event, the company said it does not expect any quantum technology to displace GPUs and instead sees future systems combining GPUs, QPUs, and CPUs to boost computing performance.
Tongtai Machine & Tool's chairman warned that shifts caused by the Russia-Ukraine war and China's industrial growth have global implications for supply chains and industrial sourcing, affecting competitiveness in semiconductors, automotive, aerospace, and defense markets worldwide.
US-based Coupang announced on March 26, 2026, the official launch of its fourth warehouse and logistics center in Taiwan, further expanding its storage and logistics capacity.

Artificial intelligence is entering a new phase in which inference, rather than training, is becoming the dominant driver of computing demand, as rising costs and memory constraints begin to reshape AI infrastructure, according to researchers.