Nvidia used GTC Taipei on June 1, 2026, to unveil RTX Spark, also known as N1X, a new AI PC system-on-chip designed for native AI agent workloads rather than mainstream Windows PCs. The chip appears designed to fill a gap in consumer hardware that cannot reliably handle local, autonomous AI tasks

At a recent product launch, BYD Chairman and President Wang Chuanfu unveiled the company's first in-house autonomous driving system-on-chip, the Xuanji A3, marking a significant milestone in BYD's push toward greater technological self-sufficiency

Nvidia and MediaTek have formally entered the AI PC and Windows on Arm market with the unveiling of RTX Spark at Computex 2026, ending two years of low-profile development. The first products are expected from Dell, HP, Lenovo, and MSI in autumn 2026

Intel's foundry revival may depend less on beating TSMC at the most advanced process nodes than on whether it can turn AI-driven demand into a profitable advanced packaging business

AI holds enormous potential to benefit the environment, but it simultaneously consumes massive amounts of water and energy. One generative AI data center can use up to 5 million gallons of water a day, and AI as a whole draws as much power as 100,000 households. A single AI query can use up to 1,000 times more electricity than a traditional Google search. The result is an urgent paradox: AI is becoming one of the most sophisticated tools ever built to combat climate change, yet it is also one of the fastest-growing strains on the planet's resources

Agentic AI is reshaping corporate procurement by moving beyond decision support to autonomous execution. Pactum is using it to automate tasks such as requisition handling, supplier communication, and compliance checks, helping enterprises manage procurement more efficiently across large supplier networks

When Nvidia CEO Jensen Huang stepped off a plane in Taipei on Saturday, May 23, he had already begun documenting the trip on X — night markets, fried food, and family. By the time he hosted more than 30 executives at a brick-walled restaurant six days later, the week had traced something much larger than a Computex schedule. It had mapped, dinner by dinner and post by post, the anatomy of the world's most consequential AI supply chain

The building where Saeed Amidi runs his global venture empire was once one of the most important semiconductor facilities on the West Coast. Philips Electronics operated a fabrication plant here in Sunnyvale, California, employing 8,000 people at its peak. Then, like much of America's chip manufacturing base, it moved to Asia — to Taiwan, to Korea, to the supply chains that would come to define the global electronics industry for the next three decades

Three days at Plug and Play's Silicon Valley May summit left me with a clear takeaway: the technology industry is undergoing a structural shift, not just another hype cycle. Here are the five trends that stood out from the conversations, keynotes, and startup pitches I observed on the ground

Cloud service providers' demand for application-specific integrated circuits, or ASICs, is increasingly locked in as advanced process nodes, advanced packaging, and component supply tighten worldwide. For readers across global tech markets, the shift means access to manufacturing capacity, not just chip design, is becoming the main determinant of who can supply the next wave of AI hardware

China has brought AI chips into its national security and reliability evaluation framework for the first time, turning what looks like a product certification process into something more consequential: an emerging gatekeeping system for AI computing infrastructure

AI's rapid evolution — from AI servers to agentic AI and emerging physical AI — centers on high-performance computing, and integrating general fault-tolerant quantum computers into that stack could change what HPC can do. The transition, however, confronts deep technical mismatches between classical AI servers and quantum processors

In recent weeks, Stellantis, one of the world's five largest automakers, unveiled an ambitious five-year plan titled Fastlane 2030. At its core is a striking reallocation of capital: 60% of its EUR60 billion (approx. US$69.8 billion) investment program will be directed toward North America

As the global semiconductor industry approaches the physical limits of transistor scaling, Huawei has proposed a new framework for the post-Moore era through its recently introduced "Tau (τ) Law" and a related time-scaling theory

Nvidia CEO Jensen Huang is pushing the company deeper into the CPU market, betting that the rise of agentic AI will create a new growth engine beyond the GPUs that made Nvidia the dominant supplier of AI computing hardware