Intel is grappling with an operational crisis as its IDM 2.0 transformation plan has yet to yield results, casting doubt on when its foundry business might finally become profitable. This raises the question of whether Intel should consider abandoning its IDM model and separating its product design and manufacturing divisions—a move with both potential advantages and drawbacks. Industry leaders, including former board members, are offering advice in hopes of helping Intel find a viable path forward. However, the conflicting nature of their advice highlights the complexity of the company's dilemma
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
The global semiconductor industry is at an inflection point, split between those who can still shrink transistors and those who can no longer do so. US export controls and the denial of EUV lithography equipment have effectively capped China's front-end chip manufacturing at older process nodes, while Taiwan's TSMC extends its lead by layering chips vertically in three dimensions — a technique known as 3D stacking — binding the world's top AI chip designers ever more tightly to its ecosystem
Huawei's Tau Law is being framed in China as a new semiconductor principle, but its strategic value may lie beyond catching TSMC in process nodes. The real question is whether Huawei can combine LogicFolding, optical interconnects, and system-level scaling to reduce China's reliance on Nvidia
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
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
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
For AMD CEO Lisa Su, the current moment presents an opening that Nvidia does not have. Nvidia's high-end chips have repeatedly faced scrutiny and export restrictions in China, and Nvidia CEO Jensen Huang only recently confirmed in May that Nvidia once held as much as 95% market share there. That dominance has since been reset, with the bulk of that share ceding to domestic rival Huawei
Under CEO Lisa Su, AMD is reshaping itself for the age of artificial intelligence. To describe AMD today simply as a hardware company is no longer accurate. As Jensen Huang has often said of Nvidia, his company is "not just a GPU company." AMD is making a similar argument about its own future
