The 2026 World Artificial Intelligence Conference (WAIC) opens in Shanghai on July 17, with Chinese President Xi Jinping set to attend and deliver a keynote speech.
Reports of longer chip lead times have been mounting. ADI has notified customers that, as recovering demand tightens supply, lead times for some analog chip products have stretched to six months, and it has urged customers to place orders early to avoid delivery delays. Meanwhile, a channel player said STMicroelectronics (ST) MCU lead times have extended to 52 weeks, prompting distributors to begin asking customers about demand for all of 2027.
At a humanoid robotics summit in Tokyo in May 2026, I saw a consulting firm's global labor automation map for Physical AI. After returning, I recreated the same map using the firm's research on Digital AI job functions. Placing the two side by side revealed something unexpected.
In the second quarter of 2025, DIGITIMES visited the rapidly expanding Johor-Singapore Special Economic Zone (JS-SEZ) and Wiwynn's massive AI server system integration (SI) factory. Microsoft also granted a media interview, using the occasion to discuss Singapore's role as the hub of the broader ASEAN AI ecosystem.
US President Donald Trump recently claimed that Taiwan's TSMC will double the size of its Arizona fab project, reviving attention on his goal of raising the US share of the global chip market to 50% before the end of his term. TSMC declined to comment on the report, but investors may press the company on the issue at its second-quarter 2026 earnings call.
The AI race is expanding from computing power to data transmission, making optical interconnects a critical battleground for next-generation AI infrastructure.
Reports that Meta is considering leasing out idle AI computing capacity have rattled investors. But treating Meta's predicament as a warning sign for the entire AI industry is a classic case of overgeneralization.
As the world enters an AI-centric era, the global race for technological leadership is no longer defined only by who can build the most advanced models. It is increasingly shaped by who can secure compute, deploy infrastructure at scale, reduce energy constraints, and turn research into commercial capability.
The world's most powerful AI models are encountering a new constraint beyond chips, data and engineering talent: governments increasingly want a say in when frontier systems are released, who may access them and which capabilities should remain restricted.
As generative AI fuels rapid growth in demand for high-performance computing (HPC), the semiconductor industry is shifting from a process race to a materials race. Geckos chairman Shen Tsung-huan says that as chip manufacturing moves to 2nm and even more advanced nodes, gains in AI computing power are no longer just a chip design issue, but are increasingly constrained by the thermal conductivity and high-frequency signal transmission capabilities of materials.
Samsung Electronics' preliminary earnings have shaken financial markets. Drawing on a report from a US brokerage, DIGITIMES Intelligence analyst Luke Lin examined the actual progress of advanced-node capacity expansion at TSMC, Intel, and Samsung, arguing that market expectations in several areas have run ahead of reality.
The UK is pitching itself as a new base and technology partner for Taiwanese electronics suppliers, seeking to turn its AI infrastructure push into a market and investment opportunity for companies in chips, packaging, servers, cooling, power, and data centers.
As generative AI drives rapid growth in high-performance computing (HPC) demand, the semiconductor industry is shifting from process-node competition to materials competition. Geckos chairman Raymond Shen said that once chip manufacturing advances to 2nm and beyond, improvements in AI computing power are no longer just a chip-design issue, but are increasingly constrained by materials' heat dissipation and high-frequency signal transmission capabilities.
