Qianer Liu

TSMC's capacity constraints are prompting major AI chip designers, including Google and Nvidia, to explore Intel as a backup manufacturer for advanced processors. The shift reflects growing demand for AI chip production that outpaces TSMC's current manufacturing capacity. Intel stands to benefit from diversification of supply chains among leading AI companies.

Nvidia and SK Hynix have signed a multiyear agreement to develop advanced memory chips together, addressing strain on global memory supply driven by AI demand. The deal covers chip design and manufacturing, with memory components intended for Nvidia's Vera Rubin platform, the company's next major AI system. The partnership reflects intensifying competition for specialized memory capacity as AI infrastructure scales.

SK Hynix announced plans to double its memory chip capacity within five years to address persistent AI-driven demand strains on global supply. Chairman Chey Tae-won made the statement in Taipei, signaling that memory constraints will continue to challenge AI data center operations. The expansion targets one of the most significant hardware bottlenecks limiting AI infrastructure deployment.

Intel plans to ship a new AI chip codenamed Crescent by year-end, according to Kevork Kechichian, who leads the company's data centre group. The processor is positioned as a cheaper, simpler alternative to Nvidia's dominant offerings. Intel is betting this approach can carve out market share in the AI chip space where Nvidia currently holds substantial control.

The U.S. Commerce Department issued guidance clarifying that Chinese companies must obtain licenses to purchase advanced U.S. AI chips, even when attempting to circumvent restrictions through overseas subsidiaries. The move closes a potential regulatory loophole that allowed Chinese firms to source powerful AI chips indirectly. This represents a tightening of existing export controls on advanced semiconductor technology.

ByteDance is developing a new AI chip designed to run language models at low cost, modeled after Groq's architecture. The Chinese tech giant is collaborating with InnoStar Semiconductor to integrate the startup's memory technology into the chip. This move represents ByteDance's effort to build independent AI infrastructure amid U.S. export restrictions on advanced semiconductors.

Huawei announced Monday that it is pursuing a new semiconductor development approach to close the gap with leading chipmakers despite U.S. export controls limiting China's access to advanced manufacturing equipment. Board director He Tingbo outlined the strategy without providing specific technical details. The move reflects Huawei's effort to maintain competitive chip capabilities under sustained sanctions pressure.

Anthropic is negotiating with Microsoft to rent servers equipped with Microsoft-designed AI chips to expand its computing capacity. The deal would represent a significant win for Microsoft's chip division, which faced delays in its effort to compete with Nvidia's dominant position in AI infrastructure. Microsoft aims to replicate the in-house chip strategies of Google and Amazon to reduce reliance on Nvidia for its cloud customers.

Google is negotiating with Marvell Technology to develop two specialized AI chips: a memory processing unit to complement Google's tensor processing units, and a new TPU optimized for inference workloads. The effort reflects intensifying competition in inference chips, a critical bottleneck as companies deploy AI models in production systems like autonomous agents. Nvidia has similarly prioritized inference efficiency, recently releasing a language processing unit based on licensed Groq technology.

TSMC raised its 2026 revenue growth forecast to more than 30 percent, up from its January projection, citing sustained surge in AI chip demand that continues to outpace supply. The world's leading advanced chip manufacturer, which produces the majority of cutting-edge semiconductors, is benefiting from persistent customer demand for AI accelerators and processors. The upgrade signals confidence in sustained AI infrastructure spending despite earlier concerns about market saturation.