Nvidia will showcase its expanding partnerships with South Korean companies at AI Day Seoul, where Samsung Electronics and SK Hynix will present semiconductor development cases using Nvidia AI technologies. LG Electronics and Doosan Robotics will demonstrate robotics technologies, while SK Telecom (SKT), Naver Cloud, and Coupang will discuss the development and operation of AI data centers and infrastructure.

Competition in the AI application-specific integrated circuit (ASIC) market will extend beyond 2028, industry sources said, with MediaTek, Broadcom, and Marvell competing not only for design wins, but also for secure access to wafers, advanced packaging, substrates, and high-bandwidth memory (HBM). The effectiveness of their supply-chain partnerships will determine how much revenue each company can ultimately generate.

Marvell Technology's agreement to buy Lumentum Holdings would give the custom chip designer its own supply of indium phosphide (InP) lasers, one of the scarcest components in AI data center networking, and make it one of the few suppliers spanning both the electrical and optical sides of the link. The deal positions Marvell more directly against Broadcom as connections inside AI clusters move from copper toward optics packaged alongside processors and switches.

Taiwan is aggressively pursuing a core strategy of "Team Taiwan to Team Global," according to Cheng-Wen Wu, Minister of the National Science and Technology Council (NSTC). Wu noted that when AI chips are manufactured in Taiwan, local tech companies are the first to understand their application scenarios and strengths—giving domestic industries a head start in integrating advanced AI into their own manufacturing processes.

The US Department of Commerce is leveraging federal funding and policy initiatives to bolster America's global competitiveness in quantum technology. Its core strategy centers on consolidating fragmented industry demand by backing shared manufacturing platforms through public subsidies and government equity stakes. The Trump administration maintains that developing the domestic quantum sector requires more than just algorithms, chip design, and system-level R&D—it also demands dedicated manufacturing infrastructure capable of serving diverse market players.

Chinese AI chipmaker Iluvatar CoreX has released benchmarks showing its next-generation Tiangai 300 general-purpose GPU outperforming Nvidia's H200 in selected large language model (LLM) inference, long-context processing and multimodal generation workloads.

China's leading electronic design automation (EDA) supplier, Empyrean Technology, plans to acquire a controlling stake in Easy-Logic Technology, a specialist in digital logic optimization, for about CNY219 million (≈ US$32.9 million). The acquisition will address a gap in Empyrean's digital chip design tools and support its development of next-generation solutions for AI chips and 3D integrated circuits (3DIC).

Iluvatar CoreX has reported benchmark results showing its Tiangai 300 AI accelerator outperforming Nvidia's H200 on selected metrics, drawing renewed attention to China's progress in developing domestic alternatives to high-end GPUs. Yet the broader competition extends beyond raw processing power, as Chinese chipmakers seek to narrow the gap with leading international AI computing platforms through chip design, software optimisation and system integration.

Taiwan can manufacture some of the world's most advanced chips, package them into increasingly complex AI systems, and connect much of the surrounding electronics supply chain within a remarkably small geographic footprint.

Taiwan's semiconductor strength is often described today through leading-edge process nodes, advanced packaging capacity, or its pivotal role in the global AI supply chain. At the Taiwan Semiconductor Industry Association's (TSIA) 30th anniversary gathering in Hsinchu, however, industry pioneer Shih Chin-Tay offered a different way to understand that advantage: not as the product of one breakthrough, one company or even one technology cycle, but as the cumulative result of six decades of learning.

The launch of Muse in September across Meta's expanding agent ecosystem has highlighted how quickly AI agents are evolving beyond conventional chatbot architectures, bringing more complex operating requirements and increasingly diversified roles into the definition of what an AI agent can do.

Taiwan already manufactures much of the physical infrastructure on which the AI boom depends. Advanced logic, packaging, substrates, testing, power delivery, cooling, and server assembly can all be sourced through an unusually dense industrial base.

AUO is accelerating its strategic push into optical communications and advanced semiconductor packaging, establishing optical engines and glass core substrates (GCS) as its two primary technological pillars. According to AUO chairman and CEO Paul Peng, while these technologies are still in their early phases and specific operational targets have yet to be finalized, they are projected to make significant contributions to overall revenue within two to three years.

MediaTek reported third-quarter 2026 revenue of NT$168.06 billion (US$5.17 billion), up 10.4% quarter-over-quarter (QoQ) and 18.3% year-over-year, and projected fourth-quarter revenue growth of as much as 32% on accelerating shipments of AI accelerator application-specific integrated circuits (ASICs). The Taiwanese IC design company disclosed the results and outlook at an investor conference on October 30, citing stronger-than-expected customer demand, improved capacity availability, and new smart-device platforms entering mass production.

The AI hardware race is usually measured in nanometers, memory bandwidth, and accelerator performance. But another constraint is emerging much earlier in the development process: whether dozens of specialized suppliers can move fast enough together.

Japan’s Renesas Electronics expects strong demand for AI data centers, industrial applications, and automotive semiconductors to drive 2026 revenue to JPY1.6668 trillion (US$10.55 billion), up 26.4% year-over-year, with its operating margin rising to 33.2%, according to its third-quarter 2026 earnings report.

Realtek Semiconductor quantified its AI business for the first time at an investor conference on October 29, setting a target for high-performance computing (HPC) and edge AI revenue—including automotive and robotics applications—to exceed 30% of total revenue by 2030. These businesses currently account for a high-single-digit percentage of revenue, as AI expands into infrastructure and edge devices.

Microcontroller unit (MCU) major Holtek Semiconductor has secured a substantial order for brushless DC (BLDC) motors, with adoption in Taiwanese server cooling fans slated to begin in 2027, paving the way for steep year-over-year growth. In addition, the company's optical communication products, specifically storage area network (SAN) disk arrays tailored for AI servers, are scheduled to enter mass production in the first quarter of 2027.

Google is deepening its strategic partnership with Foxconn to accelerate AI infrastructure deployment, aiming to cut the time from chip supply to data-center deployment from the traditional 12 to 18 months to about six months, said Rehan Sheikh, vice president of global silicon chip technology and manufacturing at Google Cloud, at Hon Hai Tech Day (HHTD 26) on October 30.

The rapid development of AI robotics applications is driving a sharp increase in semiconductor computing requirements. According to DIGITIMES Intelligence, Nvidia is set to dominate the 2026 AI robotics computing IC market with a 69% share, far outpacing Intel (11%), Qualcomm (5%), and AMD (2%). Beyond raw computing power, Nvidia's comprehensive software ecosystem is the critical factor leaving competitors in its wake.

After The New York Times reported that a female executive at Singapore-based Megaspeed International was under investigation for allegedly conducting espionage activities for China, Nvidia CEO Jensen Huang said the company's dealings with Megaspeed were normal and involved no irregularities.

Intel's growing server business is strengthening its operating recovery, but a factory disruption and a prolonged PC downturn threaten its ability to convert demand into near-term sales. Its third-quarter results show why the turnaround now depends as much on supplying data centers as on reviving the client business that has long anchored the company.

Oracle will offer cloud services powered by Cerebras' AI computing systems in its cloud data centers starting in 2027, giving the wafer-scale chipmaker another major cloud customer. Although the companies did not disclose Oracle's planned Cerebras hardware purchases, the deal highlights the shift toward diversified AI compute resources as inference demand accelerates.

Strong demand for AI applications and cloud services is driving investment in high-performance computing chips and AI servers, prompting Taiwan manufacturers to expand capacity and borrow from banks while retaining cash. At the same time, banks' property-related loan balances continue to decline as credit resources flow into production and the real economy.

Anthropic's "multi-platform resource pool" strategy, disclosed in its S-1 filing, is sending an important signal to the AI chip industry. The company uses Amazon Trainium, Google tensor processing units (TPUs), Nvidia GPUs, and Advanced Micro Devices (AMD) GPUs, integrating computing capacity from different partners into a unified resource pool through software and allocating it across chip platforms based on task requirements.