The US administration has approved the export of Nvidia’s H200 AI chips to China, reversing years of tight US restrictions on advanced AI hardware. The Nvidia H200 chips represent the company’s second-most-powerful chip series and were previously barred from sale due to national security concerns.
The US president announced the move last month, linking approval to a 25 per cent fee payable to the US government. The administration said the policy balances economic competitiveness with security interests, while critics warned it could strengthen China’s military and surveillance capabilities.
Under the new rules, Nvidia H200 chips may be shipped to China only after third-party testing verifies their performance. Chinese buyers are limited to 50 per cent of the volume sold to US customers and must provide assurances that the chips will not be used for military purposes.
Nvidia welcomed the decision, saying it would support US jobs and global competitiveness. However, analysts questioned whether the safeguards can be effectively enforced, noting that Chinese firms have previously accessed restricted technologies through intermediaries.
Chinese companies have reportedly ordered more than two million Nvidia H200 chips, far exceeding the chipmaker’s current inventory. The scale of demand has intensified debate over whether the policy will limit China’s AI ambitions or accelerate its access to advanced computing power.
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The United Arab Emirates has joined Pax Silica, a US-led alliance focused on AI and semiconductor supply chains. The move places Abu Dhabi among Washington’s trusted technology partners.
The pact aims to secure access to chips, computing power, energy and critical minerals. The US Department of State says technology supply chains are now treated as strategic assets.
UAE officials view the alliance as supporting economic diversification and AI leadership ambitions. Membership strengthens access to advanced semiconductors and large-scale data centre infrastructure.
Pax Silica reflects a broader shift in global tech diplomacy towards allied supply networks. Analysts say participation could shape future investment in AI infrastructure and manufacturing.
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TSMC reported a strong fourth-quarter performance, posting a 35 percent rise in profit to a record level, supported by sustained demand for advanced chips.
The company forecast robust growth for 2026, citing continued customer interest and tight capacity, while highlighting expectations for a significant increase in revenue in the first quarter of the year.
The Taiwanese semiconductor manufacturer confirmed that capital spending reached US$40.9 billion in 2025, slightly above earlier guidance, and indicated further increases ahead, with investment potentially rising to as much as US$56 billion in 2026 and accelerating later in the decade.
Ongoing projects include additional manufacturing capacity in the US, expansion in Japan, and continued investment in Taiwan.
TSMC also signalled that more US facilities may be planned, following earlier commitments to large-scale investment in Arizona.
Developments come amid discussions between Taiwan and the US on trade and tariffs, as well as broader policy efforts in Washington to encourage domestic semiconductor production.
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Gadget makers face rising costs as AI drives intense demand for memory chips. Supplies of DRAM and storage components have tightened across global markets.
Manufacturers have shifted production towards AI data centres, squeezing availability for consumer devices. Analysts warn the memory shortage could extend well into next year.
Higher prices are already affecting laptops, smartphones and connected devices. Some companies are redesigning products or limiting features to manage the costs of chip components.
Industry experts say engineers are writing leaner software to reduce memory use. The AI surge is marking the end of an era of cheap and abundant memory.
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Canadian quantum computing company Photonic has raised $130 million in the first close of a new investment round led by Planet First Partners. New backers include RBC and TELUS, alongside returning investors.
The funding brings Photonic’s total capital raised to $271 million and supports the development of fault-tolerant quantum systems. The company combines silicon-based qubits with built-in photonic connectivity.
Photonic’s entanglement-first architecture is designed to scale across existing global telecom networks. The approach aims to enable large, distributed quantum computers rather than isolated machines.
Headquartered in Vancouver, Photonic plans to utilise the investment to accelerate key product milestones and expand its team. Investors see strong potential across finance, sustainability, telecommunications and security sectors.
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China’s AI sector could narrow the technological AI gap with the United States through growing risk-taking and innovation, according to leading researchers. Despite export controls on advanced chipmaking tools, Chinese firms are accelerating development across multiple AI fields.
Yao Shunyu, a former senior researcher at ChatGPT maker OpenAI and now Tencent’s AI scientist, said a Chinese company could become the world’s leading AI firm within three to five years. He pointed to China’s strengths in electricity supply and infrastructure as key advantages.
Yao said the main bottlenecks remain production capacity, including access to advanced lithography machines and a mature software ecosystem. Such limits still restrict China’s ability to manufacture the most advanced semiconductors and narrow the AI gap with the US.
China has developed a working prototype of an extreme-ultraviolet lithography machine that could eventually rival Western technology. However, Reuters reported the system has not yet produced functioning chips.
Sources familiar with the project said commercial chip production using the machine may not begin until around 2030. Until then, Chinese AI ambitions are likely to remain constrained by hardware limitations.
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Taiwan aims to train 500,000 AI professionals by 2040, backed by a NT$100 billion (US$31.6 billion) government venture fund. President Lai Ching-te announced the 2026 AI talent forum in Taipei.
The government’s 10-year AI plan includes a national computing centre and the development of technologies such as silicon photonics, quantum computing, and robotics. President Lai said that national competitiveness depends on both chipmaking and citizens’ ability to utilise AI across various disciplines.
To achieve these goals, AI training courses are being introduced for public sector employees, and students are being encouraged to acquire AI skills. The initiative aims to foster cooperation between government, industry, and academia to drive economic transformation.
With a larger pool of AI professionals, Taiwan hopes to help small and medium-sized enterprises accelerate digital upgrades, enhance innovation, and strengthen the nation’s global competitiveness in emerging technologies.
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The US administration’s new AI action plan frames global development as an AI race with a single winner. Officials argue AI dominance brings economic, military, and geopolitical advantages. Experts say competition is unfolding across multiple domains.
The United States continues to lead in the development of advanced large language and multimodal models by firms such as OpenAI, Google, and Anthropic. American companies also dominate global computing infrastructure. Control over high-end AI chips and data-centre capacity remains concentrated in US firms.
Chinese companies are narrowing the gap in the practical applications of AI. Models from Alibaba, DeepSeek, and Moonshot AI perform well in tasks such as translation, coding, and customer service. Performance at the cutting edge still lags behind US systems.
Washington’s decision to allow limited exports of Nvidia’s H200 AI chips to China reflects a belief that controlled sales can preserve US leadership. Critics argue the move risks weakening America’s computing advantage. Concerns persist over long-term strategic consequences.
Rather than a decisive victory for either side in the AI race, analysts foresee an era of asymmetric competition in AI. The United States may dominate advanced AI services, but China is expected to lead in large-scale industrial deployment within the evolving AI race.
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Nvidia used CES in Las Vegas to signal its next push in AI hardware, with chief executive Jensen Huang unveiling a new AI chip designed to deliver more computing power with lower energy use. The chip, named Vera Rubin, is scheduled to ship in the second half of the year.
Huang said the Rubin platform would let companies train AI models with far fewer chips than earlier generations. The redesign is also intended to lower the cost and energy demands of running AI services.
The move comes as demand for AI infrastructure accelerates, straining power supplies and intensifying competition. Rivals and major customers developing their own chips are putting pressure on Nvidia to improve efficiency.
Alongside chips, Nvidia highlighted its growing focus on autonomous vehicles. The company said new AI software would support self-driving development for carmakers and mobility firms, with vehicles using the chipmaker’s technology expected to ship later this year.
Huang said AI, robotics, and autonomy are central to the company’s long-term strategy, as the company seeks to expand beyond data centres. Rising competition and geopolitical scrutiny remain challenges, but Nvidia is betting that more efficient chips will keep it at the centre of the AI boom.
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AMD used CES 2026 to position AI as a default feature of personal and commercial computing. The company said AI is no longer limited to premium systems. Instead, it is being built directly into processors for consumer PCs, business laptops, compact desktops, and embedded platforms.
Executives described the shift as a new phase in AI adoption. CEO Lisa Su said usage has grown from early experimentation to more than one billion active users worldwide. Senior vice president Jack Huynh added that AI is redefining the PC by embedding intelligence, performance, and efficiency across devices.
The strategy centres on the Ryzen AI 400 Series and Ryzen AI PRO 400 Series processors. These chips integrate neural processing units delivering up to 60 TOPS of local AI compute. Built on Zen 5 architecture and XDNA 2 NPUs, they target Copilot+ PCs and enterprise deployments.
AMD also expanded its Ryzen AI Max+ portfolio for ultra-thin laptops, mini-PCs, and small workstations. The processors combine CPU, GPU, and NPU resources in a unified memory design. Desktop users saw the launch of the Ryzen 7 9850X3D, while developers were offered the Ryzen AI Halo platform.
Beyond PCs, AMD introduced a new Ryzen AI Embedded processor lineup for edge deployments. The chips are aimed at vehicles, factories, and autonomous systems. AMD said single-chip designs will support real-time AI workloads in robotics, digital twins, smart cameras, and industrial automation.
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