Semiconductors

US administration pushes back on proposal to restrict Nvidia sales to China

The White House is urging Congress to reject a bipartisan proposal that would restrict Nvidia from selling advanced AI chips to China and other countries subject to an embargo. The GAIN AI Act would require chipmakers to prioritise US buyers before exporting high-performance hardware.

Lawmakers are debating whether to attach the provision to the annual defence spending bill, a move that could accelerate approval. The White House intervention represents a significant win for Nvidia, which has lobbied to maintain export flexibility amid shifting trade policies.

China was previously a significant market for Nvidia, but the firm has pared back expectations due to rising geopolitical risks. Beijing has also increased scrutiny of US-made chips as it pushes for self-reliance in AI and semiconductor technology.

The policy discussions come shortly after Nvidia posted stronger-than-expected third-quarter earnings and issued an upbeat outlook. CEO Jensen Huang has pushed back against concerns of an AI-driven valuation bubble, arguing demand remains robust.

Nvidia’s shares rose 5 percent after hours following the earnings report, reflecting investor confidence as Washington continues to debate the future of AI chip export controls.

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Foxconn and OpenAI strengthen US AI manufacturing

OpenAI has formed a new partnership with Foxconn to prepare US manufacturing for a fresh generation of AI infrastructure hardware.

The agreement centres on design support and early evaluation instead of immediate purchase commitments, which gives OpenAI a path to influence development while Foxconn builds readiness inside American facilities.

Both companies expect rapid advances in AI capability to demand a new class of physical infrastructure. They plan to co-design several generations of data centre racks that can keep pace with model development instead of relying on slower single-cycle upgrades.

OpenAI will share insight into future hardware needs while Foxconn provides engineering knowledge and large-scale manufacturing capacity across the US.

A key aim is to strengthen domestic supply chains by improving rack architecture, widening access to domestic chip suppliers and expanding local testing and assembly. Foxconn intends to produce essential data centre components in the US, including cabling, networking, cooling and power systems.

The companies present such an effort as a way to support faster deployment, create more resilient infrastructure and bring economic benefits to American workers.

OpenAI frames the partnership as part of a broader push to ensure that critical AI infrastructure is built within the US instead of abroad. Company leaders argue that a robust domestic supply chain will support American leadership in AI and keep the benefits widely shared across the economy.

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Diplomatic progress slows Nexperia crisis

The Dutch government has paused its intervention in chipmaker Nexperia after officials described promising diplomatic progress with China, easing a months-long standoff that had disrupted global supply chains. The suspension follows talks in which Beijing began relaxing export limits it had imposed on Nexperia’s finished chips, restrictions that had deepened shortages for major carmakers including BMW, Honda, Nissan, Volkswagen, and Bosch.

The dispute began in September when the Netherlands seized control of Nexperia from its Chinese owner Wingtech, invoking the Goods Availability Act, a Cold War-era law that had never been used before. Dutch authorities stated that the takeover was necessary to safeguard national security and prevent Wingtech founder Zhang Xuezheng from relocating production to China, citing allegations of mismanagement and attempts to undermine European operations.

Beijing retaliated by restricting chip exports, while management on both sides blocked shipments and orders amid a worsening internal corporate conflict.

Economy Minister Vincent Karremans stated that the government was encouraged by China’s efforts to restore chip supplies and would continue negotiations alongside European and international partners. The EU trade chief Maroš Šefčovič and several major automakers welcomed the announcement, though industry leaders cautioned that it remains too early to predict how quickly supply chains will stabilise.

With the Chinese side now selling stockpiled chips to ease shortages and the European side planning its response, the easing of tensions marks a temporary reprieve in a dispute that highlighted the fragility of Europe’s semiconductor dependencies and the geopolitical risks tied to them.

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AI energy demand strains electrical grids

Microsoft CEO Satya Nadella recently delivered a key insight, stating that the biggest hurdle to deploying new AI solutions is now electrical power, not chip supply. The massive energy requirements for running large language models (LLMs) have created a critical bottleneck for major cloud providers.

Nadella specified that Microsoft currently has a ‘bunch of chips sitting in inventory’ that cannot be plugged in and utilised. The problem is a lack of ‘warm shells’, meaning data centre buildings that are fully equipped with the necessary power and cooling capacity.

The escalating power requirements of AI infrastructure are placing extreme pressure on utility grids and capacity. Projections from the Lawrence Berkeley National Laboratory indicate that US data centres could consume up to 12 percent of the nation’s total electricity by 2028.

The disclosure should serve as a warning to investors, urging them to evaluate the infrastructure challenges alongside AI’s technological promise. This energy limitation could create a temporary drag on the sector, potentially slowing the massive projected returns on the $5 trillion investment.

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Google commits 40 billion dollars to expand Texas AI infrastructure

Google will pour 40 billion dollars into Texas by 2027, expanding digital infrastructure. Funding focuses on new cloud and AI facilities alongside existing campuses in Midlothian and Dallas.

Three new US data centres are planned, one in Armstrong County and two in Haskell County. One Haskell site will sit beside a solar plant and battery storage facility. Investment is accompanied by agreements for more than 6,200 megawatts of additional power generation.

Google will create a 30 million dollar Energy Impact Fund supporting Texan energy efficiency and affordability projects. The company backs training for existing electricians and over 1,700 apprentices through electrical training programmes.

Spending strengthens Texas as a major hub for data centres and AI development. Google says expanded infrastructure and workforce will help maintain US leadership in advanced computing technologies. Company highlights its 15 year presence in Texas and pledges ongoing community support.

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Purdue and Google collaborate to advance AI research and education

Purdue University and Google are expanding their partnership to integrate AI into education and research, preparing the next generation of leaders while advancing technological innovation.

The collaboration was highlighted at the AI Frontiers summit in Indianapolis on 13 November. The event brought together university, industry, and government leaders to explore AI’s impact across sectors such as health care, manufacturing, agriculture, and national security.

Leaders from both organisations emphasised the importance of placing AI tools in the hands of students, faculty, and staff. Purdue plans a working AI competency requirement for incoming students in fall 2026, ensuring all graduates gain practical experience with AI tools, pending Board approval.

The partnership also builds on projects such as analysing data to improve road safety.

Purdue’s Institute for Physical Artificial Intelligence (IPAI), the nation’s first institute dedicated to AI in the physical world, plays a central role in the collaboration. The initiative focuses on physical AI, quantum science, semiconductors, and computing to equip students for AI-driven industries.

Google and Purdue emphasised responsible innovation and workforce development as critical goals of the partnership.

Industry leaders, including Waymo, Google Public Sector, and US Senator Todd Young, discussed how AI technologies like autonomous drones and smart medical devices are transforming key sectors.

The partnership demonstrates the potential of public-private collaboration to accelerate AI research and prepare students for the future of work.

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Baidu launches new AI chips amid China’s self-sufficiency push

In a strategic move aligned with national technology ambitions, Baidu announced two newly developed AI chips, the M100 and the M300, at its annual developer and client event.

The M100, designed by Baidu’s chip subsidiary Kunlunxin Technology, targets inference efficiency for large models using mixture-of-experts techniques, while the M300 is engineered for training very large multimodal models comprising trillions of parameters.

The M100 is slated for release in early 2026 and the M300 in 2027, according to Baidu, which claims they will deliver ‘powerful, low-cost and controllable AI computing power’ to support China’s drive for technological self-sufficiency.

Baidu also revealed plans for clustered architectures such as the Tianchi256 stack in the first half of 2026 and the Tianchi512 in the second half of 2026, intended to boost inference capacity through large-scale interconnects of chips.

This announcement illustrates how China’s tech ecosystem is accelerating efforts to reduce dependence on foreign silicon, particularly amid export controls and geopolitical tensions. Domestically-designed AI processors from Baidu and other firms such as Huawei Technologies, Cambricon Technologies and Biren Technology are increasingly positioned to substitute for western hardware platforms.

From a policy and digital diplomacy perspective, the development raises questions about the global semiconductor supply chain, standards of compute sovereignty and how AI-hardware competition may reshape power dynamics.

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Nvidia stake sale powers SoftBank’s $22.5bn OpenAI bet

SoftBank sold its entire Nvidia stake for $5.83 billion and part of its T-Mobile holding for $9.17 billion, raising cash for OpenAI. Alongside a margin loan on Arm, the proceeds fund a $22.5 billion commitment and other projects. Nvidia slipped 2%; SoftBank referred to it as asset monetisation, not a valuation call.

Executives said the goal is an investor opportunity with balance-sheet strength, including backing for ABB’s robotics deal. Analysts called the quarter’s funding need unusually large but consistent with an AI pivot. SoftBank said the sale recycles capital, not a retreat from Nvidia.

SoftBank has a history with Nvidia: the Vision Fund invested in 2017 and exited in 2019; group ventures still utilise its technology. Projects include the $500 billion Stargate data centre programme, built on accelerated computing. Shares remain volatile amid concerns about the AI bubble and questions regarding the timing of deployment.

Results reflected the shift, with $19 billion in Vision Fund gains helping to double profit in fiscal Q2. SoftBank says its OpenAI stake will rise from 4% to 11% after the recapitalisation, with scope to increase further. The group aims to avoid setting a controlling threshold while scaling exposure to AI.

Management stressed liquidity and shareholder access, flagging a four-for-one stock split and ‘very safe’ funding plans. Further portfolio monetisation is possible as it backs AI infrastructure and applications at scale. Investors will closely monitor execution risks and the timing of returns from OpenAI and its adjacent bets.

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MK1 joins AMD to accelerate enterprise AI and reasoning technologies

AMD has completed the acquisition of MK1, a California-based company specialising in high-speed inference and reasoning-based AI technologies.

The move marks a significant step in AMD’s strategy to strengthen AI performance and efficiency across hardware and software layers. MK1’s Flywheel and comprehension engines are designed to optimise AMD’s Instinct GPUs, offering scalable, accurate, and cost-efficient AI reasoning.

The MK1 team will join the AMD Artificial Intelligence Group, where their expertise will advance AMD’s enterprise AI software stack and inference capabilities.

Handling over one trillion tokens daily, MK1’s systems are already deployed at scale, providing traceable and efficient AI solutions for complex business processes.

By combining MK1’s advanced AI software innovation with AMD’s compute power, the acquisition enhances AMD’s position in the enterprise and generative AI markets, supporting its goal of delivering accessible, high-performance AI solutions globally.

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Winning the AI race means winning developers in China, says Huang of Nvidia

Nvidia CEO Jensen Huang said China is ‘nanoseconds’ behind the US in AI and urged Washington to lead by accelerating innovation and courting developers globally. He argued that excluding China would weaken the reach of US technology and risk splintering the ecosystem into incompatible stacks.

Huang’s remarks came amid ongoing export controls that bar Nvidia’s most advanced processors from the Chinese market. He acknowledged national security concerns but cautioned that strict limits can slow the spread of American tools that underpin AI research, deployment, and scaling.

Hardware remains central, Huang said, citing advanced accelerators and data-centre capacity as the substrate for training frontier models. Yet diffusion matters: widespread adoption of US platforms by global developers amplifies influence, reduces fragmentation, and accelerates innovation.

With sales of top-end chips restricted, Huang warned that Chinese firms will continue to innovate on domestic alternatives, increasing the likelihood of parallel systems. He called for policies that enable US leadership while preserving channels to the developer community in China.

Huang framed the objective as keeping America ahead, maintaining the world’s reliance on an American tech stack, and avoiding strategies that would push away half the world’s AI talent.

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