Semiconductors

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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Jensen Huang of Nvidia rules out China Blackwell talks for now

Nvidia CEO Jensen Huang said the company is not in active discussions to sell Blackwell-family AI chips to Chinese firms and has no current plans to ship them. He also clarified remarks about the US-China AI race, saying he intended to acknowledge China’s technical strength rather than predict an outcome.

Huang spoke in Taiwan ahead of meetings with TSMC, as Nvidia expands partnerships and pitches its platforms across regions and industries. The company has added roughly a trillion dollars in value this year and remains the world’s most valuable business despite recent share volatility.

US controls still bar sales of Nvidia’s most advanced data-centre AI chips into China, and a recent bilateral accord did not change that. Officials have indicated approvals for Blackwell remain off the table, keeping a potentially large market out of reach for now.

Analysts say uncertainty around China’s access to the technology feeds broader questions about the durability of hyperscale AI spending. Rivals, including AMD and Broadcom, are racing to win share as customers weigh long-term returns on data-centre buildouts.

Huang is promoting Nvidia’s end-to-end stack to reassure buyers that massive investments will yield productivity gains across sectors. He said he hopes policy environments eventually allow Nvidia to serve China again, but reiterated there are no active talks.

Naver expands physical AI ambitions with $690 million GPU investment

South Korean technology leader Naver is deepening its AI ambitions through a $690 million investment in graphics processing units from 2025.

A move that aims to strengthen its AI infrastructure and drive the development of physical AI, a field merging digital intelligence with robotics, logistics, and autonomous systems.

Beyond its internal use, Naver plans to monetise its expanded computing power by offering GPU-as-a-Service to clients across sectors, creating new revenue opportunities aligned with its AI ecosystem.

Chief Executive Choi Soo-yeon described physical AI as the firm’s next growth pillar, combining robotics, data, and generative AI to reshape both digital and industrial environments. The company already holds a significant share of the global robotics operating system market, underlining its technological maturity.

An investment that marks a strategic shift from software-based AI to infrastructure-driven intelligence, positioning Naver as a leader in integrating AI with real-world applications.

As global competition intensifies, Naver’s model of coupling high-performance computing with robotics innovation signals the emergence of South Korea as a centre for applied AI technology.

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Blackwell stance on China exports holds as Washington weighs tech pace

AI export policy in Washington remains firm, with officials saying the most advanced Nvidia Blackwell chips will not be sold to China. A White House spokesperson confirmed the stance during a briefing. The position follows weeks of speculation about scaled-down variants.

Senior economic officials floated the possibility of a shift later, citing the rapid pace of chip development. If Blackwell quickly becomes superseded, future sales could be reconsidered. Any change would depend on achieving parity in technology, licensing, and national security assessments.

Nvidia’s chief executive signalled hope that parts for Blackwell family products could be supplied from China, while noting there are no current plans to do so. Company guidance emphasises both commercial and research applications. Analysts say licensing clarity will dictate data centre buildouts and training roadmaps.

Policy hawks argue that cutting-edge accelerators should remain in US allied markets to protect strategic advantages. Others counter that export channels can be reopened once hardware is no longer state-of-the-art. The debate now centres on timelines measured in product cycles.

Diplomatic calendars may influence further discussions, with potential leader-level meetings next year alongside major international gatherings. Officials portrayed the broader bilateral relationship as steadier. The industry will track any signals that link geopolitical dialogue to chip export regulations.

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Nexperia chip exports may resume as China softens stance on ban

China’s Ministry of Commerce announced plans to exempt specific Nexperia orders from its export ban, aiming to stabilise the global semiconductor supply chain after the Netherlands seized control of the Chinese-owned Dutch chipmaker.

The ministry stated that exemptions would be granted when the criteria were met, encouraging affected firms to apply.

A move that follows a meeting between Chinese President Xi Jinping and US President Donald Trump in Busan, where both sides reached a framework allowing Nexperia to resume shipments under eased restrictions.

Washington reportedly agreed to pause the 50 percent subsidiary rule, which restricts exports from companies half-owned by entities on its trade blocklist. Wingtech Technology, Nexperia’s Chinese parent, has been under these restrictions since December.

Beijing’s export ban, introduced after the Dutch takeover citing national security concerns, disrupted supplies from Nexperia’s Dongguan factory, which assembles about 70 percent of its products.

China condemned the Netherlands for intervening in corporate affairs, warning that such actions deepen global supply chain instability.

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