Semiconductors

EU supports Germany’s semiconductor expansion

The European Commission has approved €623 million in German support for two first-of-a-kind semiconductor factories in Dresden and Erfurt.

A funding that will help GlobalFoundries expand its site to create new wafer capacity and will assist X-FAB in building an open foundry designed for advanced micro-electromechanical systems.

Both projects aim to increase Europe’s strategic autonomy in chip production, rather than allowing dependence on non-European suppliers to deepen.

The facility planned by GlobalFoundries will adapt technologies developed under the IPCEI Microelectronics and Communication Technologies framework for dual-use needs in aerospace, defence and critical infrastructure.

The manufacturing process will take place entirely within the EU to meet strict security and reliability demands. X-FAB’s project will offer services that European firms, including start-ups and small companies, currently source from abroad.

A new plant that is expected to begin commercial operation by 2029 and will introduce manufacturing capabilities not yet available in Europe.

In return for public support, both companies will pursue innovation programmes, strengthen cross-border cooperation, and apply priority-rated orders during supply shortages, in line with the European Chips Act.

They will also develop training schemes to expand the pool of skilled workers, rather than relying on the limited existing capacity. Each company has committed to seeking recognition for its facilities as Open EU Foundries.

The Commission concluded that the aid packages comply with the EU State aid rules because they encourage essential economic activity, show apparent incentive effects and remain proportionate to funding gaps identified during assessment.

These measures form part of Europe’s broader shift toward a more resilient semiconductor ecosystem and follow earlier decisions supporting similar investments across member states.

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Big Tech boosts India’s AI ambitions amid concerns over talent flight and limited infrastructure

Major announcements from Microsoft ($17.5bn) and Amazon (over $35bn by 2030) have placed India at the centre of global AI investment trends, offering momentum at a time when analysts frame Indian markets as a ‘hedge’ against a potential global AI bubble.

While India has rapidly adopted AI and attracted substantial funding for data centres and chip manufacturing, including a new collaboration between Intel and Tata Electronics, the country remains a follower rather than a frontrunner in sovereign AI capabilities.

India’s government is preparing to launch its first sovereign AI model, which will support more than 22 languages. Yet its $1.25 billion investment is dwarfed by France’s €117 billion and Saudi Arabia’s $100 billion AI programmes, leaving India far behind in compute availability, R&D depth, and semiconductor infrastructure.

Despite having 2.5 times the global average concentration of AI-skilled professionals, the country faces persistent talent flight due to limited high-end domestic opportunities and a lack of competitive policy incentives.

According to EY and UNCTAD, India’ punches above its weight’ relative to its economic stage, ranking among the top nations in AI talent, startup activity, and scientific publications. Still, funding gaps remain stark: Indian AI startups raised just $1.16 billion, compared to more than $100 billion in the US and nearly $10 billion in China.

India’s emerging strength lies less in foundation-model development and more in downstream AI applications, where cost-efficient tools can drive entrepreneurship and solve local challenges such as agriculture, education, and public service delivery. Apps like MahaVISTAAR, reaching over 15 million farmers, illustrate this direction.

Yet AI also poses a threat to India’s economic backbone. Analysts warn that the country’s IT services sector, which has long been a pillar of growth, is becoming increasingly vulnerable as AI automates core business functions. Underperformance in IT stocks, reduced hiring, and stagnant wages signal early disruption.

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Trump allows Nvidia to sell chips to approved Chinese customers

US President Donald Trump has allowed Nvidia to sell H200 AI chips to approved customers in China, marking a shift in export controls. The decision also covers firms such as AMD and follows continued lobbying by Nvidia chief executive Jensen Huang.

Nvidia had been barred from selling advanced chips to Beijing, but a partial reversal earlier required the firm to pay a share of its Chinese revenues to the US government. China later ordered firms to stop buying Nvidia products, pushing them towards domestic semiconductors.

Analysts suggest the new policy may buy time for negotiations over rare earth supplies, as China dominates processing of these minerals. Access to H200 chips may aid China’s tech sector, but experts warn they could also strengthen military AI capabilities.

Nvidia welcomed the announcement, saying the decision strikes a balance that benefits American industry. Shares rose slightly after the news, although the arrangement is expected to face scrutiny from national security advocates.

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Canada-EU digital partnership expands cooperation on AI and security

The European Union and Canada have strengthened their digital partnership during the first Digital Partnership Council in Montreal. Both sides outlined a joint plan to enhance competitiveness and innovation, while supporting smaller firms through targeted regulation.

Senior representatives reconfirmed that cooperation with like-minded partners will be essential for economic resilience.

A new Memorandum of Understanding on AI placed a strong emphasis on trustworthy systems, shared standards and wider adoption across strategic sectors.

The two partners will exchange best practices to support sectors such as healthcare, manufacturing, energy, culture and public services.

They also agreed to collaborate on large-scale AI infrastructures and access to computing capacity, while encouraging scientific collaboration on advanced AI models and climate-related research.

A meeting that also led to an agreement on a structured dialogue on data spaces.

A second Memorandum of Understanding covered digital credentials and trust services. The plan includes joint testing of digital identity wallets, pilot projects and new use cases aimed at interoperability.

The EU and Canada also intend to work more closely on the protection of independent media, the promotion of reliable information online and the management of risks created by generative AI.

Both sides underlined their commitment to secure connectivity, with cooperation on 5G, subsea cables and potential new Arctic routes to strengthen global network resilience. Further plans aim to deepen collaboration on quantum technologies, semiconductors and high-performance computing.

A renewed partnership that reflects a shared commitment to resilient supply chains and secure cloud infrastructure as both regions prepare for future technological demands.

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Japan aims to boost public AI use

Japan has drafted a new basic programme aimed at dramatically increasing public use of AI, with a target of raising utilisation from 50% to 80%. The government hopes the policy will strengthen domestic AI capabilities and reduce reliance on foreign technologies.

To support innovation, authorities plan to attract roughly ¥1 trillion in private investment, funding research, talent development and the expansion of AI businesses into emerging markets. Officials see AI as a core social infrastructure that supports both intellectual and practical functions.

The draft proposes a unified AI ecosystem where developers, chip makers and cloud providers collaborate to strengthen competitiveness and reduce Japan’s digital trade deficit. AI adoption is also expected to extend across all ministries and government agencies.

Prime Minister Sanae Takaichi has pledged to make Japan the easiest country in the world for AI development and use. The Cabinet is expected to approve the programme before the end of the year, paving the way for accelerated research and public-private investment.

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EU partners with EIB to support AI gigafactories

The European Commission and the European Investment Bank Group (EIB) have signed a memorandum of understanding to support the development of AI Gigafactories across the EU. The partnership aims to position Europe as a leading AI hub by accelerating financing and the construction of large-scale AI facilities.

The agreement establishes a framework to guide consortia responding to the Commission’s informal Call for Expression of Interest. EIB advisory support will help turn proposals into bankable projects for the 2026 AI Gigafactory call, with possible co-financing.

The initiative builds on InvestAI, announced in February 2025, mobilising €20 billion to support up to five AI Gigafactories. These facilities will boost Europe’s computing infrastructure, reinforce technological sovereignty, and drive innovation across the continent.

By translating Europe’s AI ambitions into concrete, large-scale projects, the Commission and the EIB aim to position the EU as a global leader in next-generation AI, while fostering investment and industrial growth.

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NVIDIA platform lifts leading MoE models

Frontier developers are adopting a mixture-of-experts architecture as the foundation for their most advanced open-source models. Designers now rely on specialised experts that activate only when needed instead of forcing every parameter to work on each token.

Major models, such as DeepSeek-R1, Kimi K2 Thinking, and Mistral Large 3, rise to the top of the Artificial Analysis leaderboard by utilising this pattern to combine greater capability with lower computational strain.

Scaling the architecture has always been the main obstacle. Expert parallelism requires high-speed memory access and near-instant communication between multiple GPUs, yet traditional systems often create bottlenecks that slow down training and inference.

NVIDIA has shifted toward extreme hardware and software codesign to remove those constraints.

The GB200 NVL72 rack-scale system links seventy-two Blackwell GPUs via fast shared memory and a dense NVLink fabric, enabling experts to exchange information rapidly, rather than relying on slower network layers.

Model developers report significant improvements once they deploy MoE designs on NVL72. Performance leaps of up to ten times have been recorded for frontier systems, improving latency, energy efficiency and the overall cost of running large-scale inference.

Cloud providers integrate the platform to support customers in building agentic workflows and multimodal systems that route tasks between specialised components, rather than duplicating full models for each purpose.

Industry adoption signals a shift toward a future where efficiency and intelligence evolve together. MoE has become the preferred architecture for state-of-the-art reasoning, and NVL72 offers a practical route for enterprises seeking predictable performance gains.

NVIDIA positions its roadmap, including the forthcoming Vera Rubin architecture, as the next step in expanding the scale and capability of frontier AI.

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Amazon rolls out Trainium3 AI chip to challenge Nvidia’s dominance

AWS has launched its in-house AI processor, Trainium3, marking a fresh push to compete with established players in the AI-hardware market. The chip and its associated UltraServer platform were unveiled at the launch event in Las Vegas.

According to Amazon, servers powered by Trainium3 deliver more than four times the performance of the previous generation while using around 40% less energy. Several AI firms, including startups working on large language models, are already utilising the new hardware to reduce their inference or training costs.

Looking ahead, AWS has signalled plans for a follow-up chip, Trainium4, which is expected to integrate with Nvidia’s NVLink Fusion interconnect technology. That would permit hybrid deployments combining Amazon’s ASICs with traditional GPUs, potentially appealing to AI workloads already built around Nvidia’s ecosystem.

The move highlights a broader trend: major tech firms are increasingly investing in their own AI infrastructure, aiming to reduce dependence on dominant vendors and lower costs. As AWS scales out its custom chips, the AI infrastructure market is poised to become more diverse with price-performance and energy efficiency as key differentiators, rather than raw hardware dominance alone.

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Singapore and the EU advance their digital partnership

The European Union met Singapore in Brussels for the second Digital Partnership Council, reinforcing a joint ambition to strengthen cooperation across a broad set of digital priorities.

Both sides expressed a shared interest in improving competitiveness, expanding innovation and shaping common approaches to digital rules instead of relying on fragmented national frameworks.

Discussions covered AI, cybersecurity, online safety, data flows, digital identities, semiconductors and quantum technologies.

Officials highlighted the importance of administrative arrangements in AI safety. They explored potential future cooperation on language models, including the EU’s work on the Alliance for Language Technologies and Singapore’s Sea-Lion initiative.

Efforts to protect consumers and support minors online were highlighted, alongside the potential role of age verification tools.

Further exchanges focused on trust services and the interoperability of digital identity systems, as well as collaborative research on semiconductors and quantum technologies.

Both sides emphasised the importance of robust cyber resilience and ongoing evaluation of cybersecurity risks, rather than relying on reactive measures. The recently signed Digital Trade Agreement was welcomed for improving legal certainty, building consumer trust and reducing barriers to digital commerce.

The meeting between the EU and Singapore confirmed the importance of the partnership in supporting economic security, strengthening research capacity and increasing resilience in critical technologies.

It also reflected the wider priorities outlined in the European Commission’s International Digital Strategy, which placed particular emphasis on cooperation with Asian partners across emerging technologies and digital governance.

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NVIDIA and Synopsys shape a new era in engineering

The US tech giant, NVIDIA, has deepened its long-standing partnership with Synopsys through a multi-year strategy designed to redefine digital engineering across global industries.

An agreement that includes a significant investment of two billion dollars in Synopsys shares and a coordinated effort to bring accelerated computing into every stage of research and development.

The aim is to replace slow, fragmented workflows with highly efficient engineering supported by GPU power, agentic AI and advanced physics simulation.

Research teams across semiconductor design, aerospace, automotive and industrial manufacturing continue to face rising complexity and escalating development costs. NVIDIA and Synopsys plan to respond by unifying their strengths, rather than relying on traditional CPU-bound methods.

NVIDIA’s accelerated computing platforms will connect with Synopsys tools to enable faster design, broader simulation capability and more precise verification. The collaboration extends to autonomous engineering through AI agents built on Synopsys AgentEngineer and NVIDIA’s agentic AI stack.

Digital twins stand at the centre of the new strategy. Accurate virtual models, powered through Omniverse and Synopsys simulation environments, will allow engineers to test and validate products in virtual space before physical production.

Cloud-ready access will support companies of all sizes, rather than restricting advanced engineering to large enterprises with specialised infrastructure. Both firms intend to promote adoption through a shared go-to-market programme.

The partnership remains open and non-exclusive, ensuring continued cooperation with the broader semiconductor and electronic design ecosystem.

NVIDIA and Synopsys expect accelerated engineering to reshape innovation cycles, offering a route to faster product development and more reliable outcomes across every primary technical sector.

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