Semiconductors Archives | Digital Watch Observatory

Finland ranks among EU’s digital leaders

Finland has ranked among the EU’s leading digital economies in the European Commission’s latest State of the Digital Decade report, with the country highlighted for its digital skills, AI leadership, supercomputing capabilities and advanced public services.

The report paints a mixed picture across the EU. While digital adoption, connectivity, cloud services and AI continue to advance, the bloc still faces shortages of digital skills and lags in semiconductor production and globally competitive technology companies. According to the Commission, insufficient investment and market fragmentation remain major obstacles.

Finland performs strongly across a range of digital indicators. Businesses are highly digitalised, the population has above-average digital skills, and the country has developed advanced quantum and semiconductor ecosystems. Electronic public services rank among the EU’s best, 5G coverage is extensive, a national 6G roadmap is already in place, and cybersecurity remains strong, with nearly 80% of businesses implementing cybersecurity measures.

Finland has also played a leading role in shaping the EU’s digital policy agenda by steering the Digital Decade Board’s work on updating the programme’s targets and indicators. The board has proposed new priorities, including digital sovereignty, cybersecurity, sustainable digitalisation and greater data accessibility for AI development. The European Commission is expected to present its formal proposal for revising the Digital Decade Policy Programme in early 2027, following discussions among Member States.

Why does it matter?

Finland’s performance highlights how digital competitiveness is becoming increasingly linked to economic resilience and technological sovereignty. Its strengths in AI, cybersecurity, digital public services and advanced computing demonstrate the type of capabilities the EU is seeking to expand as it reduces dependence on external technology providers.

The proposed updates to the Digital Decade agenda also reflect a broader shift in EU digital policy. Alongside connectivity and digital skills, priorities such as digital sovereignty, cybersecurity and AI-ready data infrastructure are becoming central to Europe’s long-term competitiveness and strategic autonomy.

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UNCTAD warns that strategic investment is becoming more concentrated

Investment in strategic sectors, including AI infrastructure, semiconductors, critical minerals and energy transition technologies, has surged over the past five years. According to UN Trade and Development’s (UNCTAD) World Investment Report 2026, these sectors accounted for 44% of global greenfield investment in 2025, up from 16% in 2020.

The report also highlights a growing concentration of investment among advanced economies. The three largest investor economies accounted for 72% of strategic sector project values in 2025, while the three biggest recipient economies attracted 56%. Low-income and lower-middle-income countries received just 10% of global greenfield investment in strategic sectors between 2020 and 2025, compared with more than 20% in other industries.

At the same time, manufacturing investment outside strategic sectors is declining. The value of announced greenfield manufacturing investment beyond these industries fell by 17% between 2021 and 2025 compared with the 2015–2019 period. The decline was particularly pronounced in developing and least-developed countries, where manufacturing has traditionally played a key role in building productive capacity and creating jobs.

The report also highlights widening differences in technological capabilities. The United States leads outward investment in AI and advanced technologies, while the EU has become the largest destination for those investments. China remains a major investor in critical minerals and downstream supply chains. Between 2016 and 2024, developed economies provided an estimated US$174 billion in industrial subsidies, compared with just US$19 billion in developing economies.

Why does it matter?

The report points to a structural shift in global investment that could deepen the divide between advanced and developing economies. Countries lacking the capital, infrastructure and skills needed to compete in strategic sectors risk missing out on the industries expected to drive future growth and productivity.

Rather than competing directly with the large subsidy programmes of major economies, UNCTAD argues that developing countries should identify targeted opportunities within strategic value chains, such as critical minerals processing, data infrastructure or regional manufacturing networks. Without stronger international cooperation and investment partnerships, the report warns that technological and economic disparities are likely to widen, with implications for global development and geopolitical stability.

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China calls for greater self-reliance in science and technology

Chinese President Xi Jinping has called for faster progress towards high-level scientific and technological self-reliance, arguing that innovation should become the primary driver of China’s modernisation.

Speaking at the national science and technology conference in Beijing, Xi described the 2026–2030 period as critical to achieving China’s goal of becoming a global science and technology leader by 2035.

Xi highlighted China’s recent advances in AI, quantum technology, advanced manufacturing, robotics, pharmaceuticals and space exploration. At the same time, he acknowledged persistent challenges, including gaps in original innovation, inefficient research investment and shortages of high-quality scientific talent.

He called for stronger coordination of national research priorities, greater support for technology transfer, improved intellectual property protection and a financial system better aligned with scientific and technological innovation.

Xi also emphasised the importance of frontier technologies, calling for greater investment in AI, quantum technologies, life sciences, integrated circuits, and strategic areas including deep-sea, deep-space and deep-earth exploration.

He argued that scientific research should become more application-oriented while industry should play a greater role in scientific discovery, strengthening links between research institutions and commercial innovation.

Alongside investment, Xi stressed that technological development must remain secure, ethical and people-centred. He called for stronger governance of AI and other emerging technologies, clearer ethical standards, improved security risk monitoring and greater support for young scientific talent.

China also honoured 258 scientific projects and researchers during the conference, underscoring the country’s continued emphasis on innovation as a strategic national priority.

Why does it matter?

The speech reinforces China’s long term strategy of reducing dependence on foreign technologies while accelerating domestic innovation in critical fields such as AI, semiconductors and quantum computing. It also illustrates how Beijing increasingly views scientific leadership as a foundation of economic competitiveness, national security and geopolitical influence.

By linking research policy, industrial development and AI governance, China is pursuing a coordinated model in which technological innovation is treated as a strategic state priority. That approach is likely to shape global competition in emerging technologies as countries race to build sovereign capabilities in frontier sectors.

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EU proposes Cloud and AI Development Act to boost tech sovereignty

The European Commission has published a proposal for the Cloud and AI Development Act to strengthen Europe’s cloud and AI ecosystem, investment and infrastructure.

CADA forms part of the Commission’s Tech Sovereignty Package and is also linked to the AI Continent Action Plan.

The proposal aims to make it easier and faster to deploy sustainable data centres and cloud infrastructure across the EU.

The Commission said Europe needs more cloud, data centre and computing capacity as demand for AI grows across businesses and public administrations.

It also warned that long permitting procedures, limited access to energy, land and financing, and overreliance on non-EU cloud service providers are holding back Europe’s digital autonomy and resilience.

The Act is intended to accelerate cloud and AI deployment in critical sectors while keeping the European market open to international partners.

The broader Tech Sovereignty Package also includes Chips Act 2.0, an EU Open Source Strategy and a Strategic Roadmap for Digitalisation and AI in Energy.

The proposal will now need to go through the EU legislative process before final rules are adopted.

Why does it matter?

Cloud infrastructure is becoming the foundation for AI deployment, public services and critical industries. CADA shows the EU trying to treat cloud and compute capacity as strategic infrastructure, not only as a commercial service. The proposal could shape data-centre deployment, public procurement and investment in European cloud and AI capacity, while also raising difficult questions about energy demand, semiconductor dependence, market openness and how far digital sovereignty can realistically go.

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NVIDIA unveils RTX Spark for the AI-powered PC era

NVIDIA and Microsoft have introduced RTX Spark, a new Windows PC platform designed for personal AI agents.

NVIDIA describes RTX Spark as a 1-petaflop superchip that combines its AI and graphics stack with Windows-native agent capabilities.

NVIDIA’s Blackwell architecture powers the platform and supports up to 128GB of unified memory.

According to NVIDIA, RTX Spark will allow users to run local AI agents, large language models, creative workflows and advanced games on laptops and compact desktop PCs.

The company said the platform can run 120-billion-parameter large language models with up to 1 million tokens of context locally.

NVIDIA and Microsoft are also introducing new Windows security primitives and NVIDIA OpenShell to help agents run securely on primary devices.

OpenShell will allow users to define what agents can and cannot do, route queries to local models according to privacy policies and mask personal information when cloud models are used.

RTX Spark-powered laptops and compact desktops are expected to be available this autumn from manufacturers including ASUS, Dell, HP, Lenovo, Microsoft Surface and MSI, with Acer and GIGABYTE models to follow.

Why does it matter?

RTX Spark reflects the industry shift towards AI-native personal computers, where more AI processing happens locally on the device. Running agents and large models on PCs could improve privacy, reduce latency and make advanced AI tools less dependent on cloud access. The governance question is whether local agents can operate with clear user permissions, strong containment and meaningful accountability as they gain the ability to search files, interact with apps and execute tasks across a personal device.

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CSIS says Chinese AI models are narrowing the gap with US systems

Chinese AI models are narrowing the gap with leading US systems, according to a new analysis by the Center for Strategic and International Studies.

CSIS said recent releases from Z.ai, Moonshot, DeepSeek and Alibaba-backed Qwen show that China’s rapid progress in AI was not limited to DeepSeek-R1, but reflects a broader pattern of fast technical catch-up.

The analysis points to Z.ai’s GLM-5.2 model, which performs close to the top US closed models in coding and agent-based tasks. It also highlights strong results from Moonshot’s Kimi, DeepSeek V4-Pro and Qwen3.7-Max across software engineering, reasoning and agent benchmarks.

CSIS argues that Chinese models are now only months, rather than years, behind US frontier systems in several practical areas.

The report identifies knowledge distillation, open-weight research communities and efficiency-driven engineering as key factors behind this progress. Chinese labs can learn quickly from stronger models, shared research practices and open-source ecosystems, while US chip export controls have pushed them towards more efficient training and inference strategies.

Cost is another important factor. CSIS said Chinese models are often cheaper to access than leading US closed systems because open-source releases can be hosted by many providers, increasing price competition and making them easier for developers and governments to adopt.

The analysis says US firms still retain major advantages in frontier capabilities, cloud platforms, enterprise products and user feedback loops. However, Chinese models are now capable, affordable and open enough to shape global AI competition.

CSIS argues that US policy should therefore focus not only on protecting technological advantage, but also on building global trust, lowering access costs and ensuring partners see the American AI stack as reliable.

Why does it matter?

The analysis shows that AI competition is not only about which country has the most powerful frontier model. Chinese open-weight models are spreading because they are increasingly capable, cheaper to run and easier to deploy through third-party hosts or local infrastructure. That could shape global adoption, especially for governments, startups and developers that cannot afford or do not want to depend entirely on US closed-model providers. For the US, the challenge is no longer only maintaining a technical lead, but also making its AI ecosystem trusted, affordable and reliable for international partners.

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India and Japan expand strategic AI partnership

India and Japan have agreed to deepen cooperation on AI, linking AI governance, cybersecurity, infrastructure, research and talent development.

In a joint statement, the two countries described AI as a transformative technology with long-term implications for innovation, economic security, governance and the international order.

Both sides are committed to building a safe, secure, trustworthy, inclusive and human-centric AI ecosystem. They also agreed to strengthen cooperation with partners in the Indo-Pacific and the Global South.

The statement identifies international AI governance, safety and cybersecurity as priority areas. India and Japan said they would coordinate in forums including the G20, OECD, Global Partnership on AI and the UN, while supporting responsible innovation and risk-based governance.

The two countries also agreed to cooperate on AI-enabled cybersecurity and the security of AI systems, with particular attention to critical infrastructure. They highlighted the need for safeguards to ensure AI supports children’s learning and growth rather than causing harm.

AI infrastructure is another focus. India and Japan will strengthen cooperation on data centres, GPU and other compute resources, semiconductors and trustworthy supply chains across the AI technology stack.

The statement also supports collaboration on multilingual, open-source and domain-specific AI models, including models for native languages and public-interest applications. Several memoranda were signed, including partnerships involving IIT Bombay, BharatGen, Japan’s National Institute of Informatics, Sarvam, Preferred Networks, IndiaAI and Japan’s Ministry of Economy, Trade and Industry.

Both sides also committed to researcher exchanges, industry-academia collaboration and talent mobility. Japan reaffirmed its goal of welcoming 500 highly skilled AI professionals from India by 2030.

Why does it matter?

The joint statement shows how AI cooperation is becoming part of broader economic and security strategies in the Indo-Pacific. India and Japan are not only discussing AI governance, but also the infrastructure and supply chains needed to build and deploy AI systems, including compute, semiconductors, data centres and talent. The focus on multilingual and open-source models also matters for countries seeking AI systems that reflect local languages, public-interest needs and Global South priorities.

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UAE and US deepen AI partnership under Pax Silica framework

The United Arab Emirates is expanding its AI cooperation with the United States, describing the partnership as a long-term strategic framework centred on investment, trusted technology and joint innovation across multiple sectors.

The UAE is investing across the US AI ecosystem, including semiconductors, AI applications, energy and digital infrastructure. Officials said the partnership reflects years of institutional cooperation, reinforced through continued policy alignment, economic collaboration and high-level engagement.

At the second Pax Silica Summit in Washington, UAE representatives joined international partners in advancing the Joint Statement on AI Opportunity, with 35 countries reaffirming their commitment to innovation-driven policies, private-sector research and resilient technology supply chains. The UAE joined the Pax Silica initiative in January 2026 as part of a broader US$1.4 trillion economic and technology framework.

The partnership also includes major infrastructure and investment projects, including advanced US semiconductor exports to the UAE, a joint AI campus in Abu Dhabi and expanding data centre capacity. Officials said cooperation will continue to deepen through long-term investment, research and technology integration.

Why does it matter?

The partnership illustrates how AI is increasingly shaping strategic relationships between countries, extending beyond research cooperation into semiconductors, computing infrastructure, investment and supply chains. Governments are treating AI capabilities as a foundation of long-term economic competitiveness and technological influence.

It also reflects the growing importance of trusted international technology partnerships. As countries seek secure access to advanced chips, data centres and AI infrastructure, collaborations such as the UAE-US partnership are becoming an important part of broader industrial, economic and geopolitical strategies.

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Canada and Germany strengthen semiconductor supply chains

Canada and Germany have signed a joint declaration of intent to strengthen semiconductor supply chains and deepen industrial cooperation, reinforcing collaboration in a technology that underpins AI, advanced computing and the digital economy.

The declaration was signed on the sidelines of the International Energy Agency’s (IEA) Annual Global Conference on Energy Efficiency by Carlos Leitão, Parliamentary Secretary to Canada’s Minister of Industry, and Stefan Rouenhoff, Parliamentary State Secretary at Germany’s Federal Ministry for Economic Affairs and Energy.

Canada said resilient and diversified semiconductor supply chains are becoming increasingly important as global demand grows for AI, advanced computing and connected technologies.

The declaration establishes a framework for policy dialogue and cooperation on investment, industrial development, technology and research. It also aims to support start-ups, scale-ups and small and medium-sized enterprises while building on both countries’ semiconductor expertise to strengthen competitiveness.

Canada described semiconductors as foundational technologies for the digital economy, highlighting their role in enabling AI and other emerging technologies.

The declaration also supports Canada’s National Artificial Intelligence Strategy: AI for All, particularly its focus on infrastructure, international partnerships and long-term competitiveness. It builds on a series of bilateral initiatives launched since late 2025, including the Canada-Germany Digital Alliance, a joint AI declaration, the Sovereign Technology Alliance, and cooperation on automotive manufacturing, batteries and critical minerals.

A separate February 2026 declaration also expanded bilateral industrial cooperation in auto and battery manufacturing and critical minerals. Officials from both countries said stronger semiconductor supply chains can support innovation, economic resilience and long-term prosperity.

The partnership adds semiconductor supply chains to a wider Canada-Germany agenda focused on trusted advanced technologies, economic security and the next generation of AI-enabled digital infrastructure.

Why does it matter?

Semiconductors have become strategic assets that underpin AI, advanced computing, telecommunications and many other digital technologies. By strengthening cooperation on chip supply chains, Canada and Germany aim to reduce supply chain vulnerabilities, encourage investment and support long-term technological competitiveness.

The agreement also reflects a broader trend of trusted technology partnerships among like-minded countries. Rather than focusing solely on trade, governments are increasingly coordinating industrial policy, research and supply chains to strengthen economic security and reduce dependence on concentrated sources of critical technologies.

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South Korea plans $518 billion semiconductor hub for AI demand

Samsung Electronics and SK Hynix have announced plans to invest a combined 800 trillion won, about $518 billion, in a new semiconductor manufacturing hub in South Korea’s southwest.

The two companies, which together produce around two-thirds of the world’s memory chips, will each build two new fabrication plants outside their existing manufacturing base in Gyeonggi Province.

Samsung’s new facilities are planned for the city of Gwangju, with several possible sites under consideration, including land linked to a military air base planned for relocation.

The investment responds to rising demand for memory chips used in AI data centres, industrial robotics and autonomous vehicles. Existing semiconductor facilities in Gyeonggi Province are expected to face capacity pressure sooner than previously projected.

South Korea’s government is also linking the project to a broader strategy to build a nationwide semiconductor ecosystem. Existing hubs in the Southeast are expected to expand chip component and material production. At the same time, the central Chungcheong region will focus on chip packaging, and data centres will be developed across the country.

The project also supports the government’s goal of spreading major technology investment beyond the Seoul metropolitan area, where much of the country’s semiconductor industry has historically been concentrated.

Why does it matter?

The planned investment shows how AI demand is driving long-term semiconductor capacity expansion at a national scale. Memory chips are central to AI data centres and high-performance computing, and Samsung and SK Hynix remain two of the most important suppliers in the global market. South Korea’s decision to link new chip fabrication with regional development also shows how AI infrastructure is becoming part of broader industrial and economic planning, not only technology strategy.

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