The government argues that access to large-scale computing infrastructure is becoming essential for researchers, universities, startups and businesses seeking to develop advanced AI systems and remain competitive in an increasingly AI-driven economy.
The investment builds on Spain’s existing role within Europe’s supercomputing ecosystem. The country already hosts AI factories at the Barcelona Supercomputing Center and the Galician Supercomputing Center, while the MareNostrum 5 supercomputer has supported projects ranging from genomic research to climate and digital twin initiatives.
The funding also aims to strengthen Spain’s position in quantum technologies, an area increasingly viewed as strategically important for Europe’s long-term technological autonomy.
The announcement reflects a wider European push to expand sovereign computing capabilities as demand for AI training infrastructure grows worldwide.
By seeking to host an AI gigafactory, Spain hopes to attract investment, support innovation, strengthen domestic technological capabilities and position itself as a central player in Europe’s next-generation AI ecosystem.
Why does it matter?
Access to large-scale computing infrastructure is becoming a strategic prerequisite for advanced AI development. Training frontier AI models, running large-scale simulations and supporting scientific research require computing resources that are increasingly concentrated among a small number of global technology providers. Spain’s investment seeks to strengthen both national and European capacity in this critical area.
The announcement also reflects the EU’s broader push for technological sovereignty. By expanding domestic AI and supercomputing infrastructure, Europe aims to reduce dependence on foreign computing resources, support innovation ecosystems and ensure that advanced technologies are developed within frameworks aligned with European values, regulations and industrial priorities. The competition to host AI gigafactories is therefore as much about economic competitiveness and strategic autonomy as it is about computing power.
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NVIDIA has introduced the Vera Rubin platform, a new supercomputing architecture designed to accelerate scientific research, AI development and large-scale data analysis. NVIDIA says a single rack of the system can deliver performance comparable to some of the world’s most powerful supercomputers.
The platform combines NVIDIA Rubin GPUs, Vera CPUs and high-speed networking technologies to support advanced simulations, AI training and data-intensive research workloads. With more than 7 exaflops of AI performance and 5 petaflops of native FP64 computing power, Vera Rubin is aimed at demanding workloads including climate modelling, computational fluid dynamics, and quantum chemistry.
Several leading research institutions have already announced plans to deploy systems based on the platform. Planned installations include the Blue Lion system at the Leibniz Supercomputing Centre, the Doudna supercomputer at Lawrence Berkeley National Laboratory, and new systems at Los Alamos National Laboratory.
According to NVIDIA, Vera Rubin will provide a unified environment for simulation, AI training, inference, and data processing, enabling researchers to tackle increasingly complex scientific and industrial challenges. Commercial availability is expected later this year.
Why does it matter?
Vera Rubin highlights the growing convergence of AI and high-performance computing, allowing researchers to run advanced simulations, analyse vast datasets, and train AI models on a single platform.
Greater computing power can accelerate breakthroughs in fields such as climate science, energy, healthcare, and materials research, reducing the time and cost required to solve complex scientific problems while strengthening global competitiveness in AI and advanced technology.
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US President Donald Trump has signed an executive order setting deadlines for federal agencies to migrate high-priority systems to post-quantum cryptography.
Executive Order 14409 says large-scale quantum computers could threaten widely used cryptographic systems and create risks for sensitive government data, critical infrastructure and the digital economy. It also highlights ‘harvest now, decrypt later’ attacks, where adversaries collect encrypted information today and decrypt it once quantum capabilities become available.
The order makes it US policy to transition federal information systems to National Institute of Standards and Technology-approved Federal Information Processing Standards for post-quantum cryptography. It also directs the federal government to assist critical infrastructure owners and operators with their own migration planning.
Within 30 days, each federal agency must name a post-quantum cryptography migration lead responsible for cryptographic inventories, migration planning and cross-agency coordination.
The Office of Management and Budget must issue guidance within 90 days requiring agencies to review inventories of high-value assets and high-impact systems (excluding National Security Systems) and submit migration plans.
Federal high-value assets and high-impact systems must transition to post-quantum cryptography for key establishment by 31 December 2030 and for digital signatures by 31 December 2031.
The order also directs CISA, in coordination with NIST, to publish public guidance within 270 days on minimum elements for a cryptographic bill of materials, supporting automated assessment of cryptographic assets in hardware and software.
Procurement rules are also expected to change. The Federal Acquisition Regulatory Council must propose requirements for covered contractors to comply with NIST cryptographic standards, including applicable post-quantum standards, by 31 December 2030.
Why does it matter?
The order gives the US post-quantum transition concrete deadlines and turns cryptographic migration into an operational, procurement and critical infrastructure issue. Quantum-capable attacks remain a future risk, but encrypted data can be stolen now and decrypted later. By requiring inventories, migration leads, contractor obligations and cryptographic bills of materials, the EO pushes agencies and suppliers to understand where vulnerable cryptography is used before quantum threats become practical.
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Researchers and technology experts in Ottawa are contributing to advances in quantum computing, a technology that could transform fields such as drug discovery, clean energy and space exploration by solving highly complex problems beyond the reach of many conventional computers.
Researchers said quantum computing could accelerate scientific discovery and enable breakthroughs that may eventually translate into practical applications across a range of industries. However, the technology also presents significant cybersecurity challenges, as sufficiently advanced quantum computers could eventually undermine widely used encryption methods that protect digital communications and online services.
Industry representatives said Ottawa’s concentration of cryptographic expertise has helped establish this city in Canada as an important centre for quantum cybersecurity research and innovation.
Why does it matter?
Quantum computing has the potential to become one of the most transformative technologies of the coming decades. Its ability to process certain types of complex calculations far more efficiently than conventional computers could accelerate advances in areas such as materials science, pharmaceuticals, energy systems and scientific research.
At the same time, quantum technologies present a major cybersecurity challenge. Many of today’s encryption systems were designed for classical computers and could become vulnerable to future quantum attacks. As a result, governments, universities and technology companies are investing in quantum-safe cryptography and secure communications. Ottawa’s growing role in quantum research reflects a broader international effort to prepare for both the opportunities and security implications of the quantum era.
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The European Commission has welcomed a new G7 Cybersecurity Working Group Declaration aimed at strengthening international cooperation in response to growing cyber threats.
Adopted under France’s G7 Presidency, the declaration calls for coordinated action to address cybersecurity challenges associated with quantum computing, AI, telecommunications infrastructure, and the protection of small and medium-sized enterprises (SMEs).
One of the declaration’s central priorities is accelerating the transition to post-quantum cryptography. As quantum computing capabilities continue to advance, governments and industry are being urged to accelerate preparations for new encryption standards capable of resisting future quantum attacks. The declaration describes migration to quantum-resistant encryption as an urgent cybersecurity priority that organisations should begin addressing now.
AI is another major focus of the declaration. The G7 declaration recognises that AI can both strengthen and threaten cybersecurity. Concerns include AI-enabled cyberattacks, model manipulation, data breaches, and software vulnerabilities.
The European Commission noted that it is preparing an action plan on AI and cybersecurity to help Member States and businesses address emerging risks while strengthening Europe’s cyber resilience.
The declaration also emphasises the importance of resilient telecommunications infrastructure and stronger protection for SMEs. Building on initiatives such as the NIS2 Directive and the Cyber Resilience Act, the EU said it will continue working with international partners to strengthen cybersecurity standards, protect critical infrastructure and support organisations facing increasingly sophisticated cyber threats.
Why does it matter?
The declaration reflects growing international recognition that cybersecurity challenges are increasingly transnational and require coordinated responses. Emerging technologies such as AI and quantum computing are creating new opportunities for innovation, but also introducing new vulnerabilities that could affect governments, businesses and critical infrastructure.
The emphasis on post-quantum cryptography is particularly significant, as organisations worldwide face the long-term challenge of protecting sensitive data against future quantum-enabled attacks. The declaration also highlights the growing importance of international cooperation in building cyber resilience and securing digital ecosystems.
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The five-year initiative is expected to mobilise around $1 billion, with funding reportedly split between the two governments. The collaboration will focus on using AI to accelerate research in advanced fields, including quantum technologies, nuclear fusion, biotechnology, and other strategically important areas.
The Genesis Mission is a US Department of Energy initiative designed to use AI, scientific datasets, national laboratories, universities, and industry partners to accelerate discovery science, energy innovation, and national security research.
Japan’s participation builds on earlier cooperation between the US Department of Energy and Japan’s Ministry of Education, Culture, Sports, Science and Technology on AI-enabled scientific discovery, high-performance computing, and quantum technologies.
Joint projects are expected to involve US national laboratories and Japanese research institutions, including RIKEN and the University of Tokyo. The collaboration is also expected to support AI and robotics-powered autonomous laboratories capable of conducting experiments with limited human intervention.
The partnership reflects a broader shift towards AI for Science, where AI systems are used to generate hypotheses, analyse complex data, automate research workflows, and shorten development timelines in frontier research fields.
Why does it matter?
The collaboration shows how AI for Science is becoming part of strategic technology competition and international research diplomacy. By linking AI, high-performance computing, quantum technologies, fusion, and biotechnology, Japan and the United States are trying to accelerate scientific discovery while strengthening technological leadership in fields with economic, security, and industrial importance.
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The event focuses on how AI methods and new data sources can support financial stability analysis, while also creating new challenges for economies and financial markets.
The conference aims to present research on financial stability and systemic risk analysis using AI methods, novel techniques, and new data sources. Topics include the use of large language models and trustworthy AI, changing interdependencies in financial markets, cybersecurity and operational risks, and AI combined with quantum computing as a possible source of new systemic risks.
The programme also covers more traditional systemic risk analytics and macroprudential policy tools, including early-warning indicators, network and contagion analysis, macro stress-testing, big data analytics, market-based finance, and geopolitical risk modelling.
Speakers include Bank of Finland Governor and ESRB First Vice-Chair Olli Rehn, who will address systemic risk, resilience, and competitiveness in a changing technological landscape. Other sessions will examine systemic cyber risk in financial networks, AI and risk-taking in banking, generative AI in economics and finance research, and AI-related financial system interdependencies.
The hybrid conference will include keynotes, panel discussions, presentations, and poster sessions, with online participation available.
Why does it matter?
The conference shows that AI is becoming a financial stability issue, not only a tool for efficiency or market analysis. Central banks and systemic risk authorities are examining how AI can improve risk detection, stress testing, and data analysis, while also creating new vulnerabilities through cyber risk, operational dependencies, market interconnections, and potential herding behaviour.
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The Computers, Privacy and Data Protection (CPDP) conference is an annual gathering that brings together academics, policymakers, industry representatives, civil society, students, and EU institutions to discuss emerging digital policy challenges. This year’s theme was ‘Competing Visions, Shared Futures’, the 19th in the series, and it hosted approximately 150 panels over the span of 3 days in Brussels.
What is CPDP?
CPDP’s value lies in its multidisciplinary approach. With academics presenting their work or debating topical issues, as well as with industry and policy experts bringing their expertise to the table, the event creates a space for honest conversations among participants.
The conference is sponsored by organisations such as Google, TikTok, Apple, as well as the European Data Protection Supervisor (EDPS), European Union Agency for Fundamental Rights (FRA) and VBU. Google even presented its Banana AI model in a photo booth, allowing participants to modify photos they took in the booth.
Alongside panels, CPDP hosts an array of workshops, short films, artwork, radio programming, promotion booths, dedicated DPO, youth, finance and IT tracks, book launches, and pop-up exhibitions. The event always closes the day in style with an open bar and a party to chat and network at.
CPDP is not a typical conference with just panels, attendees, moderators, and lengthy speeches. The conference inspires creativity and gives the freedom to achieve it. This was proven by the diverse topics showcased in the event’s schedule over the three days.
From a fireside chat with the artist, Simon Denny, behind the conference’s art, who uses AI as a medium in some of his work, to typical discussions about the Digital Omnibus or tracking period apps, all the way to an exiled journalist talking about Russian internet censorship. There was something for everyone.
Image via Magnific
What was presented?
The breadth of topics discussed at CPDP offers insight into the issues currently shaping Europe’s digital policy agenda. There were approximately 150 panels in total, with data protection, AI, the Digital Omnibus and the topics of digital sovereignty receiving the most attention. Data protection received the most attention overall, as 33 panels were dedicated to the topic. This was followed by 26 panels on AI, 12 on the Digital Omnibus, 10 on digital sovereignty, and 7 on child-related protection.
The distribution of panels reflects the growing prominence of AI in digital policy discussions. However, data protection topics, including privacy and the GDPR, are still the frontrunners in terms of topic relevance. Newer and emerging topics reveal what is topical in the digital world.
Growing concerns over US tech reliance have intensified discussions about EU digital sovereignty. Alongside this, another heavily debated and sensitive topic is child protection in the online context and its generative AI implications, which raises questions about how to better protect children online.
Emerging topics at CPDP
Digital sovereignty is a challenging topic as it encompasses a lot and has yet to be defined, meaning that taking action can look different for a wide variety of actors. Several discussions framed digital sovereignty as a pathway towards greater digital independence and reduced reliance on external technology providers. In order to try to achieve digital sovereignty, public procurement should be steered away from non-EU actors and towards EU businesses to develop a European stack.
Yes, private partnerships are important, but public ones set the tone. Several participants argued that public procurement choices will play an important role in determining whether EU can strengthen domestic digital capabilities and reduce strategic dependencies. Digital sovereignty needs to come from all corners of the market and society; that is the challenge.
A very interesting panel on data protection and AI, the GDPR, and privacy occurred. In Academic Session I, Stephanie von Maltzan presented findings about her groundbreaking research on LLM unlearning. The larger the LLM, the more data points it will be trained on and the more complex its ‘web’ will be.
Removing data points is not a common practice, given how data points interact with each other, meaning that complexity overrides certain fundamental rights. For example, when data subjects invoke their right to erasure under Article 17 of the GDPR, they may request that certain data be deleted in an LLM, yet this request is difficult to carry out in practice.
The research highlights one of the emerging challenges at the intersection of AI governance and data protection. She presents a two tier model in which the actively deployed LLM is accompanied by a parallel ‘shadow’ model.
After receiving a valied erasure request, the ‘shadow model’ would undergo the necessary unlearning processes to remove the relevant data. In the second tier, in a scheduled update, the ‘shadow’ model, which had undergone unlearning, would replace the initial LLM, thereby upholding data subject requests.
Apart from these insightful exchanges of knowledge on AI, digital sovereignty and data protection, the conference offered practical workshops on how to brainstorm re-writing the proposed Article 88b of the Omnibus, data protection officer and cybersecurity crisis scenarios, as well as open conversations about how to protect children in online environments.
Remaining questions
The conference also highlighted several unresolved policy questions that continue to shape European digital governance debates.
Regarding the Digital Omnibus, would companies scale up overnight if we removed regulations?
Does digital sovereignty need/have a definition, or should it be left to the meaning of ‘digital independence’?
Open markets vs data protection, where is the balance?
Regarding digital sovereignty, which clouds should be used in the EU?
Should simplification mean using the once-used definition of personal data by the CJEU, or sticking to the definition relied on in law, cases, and practice?
In order to protect EU sovereignty, should parts of the stack be a public utility?
Why does it matter?
CPDP 2026 demonstrated that while privacy and data protection remain central pillars of European digital policy, debates around AI governance, digital sovereignty and online child protection are rapidly gaining prominence.
The discussions highlighted the growing challenge of balancing innovation, competitiveness, fundamental rights and strategic autonomy as Europe defines its digital future.
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Microsoft has introduced Majorana 2, its next-generation topological quantum chip, alongside the general availability of Microsoft Discovery, an AI-powered research platform designed to accelerate scientific discovery.
The company says the new chip delivers a 1,000-fold improvement in qubit reliability compared with the previous generation, representing a step towards more scalable quantum computing.
Majorana 2 incorporates a new materials stack based on lead superconductors, enabling a mean qubit lifetime of 20 seconds, with some qubits remaining stable for up to 1 minute. Microsoft says the improvement has allowed it to shorten its projected timeline for a scalable quantum computer, aiming for 2029.
A key element of the announcement is the role of Microsoft Discovery, the company’s agentic AI platform for scientific research and development. Microsoft said its quantum team used specialised AI agents to automate measurements, optimise fabrication processes, analyse large datasets, identify previously unnoticed flaws, and generate new research hypotheses.
According to Microsoft, agentic AI has become a regular part of its quantum research workflow, supporting scientists and engineers as they manage complex materials, fabrication, software, and measurement challenges.
The company also announced that Microsoft Discovery is now generally available for organisations conducting research in sectors such as life sciences, materials science, chemicals, energy, manufacturing, and consumer goods. A free local application is also being released in preview, allowing individual researchers to access core AI-driven research capabilities through a GitHub Copilot account.
Why does it matter?
Quantum computing still faces major barriers around qubit stability, reliability, error correction, and scalability. Microsoft’s announcement is significant because it links progress in quantum hardware with the use of agentic AI in scientific workflows. If the company’s roadmap holds, AI-assisted research could help accelerate progress towards practical quantum systems, with potential long-term implications for materials science, energy, health, chemistry, and other fields that depend on complex simulation.
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Researchers at the University of California, Riverside, have advanced understanding of how quantum wave functions behave in ultra-thin layered materials, a development that could eventually improve solar energy technologies and support future quantum computing systems.
The findings show that electric fields can be used to control the position and behaviour of quantum wave functions in materials only a few atoms thick. Experiments showed that wave functions can shift between layers or exist in multiple layers simultaneously through quantum superposition, affecting a material’s optical properties.
The researchers also drew parallels with natural systems such as photosynthesis, where quantum processes are believed to support highly efficient energy transfer. By studying similar mechanisms in engineered materials, scientists hope to improve control over energy conversion and transport, particularly in solar technologies where energy losses remain a major challenge.
Researchers are also exploring whether vibrations can be used to control quantum states, potentially enabling new types of ‘quantum vibronic switches’. The findings could have applications beyond energy systems, including quantum computing, sensing and photonic technologies.
Why does it matter?
The research highlights progress towards actively controlling quantum behaviour in engineered materials, an important step in the development of practical quantum technologies. Such control could enable more efficient energy systems and improve the performance of future quantum devices.
The findings also illustrate how insights from natural processes such as photosynthesis can inform the design of next-generation materials for computing, sensing and renewable energy applications.
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