Artificial intelligence Archives | Page 4 of 677

Spain backs AI gigafactory to boost European technological sovereignty

Spain has approved a €719 million investment in a national AI gigafactory project aimed at expanding advanced computing capacity and strengthening European technological sovereignty.

The investment was authorised by Spain’s Council of Ministers through the Ministry for Digital Transformation and Public Service. The investment will be channelled through the Spanish Society for Technological Transformation (SETT), which will establish a public-private consortium to develop the project and submit a bid under a forthcoming European Commission call for AI gigafactories.

The government said the project is intended to expand European access to advanced computing resources, reduce technological dependencies and support AI development under European regulatory frameworks.

The planned Spanish bid will use a multi-site model, with locations in Móra la Nova in Tarragona and San Fernando de Henares in Madrid. The government said the AI gigafactory is designed as a large-scale industrial initiative and could become part of one of Europe’s main AI infrastructures.

Spain’s Minister for Digital Transformation and Public Service, Óscar López, said the investment supports technological sovereignty, reindustrialisation and leadership in reliable and sustainable AI. He argued that greater European access to advanced computing resources would accelerate innovation, support scientific research and enable public administrations to develop more advanced and secure digital services.

According to the government, AI gigafactories are specialised data centres designed to host hundreds of thousands of GPUs required to train and deploy advanced AI models. These include large language models and advanced computer vision systems.

The ministry said such facilities differ from conventional data centres because they are specialised for the large-scale computing capacity required by the next generation of AI. The ministry noted that infrastructure for training frontier AI models is currently dominated by US hyperscalers and, to a lesser extent, China’s domestic AI ecosystem.

Spain said the AI gigafactory project would support European efforts to build sovereign supercomputing hubs through EuroHPC, which includes the MareNostrum 5 supercomputer at the Barcelona Supercomputing Center, and programmes such as PERTE Chip.

The government said an AI gigafactory would benefit startups, SMEs, large companies, universities, research centres and public administrations that need significant computing capacity to develop advanced AI. It would also allow the European ecosystem to train, test, and deploy AI models without depending entirely on foreign providers.

The project is structured through a public-private consortium whose composition is still being finalised. Spain said the scale of the initiative requires a combination of public leadership, industrial capabilities, financing and technological expertise.

The ministry said SETT’s participation will provide public strategic direction, coordination, and execution capacity. The operation also builds on Spain’s existing AI infrastructure ecosystem, including two AI Factories linked to EuroHPC: the Barcelona Supercomputing Center and the Galician Supercomputing Center, both supported by Spanish government funding.

Why does it matter?

The announcement reflects the growing importance of computing infrastructure in the global AI race. Access to large-scale compute resources has become a strategic requirement for training and deploying advanced AI systems, yet much of that capacity remains concentrated among a small number of US technology companies and, increasingly, Chinese providers.

Spain’s investment, therefore, goes beyond digital infrastructure. It forms part of a broader European effort to strengthen technological sovereignty, support domestic innovation ecosystems and reduce dependence on foreign AI platforms. If successful, the project could provide startups, research institutions, public administrations and businesses with greater access to advanced computing resources while reinforcing the EU’s ambitions to build a more competitive and autonomous AI ecosystem.

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UK cyber agency warns of growing vulnerability risks from Frontier AI

The UK’s National Cyber Security Centre (NCSC) has issued guidance for network defenders on managing the growing risk associated with software vulnerabilities discovered using Frontier AI.

The guidance states that Frontier AI models represent the most advanced AI systems and have already demonstrated the ability to identify vulnerabilities in software products. According to the NCSC, this has significant implications for the threat landscape because Frontier AI can help both defenders and threat actors identify weaknesses at greater speed and scale. The UK’s National Cyber Security Centre has issued guidance for network defenders on managing the growing risk from software vulnerabilities discovered with Frontier AI.

The guidance states that Frontier AI models represent the most advanced AI systems and have demonstrated the ability to discover vulnerabilities in software products. The NCSC says this has implications for the threat landscape because Frontier AI can help both defenders and threat actors identify weaknesses more quickly.

The NCSC emphasises that organisations using AI for vulnerability discovery should do so within secure and controlled environments. It recommends limiting what the AI system can access, ideally using it only in testing or development environments, running it through a service account with only necessary permissions, and placing it in a sandboxed environment.

Organisations should also consider legal, contractual, and security obligations before using AI-as-a-service tools for vulnerability discovery. Sending source code, intellectual property or other sensitive information to external AI providers could introduce additional security, confidentiality and compliance risks.

The NCSC notes that AI-assisted vulnerability discovery is only effective if organisations have the processes and resources needed to manage the findings. That means having processes for patch management, vulnerability identification, prioritisation, validation, remediation, and reporting, as well as the ability to filter false positives and address root causes rather than only individual flaws.

The NCSC stresses that Frontier AI should complement, rather than replace, human cybersecurity expertise. Staff with experience in cybersecurity or the relevant IT systems should guide and validate AI-based vulnerability discovery to improve speed and accuracy.

The NCSC also warns that threat actors are increasingly using Frontier AI to identify and exploit vulnerabilities, potentially accelerating cyberattack timelines. Frontier AI may reduce the time between discovery and exploitation of newly published vulnerabilities, leaving organisations with less time to patch. The guidance says organisations should therefore adopt an assume-compromised mindset.

The NCSC recommends that organisations meet minimum cybersecurity standards, apply defence-in-depth principles, monitor networks and endpoints for suspicious behaviour and maintain a strong incident response plan.

The guidance also urges organisations to reduce the number of systems exposed to the internet, especially high-risk systems such as admin login panels, legacy systems, and operational technology. Organisations should identify internet-accessible systems and assess whether they need to remain exposed.

The guidance also highlights the growing importance of software supply chain security. Organisations should understand the commercial software, cloud services, open-source software, and dependencies they use, review supplier security and AI assurance policies, apply updates quickly, and use software bills of materials or similar tools to identify vulnerable dependencies.

The NCSC says Frontier AI is likely to be used extensively to discover vulnerabilities in open-source software because source code is accessible. It also notes that open-source supply chains have already been targeted through malware campaigns affecting major packages.

Why does it matter?

The guidance reflects a growing shift in cybersecurity as advanced AI systems become capable of identifying software vulnerabilities at unprecedented speed. While these capabilities can help defenders improve security testing and vulnerability management, they can also enable attackers to discover and exploit weaknesses more quickly, potentially reducing the time organisations have to respond.

The NCSC’s recommendations also point to a broader governance challenge surrounding AI adoption in cybersecurity. Organisations must not only defend against AI-enabled threats but also ensure that their own use of AI tools does not introduce new risks related to sensitive data, software supply chains or overreliance on automated systems. As Frontier AI capabilities continue to improve, cyber resilience will increasingly depend on combining AI-driven analysis with strong human oversight, secure development practices and effective incident response.

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EU’s 2026 State of the Digital Decade report highlights progress and remaining challenges

The European Commission’s 2026 State of the Digital Decade report shows that the EU continues to make progress towards its digital transformation goals, although significant structural challenges remain on the path to its 2030 targets.

The report highlights progress in digital infrastructure, business digitalisation and public services. Basic 5G coverage now reaches 96.8% of households, while nearly one in five businesses uses AI.

AI adoption accelerated significantly during 2025, increasing by 48% compared with the previous year. More than 60% of Europeans now possess at least basic digital skills.

Despite the progress, the Commission identified several areas requiring urgent attention. However, the EU currently accounts for only 9% of the global semiconductor market, well below its target of reaching 20% by 2030.

Europe also remains heavily dependent on non-EU cybersecurity suppliers and continues to face shortages of ICT specialists, particularly women in digital professions.

The report also revealed strong public support for digital sovereignty and technological self-reliance. According to a new Eurobarometer survey, most citizens support greater investment in local digital infrastructure, reduced dependence on foreign technologies and stronger regulation of AI.

Citizens also identified digital health, green technologies, connectivity and AI as areas likely to deliver the greatest benefits over the next decade.

Why does it matter?

The report provides one of the most comprehensive assessments of Europe’s progress towards its 2030 Digital Decade objectives and offers insight into the EU’s broader competitiveness agenda. Strong growth in AI adoption, connectivity and digital public services suggests that digital transformation is accelerating across the Union.

At the same time, the findings highlight persistent challenges related to technological sovereignty. Europe’s limited share of the global semiconductor market, continued dependence on foreign technology suppliers, and ongoing digital skills shortages could constrain its long-term competitiveness. As the EU increasingly links economic resilience, security and digital policy, addressing these gaps will be critical to achieving its 2030 ambitions and strengthening strategic autonomy in key technologies.

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IWF backs Pope Leo XIV call for responsible AI development

The Internet Watch Foundation has welcomed Pope Leo XIV’s reflections on AI, arguing that AI systems must be developed with stronger safeguards to protect children from abuse.

In a blog post, the IWF said the Pope’s message that technology should serve the common good and remain subject to human judgement and accountability reflects the risks its analysts are already seeing online.

The organisation warned that AI is being used to generate highly realistic child sexual abuse images and videos at scale. It said the number of AI-generated child sexual abuse videos identified by the IWF in 2025 increased by more than 260%, with nearly two-thirds falling into the most severe category of abuse.

The IWF also raised concerns about AI-nudification tools, which can generate realistic sexualised images of children and other individuals. Following the Child Dignity in the Artificial Intelligence Era conference in Rome, the organisation joined more than 100 organisations and individuals in supporting calls for a global ban on such tools.

The IWF said AI safety should be built into products from the earliest stages of development. Through its Safety by Design work, the organisation is calling for companies to assess, test and mitigate risks before AI systems reach the public.

It also called for stronger regulation, global alignment and enforceable safety-by-design standards to prevent the creation and spread of AI-generated child sexual abuse material.

Why does it matter?

The IWF’s warning shows how generative AI is creating urgent child protection risks, especially through realistic synthetic abuse material and nudification tools. The issue is no longer only content moderation after harm occurs; it increasingly concerns model design, testing, deployment and accountability before AI systems reach users. That makes safety by design, developer responsibility and international coordination central to AI governance.

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EPO and Jio discuss AI, 5G and 6G patent strategy

The European Patent Office held a high-level online meeting with Jio Platforms to discuss patent quality, innovation and developments in the European patent system.

The meeting formed part of the EPO’s 2026 Quality Action Plan and wider user engagement with companies using the European patent system. Jio Platforms, India’s largest mobile network operator, is described by the EPO as an increasingly active user of the system.

Discussions covered AI, 5G, future 6G technologies, satellite communications and automation. Jio highlighted Europe’s growing importance for its patent strategy and outlined a global patent portfolio covering India, Europe, the United States and other jurisdictions.

A significant part of the exchange focused on standards and standard-essential patents. The EPO said the discussion explored developments in 5G and future 6G standards, as well as the Office’s recent work and research in the field.

The meeting also covered the Unitary Patent and Unified Patent Court. Jio does not currently use the Unitary Patent system, but the company expressed interest in assessing it as a possible option for future European patent protection.

Why does it matter?

The meeting highlights how patent strategy is becoming part of global competition in AI, 5G, 6G and digital infrastructure. For companies active in next-generation networks, standard-essential patents can shape market access, licensing power and participation in technical standards. Jio’s engagement with the EPO also reflects the growing internationalisation of Indian technology firms as they seek protection for innovation in European markets.

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US backs photonics expansion for AI data centres under CHIPS Act

The Department of Commerce’s CHIPS Program Office has signed a letter of intent to provide up to $50 million in direct funding to Coherent Corp. under the CHIPS and Science Act.

According to the CHIPS Program Office, the proposed funding would support the expansion of Coherent’s facility in Sherman, Texas, which it describes as the first and largest high-volume 150mm indium phosphide semiconductor manufacturing facility in the United States.

The expansion would add wafer fabrication equipment and cleanroom capacity to increase production of indium phosphide-based photonic components. These components are used in high-speed optical interconnects that enable rapid data transfer within advanced AI data centres.

The Department of Commerce said the project would create high-skilled manufacturing jobs and strengthen domestic supply chains for critical photonics technologies that support next-generation computing and AI infrastructure.

Why does it matter?

The announcement highlights the growing importance of photonics technologies in the AI economy. As demand for AI computing continues to rise, data centres require increasingly efficient methods for transferring vast amounts of information between processors, servers and storage systems. Optical interconnect technologies based on indium phosphide semiconductors are becoming a critical part of that infrastructure.

The investment also reflects broader US industrial policy goals under the CHIPS and Science Act. Beyond traditional semiconductor manufacturing, policymakers are increasingly targeting specialised components and supply chains considered strategically important for AI competitiveness, economic security and technological resilience.

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Japan and the Philippines partner on an AI-powered disaster risk platform

The Japan International Cooperation Agency (JICA) and the Philippines Department of Science and Technology (DOST) have agreed to collaborate on the GATES programme, a national geospatial and AI initiative aimed at strengthening disaster risk reduction and data-driven governance.

The Geospatial Analytics & Technology Solutions (GATES) programme is led by DOST and aims to integrate fragmented disaster-risk, geospatial, climate, hazard and strategic datasets from across government into a unified and interoperable data ecosystem. The programme uses geospatial analytics and artificial intelligence to support digital transformation, evidence-based policymaking, and science, technology, and innovation.

The collaboration will be carried out through the JICA Digital Transformation Lab and will begin in June 2026 for around four months. JICA DXLab will provide technical expertise to support data interoperability, governance frameworks and digital transformation capabilities under the GATES programme.

The partnership will also explore how the platform could contribute to broader digital public infrastructure for climate and disaster-risk information. DOST and JICA said the goal is to build a secure, reliable, and trusted AI ecosystem for disaster risk reduction and data-driven governance.

The collaboration builds on a long-running Japan–Philippines partnership in disaster resilience. Since the 1970s, JICA has supported the Philippine Atmospheric, Geophysical and Astronomical Services Administration through meteorological equipment and technical cooperation, helping strengthen observation, forecasting, and early warning systems for typhoons, heavy rainfall, and flooding.

JICA has also worked with the Philippine Institute of Volcanology and Seismology, including through the 2004 Metro Manila Earthquake Impact Reduction Study and ongoing cooperation on seismic monitoring, early warning systems, and data analysis capabilities.

Launched in 2025 as part of DOST’s ELEV8PH initiative, GATES is a three-year programme designed to create an AI-ready national disaster-risk data platform to support decision-making. The programme has already deployed the HANDA integrated preparedness platform, developed an initial data architecture blueprint, and started capacity-building and training activities.

The engagement has two main objectives. The first is to strengthen the platform’s data foundations by helping DOST connect disaster-risk datasets across agencies while preserving agency ownership, developing standards for AI-ready data and establishing a framework for responsible AI use.

The second objective is to turn disaster risk data into decisions. JICA will work with DOST and partner agencies to identify use cases that can improve disaster response and climate risk management, including tools for modelling incoming typhoons, dashboards for tracking climate-related risks, and planning aids for evacuation.

The cooperation is expected to strengthen disaster-risk management systems, support data-driven policymaking and expand the use of disaster-risk data for resilience and sustainable development. The partners also expect the work to strengthen the use of data and AI in policymaking in both the Philippines and Japan.

Why does it matter?

The initiative highlights the growing role of AI, geospatial analytics and interoperable data systems in disaster resilience and climate adaptation. Countries vulnerable to extreme weather events increasingly rely on integrated data platforms to improve forecasting, early warning systems, evacuation planning and emergency response.

The partnership also demonstrates how digital public infrastructure is evolving beyond identity and payments to include critical public-interest datasets. By creating an AI-ready and interoperable disaster-risk data ecosystem, the Philippines could strengthen evidence-based policymaking, improve coordination across government agencies and provide a model for other climate-vulnerable countries seeking to use AI and data more effectively in public administration.

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UK unveils AI tools to speed up planning decisions and housing delivery

The Department for Science, Innovation and Technology (DSIT) and the Ministry of Housing, Communities and Local Government have unveiled two AI tools designed to modernise England’s planning system and accelerate housing delivery.

One new AI prototype is being tested by Barnet, Camden and Dorset councils and aims to reduce average decision times for routine householder planning applications from eight weeks to four. The system triages applications and provides planning officers with preliminary assessments to support decision-making.

A second tool, called Extract, has been made available to local authorities across England. It uses AI to convert decades of planning documents and maps into structured digital data, reducing the need for manual processing and allowing staff to focus on more complex cases.

The government said the initiatives support its target of building 1.5 million homes during this Parliament while improving the efficiency of public services through technology. Subject to successful trials, the new planning application tool is expected to be rolled out nationally in England from 2027.

Why does it matter?

The initiative illustrates how governments are increasingly using AI to address administrative bottlenecks and improve public-service delivery. Planning systems often face challenges related to outdated records, resource constraints and lengthy approval processes, making them a key target for digital transformation efforts.

The UK’s approach also highlights the growing role of AI in housing and infrastructure policy. If successful, the tools could help accelerate housing development, improve the use of public-sector resources and demonstrate how AI can support decision-making while leaving final judgments in the hands of public officials.

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New AI breakthrough in cardiology balances patient data privacy and diagnosis

Researchers at the University of Kansas have developed a new AI model designed to improve the analysis of electrocardiogram (ECG) data while strengthening protections for patient privacy. The innovation responds to growing concerns that AI-enhanced ECGs can reveal sensitive personal attributes beyond heart activity.

The model, known as PP-VAE, aims to preserve clinically relevant insights, such as indicators of heart disease and mortality risk, while reducing the risk of exposing biometric and demographic information, including age and sex. The system uses advanced neural network architectures to separate clinically relevant signals from identifiable personal characteristics.

Published in Scientific Reports, the study highlights the model’s ability to predict outcomes such as left ventricular ejection fraction (LVEF) while limiting the disclosure of personal information. Researchers report that the system performs competitively compared with existing machine-learning approaches, while improving privacy safeguards.

The researchers also emphasised the importance of reducing bias and improving the representativeness of medical AI systems. Future plans include testing the model across more diverse datasets and releasing it publicly to support safer sharing of ECG data between healthcare institutions.

Why does it matter?

The development might be a critical turning point in medical AI, where improving diagnostic accuracy must be balanced with safeguarding highly sensitive patient information.

As healthcare systems increasingly rely on AI-driven analysis of ECGs and other clinical data, the ability to prevent unintended identification of individuals becomes essential for maintaining trust, enabling secure cross-institutional data sharing, and ensuring compliance with privacy standards.

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New benchmark tests AI on unpublished mathematics problems

AI systems have demonstrated growing capabilities in advanced mathematics, according to benchmark results published by the non-profit organisation First Proof.

The organisation evaluated four frontier AI systems, including ChatGPT 5.5 Pro, against ten unpublished research-level mathematical problems contributed by leading mathematicians.

The benchmark found that seven of the ten problems received at least one solution judged to be correct by expert reviewers across the participating systems. One notable result involved a stochastic partial differential equations problem, where an AI system produced a correct solution using an approach different from the human-developed proof, drawing praise from expert referees for its originality.

Despite the progress, significant limitations remain.

Several problems remained unsolved, including a metric geometry challenge on which none of the systems made meaningful progress. Reviewers also reported that AI systems handled routine mathematical reasoning effectively but continued to struggle with the most challenging conceptual and creative aspects of proof construction.

Why does it matter?

The benchmark offers one of the most demanding independent tests of AI performance in advanced mathematics, a field often viewed as a proxy for higher-level reasoning and scientific problem-solving. The results suggest that frontier AI systems are increasingly capable of contributing to specialised research tasks and, in some cases, generating approaches that differ from those developed by human experts.

At the same time, the findings highlight the limits of current AI systems. While they can assist with complex reasoning and formal problem-solving, they continue to struggle with the deepest conceptual challenges that often drive mathematical breakthroughs. This suggests that AI may increasingly serve as a research assistant and discovery tool, while human expertise remains essential for guiding and validating scientific advances.

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