Artificial intelligence

Greece adopts national framework to implement EU AI Act

The Greek Parliament has approved the national implementing framework for the EU AI Act, making Greece one of the first member states to establish a comprehensive national system for enforcing the regulation.

The new law in Greece establishes the institutional framework for supervising AI systems, coordinating enforcement, supporting innovation and ensuring compliance with the EU AI Act.

The legislation designates the Hellenic Data Protection Authority (HDPA) as the central market surveillance authority and the Hellenic Telecommunications and Post Commission (EETT) as the notifying authority, while establishing a dedicated AI Coordination and Expertise Centre.

It also introduces complaint procedures, administrative sanctions, a national registry of AI systems used by public authorities, regulatory sandboxes for AI testing and criminal penalties for removing transparency labels from deepfake content.

Alongside the implementing framework, the government presented its broader national AI strategy, highlighting investments in infrastructure, data governance and research. These include the Daedalus supercomputer, the Pharos AI Factory, new high-performance computing infrastructure in Kozani, the data.gov.gr platform and partnerships with companies such as Mistral and ElevenLabs, which the government said will strengthen Greece’s AI capabilities and technological sovereignty.

The government said these initiatives form part of a coordinated strategy to strengthen Greece’s AI capabilities and technological sovereignty.

The minister also highlighted current and planned AI applications across the public sector, including tools to accelerate legal reviews at the Hellenic Cadastre and improve public access to parliamentary work through AI services for the Hellenic Parliament.

Additional provisions include the creation of a digital registry for accessibility infrastructure, which will integrate with the MyStreet application to improve mobility for people with disabilities.

Why does it matter?

The legislation gives Greece the institutional architecture needed to implement the EU AI Act while combining regulatory oversight with investment in AI infrastructure and innovation. By establishing supervisory authorities, regulatory sandboxes and governance mechanisms alongside major computing and data initiatives, Greece is seeking to align AI regulation with industrial and digital development.

The framework also illustrates how implementation of the AI Act is becoming a national governance exercise rather than simply a compliance task. As member states designate authorities and build supporting institutions, national implementation strategies are likely to shape how consistently the Act is applied across the EU.

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Rome Declaration calls for human control over AI and nuclear weapons

Nobel laureates, scientists, religious leaders and former heads of state and government have signed the Rome Declaration for an Unarmed and Disarming Peace in the Age of Artificial Intelligence, Nuclear and Autonomous Weapons, New Digital Protocols, and Emerging Models of Digital Development.

The declaration was adopted on 16 July on Rome’s Capitoline Hill following the Global Nobel Laureates Assembly on Artificial Intelligence and Nuclear War, hosted by the Vatican.

The declaration calls for renewed international cooperation to address the challenges posed by AI, nuclear weapons and other emerging technologies. It stresses that decisions concerning life and death, peace and war, and the future of humanity should remain under meaningful human control, while highlighting the importance of ensuring that technological progress is guided by ethics, responsibility and respect for human dignity.

The declaration concludes the Global Nobel Laureates Assembly, which brought together more than 200 participants from research institutions, international organisations and civil society. The organisers said the initiative seeks to encourage dialogue on the governance of AI, nuclear weapons and other technologies with significant implications for international peace and security.

Why does it matter?

The declaration reflects growing international efforts to address AI alongside nuclear risks and other emerging technologies through a common governance framework. It also adds to ongoing discussions about maintaining meaningful human control over decisions involving the use of force and other technologies with potentially existential consequences.

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White House launches GOLD EAGLE cybersecurity initiative

The White House has announced the launch of GOLD EAGLE, a cybersecurity vulnerability coordination initiative established under President Donald Trump’s Executive Order 14410, Promoting Advanced Artificial Intelligence Innovation and Security.

According to the administration, the initiative brings together federal agencies, open-source software partners and operators of critical infrastructure to accelerate the identification and remediation of cybersecurity vulnerabilities using AI.

The initiative is being implemented through collaboration between the White House, the Department of the Treasury, the Department of Homeland Security, including the Cybersecurity and Infrastructure Security Agency (CISA), and the Department of War. The administration said GOLD EAGLE is intended to reduce duplicative vulnerability scanning, improve exploit detection and provide prioritised threat and remediation information to government and private-sector defenders.

According to the announcement, GOLD EAGLE has already begun receiving and prioritising reported cybersecurity vulnerabilities from multiple sectors, coordinating verification efforts and supporting remediation activities. The White House said the initiative represents a new operational model for cyber defence that combines government resources with private-sector capabilities to strengthen the resilience of critical infrastructure and software systems.

Why does it matter?

GOLD EAGLE marks a shift towards more centralised public-private coordination of cybersecurity vulnerability management in the USA. By combining AI-assisted vulnerability prioritisation with information sharing across government agencies and critical infrastructure operators, the initiative aims to accelerate the detection and remediation of cyber threats.

It also reflects the Trump administration’s broader strategy of linking AI innovation with national cybersecurity and critical infrastructure protection.

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UAE highlights AI-driven labour market strategy at BRICS meeting

The United Arab Emirates presented its AI-driven labour-market policies at the 2026 BRICS Labour and Employment Ministers’ Meeting in India.

The country highlighted public-private cooperation, adaptable legislation and investment in AI as part of its approach to workforce development.

UAE Minister of Human Resources and Emiratisation Abdulrahman Al Awar said AI is being used to forecast labour-market needs, identify future skills and support data-based decision-making.

He also said digital platforms are helping strengthen worker protection through wage monitoring, occupational safety systems and labour dispute-resolution tools.

The UAE pointed to growth in its labour market, saying private-sector employment had more than doubled over the past five years, registered companies had increased by 46%, and women’s participation had risen by 109%.

The government said its AI-supported skills initiatives are intended to align education and training with future labour-market needs.

BRICS members concluded the meeting by adopting a joint declaration focused on social protection, skills development, workforce participation and digital transformation.

The UAE said it remains committed to international cooperation on building more resilient and inclusive labour markets.

Why does it matter?

The UAE’s presentation shows how governments are increasingly using AI and digital platforms for labour-market planning, skills forecasting and worker-protection systems. The approach reflects a wider shift in employment policy, where competitiveness depends not only on automation and productivity, but also on whether countries can prepare workers for new skills demand, protect labour rights and adapt regulation as work changes.

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Japan and NVIDIA launch national AI infrastructure

Japan is moving to build what NVIDIA describes as the world’s first national AI infrastructure for physical AI, in partnership with Noetra and supported by government and industry leaders.

The initiative is designed to strengthen Japan’s AI ecosystem across manufacturing, logistics, healthcare, telecommunications and other industrial sectors.

Noetra will establish an NVIDIA Vera Rubin AI factory using 13,750 NVIDIA Vera CPUs and 27,500 NVIDIA Rubin GPUs.

NVIDIA said the facility will deliver 140 megawatts of data-centre capacity and will be based on its DSX platform.

The AI factory will support the development of open multimodal foundation models for AI agents, digital twins, robotics and other physical AI applications.

It will provide the computing foundation for Japan’s FRONTia Project, launched by the Ministry of Economy, Trade and Industry.

The project aims to combine Japan’s manufacturing expertise, real-world industrial data and international technology partnerships to develop reliable multimodal foundation models for robotics and physical AI.

Pretrained weights from Noetra’s multimodal foundation models will be made available to domestic model developers and enterprises, alongside NVIDIA software tools for agentic AI, robotics and model development.

NVIDIA said the infrastructure will support Japan’s wider AI robotics strategy, which aims to capture more than 30% of the global AI robotics market by 2040.

As the AI factory expands, it is expected to support trillion-parameter-scale model training and give organisations in Japan access to advanced AI computing capacity.

Why does it matter?

The initiative shows how national AI strategies are increasingly tied to compute infrastructure, industrial data and sector-specific foundation models. For Japan, physical AI connects AI policy with manufacturing, robotics, logistics and healthcare, areas where domestic expertise and trusted infrastructure could become strategic advantages. The project also highlights the growing role of private chip and platform providers in national AI capacity, raising longer-term questions about sovereignty, dependency and who controls the infrastructure behind industrial AI.

WHO convenes global summit on AI governance in healthcare

The World Health Organization has brought ministers and senior officials from 37 countries to Lisbon to develop a shared approach to AI health governance, patient safety and equitable access to emerging technologies.

The global conference, co-hosted by WHO/Europe and the Portuguese government, brings together representatives from all six WHO regions, alongside leaders from the European Commission, the World Bank, the Wellcome Trust, the Aga Khan University and the Gates Foundation.

WHO said its assessment of AI readiness across the European Region revealed a substantial gap between AI adoption and governance. Nearly two-thirds of countries already use AI in diagnostics, but only 8% have a health-specific AI strategy and only 8% have standards defining liability when AI systems fail.

The Lisbon meeting is organised around three pillars: regulation and accountability, tools and infrastructure for safe deployment, and the people and institutions responsible for implementing AI in practice. Rather than promoting a single model, WHO is exploring how countries at different levels of digital development can adapt common governance principles to their own health systems.

Discussions cover legal accountability, ethics, data governance, interoperability, workforce preparation and responsible investment. Participants also stressed that effective AI governance will be essential to ensure AI narrows rather than widens inequalities between well-resourced and under-resourced health systems.

The conference also includes a meeting involving Angola, Brazil, Cabo Verde, Portugal, São Tomé and Príncipe, and Timor-Leste. The session is intended to lay the foundations for cooperation on AI and health among Portuguese-speaking countries.

WHO Regional Director for Europe, Hans Kluge, said governments need a shared approach to governance, workforce training and equitable access. He warned that people are increasingly consulting generative AI chatbots about medical symptoms before speaking with healthcare professionals, highlighting the urgency of effective governance.

The conference opened with technical discussions on 13 and 14 July involving researchers, clinicians and international organisations. Ministerial sessions on 15 and 16 July are expected to translate those discussions into a practical agenda for international cooperation.

Why does it matter?

The conference reflects a growing recognition that healthcare is becoming one of the most important sectors for AI governance. As hospitals and health systems adopt AI more rapidly, governments are increasingly seeking common approaches to accountability, patient safety and regulatory oversight.

WHO’s findings also expose a widening governance gap: many countries are already deploying AI in clinical settings without dedicated strategies or clear liability frameworks. International cooperation could help countries develop compatible governance approaches while reducing inequalities in access to safe and trustworthy AI-enabled healthcare.

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Claude for Teachers released for verified US educators

Anthropic has launched Claude for Teachers, offering verified K-12 educators in the US free access to premium Claude features, teaching skills and curriculum-aligned resources.

The product is designed to help teachers plan lessons, adapt materials, differentiate instruction and manage classroom workflows.

Claude for Teachers connects to Learning Commons, giving it access to academic standards across all 50 US states and related learning competencies.

Anthropic says the tool can use those standards to draft scaffolded lesson plans and student-facing materials based on widely used curricula, including OpenSciEd and Illustrative Mathematics.

Educators can also connect Claude with K-12 tools such as ASSISTments, Brisk Teaching, Canva Education, Coteach, Diffit, Eedi, MagicSchool, Snorkl and TeachFX.

The platform includes tailored teaching skills grounded in learning science, with use cases including standards-aligned lesson planning, differentiated materials and analysis of class data for instructional planning.

Anthropic says that Claude for Teachers is for educators only and complies with K-12 privacy requirements.

Data from the product will not be used for model training, and student information is covered by a K-12 Data Processing Addendum designed to comply with FERPA.

The company is also working with the American Federation of Teachers on safety and privacy principles for AI in education.

Verified educators can access Claude for Teachers free of charge if they sign up by 30 June 2027, with a dedicated version for schools and districts planned later.

Why does it matter?

Claude for Teachers shows how major AI companies are moving from general-purpose chatbots into specialised education tools with curriculum alignment, workflow integrations and sector-specific privacy commitments. The launch could support lesson planning and differentiated instruction. Still, it also raises familiar questions about student data, vendor dependence, AI quality, teacher autonomy and how schools evaluate the educational impact of AI tools before scaling them.

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OpenAI calls for aligned US AI safety framework

OpenAI has called for closer alignment between US state and federal AI safety efforts, arguing that a common framework is needed to govern frontier AI systems.

In a policy blog post, the company said recent frontier AI legislation in California, New York and Illinois shows how states can help create a shared baseline before a single federal framework is in place.

OpenAI describes this process as ‘reverse federalism’, where state laws move in similar directions and gradually shape a de facto national standard.

The company says core elements should include documented safety frameworks, risk assessments for frontier models, public disclosure of results, serious incident reporting and independent audits.

At the federal level, OpenAI argues that the US government should lead testing and evaluation of the most advanced AI systems, particularly when national security and cybersecurity are at stake.

It says a consistent federal testing framework would help advanced AI tools reach trusted users, including government agencies, critical infrastructure defenders, allies and other partners.

OpenAI also supports clearer requirements for companies developing the most capable systems, including strong security standards, incident reporting, independent audits and whistle-blower protections.

The company warns that neither a fragmented patchwork of state laws nor an undefined federal process would create a coherent frontier safety regime.

Why does it matter?

OpenAI’s proposal highlights the growing tension in US AI governance between state-led action, federal oversight and international standard-setting. A shared framework could reduce regulatory fragmentation and create clearer expectations for frontier model developers. Still, the company’s position also reflects the interests of a major AI lab seeking predictable rules for deployment, testing and access. The debate will shape how the US balances safety, innovation, national security and global influence in AI governance.

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Microsoft and 3M partner on AI data centre infrastructure

Microsoft and 3M have announced a strategic partnership covering AI data centre infrastructure and the deployment of Microsoft AI tools across 3M’s business operations.

Microsoft Azure will become the first hyperscale cloud provider to deploy 3M’s Expanded Beam Optical technology, which is designed to improve the physical connectivity needed for expanding cloud and AI workloads. Unlike conventional fibre connectors that rely on direct physical contact, the technology uses an expanded optical beam, making connections more resistant to dust and contamination during installation and maintenance.

Microsoft said early deployments suggest the technology could shorten network installation times in some environments while maintaining reliable signal performance under typical data centre conditions.

3M is expanding production as hyperscalers and data centre operators invest in AI infrastructure. The company has also supported an industry agreement to standardise expanded beam optical connections.

The partnership will combine Microsoft’s cloud infrastructure with 3M’s expertise in materials science, optical connectivity and precision manufacturing, with further collaboration focusing on deployment speed, reliability, density and long-term scalability.

Alongside the infrastructure agreement, 3M will deploy Microsoft AI and digital platforms across customer service, finance, sales and marketing to simplify processes, improve decision-making and increase productivity.

Microsoft engineers are also working with 3M’s Global Business Services team on an AI agent-based customer order workflow covering credit checks, delinquency assessments and system updates while retaining human approval. A monitoring dashboard will provide employees with real-time visibility into the process to improve consistency, reduce manual work and support auditability.

The partnership links investment in the physical infrastructure that supports AI with the adoption of AI across enterprise operations, illustrating how cloud providers and industrial companies are increasingly collaborating across both domains.

Why does it matter?

The partnership highlights that scaling AI depends not only on chips and computing power but also on the physical networking infrastructure connecting data centres. Improvements in optical connectivity could help cloud providers deploy increasingly dense AI infrastructure more efficiently and reliably.

It also illustrates how infrastructure partnerships are becoming broader digital transformation initiatives. By combining hardware innovation with enterprise AI deployment, Microsoft and 3M are reflecting a wider trend in which AI investment spans both the technology underpinning AI services and the business processes that use them.

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