EU delays tech sovereignty package with AI and Chips Act 2

The European Commission has delayed a flagship tech sovereignty package for the second time, according to its latest College agenda. The measures are now scheduled for adoption on 27 May, after previously being postponed from March to April.

The tech sovereignty package includes several major initiatives aimed at strengthening EU tech sovereignty, such as the Cloud and AI Development Act, the Chips Act 2, an open-source strategy, and a roadmap for digitalisation and AI in energy. European Commission officials have not provided a reason for the latest delay.

The Cloud and AI Development Act is expected to define what constitutes a ‘sovereign’ cloud and simplify rules for building data centres. The proposal is designed to accelerate infrastructure development as Europe seeks to compete in the global AI race.

Chips Act 2 will follow up on the EU’s earlier semiconductor strategy, which struggled to boost domestic chip production significantly. The new proposal is expected to refine industrial policy efforts to reduce reliance on foreign suppliers.

Meanwhile, the planned open source strategy aims to support European software ecosystems and reduce dependence on large US technology firms. By encouraging commercially viable open source projects, the EU hopes to strengthen its long-term digital autonomy.

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UN calls for global action against online scam networks

Online scam networks operating across Southeast Asia are defrauding victims worldwide, using AI, impersonation techniques, and complex cyber tools to steal billions of dollars.

At the Global Fraud Summit in Vienna, the UN Office on Drugs and Crime (UNODC) and INTERPOL brought together governments, law enforcement, and private-sector actors to strengthen international cooperation against these crimes.

Victims include individuals from diverse backgrounds, often highly educated and financially experienced. One Australian couple, Kim and Allan Sawyer, lost more than $2.5 million after engaging with what appeared to be a legitimate investment opportunity. ‘The scammer was extraordinarily believable,’ Kim Sawyer said. ‘He had a British accent, used all the right financial market terms and knew how to induce us by appearing credible every time.’

UNODC officials warn that these operations extend beyond fraud, forming part of a broader criminal ecosystem driven by organised scam networks, involving human trafficking, corruption, and money laundering.

‘We need to be looking into prosecuting high-level criminals, following the money through financial investigations and identifying the giant networks that operate behind these operations,’ said Delphine Schantz, UNODC’s regional representative for Southeast Asia and the Pacific.

Authorities say the scale and complexity of these crimes require a coordinated global response to dismantle scam networks effectively. ‘The complexity of these crimes requires an equally complex, whole-of-government approach and enhanced coordination among governments, financial intelligence units and digital banks,’ Schantz added.

Investigations in countries such as the Philippines and Cambodia have revealed how scam networks operate on the ground. In Manila, a former scam compound uncovered facilities used to control trafficked workers and evidence of corruption linked to local officials. ‘How do you prove a cybercrime in 36 hours? It is not possible,’ said the Philippines’ Presidential Anti-Organised Crime Commission (PAOCC) operations director, recalling the challenges investigators faced during early raids.

In Cambodia, international prosecutors and investigators have focused on improving cooperation mechanisms, including extradition, asset recovery, and the handling of digital evidence. These efforts are seen as critical in addressing the cross-border nature of scam networks.

Despite increased enforcement efforts, these networks continue to adapt and relocate, maintaining a global reach. At recent international meetings, including a summit in Bangkok involving nearly 60 countries and major technology firms, officials agreed on the need for shared intelligence, joint investigations and coordinated prosecutions.

Victims continue to call for stronger responses. ‘The scammer works twice: they take your money, and they take your soul. They really do. They take your self-worth. And then, you feel like you’re being scammed again, by the authorities’ lack of response,’ Sawyer said.

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Google launches AI skills initiative to support Europe’s workforce transition

At the Future of Work Forum, Google introduced ‘AI Works for Europe’, a programme aimed at strengthening digital skills and supporting workforce adaptation to AI across the region.

Funding of $30 million will be directed through Google.org to expand training opportunities, alongside broader access to AI certification programmes designed to help individuals and businesses adopt new technologies in practical contexts.

A central focus involves preparing workers and students for labour market changes.

Partnerships with organisations such as INCO are supporting the development of targeted training programmes, particularly in sectors where demand for AI-related skills is increasing, including finance, logistics and marketing.

New educational pathways are also being introduced, including an expanded AI Professional Certificate available in multiple European languages. These initiatives aim to improve AI literacy and provide hands-on experience aligned with employer expectations.

Collaboration with local organisations and institutions remains a key element, reflecting a broader strategy to ensure access to training across different regions and communities.

Efforts to expand AI capabilities across Europe highlight the growing importance of skills development as AI becomes more integrated into economic activity.

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MIT research highlights embedded and enacted risks in AI

Generative AI offers major productivity and growth opportunities, but also brings new risks as organisations move from experiments to full deployment. MIT research highlights key risk areas, including training data, foundation models, user prompts, and system prompts.

Researchers identify two types of risk.

Embedded risks come from the technology itself, shaped by model behaviour, data quality, and vendor updates, and are mostly outside an organisation’s control.

Enacted risks arise from choices in deploying AI, from prompt design to agent permissions, and require strong governance.

Advanced uses such as retrieval-augmented generation (RAG) and autonomous AI agents increase exposure. RAG uses internal data to improve outputs, but may reveal sensitive information or control gaps. AI agents acting across multiple tools can lead to ‘autonomy creep,’ performing tasks without proper oversight.

To manage AI risk, organisations should map tools, assign ownership, track outputs, and use separate strategies for embedded and enacted risks. Vendor engagement, governance frameworks, and technical controls are essential for safe AI use.

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AI-powered MRI previews aim to reduce errors and rescans

Philips is creating AI-driven predictive MRI previews to improve scan planning and reduce operator variability. Using NVIDIA accelerated computing and foundation models, the system creates a pre-scan image to validate protocols, optimise positioning, and spot potential issues.

The technology is based on a dedicated MR foundation model trained on diverse datasets covering anatomies, field strengths, protocols, and artefacts.

When combined with NVIDIA’s NV‑Generate, NV‑Segment, and NV‑Reason models, the platform integrates image generation, segmentation, and interpretation. It creates a single intelligent workflow that supports consistent and efficient MRI procedures.

Predictive previews reduce rescans, enhance image quality, and increase technologist confidence, especially in complex exams or areas with limited expertise. Early guidance helps confirm protocols, optimise positioning, and flag issues that could affect diagnostic outcomes.

Philips envisions autonomous MRI, with AI monitoring image quality, guiding positioning, and assisting radiologists with actionable insights. Predictive imaging boosts consistency, efficiency, and access, improving patient experience and expanding MRI availability.

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New licensing rules for crypto platforms in Australia

Australia is advancing plans to regulate digital asset platforms under its financial services framework. The Senate committee recommended passing the Digital Assets Framework Bill 2025, bringing Australia closer to licensing crypto exchanges and tokenisation platforms.

Industry groups have raised concerns about definitions such as ‘digital token’ and ‘factual control.’ Broad wording could inadvertently cover infrastructure providers, including multi-party wallet systems, potentially classifying them as financial service operators.

Ripple Labs emphasised the need for precise language to avoid unintended regulation.

The committee supported the Treasury’s approach while planning to refine technical details through future regulations. Coinbase welcomed the progress but noted ongoing banking challenges for crypto firms.

The bill now proceeds to the Senate for debate and a final vote, which could reshape digital asset operations in Australia.

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Green light for massive UK AI tech park

North Lincolnshire Council has granted outline planning permission for the Elsham Tech Park, a proposed AI data centre campus that would rank among the largest of its kind in the UK.

At full build-out, the site would include up to 15 hyperscale data centre buildings across 176 hectares, delivering more than 1.5 million square metres of floorspace and up to 1GW of computing capacity.

The development is expected to cost between £5.5 billion and £7.5 billion to build and could attract up to £10 billion in private investment over its lifetime.

Developer Greystoke plans to begin construction in 2027, with the first phase due to open in 2029, and the full campus to be delivered in phases over approximately a decade.

The project is also required to source at least 30% of build costs from businesses within a 30-mile radius, injecting an estimated £1.65 billion to £2.25 billion into the local economy.

The scheme received over 380 letters of objection from residents and environmental groups. Critics raised concerns, including loss of privacy for neighbouring properties, around-the-clock noise and light, and the scale of carbon emissions, with one campaign group estimating the equivalent of twice the woodland of Wales would be needed to offset the development’s environmental impact.

Permission was nonetheless granted unanimously by councillors.

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NVIDIA expands physical AI ecosystem to accelerate real world robotics

Partnerships across the robotics sector are positioning NVIDIA at the centre of what is increasingly described as ‘physical AI’, a shift towards intelligent machines capable of perceiving, reasoning and acting in real environments.

A new generation of tools, including NVIDIA Cosmos world models and updated NVIDIA Isaac simulation frameworks, aims to support developers in training and validating robots before deployment.

These systems enable companies to simulate complex environments, reducing the risks and costs of real-world testing.

Industrial robotics leaders such as ABB Robotics, KUKA, and FANUC are integrating NVIDIA technologies into digital twin environments, enabling more accurate modelling of production lines and automation systems.

Advances are also extending into humanoid robotics, where companies are using AI models to develop machines capable of more flexible and adaptive behaviour.

New foundation models, including GR00T systems, are designed to give robots general-purpose capabilities instead of limiting them to specific tasks.

Healthcare and logistics represent additional areas of deployment, with robotics platforms being tested in surgical systems, warehouse automation and manufacturing environments. These applications highlight how physical AI could reshape industries requiring precision, safety and scalability.

Growing collaboration across cloud providers, manufacturers and AI developers suggests that robotics is moving toward a more integrated ecosystem, where simulation, data generation and deployment are increasingly interconnected.

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6G will make wireless networks capable of thinking for themselves

Unlike its predecessors, 6G is being designed from the ground up with AI as a core feature rather than a performance add-on.

From user devices and base stations through to the network core, AI and machine learning will enable 6G networks to self-optimise, manage interference, predict user mobility, and make real-time decisions with minimal human intervention.

One of 6G’s most distinctive capabilities will be Integrated Sensing and Communication (ISAC), which allows radio signals to simultaneously carry data and sense the surrounding environment, effectively turning the network into a vast, distributed sensor capable of detecting motion, tracking objects, and supporting applications such as predictive maintenance and autonomous vehicles.

AI plays a central role in interpreting this sensing data in real time, enabling split-second responses to real-world conditions.

Standardisation efforts are already underway, with 3GPP’s Release 20 exploring how AI and machine learning can optimise the air interface and improve tasks such as channel state information compression.

Commercial 6G deployment is expected in the early 2030s, by which point AI is projected to act as the brain and nervous system of key parts of the network, constantly learning, adapting, and optimising with little human oversight.

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How IBM is making quantum-centric supercomputing accessible to scientists

IBM has published a detailed reference architecture for quantum-centric supercomputing, providing a blueprint for integrating quantum processing units (QPUs) into existing high-performance computing (HPC) infrastructure without disruptive changes to current systems.

The release marks a significant step toward realising the vision articulated by physicist Richard Feynman, who argued decades ago that accurately simulating nature would require quantum-mechanical computation.

The architecture describes how quantum and classical systems, including CPUs, GPUs, and QPUs, can work together across multiple layers, from application and middleware tools such as Qiskit and CUDA through to resource management systems that orchestrate workloads in real time.

New algorithms such as Sample-based Krylov Quantum Diagonalisation (SKQD) are already demonstrating cases where quantum-centric workflows outperform leading classical-only methods, including in molecular ground-state energy calculations, where classical techniques failed to converge.

Real-world research applications are already emerging.

Scientists at the Cleveland Clinic Foundation used quantum-centric methods to simulate a 300-atom protein, the largest molecular simulation to date. In contrast, a team spanning IBM, Oxford, ETH Zurich, and other institutions used quantum algorithms to study a newly engineered ‘half-Möbius’ molecule whose electronic structure cannot easily be modelled classically.

IBM describes the trajectory as pointing toward a near future in which quantum computing can predict molecular properties that scientists can then bring to life in the laboratory.

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