Key Internet developments

Microsoft expands Sovereign Cloud with secure offline support for large AI models

Digital sovereignty is gaining urgency as organisations seek infrastructure that remains secure and reliable under strict regulatory conditions.

Microsoft is expanding its Sovereign Cloud to help public bodies, regulated industries and enterprises maintain control of data and operations even when environments must operate without external connectivity.

The updated portfolio allows customers to choose how each workload is governed, rather than relying on a single deployment model.

Azure Local now supports disconnected operations, keeping mission-critical systems running with full Azure governance within sovereign boundaries. Management, policies and workloads stay entirely on site, so services continue during periods of isolation.

Microsoft 365 Local extends the resilience to the productivity layer by enabling Exchange Server, SharePoint Server and Skype for Business Server to run locally, giving teams secure collaboration within the same protected boundary as their infrastructure.

Support for large multimodal AI models is delivered through Foundry Local, which enables advanced inference on customer-controlled hardware using technology from partners such as NVIDIA.

Such an approach helps organisations bring modern AI capabilities into highly restricted environments while preserving control over data, identities and operational procedures.

Microsoft positions it as a unified stack that works across connected, hybrid and fully disconnected modes without increasing operational complexity.

These additions create a framework designed for governments and regulated industries that regard sovereignty as a strategic priority.

With global availability for qualified customers, the Sovereign Cloud aims to preserve continuity, reinforce governance and expand AI capability while keeping every layer of the environment within local control.

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Over 299 million people gain internet access through global connectivity

Microsoft has exceeded its 2025 internet access target, reaching over 299 million people globally, including more than 124 million in Africa. The milestone reflects years of partnerships to connect communities lacking reliable digital access.

Efforts are shifting from simple coverage to holistic digital participation, combining connectivity with energy, devices, digital skills, and AI tools.

Microsoft aims to enable meaningful adoption, ensuring communities can fully engage in the growing AI economy. Partnerships focus on scalable, community-based models aligned with national development priorities.

As adoption accelerates, Microsoft plans to expand its approach by integrating financing, energy access, and community-first AI solutions. The initiative highlights the need for long-term, locally led strategies for fair participation in the digital and AI economy.

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OURA launches AI model tailored to women’s physiology with privacy-first design

Guidance for women’s health is entering a new phase as ŌURA introduces a proprietary large language model designed specifically for reproductive and hormonal wellbeing.

The model sits within Oura Advisor and is available for testing through Oura Labs, drawing on clinical standards, peer-reviewed evidence and biometric signals collected through the Oura Ring to create personalised and context-aware responses.

The system interprets questions through women’s physiology instead of depending on general-purpose models that miss critical hormonal and life-stage variables.

It supports the full spectrum of reproductive health, from the earliest menstrual patterns to menopause, and is intentionally tuned to be non-dismissive and emotionally supportive.

By combining longitudinal sleep, activity, stress, cycle and pregnancy data with clinician-reviewed research, the model aims to strengthen understanding and preparation ahead of medical appointments.

Privacy forms the centre of the architecture, with all processing hosted on infrastructure controlled entirely by the company. Conversations are neither shared nor sold, reflecting ŌURA’s broader push for private AI.

Oura Labs operates as an opt-in experimental environment where new features are tested in collaboration with members who can leave at any time.

Women who take part influence the model’s evolution by contributing feedback that informs future development.

These interactions help refine personalised insights across fertility, cycle irregularities, pregnancy changes and other hormonal shifts, marking a significant step in how the Finland-founded company advances preventive, data-guided care for its global community.

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NVIDIA healthcare survey shows surge in AI adoption and strong ROI

AI is reshaping healthcare as organisations shift from trial projects to large-scale deployment.

The latest industry survey from NVIDIA shows widespread adoption across digital healthcare, biotechnology, pharmaceuticals and medical technology, signalling a sector that is now executing rather than experimenting.

Uptake is expanding rapidly, with generative AI and large language models becoming central tools for clinical and operational tasks.

The report highlights how medical imaging, drug discovery and clinical decision support are among the most prominent applications. Radiologists are using AI to accelerate image analysis, while research teams apply advanced models to speed early-stage drug development.

Organisations benefit from workflow optimisation instead of relying on manual administrative routines, with many citing improvements in patient coordination, documentation and coding.

Open-source models are increasingly important, with most respondents considering them vital for domain-specific development.

Experts argue that open-source innovation will guide exploration, whereas deployment in clinical environments will demand rigorous validation and accountability rather than unrestricted experimentation.

Agentic AI is emerging as a new capability for knowledge retrieval and literature analysis.

Evidence of return on investment is clear, prompting 85% of organisations to expand their AI budgets. Many report higher revenue, reduced costs and significant gains in back-office productivity.

Evaluation is becoming a core operational requirement, ensuring AI continues to improve safety, quality and overall clinical performance over time.

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New Relic advances AI agents for enterprise observability

The expansion into enterprise AI comes with a no-code platform from New Relic that allows companies to build and supervise their own observability agents.

A system that assembles AI-driven monitors designed to detect bugs and performance problems before they affect users, instead of leaving teams to rely on manual tracking.

It also supports the Model Context Protocol so organisations can link external data sources to the agents and integrate them with existing New Relic tools.

The company stresses that the platform is intended to complement other agent systems rather than replace them.

As AI agent software spreads across the market, enterprises are searching for ways to manage risk when giving automated tools access to internal systems.

Industry players such as Salesforce and OpenAI have already introduced their own agent platforms, and assessments from Gartner describe these frameworks as essential infrastructure for wider AI adoption.

New Relic also introduced new tools for the OpenTelemetry framework to remove friction around observability standards.

Its application performance monitoring agents now support OTel data, allowing enterprises to manage these streams in one place instead of operating separate collectors.

The update aims to reduce fragmentation that has slowed OTel deployment across large organisations and to simplify how engineering teams handle diverse observability pipelines.

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CrowdStrike warns of faster AI driven threats

Cyber adversaries increasingly used AI to accelerate attacks and evade detection in 2025, according to CrowdStrike’s 2026 Global Threat Report. The company described the period as the year of the evasive adversary, marked by subtle and rapid intrusions.

The average time to a financially motivated online crime breakout fell to 29 minutes, with the fastest recorded at 27 seconds. CrowdStrike observed an 89 percent rise in attacks by AI-enabled threat actors compared with 2024.

Attackers also targeted AI systems themselves, exploiting GenAI tools at more than 90 organisations through malicious prompt injection. Supply chain compromises and the abuse of valid credentials enabled intrusions to blend into legitimate activity, with most detections classified as malware-free.

China linked activity rose by 38 percent across sectors, while North Korea linked incidents increased by 130 percent. CrowdStrike tracked more than 281 adversaries in total, warning that speed, credential abuse, and AI fluency now define the modern threat landscape.

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Commission delays high risk AI guidance

The European Commission has confirmed it will again delay publishing guidance on high-risk AI systems under the EU AI Act. The guidelines were due by 2 February 2026, but will now follow a revised timeline.

According to Euractiv, the document is intended to clarify which AI systems fall into the high-risk category and therefore face stricter obligations. Officials said more time is needed to incorporate significant stakeholder feedback.

The delay marks the second missed deadline and adds to broader implementation setbacks surrounding the EU AI Act. Several member states have yet to designate national enforcement bodies, complicating oversight preparations.

Brussels is also considering postponing the application of high-risk rules through a digital simplification package. Parliament and Council appear supportive of moving the August deadline back by more than a year, easing pressure on companies awaiting guidance.

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IQM puts Finland on Europe’s quantum computing map

Finland is emerging as a key hub in Europe’s quantum computing landscape as startup IQM prepares to become one of the continent’s first publicly listed quantum firms.

The company is developing full-stack, open-architecture quantum systems designed for on-premise deployment or cloud access. It aims to advance the practical use of quantum computing across research and industry.

Founded in 2018, IQM has already delivered 21 quantum systems to 13 customers, highlighting growing European interest in commercial quantum technologies.

Analysts note that while challenges remain, meaningful breakthroughs are now occurring, signalling that quantum computing is shifting from purely experimental science to an operational industry.

IQM’s technology could support advancements in medicine, science, and computational research, enabling the solution to complex problems far beyond the reach of classical computers.

The firm exemplifies Europe’s ambition to build quantum capabilities independently of larger players in the US and China, positioning Finland as a strategic hub for next-generation computing.

The company’s work aligns with broader European efforts to foster innovation in quantum technologies.

By combining domestic expertise with open-access systems, IQM demonstrates how Finland is contributing to the continent’s emerging quantum ecosystem, bridging academic research and industrial application.

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AI-driven physics speeds up industrial innovation

PhysicsX, a London-based startup founded by former F1 engineers and AI experts, is redefining engineering with its AI-driven physics platform.

Design and testing cycles are reduced from weeks or months to seconds. Engineers can now iterate rapidly and optimise systems across multiple industries, including aerospace, automotive, semiconductors, energy, and materials.

The technology enables teams to evaluate thousands of design variations simultaneously. Semiconductor firms speed up prototype development, electronics improve thermal performance, and mining boosts copper recovery for renewable energy and AI data centres.

PhysicsX achieves this using Large Physics Models and Large Geometry Models that base design evaluation on real-world physics rather than assumptions.

Predictive reasoning lets engineers simulate multiple parameter changes before acting. The approach shifts control from reactive adjustments to proactive optimisation, helping teams make faster, better-informed decisions.

PhysicsX also bridges disciplinary divides, enabling aerodynamics, structural, and thermal considerations to be optimised together rather than in isolation.

By combining speed, system-level insight, and predictive control, PhysicsX is shrinking the gap between cutting-edge research and practical industrial impact. The platform uses physics-based AI to improve efficiency, drive innovation, and support sustainable growth.

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NVIDIA drives a new era of industrial AI cybersecurity

AI-driven defences are moving deeper into operational technology as NVIDIA leads a shift toward embedded cybersecurity across critical infrastructure.

The company is partnering with firms such as Akamai Technologies, Forescout, Palo Alto Networks, Siemens and Xage Security to protect energy, manufacturing and transport systems that increasingly operate through cloud-linked environments.

Modernisation has expanded capabilities across these sectors, yet it has widened the gap between evolving threats and ageing industrial defences.

Zero-trust adoption in operational environments is gaining momentum as Forescout and NVIDIA develop real-time verification models tailored to legacy devices and safety-critical processes.

Security workloads run on NVIDIA BlueField hardware to keep protection isolated from industrial systems and avoid any interference with essential operations. That approach enables more precise control over lateral movement across networks without disrupting performance.

Industrial automation is also adapting through Siemens and Palo Alto Networks, which are moving security enforcement closer to workloads at the edge. AI-enabled inspection via BlueField enhances visibility in highly time-sensitive environments, improving reliability and uptime.

Akamai and Xage are extending similar models to energy infrastructure and large-scale operational networks, embedding segmentation and identity-based controls where resilience is most critical.

A coordinated architecture is now emerging in which edge-generated operational data feeds central AI analysis, while enforcement remains local to maintain continuity.

The result is a security model designed to meet the pressures of cyber-physical systems, enabling operators to detect threats faster, reinforce operational stability and protect infrastructure that supports global AI expansion.

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