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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Crypto market embraces AI and structural growth in 2026

The cryptocurrency market in 2026 is showing a shift from hype-driven cycles to structured growth and strategic maturity. Institutional strategies dominate, retail investors take a smaller role, and geopolitical uncertainty affects market sentiment.

Analysts warn that the era of speculative memecoins and whitepaper millionaires is giving way to projects prioritising revenue, sustainability, and systemic utility.

Market leaders note a widening gap between top cryptocurrencies like Bitcoin and Ethereum and smaller altcoins. Major assets gain from liquidity and institutional adoption, while many tokens face higher risk as traditional exchange listings pull capital from on-chain markets.

Investors are advised to focus on infrastructure, liquidity, and scalable systems rather than short-term trends.

AI is emerging as a defining force. Experts highlight the growing use of AI agents to trade, allocate capital, and manage risk autonomously, with blockchain providing transparency and auditability.

The convergence of AI and crypto is expected to shape next-generation financial products, driving adoption beyond speculation and into practical, revenue-generating applications.

Strategic advice for 2026 emphasises diversification, system-oriented thinking, and long-term fundamentals. Investors should diversify across crypto, traditional, and offshore assets, using automated tools to reduce emotional decisions amid ongoing volatility.

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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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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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Enterprises rethink cloud amid digital sovereignty push

Digital sovereignty has moved to the boardroom as geopolitical tensions rise and cloud adoption accelerates. Organisations are reassessing infrastructure to protect autonomy, ensure compliance, and manage jurisdictional risk. Cloud strategy is increasingly shaped by data location, control, and resilience.

Regulations such as NIS2, DORA, and national data laws have intensified scrutiny of cross-border dependencies. Sovereignty concerns now extend beyond governments to sectors such as healthcare and finance. Vendor selection increasingly prioritises sovereign regions and stricter data controls.

Hybrid cloud remains dominant. Organisations place sensitive workloads on private platforms to strengthen oversight while retaining public cloud innovation. Large-scale repatriation is rare due to cost and complexity, though compliance pressures are driving broader multicloud diversification.

Government investment and oversight are reinforcing the shift. Sovereignty is becoming part of national resilience policy, prompting stricter audits and governance expectations. Enterprises face growing pressure to demonstrate control over critical systems, supply chains, and data flows.

A pragmatic approach, often described as minimum viable sovereignty, helps reduce exposure without unnecessary complexity. Organisations can identify critical workloads, secure enforceable vendor commitments, and plan for disruption. Early adaptation supports resilience and long-term flexibility.

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Study warns AI chatbots can reinforce delusions and mania

AI chatbots may pose serious risks for people with severe mental illnesses, according to a new study from Acta Psychiatrica Scandinavica. Researchers found that tools such as ChatGPT can worsen psychiatric conditions by reinforcing users’ delusions, paranoia, mania, suicidal thoughts, and eating disorders.

The team examined health records from more than 54,000 patients and identified dozens of cases where AI interactions appeared to exacerbate symptoms. Experts warn that the actual number of affected individuals is likely far higher.

AI’s design to follow and validate a user’s input can unintentionally strengthen delusional thinking, turning digital assistants into echo chambers for psychosis.

Despite potential benefits for psychoeducation or alleviating loneliness, experts caution against using AI as a substitute for trained therapists. Chatbots should be tested in rigorous clinical trials before any therapeutic use, says Professor Søren Dinesen Østergaard.

The researchers urge healthcare providers to discuss AI chatbot use with patients, particularly those with severe mental illnesses, and call for central regulation of the technology. They argue that lessons from social media show that early oversight is essential to protect vulnerable populations.

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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 drives faster modernisation of legacy COBOL systems

Critical to finance, airlines, and government, COBOL handles about 95% of US ATM transactions. Despite its ubiquity, the pool of developers able to read and maintain COBOL is shrinking as seasoned engineers retire and universities offer limited instruction.

Institutional knowledge is now embedded in decades-old code, and documentation often lags.

Modernising COBOL differs from typical software updates. It requires untangling intricate dependencies and reverse-engineering business logic that has evolved over decades.

Traditional modernisation efforts involved large teams of consultants over the years, resulting in high costs and lengthy timelines. AI tools are changing that paradigm by automating the most labour-intensive tasks.

AI-driven solutions like Claude Code map code dependencies, trace execution paths, document workflows, and identify risks. They provide teams with actionable insights for prioritisation, risk management, and refactoring, dramatically shortening modernisation timelines from years to months.

Human experts remain essential to reviewing AI recommendations, ensuring regulatory compliance, and making strategic decisions about which components to modernise first.

Implementation follows an incremental approach. AI translates COBOL logic into modern languages, creates integration scaffolding, and supports side-by-side operation with legacy components.

Continuous validation at each step reduces risk, allowing teams to build confidence as complex parts of the system are modernised. AI automation combined with expert oversight makes large-scale COBOL modernisation feasible.

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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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