Cybersecurity

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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OpenClaw vulnerabilities exposed by AI-powered code scanner

Researchers at Endor Labs identified six high- to critical vulnerabilities in the open-source AI agent framework OpenClaw using an AI-powered static application security testing engine to trace untrusted data flows. The flaws included server-side request forgery, authentication bypass, and path traversal.

The bugs affected multiple components of the agentic system, which integrates large language models with external tools and web services. Several SSRF issues were found in the gateway and authentication modules, potentially exposing internal services or cloud metadata depending on the deployment context.

Access control failures were also found in OpenClaw. A webhook handler lacked proper verification, enabling forged requests, while another flaw allowed unauthenticated access to protected functionality. Researchers confirmed exploitability with proof-of-concept demonstrations.

The team said that traditional static analysis tools struggle with modern AI software stacks, where inputs undergo multiple transformations before reaching sensitive operations. Their AI-based SAST engine preserved context across layers, tracing untrusted data from entry points to critical functions.

OpenClaw maintainers were notified through responsible disclosure and have since issued patches and advisories. Researchers argue that as AI agent frameworks expand into enterprise environments, security analysis must adapt to address both conventional vulnerabilities and AI-specific attack surfaces.

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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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OpenClaw users face account suspensions under Google AI rules

Google has suspended access to its Antigravity AI platform for numerous OpenClaw users, citing violations of its terms of service. Developers had used OpenClaw’s OAuth plugin to access subsidised Gemini model tokens, triggering backend strain and service degradation.

OpenClaw, launched in November 2025, gained more than 219,000 GitHub stars by enabling local AI agents for tasks such as email management and web browsing. Users authenticated through Antigravity to access advanced Gemini models at reduced cost, bypassing official distribution channels.

Google said the third-party integration powered non-authorised products on Antigravity infrastructure, triggering usage flagged as malicious. In February 2026, AI Ultra subscribers reported 403 errors and account restrictions, with some citing temporary disruptions to Gmail and Workspace.

Varun Mohan of Google DeepMind said the surge had degraded service quality and that enforcement prioritised legitimate users. Limited reinstatement options were offered to those unaware of violations, while capacity constraints were cited as the reason.

The move follows similar restrictions by Anthropic on third-party OAuth usage. Developers are shifting to alternative forks, as debate intensifies over open tooling, platform control, and the risks of agentic AI ecosystems.

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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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