Key Internet developments

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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AI data centre surge pushes electricity demand in the UK to new heights

The UK faces rising pressure on its electricity system as about 140 new data centre projects could demand more power than the country’s current peak consumption, according to Ofgem.

The regulator said developers are seeking about 50 gigawatts of capacity, a level driven by rapid growth in AI and far beyond earlier forecasts.

Connection requests have surged since late 2024, placing strain on a grid already struggling to support vital renewable projects that are key to national climate targets.

Work needed to connect expanding data centre capacity could delay schemes considered essential for decarbonisation and economic growth, instead of supporting the transition at the required pace.

The growing electricity footprint of AI infrastructure also threatens the aim of creating a virtually carbon-free power system by 2030, particularly as high costs and slow grid integration continue to hinder progress.

A proposed data centre in Lincolnshire has already raised concerns by projecting emissions greater than those of several international airports combined.

Ofgem now warns that speculative grid applications are blocking more viable projects, including those tied to government AI growth zones.

The regulator is considering more stringent financial requirements and new fees for access to grid connections, arguing that developers may need to build their own routes to the network rather than rely entirely on existing infrastructure.

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OpenAI model revises proof claim

OpenAI has published its attempts to solve all 10 problems in the First Proof challenge, a research-level maths test designed to assess whether AI can produce checkable, domain-specific proofs. Leading experts created the issues and require extended reasoning rather than short answers.

The company said at least five of its proof attempts are likely correct following expert feedback, although one previously confident submission has now been judged incorrect. Several other attempts remain under review as specialists continue to assess the arguments.

According to OpenAI, the evaluation involved limited human supervision, with researchers sometimes prompting the model to refine or clarify reasoning. The process included exchanges between an internal model and ChatGPT for verification, formatting and style adjustments.

OpenAI described frontier research challenges, such as First Proof, as crucial for testing next-generation AI systems. The company said it plans to deepen its engagement with academics to develop more rigorous evaluation frameworks for research-grade reasoning.

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OpenClaw exploits spark a major security alert

A wave of coordinated attacks has targeted OpenClaw, the autonomous AI framework that gained rapid popularity after its release in January.

Multiple hacking groups have taken advantage of severe vulnerabilities to steal API keys, extract persistent memory data, and push information-stealing malware instead of leaving the platform’s expanding user base unharmed.

Security analysts have linked more than 30,000 compromised instances to campaigns that intercept messages and deploy malicious payloads through channels such as Telegram.

Much of the damage stems from flaws such as the Remote Code Execution vulnerability CVE-2026-25253, supply chain poisoning, and exposed administrative interfaces. Early attacks centred on the ‘ClawHavoc’ campaign, which disguised malware as legitimate installation tools.

Users who downloaded these scripts inadvertently installed stealers capable of full compromise, enabling attackers to move laterally across enterprise systems instead of being confined to a single device.

Further incidents emerged on the OpenClaw marketplace, where backdoored ‘skills’ were published from accounts that appeared reliable. These updates executed remote commands that allowed attackers to siphon OAuth tokens, passwords, and API keys in real time.

A Shodan scan later identified more than 312,000 OpenClaw instances running on a default port with little or no protection, while honeypots recorded hostile activity within minutes of appearing online.

Security researchers argue that the surge in attacks marks a decisive moment for autonomous AI frameworks. As organisations experiment with agents capable of independent decision-making, the absence of security-by-design safeguards is creating opportunities for organised threat groups.

Flare’s advisory urges companies to secure credentials and isolate AI workloads instead of relying on default configurations that expose high-privilege systems to the internet.

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Cloudflare outage causes global internet disruption after an internal error

A major outage on 20 February disrupted global internet traffic after an internal configuration failure at Cloudflare caused the unintended withdrawal of customer BGP routes.

The incident lasted just over six hours and left numerous services unreachable, despite early fears of a cyberattack. An internal update led to the systematic deletion of more than a thousand Bring Your Own IP prefixes, which pushed many connections into BGP path hunting instead of stable routing.

Engineers traced the disruption to an error in the company’s Addressing API, introduced during an automated cleanup task under the Code Orange resilience programme.

A flawed query interpreted an empty value as an instruction to delete all returned prefixes, removing essential bindings for hundreds of customers. Some users restored connectivity through the dashboard, while others required manual reconstruction carried out across the edge network.

An outage that affected a series of core offerings, including content delivery, security layers, dedicated egress and network protection services. Restoration took several hours because the withdrawn prefixes varied in severity, demanding different recovery methods instead of a uniform reinstatement process.

The error triggered widespread timeouts on dependent websites and applications, along with 403 responses on the 1.1.1.1 DNS resolver.

Cloudflare plans to introduce stricter API validation, circuit breakers for abnormal deletion patterns, and improved configuration separation. It has also issued a public apology for a failure that undermined its assurances of network resilience.

An event that reaffirmed the risks posed by internal automation faults when they interact with critical internet infrastructure.

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