Artificial intelligence

European tech strategy advances with Germany’s new AI factory

Germany has launched one of Europe’s largest AI factories to boost EU-wide sovereign AI capacity. Deutsche Telekom unveiled the new ‘Industrial AI Cloud’ in Munich, in partnership with NVIDIA and Polarise.

Designed to deliver high-performance AI computing for industry, research, and public institutions, the platform keeps data operations under European jurisdiction. Company executives described the project as proof that Europe can build large-scale AI infrastructure aligned with its regulatory and sovereignty goals.

The AI factory runs on nearly 10,000 NVIDIA Blackwell GPUs, providing up to 0.5 exaFLOPS of computing power. Telekom said the capacity would be sufficient to support hundreds of millions of users accessing AI services simultaneously across the EU.

Officials in Germany framed the AI factory initiative as a strategic investment in technological leadership and digital independence. The infrastructure operates under German and EU data protection rules, positioning compliance and security as core competitive advantages.

Industrial applications are central to the project, with companies such as Siemens integrating simulation tools into the platform. The AI factory also runs on renewable energy, uses river water cooling, and plans to reuse waste heat within Munich’s urban network.

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Agentic AI transforms finance systems

Organisations undergoing finance transformations are discovering that traditional system cutovers rarely go as planned. Hidden manual workarounds and undocumented processes often surface late, creating operational risks and delays during ERP migrations.

Agentic AI is emerging as a solution by deploying autonomous software agents that discover real workflows directly from system data. Scout agents analyse transaction logs to uncover hidden dependencies, allowing companies to build more accurate future systems based on actual operations.

Simulator agents to stress test new systems by generating thousands of realistic transactions continuously. When problems arise, agents analyse errors and automatically recommend fixes, turning testing into a continuous improvement process rather than a one-time checkpoint.

Sentinel agents monitor financial records in real time to detect discrepancies before they escalate into compliance risks. Leaders say the approach shifts focus from single go-live milestones to ongoing resilience, with teams increasingly managing intelligent systems instead of manual processes.

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New AI training platform for Olympians unveiled by Google Cloud

Google Cloud has launched an AI-powered video analysis platform designed to help US Ski & Snowboard athletes refine performance ahead of major international competitions.

Built using Gemini and advanced Google DeepMind models, the system analyses the biomechanics behind high-speed freestyle skiing and snowboarding manoeuvres.

Traditional motion capture required specialised suits and controlled lab environments. Google’s platform converts smartphone footage into biomechanical analysis, mapping body positioning, trick amplitude, and edge control within minutes.

Coaches and athletes can query performance data conversationally for immediate insight.

Near real-time delivery marks a significant shift in training methodology. Analysis can be reviewed on the slopes shortly after a run, enabling faster technical adjustments.

The technology is also supporting athlete preparation for the Milano-Cortina 2026 Winter Olympics, where marginal gains can determine podium outcomes.

Applications extend beyond winter sports. Similar AI biomechanics systems could support physical rehabilitation, robotics engineering, and industrial safety environments where precision movement analysis is essential.

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Dubai hosts launch of AI tools for university students

The UAE Ministry of Higher Education and Scientific Research has partnered with Microsoft to develop AI agents to help university students find jobs. The initiative was announced in Dubai during a major policy gathering in the UAE.

The collaboration in the UAE will use Microsoft Azure to build prototype AI agents supporting personalised learning and career navigation. Dubai-based officials said the tools are designed to align higher education with labour market needs in the UAE.

Four AI agents are being developed in the UAE, covering lifelong skills planning, personalised learning, course co creation and research alignment. Dubai remains central to the project as a hub for higher education innovation in the UAE.

Officials in the UAE said the partnership reflects national priorities around innovation and a knowledge based economy. Microsoft said Dubai offers an ideal environment to scale AI driven education tools across the UAE.

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Big Tech’s $600 billion AI spending spree spooks global investors

A based report highlights that major technology companies are planning to spend roughly $600 billion on AI-related capital expenditure in 2026, including data centres, AI hardware and infrastructure, which has unsettled global markets.

Shares of some big tech firms fell sharply on investor worries that such eye-wateringly high AI spending may not deliver near-term profits and could weaken traditional software sectors.

For example, Amazon’s share price slid after announcing a $200 billion capex plan, and other software and analytics stocks also saw significant declines.

Analysts say markets are no longer interpreting AI spending purely as a growth narrative; heightened caution reflects concerns that heavy investment may pull future earnings forward too aggressively or concentrate market leadership among a few mega-cap names, while broad profitability remains uncertain.

This investor unease has contributed to broader equity market weakness, with indices like the S&P 500 and tech weights under pressure as software and data services stocks face continued selling.

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AI stethoscope doubles detection of serious heart valve disease

Researchers in the United States have shown that an AI-enabled digital stethoscope detected moderate to severe valvular heart disease more than twice as often as traditional tools during routine clinical exams.

The study assessed 357 patients aged 50 and above in primary care settings, using both conventional and AI-assisted stethoscopes. Sensitivity rose from 46.2 percent with traditional listening to 92.3 percent with the AI-enabled device.

Valvular heart disease affects a large proportion of older adults but frequently remains undiagnosed due to subtle or absent symptoms and limitations of conventional auscultation during busy clinical practice.

The digital stethoscope records high-fidelity heart sounds and applies machine-learning models to identify acoustic patterns associated with valve abnormalities, helping clinicians make early screening decisions.

US researchers noted a small drop in specificity that could increase false positives, but argued that earlier detection could reduce complications, hospital admissions, and long-term healthcare costs.

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EU split widens over ban on AI nudification apps

European lawmakers remain divided over whether AI tools that generate non-consensual sexual images should face an explicit ban in the EU legislation.

The split emerged as debate intensified over the AI simplification package, which is moving through Parliament and the Council rather than remaining confined to earlier negotiations.

Concerns escalated after Grok was used to create images that digitally undressed women and children.

The EU regulators responded by launching an investigation under the Digital Services Act, and the Commission described the behaviour as illegal under existing European rules. Several lawmakers argue that the AI Act should name pornification apps directly instead of relying on broader legal provisions.

Lead MEPs did not include a ban in their initial draft of the Parliament’s position, prompting other groups to consider adding amendments. Negotiations continue as parties explore how such a restriction could be framed without creating inconsistencies within the broader AI framework.

The Commission appears open to strengthening the law and has hinted that the AI omnibus could be an appropriate moment to act. Lawmakers now have a limited time to decide whether an explicit prohibition can secure political agreement before the amendment deadline passes.

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MIT researchers unveil EnCompass for AI agent search

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory and Asari AI have introduced EnCompass, a framework designed to enhance how AI agents interact with large language models.

The system improves agent performance by automatically backtracking when errors occur and running multiple execution paths in parallel to identify the most effective outcome.

Programming AI agents traditionally requires extensive additional code to handle model mistakes. EnCompass removes that burden by embedding retry and search logic directly into execution.

Developers annotate key decision points, allowing the framework to explore alternative reasoning paths while preserving the agent’s original workflow structure.

Efficiency gains appear significant. Trials show coding effort for search implementation reduced by as much as 80%, while accuracy in code translation tasks improved between 15% and 40%.

Researchers demonstrated the framework’s ability to optimise repository translation and rule discovery across complex digital systems.

Future applications extend to large-scale software maintenance, scientific experimentation, and engineering design. Presented at NeurIPS, EnCompass positions structured search as key to advancing reliable, high-performance AI agent systems.

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Claude Opus 4.6 sets new benchmark for enterprise AI

Anthropic has released Claude Opus 4.6, its most advanced AI model to date, introducing significant improvements in coding performance, reasoning depth, and long-context comprehension.

Engineering workflows stand to benefit from stronger debugging, code review, and better large-scale repository management, while agentic task execution now runs for more extended periods with greater reliability.

The model’s 1M token context window, now in beta, enables sustained reasoning across vast datasets and extended conversations. Performance gains span multiple benchmarks, leading in agentic coding, multidisciplinary reasoning, and high-value knowledge work.

Information retrieval in long documents has also improved, addressing persistent industry concerns around context degradation.

Operational capabilities extend beyond software development into enterprise productivity. Financial analysis, research, and document workflows gain direct support, with spreadsheet and presentation integrations enhancing daily business use.

Within Claude Code, newly introduced agent teams allow multiple AI agents to collaborate autonomously on complex workloads.

Safety remains central, with expanded evaluations showing low misalignment risk backed by interpretability research and cybersecurity safeguards. Additional tools- adaptive thinking, effort scaling, and context compaction- add flexibility for deploying long-running AI systems at scale.

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Frontier and GPT-5.3-Codex mark major OpenAI expansion

OpenAI has unveiled Frontier, a new enterprise platform designed to help organisations build, deploy, and manage AI agents capable of executing real operational work.

The launch reflects accelerating enterprise adoption, with businesses reporting measurable productivity gains across manufacturing, finance, sales, and energy operations through agent deployment.

Frontier addresses a growing gap between AI model capability and real-world implementation. The platform equips AI agents with shared organisational context, system access, governance permissions, and feedback learning mechanisms.

By integrating across existing cloud infrastructure, enterprise software, and data environments, Frontier enables AI coworkers to operate across workflows rather than within isolated tools.

Alongside the platform release, OpenAI introduced GPT-5.3-Codex, its most advanced agentic coding model to date. The system combines the coding strength of earlier Codex iterations with expanded reasoning and professional task execution.

Benchmark performance leads across SWE-Bench Pro, Terminal-Bench, OSWorld, and GDPval, reflecting gains in software engineering, computer use, and knowledge work automation.

Cybersecurity capabilities also advance with the release. GPT-5.3-Codex includes enhanced vulnerability detection training and operates under strengthened safeguards designed to support defensive research while mitigating misuse.

Together, Frontier and GPT-5.3-Codex position AI agents as scalable digital coworkers capable of executing complex technical and enterprise workloads end-to-end.

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