Recent research indicates that AI applied to sleep pattern analysis can identify signals linked to over 130 health conditions, including heart disease, metabolic dysfunction and respiratory issues, from a single night’s sleep record.
By using machine learning to analyse detailed physiological data collected during sleep, AI models may reveal subtle patterns that correlate with existing or future health risks.
Proponents suggest that this technology could support early detection and preventative healthcare by offering a non-invasive way to screen for multiple conditions simultaneously, potentially guiding timely medical intervention.
However, clinicians stress that such AI tools should complement, not replace, formal medical evaluation and diagnosis.
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The NHS England has launched an innovative pilot project that uses AI software to rapidly analyse lung scans and flag suspect nodules, followed by a robotic bronchoscopy system that can reach deep lung spots previously hard to biopsy.
This approach could replace weeks of repeat scans and invasive procedures with a single targeted session, helping doctors diagnose or rule out cancer sooner.
The project, led at Guy’s and St Thomas’ NHS Foundation Trust, aims to support expanded national lung screening programmes and reduce health outcome inequalities by detecting cancers at an earlier, more treatable stage.
Officials describe the technology as a ‘glimpse of the future’ of cancer detection, while pilots will gather evidence on effectiveness and safety before wider rollout.
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At a national meteorological work conference, the China Meteorological Administration said it will pilot an ‘imminent warning’ system and apply AI technologies to enhance detailed forecasts for extreme weather, including typhoons and heavy rain.
The initiative is part of a broader effort in 2026 to build new meteorological service systems, such as for agriculture, and improve disaster preparedness and climate risk management across the country.
Officials highlighted progress over the past year, including improved flood-season forecasting and reduced typhoon track-prediction errors. Strengthened interagency coordination and the development of new prediction products aim to support earlier warnings and better resource allocation for extreme climate events.
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Subscriptions for Facebook, Instagram and WhatsApp are set to be tested as Meta explores new revenue streams while keeping core access free. Paid tiers would place selected features and advanced sharing controls behind a subscription.
Early signals indicate the subscriptions could launch within months, with each platform offering its own set of premium tools. Meta has confirmed it will trial multiple formats rather than rely on a single bundled model.
AI plays a central role in the plan, with subscribers gaining access to AI-powered features, including video generation. The recently acquired Manus AI agent will be integrated across Meta services and offered separately to business users.
User reaction is expected to influence how far the company pushes the model, including potential bundles or platform-specific pricing. Wider acceptance could encourage other social networks to adopt similar subscription strategies.
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The renewable energy sector in Australia encounters new challenges as major tech companies establish AI data centres across the country. Projects once planned to export solar power internationally are now influenced by domestic energy demands.
Sun Cable, supported by billionaires Mike Cannon-Brookes and Andrew Forrest, aimed to deliver Australian solar energy to Singapore via a 4,300-kilometre sea cable. The project symbolised a vision for Australia to become a leading exporter of renewable electricity.
The rapid expansion of AI facilities is shifting energy priorities towards domestic infrastructure. Tech companies’ demand for electricity is creating new competition with planned renewable export projects.
Energy policy decisions now carry broader implications for emissions, the national grid, and Australia’s role in the global clean energy market. Careful planning will be essential to balance domestic growth with long-term renewable ambitions.
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Audi is expanding the use of AI in production and logistics by replacing local factory computers with a central cloud platform. The Edge Cloud 4 Production enables flexible, networked automation while reducing hardware needs, maintenance costs, and improving IT security.
AI applications are being deployed to improve efficiency, quality, and employee support. AI-controlled robots are taking over physically demanding tasks, cloud-based systems provide real-time worker guidance, and vision-based solutions detect defects and anomalies early in the production process.
Data-driven platforms such as the P-Data Engine and ProcessGuardAIn allow Audi to monitor manufacturing processes in real time using machine and sensor data. These tools support early fault detection, reduce follow-up costs, and form the basis for predictive maintenance and scalable quality assurance across plants.
Audi is also extending automation to complex production areas that have traditionally relied on manual work, including wiring loom manufacturing and installation. In parallel, the company is working with technology firms and research institutions such as IPAI Heilbronn to accelerate innovation, scale AI solutions, and ensure the responsible use of AI across its global production network.
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Universities are increasingly integrating AI into foreign language teaching as lecturers search for more flexible and personalised learning methods. AI-powered tools are being used to generate teaching materials, adapt content to student needs and expand practice beyond classroom limits.
Despite growing interest, adoption among language lecturers remains uneven across higher education. Studies suggest AI-supported learning can improve student motivation by offering personalised feedback and judgment-free speaking practice.
Educators highlight the value of AI for supporting curriculum and creating resources, particularly for less commonly taught languages. Tools can generate targeted dialogues, simplified texts and pronunciation feedback that would otherwise require significant manual effort.
Human interaction, however, remains central to effective language learning. Lecturers stress that AI works best as a supplement, enhancing teaching quality without replacing real-world communication and pedagogical expertise.
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A group of YouTubers has filed a copyright lawsuit against Snap in the US, alleging their videos were used to train AI systems without permission. The case was lodged in a federal court in California and targets AI features used within Snapchat.
The creators claim that Snap relied on large-scale video-language datasets intended initially for academic research. According to the filing in California, access to the material required bypassing YouTube safeguards and license restrictions on commercial use.
The lawsuit in the US seeks statutory damages and a permanent injunction to block further use of the content. The case is led by creators behind the h3h3 channel, alongside two smaller US-based golf channels.
The action adds Snap to a growing list of tech companies facing similar claims in the US. Courts in California and elsewhere continue to weigh how copyright law applies to AI training practices.
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The government plans to trial AI tutoring tools in secondary schools, with nationwide availability targeted for the end of 2027. The tools will be developed through a government-led tender, bringing together teachers, AI labs, and technology companies to co-create solutions aligned with classroom needs.
The initiative aims to provide personalised, one-to-one-style learning support, adapting to individual pupils’ needs and helping them catch up where they struggle. A central objective is to reduce educational inequality, with up to 450,000 disadvantaged pupils in years 9–11 potentially benefiting each year, particularly those eligible for free school meals.
AI tutoring tools are intended to complement, not replace, face-to-face teaching. Teachers will play a key role in co-designing, testing, and refining the tools, ensuring they support high-quality teaching, provide targeted help to struggling pupils, and stretch higher-performing students.
Safety and quality are positioned as non-negotiable. The tools will be rigorously tested to ensure they are safe, reliable, and aligned with the National Curriculum, and clear benchmarks will be developed for use in schools. Trials beginning later this year will generate evidence to guide wider rollout, alongside practical training for teachers and school staff to support confident and responsible use of AI.
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Researchers at the University of Zurich have received a Postdoc Team Award for SpiritRAG, an AI system designed to analyse religion and spirituality in United Nations documents. The interdisciplinary project brings together expertise from Zurich across computer science, linguistics, education and spiritual care.
SpiritRAG connects large language models with more than 7,500 UN texts, allowing users in Zurich and beyond to ask context sensitive questions grounded in original sources. The system addresses challenges where meaning varies across cultures, history and political settings.
The Zurich based team presented SpiritRAG at EMNLP 2025 in Suzhou, China, and later at the AI+X Summit in Zurich. Interest from organisations outside Zurich highlights demand for transparent AI tools supporting research and policy analysis.
Designed as open source infrastructure, SpiritRAG allows deployment with different datasets while using limited resources. Researchers in Zurich say the approach supports responsible AI use in complex domains where accuracy and context remain critical.
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