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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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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Researchers at Mass General Brigham have unveiled BrainIAC, an artificial intelligence model capable of analysing brain MRI scans to predict age, dementia risk, tumour mutations, and cancer survival. The model demonstrates remarkable flexibility, handling a wide variety of medical tasks with high accuracy.
BrainIAC employs self-supervised learning to identify features from unlabeled MRI datasets, allowing it to adapt to numerous clinical applications without requiring extensive annotated data. Its performance surpasses that of conventional task-specific AI frameworks.
Tests on nearly 49,000 MRI scans across seven different tasks revealed the model’s ability to generalise across both healthy and abnormal images. It successfully tackled both straightforward tasks, such as scan classification, and complex challenges, including tumour mutation detection.
The team highlights BrainIAC’s potential to accelerate biomarker discovery, improve diagnostic tools, and personalise patient care. While results are promising, researchers note that further studies on additional imaging techniques and larger datasets are necessary to validate its broader clinical use.
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Artificial intelligence is becoming a cornerstone of India’s economic and industrial growth. The upcoming AI summit highlights the goal of building AI as national infrastructure, reflecting India’s languages, values, and knowledge systems.
Indian IT and service industries are moving beyond software maintenance to providing AI infrastructure and intelligent systems. Such a transformation can automate workflows, boost productivity, and create new opportunities domestically and globally.
Industrial AI is set to transform manufacturing, enabling next-generation factories through virtual twin technologies. AI grounded in physics and industrial knowledge allows faster prototyping, efficient resource use, and greater competitiveness for large enterprises and MSMEs.
Collaborations between NVIDIA and Dassault Systèmes showcase AI-driven factories and industrial intelligence. India’s talent, scale, and digital ecosystem position it to lead in industrial and generative AI, setting global technological and economic benchmarks.
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Anthropic’s official announcement emphasises that Claude will not carry advertising or ad-influenced content within conversations, positioning the AI assistant as a trusted and distraction-free ‘space to think’ for tasks ranging from deep thinking and research to work and personal problem-solving.
The company argues that AI interactions differ fundamentally from search or social media, as users often share context-rich, sensitive information where commercial incentives could conflict with genuinely helpful responses.
In the post, Anthropic explains that while ads have a clear place in many digital products, introducing them into conversational AI would compromise usefulness and trust.
Instead, the company plans to generate revenue through enterprise contracts and paid subscriptions, continuing to invest in product improvements, integrations with third-party tools (e.g., Figma, Asana), and broader access initiatives, all without monetising attention or engagement directly.
The statement also notes that Claude’s conversation data is kept private and anonymous, and that ads could skew model incentives toward engagement metrics rather than solving user problems effectively.
Anthropic positions this approach as central to preserving Claude’s role as a dedicated thinking and productivity assistant.
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AI and digital technologies are set to play a central role at the Milano-Cortina 2026 Winter Olympic Games, positioning the event as a global showcase for large-scale AI deployment. Organisers aim to demonstrate how advanced technologies can transform major international events across media, operations, and public engagement.
Audience experience will be significantly reshaped through AI-powered broadcasting and digital platforms. Innovations include first-person drones following athletes in real time and AI-assisted replays that generate multi-angle freeze frames and performance data. In parallel, AI-driven tools on the official Olympic website and social media platforms will offer personalised highlights, summaries, and interactive content.
At the same time, technology will support athletes both on and off the field. AI systems will monitor and flag abusive online content, while dedicated digital applications will assist with training, injury prevention, and communication with family members during competitions.
Beyond digital innovation, the Games will also highlight sustainability through design. Transparent, reusable Olympic torches powered by biofuel and made from recycled materials will showcase how technology can support environmental responsibility alongside sporting tradition.
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The rapid expansion of AI infrastructure, especially high-bandwidth memory (HBM) used in data centres and AI accelerators, is causing memory chip makers to prioritise production capacity for high-margin AI-related products, squeezing the supply of traditional DRAM and NAND used in consumer devices like smartphones, tablets and PCs.
Industry leaders, including Samsung, SK Hynix and Micron, are shifting wafer capacity toward AI-grade memory, and major cloud and hyperscale buyers (e.g., Nvidia, AWS, Google) are securing supply through long-term contracts, which reduces available inventory for mid-tier device manufacturers.
As a result, memory pricing has climbed sharply, forcing consumer electronics makers to raise retail prices, cut specs or downgrade other components to maintain margins.
Analysts warn the mid-range smartphone segment, typically priced between roughly $400–$600, faces a particular squeeze, with fewer compelling devices expected and slower spec improvements, as memory becomes a dominant cost driver and supply constraints persist.
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Scientists are applying AI to enhance iceberg tracking and movement prediction, using machine learning models that analyse historical drift patterns, ocean currents and weather data.
These AI systems aim to identify how icebergs behave over time and improve forecasts for their positions, which can help maritime operators and climate researchers anticipate hazards and plan safe routes.
Traditional methods for tracking icebergs, relying on satellite imagery and manual analysis, are limited by coverage gaps and delays. The new AI techniques can fill these gaps by generating continuous trajectory predictions, enabling more proactive monitoring over remote polar waters.
Researchers suggest that this approach could support shipping safety, offshore operations, and environmental management as climate change alters iceberg calving and drift behaviours.
This work reflects broader trends in using AI for environmental modelling, where machine learning augments physical models to better understand complex natural systems influenced by changing climate conditions.
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Pusan National University is piloting AI-powered translation glasses that display real-time subtitles of Korean-language lectures, aiming to reduce language barriers for international students. As a result, students can follow classes more easily, grasp specialised terminology, and engage more fully without the constant risk of missing key points.
In addition to academic settings, the technology is improving communication across campus life. For example, university staff, including counsellors, report that the glasses enable more natural, face-to-face conversations with foreign students, rather than relying on phones or other intermediary devices for translation.
Moreover, the pilot supports a broader push to internationalise the campus through AI-based multilingual services, including translated course syllabi and websites, with wider rollout to follow pending evaluation.
At the same time, the company behind the glasses is looking to expand adoption beyond Busan. If deployed more widely, the technology could influence higher education policies by easing language requirements and helping universities attract more international students, particularly as domestic enrolment declines.
However, several practical challenges remain. While translation accuracy is already high, issues such as device weight and battery life have prompted the development of lighter models. As the system continues to be refined and trained on academic vocabulary, its reliability and usability are expected to improve further.
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Enterprises in France are accelerating the use of AI to manage increasingly complex multicloud environments, according to new ISG research. Companies in France are balancing innovation, compliance and rising cost pressures.
The report says multicloud adoption in France now extends beyond large corporations to midsize firms and regulated sectors. Organisations in France are spreading workloads across hyperscalers and sovereign clouds to reduce risk.
AI driven automation is becoming central to cloud governance in France as manual oversight proves unsustainable. French enterprises are using AI tools for performance optimisation, anomaly detection and real time policy enforcement.
Data sovereignty and cost control are also shaping cloud strategies in France. Companies in France are adopting FinOps practices and sovereign cloud services to meet regulatory demands and strengthen cybersecurity.
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