Seasonal influenza remains a significant global health burden, causing millions of severe infections and significant mortality each year, according to World Health Organisation estimates released in early 2025.
In several regions, flu activity has returned to or surpassed pre-pandemic levels, placing older adults, young children, and individuals with chronic conditions at the highest risk. Such patterns reinforce the need for improved prevention strategies and more effective vaccines.
Efforts to control influenza are challenged by the virus’s rapid mutation and the limitations of traditional laboratory methods. AI and machine learning are emerging as powerful tools for predicting antigenic changes, enhancing vaccine strain selection, and accelerating manufacturing.
Beyond vaccine development, AI-driven models are enhancing infection monitoring and immune response analysis by leveraging routine clinical data. These advances enhance surveillance and pave the way for personalised influenza prevention and treatment.
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The Central Bank of Russia has introduced a detailed proposal aimed at bringing cryptocurrencies under a unified regulatory framework, marking a significant step towards formal legal recognition of digital assets.
Under the proposal, both qualified and non-qualified investors would be permitted to purchase cryptocurrencies. Investor status would be determined by factors such as education, professional background, income level, and asset holdings.
Non-qualified investors would be restricted to buying up to 300,000 roubles worth of crypto per year through authorised intermediaries.
Digital currencies and stablecoins would be classified as currency values under Russian law, yet their use as a means of payment for goods and services would remain prohibited. The framework maintains the state’s long-standing opposition to domestic crypto payments.
Russian residents would also gain the right to purchase and transfer crypto assets abroad, provided such transactions are reported to the Federal Tax Service. The central bank aims to finalise the legislative groundwork by 1 July 2026.
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Rising demand for AI is pushing data centre servers to operate at extreme speeds and temperatures. Traditional air cooling is no longer sufficient for the most powerful computer chips.
Liquid cooling systems use sprays or immersion baths to remove heat more efficiently. These methods allow continuous high performance while reducing the risk of hardware failure and overheating.
Environmental concerns are growing as data centres consume vast amounts of energy and water. Closed-loop liquid cooling cuts electricity use and limits water withdrawal from local supplies and ecosystems.
Concerns persist regarding certain cooling chemicals and their potential climate impact. Researchers and companies are developing safer fluids and passive cooling inspired by natural systems and biological processes.
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An EU-funded project, AIOLIA, is examining how Europe’s approach to trustworthy AI can be applied in practice. Principles such as transparency and accountability are embedded in the AI Act’s binding rules. Turning those principles into design choices remains difficult.
The project focuses on closing that gap by analysing how AI ethics is applied in real systems. Its work supports the implementation of AI Act requirements beyond legal text. Lessons are translated into practical training.
Project coordinator Alexei Grinbaum argues that ethical principles vary widely by context. Engineers are expected to follow them, but implications differ across systems. Bridging the gap requires concrete examples.
AIOLIA analyses ten use cases across multiple domains involving professionals and citizens. The project examines how organisations operationalise ethics under regulatory and organisational constraints. Findings highlight transferable practices without a single model.
Training is central to the initiative, particularly for EU ethics evaluators and researchers working under the AI Act framework. As AI becomes more persuasive, risks around manipulation grow. AIOLIA aims to align ethical language with daily decisions.
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ChatGPT Atlas has introduced an agent mode that allows an AI browser agent to view webpages and perform actions directly. The feature supports everyday workflows using the same context as a human user. Expanded capability also increases security exposure.
Prompt injection has emerged as a key threat to browser-based agents, targeting AI behaviour rather than software flaws. Malicious instructions embedded in content can redirect an agent from the user’s intended action. Successful attacks may trigger unauthorised actions.
To address the risk, OpenAI has deployed a security update to Atlas. The update includes an adversarially trained model and strengthened safeguards. It followed internal automated red teaming.
Automated red teaming uses reinforcement learning to train AI attackers that search for complex exploits. Simulations test how agents respond to injected prompts. Findings are used to harden models and system-level defences.
Prompt injection is expected to remain a long-term security challenge for AI agents. Continued investment in testing, training, and rapid mitigation aims to reduce real-world risk. The goal is to achieve reliable and secure AI assistance.
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ChatGPT has introduced a new feature, ‘Your Year with ChatGPT,’ allowing users to review their interactions with the AI over the past 12 months. The optional summary highlights high-level themes from conversations and provides usage statistics.
The feature is gradually rolling out to Free, Plus, and Pro users in the United States, the United Kingdom, Canada, Australia, and New Zealand. Users must have Memory and Reference Chat History enabled and meet a minimum activity threshold to access the review.
Those with limited activity will only see basic statistics.
Available anytime via the prompt ‘Your Year with ChatGPT’, the review reflects on how individual usage evolved throughout 2025. ChatGPT emphasises that the experience is designed to provide insights for frequent users, with access varying by account type, region, and language.
The new feature allows AI enthusiasts to reflect on their engagement over the year and gain a personalised snapshot of their interactions, encouraging a fresh look at how ChatGPT has been integrated into daily use.
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TikTok Shop has introduced digital gift cards as part of its wider push into e-commerce. Users can purchase cards for $10 to $500 and choose animated designs for occasions such as birthdays or weddings. Availability is currently limited to the United States.
Recipients must have a TikTok account to redeem a gift card, and the balance is added to their TikTok Wallet instantly. Users can reply with a thank-you message or send a gift card as a return gesture. The approach reinforces TikTok’s focus on social interaction alongside transactions.
The feature puts the digital shop in more direct competition with established e-commerce platforms such as Amazon and eBay, which have long offered digital gift cards. Moves into higher-end retail to broaden its ambitions. The social media powerhouse is positioning itself as a full-scale online marketplace.
Momentum has continued to build, with US sales exceeding $500 million during the Black Friday and Cyber Monday period. The results highlight rising consumer confidence in the platform’s ability to drive purchases. Engagement is increasingly translating into measurable commerce.
Further developments are planned, including video messages and an interactive unboxing experience, which are expected to be released in early 2026. Expansion continues despite uncertainty around the platform’s future in the US. Negotiations over a potential sale remain unresolved ahead of January 2026.
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Madrid has strengthened emergency response capabilities through a new collaboration between Orange and Ericsson, integrating a dedicated slice within Orange’s 5G Standalone network.
Advanced radio access and core technologies allow emergency teams to operate on prioritised connectivity during high network demand.
Police, fire and medical services benefit from guaranteed bandwidth and low-latency communications, ensuring uninterrupted coordination during incidents.
The infrastructure by Ericsson enables dynamic switching between public 5G and emergency spectrum, supporting rapid deployment when physical networks are compromised.
Resilience remains central to the design, with autonomous power systems and redundancy maintaining operations during outages. Live video transmission from firefighters’ helmets illustrates how real time data improves risk assessment and decision making on the ground.
By combining telecom innovation with public safety needs, the initiative reinforces Madrid’s role in the emergency communications leadership of the EU and demonstrates how 5G can support critical services at scale.
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Researchers at the University of Tartu and Better Medicine developed an AI tool that speeds up kidney cancer detection and aids radiologists in analysing CT scans. The system, BMVision, was validated in a study published in Nature Communications Medicine.
BMVision utilises machine learning to identify both malignant and benign lesions, enabling radiologists to detect tumours faster and more accurately. In trials at Tartu University Hospital, six radiologists reviewed 200 CT scans with and without AI assistance.
Results showed that AI reduced detection and reporting time by roughly one third, while maintaining high diagnostic accuracy.
The tool complements radiologists, letting them focus on complex cases and improve patient outcomes. CE marking confirms BMVision meets European standards, making it the first commercial AI tool for early kidney cancer detection.
BMVision is now being integrated into clinical workflows at Tartu University Hospital, with the potential to process all abdominal CT scans in the future. Experts say the system demonstrates how AI can make a meaningful impact in routine medical practice and improve early cancer diagnosis.
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Scientists have developed an AI model capable of simulating complex fusion plasma in seconds, a process that previously took hours or even days. The tool, named GyroSwin, offers a faster, more cost-effective approach to designing future fusion power plants.
Traditional five-dimensional plasma simulations, which account for spatial dimensions and particle velocities, require immense supercomputing power and long computation times.
GyroSwin uses AI to learn plasma dynamics, producing accurate simulations up to 1,000 times faster than conventional methods. Faster modelling will help optimise turbulence management, a key challenge in achieving practical fusion energy.
The AI tool preserves crucial physical information, such as fluctuation scales and sheared flows, ensuring simulations remain physically interpretable.
Researchers at UK Atomic Energy Authority, Johannes Kepler University, and Emmi AI believe GyroSwin could transform the design and operation of next-generation fusion plants, including the UK’s STEP project.
GyroSwin demonstrates how AI and supercomputing can accelerate the path towards clean, abundant fusion energy while reducing the cost and complexity of plasma modelling, paving the way for a new era of fusion innovation.
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