AI is extending the clinical value of chest X-rays beyond lung and heart assessment. Researchers are investigating whether routine radiographs can support broader disease screening without the need for additional scans. Early findings suggest existing images may contain underused diagnostic signals.
A study in Radiology: Cardiothoracic Imaging examined whether AI could detect hepatic steatosis from standard frontal chest X-rays. Researchers analysed more than 6,500 images from over 4,400 patients across two institutions. Deep learning models were trained and externally validated.
The AI system achieved area-under-curve scores above 0.8 in both internal and external tests. Saliency maps showed predictions focused near the diaphragm, where part of the liver appears on chest X-rays. Results suggest that reliable signal extraction can be achieved from routine imaging.
Researchers argue the approach could enable opportunistic screening during standard care. Patients flagged by AI could be referred for a dedicated liver assessment when appropriate. The method adds clinical value without increasing imaging costs or radiation exposure.
Experts caution that the model is not a standalone diagnostic tool and requires further prospective validation. Integration with clinical and laboratory data remains necessary to reduce false positives. If validated, AI-enhanced X-rays could support scalable risk stratification.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
Use of AI chatbots for everyday tasks, from structuring essays to analysing data, has become widespread. Researchers are increasingly examining whether reliance on such tools affects critical thinking and learning. Recent studies suggest a more complex picture than simple decline.
A research study published by MIT found reduced cognitive activity among participants who used ChatGPT to write essays. Participants also showed weaker recall than those who completed tasks without AI assistance, raising questions about how learning develops when writing is outsourced.
Similar concerns emerged from studies by Carnegie Mellon University and Microsoft. Surveys of white-collar workers linked higher confidence in AI tools with lower levels of critical engagement, prompting warnings about possible overreliance.
Studies involving students present a more nuanced outcome. Research published by Oxford University Press found that many pupils felt AI supported skills such as revision and creativity. At the same time, some reported that tasks became too easy, limiting deeper learning.
Experts emphasise that outcomes depend on how AI tools are used. Educators argue for clearer guidance, transparency, and further research into long-term effects. Used as a tutor rather than a shortcut, AI may support learning rather than weaken it.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
A new research paper published in Aging-US uses AI to map a century of global ageing research. The study analyses how scientific priorities have shifted over time. Underexplored areas are also identified.
Researchers analysed more than 460,000 scientific abstracts published between 1925 and 2023. Natural language processing and machine learning were used to cluster themes and track trends. The aim was to provide an unbiased view of the field’s evolution.
Findings show a shift from basic biological studies toward clinical research, particularly age-related diseases such as Alzheimer’s and dementia. Basic science continues to focus on cellular mechanisms. Limited overlap persists between laboratory and clinical research.
Several fast-growing topics, including autophagy, RNA biology, and nutrient sensing, remain weakly connected to clinical applications. Strong links endure in areas such as cancer and ageing. Other associations, including epigenetics and autophagy, are rarely explored.
The analysis highlights gaps that may shape future ageing research priorities. AI-based mapping provides insights into how funding and policy shape focus areas. Greater integration could support more effective translation into clinical outcomes.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
Mandatory facial verification will be introduced in South Korea for anyone opening a new mobile phone account, as authorities try to limit identity fraud.
Officials said criminals have been using stolen personal details to set up phone numbers that later support scams such as voice phishing instead of legitimate services.
Major mobile carriers, including LG Uplus, Korea Telecom and SK Telecom, will validate users by matching their faces against biometric data stored in the PASS digital identity app.
Such a requirement expands the country’s identity checks rather than replacing them outright, and is intended to make it harder for fraud rings to exploit stolen data at scale.
The measure follows a difficult year for data security in South Korea, marked by cyber incidents affecting more than half the population.
SK Telecom reported a breach involving all 23 million of its customers and now faces more than $1.5 billion in penalties and compensation.
Regulators also revealed that mobile virtual network operators were linked to 92% of counterfeit phones uncovered in 2024, strengthening the government’s case for tougher identity controls.
Would you like to learn more aboutAI, tech and digital diplomacy? If so, ask our Diplo chatbot!
Amid growing attention on AI, Google DeepMind chief Demis Hassabis has argued that future systems could learn anything humans can.
He suggested that as technology advances, AI may no longer remain confined to single tasks. Instead of specialising narrowly, it could solve different kinds of problems and continue improving over time.
Supporters say rapid progress already shows how powerful the technology has become.
Other experts disagree and warn that human intelligence remains deeply complex. People rely on emotions, personal experience and social understanding when they think, while machines depend on data and rules.
Critics argue that comparing AI with the human mind oversimplifies how intelligence really works, and that even people vary widely in ability.
Elon Musk has supported the idea that AI could eventually learn as much as humans, while repeating his long-standing view that powerful systems must be handled carefully. His backing has intensified the debate, given his influence in the technology world.
The discussion matters because highly capable AI could reshape work, education and creativity, raising questions over safety and control.
For now, AI performs specific tasks extremely well yet cannot think or feel like humans, and no one can say for certain whether true human-level intelligence will ever emerge.
Would you like to learn more aboutAI, tech and digital diplomacy? If so, ask our Diplo chatbot!
Authorities in Romania have confirmed a severe ransomware attack on the national water administration ‘Apele Române’, which encrypted around 1,000 IT systems across most regional water basin offices.
Attackers used Microsoft’s BitLocker tool to lock files and then issued a ransom note demanding contact within seven days, although cybersecurity officials continue to reject any negotiation with criminals.
The disruption affected email systems, databases, servers and workstations instead of operational technology, meaning hydrotechnical structures and critical water management systems continued to function safely.
Staff coordinated activity by radio and telephone, and flood defence operations remained in normal working order while investigations and recovery progressed.
National cyber agencies, including the National Directorate of Cyber Security and the Romanian Intelligence Service’s cyber centre, are now restoring systems and moving to include water infrastructure within the state cyber protection framework.
The case underlines how ransomware groups increasingly target essential utilities rather than only private companies, making resilience and identity controls a strategic priority.
Would you like to learn more aboutAI, tech and digital diplomacy? If so, ask our Diplo chatbot!
Prime Minister Kim Min-seok has called for punitive fines of up to 10 percent of company sales for repeated and serious data breaches, as public anger grows over large-scale leaks.
The government is seeking swift legislation to impose stronger sanctions on firms that fail to safeguard personal data, reflecting President Lee Jae Myung’s stance that violations require firm penalties instead of lenient warnings.
Kim said corporate responses to recent breaches had fallen far short of public expectations and stressed that companies must take full responsibility for protecting customer information.
Under the proposed framework, affected individuals would receive clearer notifications that include guidance on their rights to seek damages.
The government of South Korea also plans to strengthen investigative powers through coercive fines for noncompliance, while pursuing rapid reforms aimed at preventing further harm.
The tougher line follows a series of major incidents, including a leak at Shinhan Card that affected around 190,000 merchant records and a large-scale breach at Coupang that exposed the data of 33.7 million users.
Officials have described the Coupang breach as a serious social crisis that has eroded public trust.
Authorities have launched an interagency task force to identify responsibility and ensure tighter data protection across South Korea’s digital economy instead of relying on voluntary company action.
Would you like to learn more aboutAI, tech and digital diplomacy? If so, ask our Diplo chatbot!
If you are piecing together a new workstation or gaming rig, or just hunting for extra RAM or SSD storage, you have stumbled into the worst possible moment. With GPU prices already sky-high, the recent surge in RAM and storage costs has hit consumers hard, leaving wallets lighter and sparking fresh worries about where the tech market is headed.
On the surface, the culprit behind these soaring prices is a sudden RAM shortage. Prices for 32GB and 64GB sticks have skyrocketed by as much as 600 percent, shelves are emptying fast, and the balance between supply and demand has completely unraveled.
But blaming the sky-high prices on empty shelves only tells part of the story. Why has affordable RAM vanished? How long will this chaos last? And most intriguingly, what role does AI play in this pricing storm?
Tracing the causes of RAM pricing spikes
The US tariffs imposed on China on 1 August 2025, played a substantial role in the increase in DRAM prices. Global imports of various goods have become more costly, investments and workforce onboarding have been halted, and many businesses relying on imports have adopted a ‘wait-and-see’ approach to how they will do business going forward.
However, the worst was yet to come. On 3 December, Micron, one of the world’s leading manufacturers of data storage and computer memory components, announced its withdrawal from the RAM consumer market, citing a ‘surge in demand for memory and storage’ driven by supply shortages of memory and storage for AI data centres.
With Micron out of the picture, we are left with only two global consumer RAM and high-bandwidth memory (HBM) manufacturers: Samsung and SK Hynix. While there are countless RAM brands on the market, with Corsair, Kingston, and Crucial leading the charge, all of them rely on the three aforementioned suppliers for memory chips.
Micron’s exit was likely met with obscured glee by Samsung and SK Hynix of South Korea, who seized the opportunity to take over Crucial’s surrendered territory and set the stage for their DRAM/HBM supply duel. The latter supplier was quick to announce the completion of its M15X semiconductor fabrication plant (fab), but warned that RAM supply constraints are likely to last until 2028 at the earliest.
Amid the ruckus, rumours surfaced that Samsung would be sunsetting its SATA SSD production, which the company quickly extinguished. On the contrary, the Korean giant announced its intention to dethrone SK Hynix as the top global RAM provider, with more than 80 percent of its projected profits coming directly from Samsung Electronics.
Despite their established market shares, both enterprises were caught off guard when their main rival threw in the towel, and their production facilities are unable, at current capacity, to accommodate the resulting market void. It is nigh certain that the manufacturers will use their newly gained market dominance to their advantage, setting prices based on their profit margins and customers’ growing demand for their products. In a nutshell, they have the baton, and we must play to their tune.
AI infrastructure and the reallocation of RAM supply
Micron, deeming commodity RAM a manufacturing inconvenience, made a move that was anything but rash. In October, Samsung and SK Hynix joined forces with OpenAI to supply the AI giant with a monthly batch of 900,000 DRAM wafers. OpenAI’s push to enhance its AI infrastructure and development was presumably seen by Micron as a gauntlet thrown by its competitors, and Crucial’s parent company took no time in allocating its forces to a newly opened front.
Lured by lucrative, long-term, high-volume contracts, all three memory suppliers saw AI as an opportunity to open new income streams that would not dry up for years to come. While fears of the AI bubble bursting are omnipresent and tangible, neither Samsung, SK Hynix, nor Micron are overly concerned about what the future holds for LLMs and AGI, as long as they continue to get their RAM money’s worth (literally).
AI has expanded across multiple industries, and three competitors judged Q4 2025 the opportune time to put all their RAM eggs in one basket. AI as a business model has yet to reach profitability, but corporate investors poured more than USD 250 billion into AI in 2024 alone. Predictions for 2025 have surpassed the USD 500 billion mark, but financiers will inevitably grow more selective as the AI startup herd thins and predicted cash cows fail to deliver future profits.
To justify massive funding rounds, OpenAI, Microsoft, Google, and other major AI players need to keep their LLMs in a perpetual growth cycle by constantly expanding their memory capacity. A hyperscale AI data centre can contain tens of thousands to hundreds of thousands of GPUs, each with up to 180 gigabytes of VRAM. Multiply that by 1,134, the current number of hyperscale data centres, and it is easy to see why Micron was eager to ditch the standard consumer market for more bankable opportunities.
The high demand for RAM has changed the ways manufacturers view risk and opportunity. AI infrastructure brings more volume, predictability, and stable contracts than consumer markets, especially during uncertain times and price swings. Even if some areas of AI do not meet long-term hopes, the need for memory in the near and medium term is built into data centre growth plans. For memory makers, shifting capacity to AI is a practical response to current market incentives, not just a risky bet on a single trend.
The aftermath of the RAM scarcity
The sudden price inflation and undersupply of RAM have affected more than just consumers building high-end gaming PCs and upgrading laptops. Memory components are critical to all types of devices, thereby affecting the prices of smartphones, tablets, TVs, game consoles, and many other IoT devices. To mitigate production costs and maintain profit margins, device manufacturers are tempted to offer their products with less RAM, resulting in substandard performance at the same price.
Businesses that rely on servers, cloud services, or data processing are also expected to get caught in the RAM crossfire. Higher IT costs are predicted to slow down software upgrades, digital services, and cybersecurity improvements. Every SaaS company, small or large, risks having its platforms overloaded or its customers’ data compromised.
Public institutions, such as schools, hospitals, and government agencies, will also have to bend backwards to cover higher hardware costs due to more expensive RAM. Operating on fixed budgets allows only so much wiggle room to purchase the required software and hardware, likely leading to delays in public digital projects and the continued use of outdated electronic equipment.
Rising memory costs also influence innovation and competition. When basic components become more expensive, it is harder for new companies to enter the market or scale up their services. This can favour large, well-funded firms and reduce diversity in the tech ecosystem. Finally, higher RAM prices can indirectly affect digital access and inclusion. More expensive devices and services make it harder for individuals and communities to afford modern technology, widening existing digital divides.
In short, when RAM becomes scarce or expensive, the effects extend far beyond memory pricing, influencing how digital services are accessed, deployed, and maintained across the economy. While continued investment in more capable AI models is a legitimate technological goal, it also raises a practical tension.
Advanced systems deliver limited value if the devices and infrastructure most people rely on lack the memory capacity required to run them efficiently. The challenge of delivering advanced AI models and AI-powered apps to subpar devices is one that AI developers will have to take into account moving forward. After all, what good is a state-of-the-art LLM if a run-of-the-mill PC or smartphone lacks the RAM to handle it?
The road ahead for RAM supply and pricing
As mentioned earlier, some memory component manufacturers predict that the RAM shortage will remain a burr under consumers’ saddles for at least a few years. Pompous predictions of the AI bubble’s imminent bursting have mostly ended up in the ‘I’ll believe it when I see it’ archive section, across the hall from the ‘NFTs are the future of digital ownership’ district.
Should investments continue to fill the budgets of OpenAI, Perplexity, Anthropic, and the rest, they will have the resources to reinforce their R&D departments, acquire the necessary memory components, and further develop their digital infrastructure. In the long run, the technology powering AI models may become more sophisticated to the point where energy demands reach a plateau. In that case, opportunities for expansion would be limitless.
Even though one of the biggest RAM manufacturers has fully shifted to making AI infrastructure components, there is still a gap large enough to be filled by small- and medium-sized producers. Companies such as Nanya Technology from Taiwan or US-based Virtium hold a tenth of the overall market share, but they have been given the opportunity to carry Micron’s torch and maintain competitiveness in their own capacities.
The current RAM price crisis is not caused by a single event, but by the way new technologies are changing the foundations of the digital economy. As AI infrastructure takes up more of the global memory supply, higher prices and limited availability are likely to continue across consumer, business, and public-sector markets. How governments, manufacturers, and buyers respond will shape not only the cost of hardware but also how accessible and resilient digital systems remain.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
Authorities in Greece have released initial results from a pilot rollout of AI-powered traffic cameras in the greater Athens area. More than 2,000 serious traffic violations were recorded over four days. The cameras were installed at high-risk locations across Attica.
A single AI camera on Syngrou Avenue logged over 1,000 violations related to mobile phone use and failure to wear seatbelts. Around 800 speeding cases were recorded on roads with a 90 km/h limit. Additional red-light violations were detected at major junctions in Agia Paraskevi and Kallithea.
The pilot programme, backed by the Hellenic Police, marks Greece’s first use of AI-based traffic cameras on Attica’s road network. The rollout forms part of a broader national road safety effort. Authorities have stressed deterrence rather than punishment.
The cameras monitor serious breaches of Greece’s Highway Code, including speeding, red-light violations, and illegal use of mobile phones. Recorded data include images, video, and time-stamped metadata transmitted in encrypted form. Drivers are notified digitally and can submit appeals online.
Plans are underway to expand the system across Greece, with up to 2,500 cameras proposed nationwide. Fixed units will target high-risk locations, while others will be installed on public transport buses. Regional authorities are also preparing to integrate motorway camera networks.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
Regulatory uncertainty has long shaped life sciences, but 2025 marked a shift in expectations. Authorities are focusing more on how companies operate in practice. Enforcement activity continues to signal sustained scrutiny.
Regulators across federal and state agencies are coordinating more closely. Attention is centred on digital system validation, AI-supported documentation, reimbursement processes, and third-party oversight. Flexibility in digital tools is no longer assumed.
Inspection priorities now extend beyond manufacturing quality. Regulators are examining governance of automated analyses, review of AI-generated records, and data consistency in decentralised trials. Clear documentation is becoming critical.
A similar shift is visible in reimbursement and data oversight. Authorities want insight into governance behind pricing, reporting, and data handling. Privacy enforcement now focuses on data flows, AI training data, and third-party access.
Looking ahead to 2026, scrutiny is expected to intensify around AI inspection standards and data sharing. Regulators are signalling higher expectations for transparency and accountability. Sound judgement and consistency may prove decisive.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
