The Japan Fair Trade Commission (JFTC) announced it will investigate AI-based online search services over concerns that using news articles without permission could violate antitrust laws.
Authorities said such practices may amount to an abuse of a dominant bargaining position under Japan’s antimonopoly regulations.
The inquiry is expected to examine services from global tech firms, including Google, Microsoft, and OpenAI’s ChatGPT, as well as US startup Perplexity AI and Japanese company LY Corp. AI search tools summarise online content, including news articles, raising concerns about their effect on media revenue.
The Japan Newspaper Publishers and Editors Association warned AI summaries may reduce website traffic and media revenue. JFTC Secretary General Hiroo Iwanari said generative AI is evolving quickly, requiring careful review to keep up with technological change.
The investigation reflects growing global scrutiny of AI services and their interaction with content providers, with regulators increasingly assessing the balance between innovation and fair competition in digital markets.
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OpenAI is said to be testing a new feature for ChatGPT that would mark a shift from Custom GPTs toward a more modular system of Skills.
Reports suggest the project, internally codenamed Hazelnut, will allow users and developers to teach the AI model standalone abilities, workflows and domain knowledge instead of relying only on role-based configurations.
The Skills framework is designed to allow multiple abilities to be combined automatically when a task requires them. The system aims to increase portability across the web version, desktop client and API, while loading instructions only when needed instead of consuming the entire context window.
Support for running executable code is also expected, providing the model with stronger reliability for logic-driven work, rather than relying entirely on generated text.
Industry observers note similarities to Anthropic’s Claude, which already benefits from a skill-like structure. Further features are expected to include slash-command interactions, a dedicated Skill editor and one-click conversion from existing GPTs.
Market expectations point to an early 2026 launch, signalling a move toward ChatGPT operating as an intelligent platform rather than a traditional chatbot.
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SK Hynix has urged the South Korean government to relax fair trade rules to allow the creation of a special-purpose company for raising funds for significant investments. The move comes as the semiconductor firm faces high capital demands amid the global AI boom.
Currently, SK hynix, a second-tier subsidiary of SK Group through SK Square, must retain full ownership when establishing third-tier subsidiaries. The government pledged to cut the ownership requirement to 50 percent, giving chipmakers more flexibility in funding projects.
The company highlighted the rising costs of advanced facilities, noting that a cleanroom at the Yongin semiconductor cluster in 2019 required 7.5 trillion won ($5.14 billion), while the new M15X fabrication plant in 2025 cost around 20 trillion won.
The size and long-term nature of modern semiconductor investments increasingly strain existing methods for raising funds.
SK hynix said letting subsidiaries partner with external investors would ease financial pressure and improve corporate health. The company added that regulatory flexibility is crucial for sustaining investment and competitiveness in a sector marked by high volatility.
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Fraudulent investment platform Nomani has surged, spreading from Facebook to YouTube. ESET blocked tens of thousands of malicious links this year, mainly in Czech Republic, Japan, Slovakia, Spain, and Poland.
The scam utilises AI-generated videos, branded posts, and social media advertisements to lure victims into fake investments that promise high returns. Criminals then request extra fees or sensitive personal data, and often attempt a secondary scam posing as Europol or INTERPOL.
Recent improvements make Nomani’s AI videos more realistic, using trending news or public figures to appear credible. Campaigns run briefly and misuse social media forms and surveys to harvest information while avoiding detection.
Despite overall growth, detections fell 37% in the second half of 2025, suggesting that scammers are adapting to more stringent law enforcement measures. Meta’s ad platforms earned billions from scams, demonstrating the global reach of Nomani fraud.
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Japan’s competition authority will probe AI search services from major domestic and international tech firms. The investigation aims to identify potential antitrust violations rather than impose immediate sanctions.
The probe is expected to cover LY Corp., Google, Microsoft and AI providers such as OpenAI and Perplexity AI. Concerns centre on how AI systems present and utilise news content within search results.
Legal action by Japanese news organisations alleges unauthorised use of articles by AI services. Regulators are assessing whether such practices constitute abuse of market dominance.
The inquiry builds on a 2023 review of news distribution contracts that warned against the use of unfair terms for publishers. Similar investigations overseas, including within the EU, have guided the commission’s approach.
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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.
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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.
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Chief financial officers predict AI will shift finance from experimentation to enterprise-wide impact in 2026. Real-time insights, scenario modelling and strategic decision-making are expected to become central to finance functions.
Success depends on trusted data, strong governance, modernised architectures and human judgement. AI will not replace expertise, but rather reveal gaps and reward organisations that integrate AI with their strategy.
CFOs plan to use AI for capital allocation, forecasting, risk management and operational efficiency. The focus is moving from efficiency gains to transformative, high-value work that drives measurable outcomes.
Enterprise-wide adoption of AI will require robust oversight and upskilling of finance teams. Leaders who modernise systems and combine AI with human expertise will gain a competitive edge.
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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.
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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.
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