ai

6G will make wireless networks capable of thinking for themselves

Unlike its predecessors, 6G is being designed from the ground up with AI as a core feature rather than a performance add-on.

From user devices and base stations through to the network core, AI and machine learning will enable 6G networks to self-optimise, manage interference, predict user mobility, and make real-time decisions with minimal human intervention.

One of 6G’s most distinctive capabilities will be Integrated Sensing and Communication (ISAC), which allows radio signals to simultaneously carry data and sense the surrounding environment, effectively turning the network into a vast, distributed sensor capable of detecting motion, tracking objects, and supporting applications such as predictive maintenance and autonomous vehicles.

AI plays a central role in interpreting this sensing data in real time, enabling split-second responses to real-world conditions.

Standardisation efforts are already underway, with 3GPP’s Release 20 exploring how AI and machine learning can optimise the air interface and improve tasks such as channel state information compression.

Commercial 6G deployment is expected in the early 2030s, by which point AI is projected to act as the brain and nervous system of key parts of the network, constantly learning, adapting, and optimising with little human oversight.

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AI tool could help detect domestic violence risk years earlier

Researchers in the United States have developed an AI system designed to help doctors identify patients who may be at risk of intimate partner violence. The tool analyses hospital data to detect patterns associated with abuse, potentially enabling healthcare professionals to intervene earlier.

Intimate partner violence refers to abuse from current or former partners and can lead to serious injuries, chronic pain, and long-term mental health problems. According to the European Commission, 18 percent of women who have had a partner reported experiencing physical or sexual violence from a partner in 2021.

The study, published in the journal Nature, examined hospital records from nearly 850 women who had experienced intimate partner violence and more than 5,200 similar patients in a control group. Researchers used the data to train three different machine learning systems to detect patterns associated with abuse.

One model analysed structured hospital data, such as age and medical history. A second model examined written clinical notes, including doctors’ observations and radiology reports. A third system combined both data types and achieved the strongest results, correctly identifying risk in 88 percent of cases.

Researchers found that the system could flag potential abuse more than three years before some patients later entered hospital-based intervention programmes. By analysing large datasets, the tool can detect patterns of physical trauma linked to abuse and alert clinicians so they can approach the issue carefully and offer support.

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Human made labels emerge as industries react to AI expansion

Organisations around the world are developing certification labels designed to show that products or creative work were made by humans rather than AI. New badges such as ‘Human made’, ‘AI free’ and ‘Proudly Human’ are appearing across books, films, marketing and websites as industries respond to the rapid spread of AI tools.

At least eight initiatives are now attempting to create a label that could achieve global recognition similar to the Fair Trade mark. Experts warn that competing definitions and inconsistent certification systems could confuse consumers unless a universal standard is agreed upon.

Some schemes allow creators to download AI-free badges with little or no verification, while others use paid auditing processes that rely on analysts and AI detection tools. Researchers note that defining ‘human-made’ is increasingly difficult because AI technologies are embedded in many everyday software tools.

Creative industries are at the centre of the debate as generative AI rapidly produces books, films and music at lower cost and higher speed. Advocates of certification argue that verified human-created content may gain greater value if consumers can clearly distinguish it from AI-generated work.

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Tinder tests AI matchmaking features for modern dating

Popular dating platform Tinder is testing a new AI-powered feature called ‘Chemistry’ designed to improve matchmaking. The tool analyses user profiles to identify more relevant connections while the app’s familiar swipe system remains central to the experience.

Developed by parent company Match Group, the feature uses AI to understand personality traits, interests and preferences through profile data. Future updates may allow users to answer questionnaires or share photo archives to refine recommendations.

Additional modes are also being introduced to further personalise matches. Music preferences and astrology signs can now influence suggested profiles, reflecting evolving trends among younger online daters.

The platform is also testing in-person events and virtual video speed dating to encourage real-world interaction. AI moderation tools are also being deployed, helping detect inappropriate messages and verify that profiles belong to real people.

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Security warning issued over OpenClaw AI agent

Cybersecurity authorities have warned that vulnerabilities in the OpenClaw AI agent could expose sensitive data. Officials in China say weak default security settings may allow attackers to exploit the system.

Experts in China warned that prompt injection attacks could manipulate OpenClaw when it accesses online content. Malicious instructions hidden in websites may cause the AI agent to reveal confidential information.

Researchers have also identified risks involving link previews in messaging apps such as Telegram and Discord. Investigators in China say attackers could trick the system into sending sensitive data to malicious websites.

Security specialists in China advise organisations to strengthen protections around AI agents. Recommendations include isolating systems, limiting network access and installing trusted software components only.

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Seoul deepens ties with global AI developers

South Korea is pursuing a partnership with AI company Anthropic as part of a national strategy to strengthen technological capabilities. Officials are working toward a memorandum of understanding with the developer of the Claude AI system.

The initiative follows discussions between South Korea’s science minister and Anthropic’s chief executive, Dario Amodei, during an AI summit in New Delhi. Authorities are also preparing for the company’s planned office opening in the city in 2026.

Government leaders in South Korea have already expanded cooperation with OpenAI. Policymakers say the strategy aims to build ties with leading global AI developers while supporting domestic innovation.

Officials are also developing a homegrown AI foundation model with local companies. The programme forms part of a national plan to position the country among the world’s leading AI powers.

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AI and robotics could offset impact of aging populations in Asia

Declining fertility rates have long been considered a major risk to economic growth, but analysts suggest the outlook may not be entirely negative for several advanced Asian economies. Rising investment in AI and robotics is increasingly viewed as a way to offset labour shortages caused by ageing populations.

According to analysts at Bank of America Global Research, technological innovation driven by AI and robotics could support productivity growth even as workforces shrink. Strong ecosystems in semiconductors, technology hardware, and industrial machinery allow some countries in the region to deploy advanced technologies faster and at lower cost than many other parts of the world.

South Korea currently has the highest robot density in the world, with about 1,012 industrial robots per 10,000 manufacturing workers. China has 470 and Japan 419, both significantly above the global average of 162, according to 2024 figures from the International Federation of Robotics.

Analysts say governments across East Asia are accelerating the adoption of AI and robotics to address demographic pressures. In particular, China, South Korea, and Japan have expanded investments in robotics, AI systems, and advanced manufacturing technologies to maintain economic productivity.

Population projections highlight the scale of the challenge facing these economies. By 2050, about 37 percent of Japan’s population and nearly 40 percent of South Korea’s population are expected to be aged 65 or older, while China’s share could reach around 31 percent.

Despite concerns about slowing growth, economists argue that advances in AI and robotics could weaken the traditional link between economic output and workforce size. Automation technologies not only replace routine tasks but also enhance human productivity in many industries.

A study by the Bank of Korea estimated that demographic pressures could reduce the country’s gross domestic product by 16.5 percent between 2023 and 2050. However, wider adoption of AI and robotics could limit the decline to around 5.9 percent under favourable conditions.

Some analysts caution that the economic benefits of automation may not be evenly distributed. While AI and robotics can improve productivity, technological gains often benefit capital owners and highly skilled workers more than others.

Economists also warn that consumption may slow as the number of households declines, while governments may face greater fiscal pressure from higher pension and healthcare costs. Policymakers may need to invest in workforce retraining and education to help workers adapt to the growing role of AI and robotics in the economy.

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Google Earth AI supports disease forecasting and public health planning

Researchers are increasingly combining geospatial data with predictive modelling to anticipate health risks.

In that context, Google has introduced new capabilities within Google Earth AI designed to help public health experts forecast outbreaks and identify vulnerable communities.

The system integrates environmental information such as weather patterns, flooding and air quality with population mobility data and health records.

These insights allow researchers to analyse how environmental conditions influence the spread of diseases, including Dengue Fever and Cholera.

Several research initiatives are already testing the models. In collaboration with the World Health Organisation Regional Office for Africa, forecasting tools combining Google’s time-series models with geospatial data improved cholera prediction accuracy by more than 35 percent.

Academic researchers are also applying the technology to other diseases. Scientists at the University of Oxford have used Earth AI datasets to improve six-month dengue forecasts in Brazil, helping local authorities prepare preventative responses.

The technology is also being tested for chronic disease analysis. In Australia, partnerships with health organisations are exploring how geospatial models can identify regional health needs and support preventative care strategies.

Combining environmental intelligence with health data could enable public health systems to shift from reactive crisis management to earlier detection and prevention of disease outbreaks.

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China prioritises AI and tech self-reliance in new five-year plan

A new five-year development plan approved by lawmakers in Beijing places innovation and advanced technology at the centre of future economic growth. The strategy is designed to strengthen technological capabilities and position China as a leading global tech power.

The plan outlines ambitions to upgrade China’s industrial sector, expand domestic research capacity, and reduce reliance on foreign technologies. Priority sectors include AI, robotics, aerospace, biotechnology, and quantum computing. Officials see these industries as key drivers of economic growth over the coming decades.

AI features prominently in the strategy, with the term appearing dozens of times in the policy document. Beijing plans to expand AI-related industries, invest in large computing clusters, and support the development of advanced systems capable of performing complex tasks beyond traditional chatbots.

China also aims to increase spending on science and technology, with government research budgets rising by around 10 percent annually. The plan sets a target of expanding research and development investment by at least 7 percent per year, reflecting Beijing’s intention to strengthen domestic innovation capacity.

Efforts to achieve greater technological self-sufficiency come amid continued tensions with the United States over trade and technology restrictions. Export controls on advanced semiconductor technologies have highlighted China’s dependence on foreign chips, prompting the government to pursue breakthroughs across the semiconductor supply chain and emerging technologies.

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France pushes EU AI gigafactories to support European technology

In the EU, France is calling for planned European AI ‘gigafactories’ to focus on testing and scaling European technologies rather than primarily increasing demand for hardware from companies such as Nvidia.

The large computing facilities are intended to provide the infrastructure needed to train advanced AI systems. However, officials in France argue that the projects should strengthen Europe’s technological capabilities rather than reinforce reliance on foreign suppliers.

Several EU countries, including Poland, Austria and Lithuania, support using the infrastructure to improve Europe’s digital resilience.

The initiative forms part of the European Commission’s wider plans to expand computing capacity and support the development of a stronger European AI ecosystem.

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