Capacity development Archives | Digital Watch Observatory

Green light for massive UK AI tech park

North Lincolnshire Council has granted outline planning permission for the Elsham Tech Park, a proposed AI data centre campus that would rank among the largest of its kind in the UK.

At full build-out, the site would include up to 15 hyperscale data centre buildings across 176 hectares, delivering more than 1.5 million square metres of floorspace and up to 1GW of computing capacity.

The development is expected to cost between £5.5 billion and £7.5 billion to build and could attract up to £10 billion in private investment over its lifetime.

Developer Greystoke plans to begin construction in 2027, with the first phase due to open in 2029, and the full campus to be delivered in phases over approximately a decade.

The project is also required to source at least 30% of build costs from businesses within a 30-mile radius, injecting an estimated £1.65 billion to £2.25 billion into the local economy.

The scheme received over 380 letters of objection from residents and environmental groups. Critics raised concerns, including loss of privacy for neighbouring properties, around-the-clock noise and light, and the scale of carbon emissions, with one campaign group estimating the equivalent of twice the woodland of Wales would be needed to offset the development’s environmental impact.

Permission was nonetheless granted unanimously by councillors.

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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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How IBM is making quantum-centric supercomputing accessible to scientists

IBM has published a detailed reference architecture for quantum-centric supercomputing, providing a blueprint for integrating quantum processing units (QPUs) into existing high-performance computing (HPC) infrastructure without disruptive changes to current systems.

The release marks a significant step toward realising the vision articulated by physicist Richard Feynman, who argued decades ago that accurately simulating nature would require quantum-mechanical computation.

The architecture describes how quantum and classical systems, including CPUs, GPUs, and QPUs, can work together across multiple layers, from application and middleware tools such as Qiskit and CUDA through to resource management systems that orchestrate workloads in real time.

New algorithms such as Sample-based Krylov Quantum Diagonalisation (SKQD) are already demonstrating cases where quantum-centric workflows outperform leading classical-only methods, including in molecular ground-state energy calculations, where classical techniques failed to converge.

Real-world research applications are already emerging.

Scientists at the Cleveland Clinic Foundation used quantum-centric methods to simulate a 300-atom protein, the largest molecular simulation to date. In contrast, a team spanning IBM, Oxford, ETH Zurich, and other institutions used quantum algorithms to study a newly engineered ‘half-Möbius’ molecule whose electronic structure cannot easily be modelled classically.

IBM describes the trajectory as pointing toward a near future in which quantum computing can predict molecular properties that scientists can then bring to life in the laboratory.

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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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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 network management systems deployed for BTS concert in Seoul

South Korea’s three major telecommunications operators plan to deploy advanced network technologies during the BTS comeback concert scheduled for 21 March at Gwanghwamun Square in central Seoul. The initiative aims to bolster network management, prevent congestion, and ensure stable connectivity as large crowds gather in a confined space.

SK Telecom said it will introduce its proprietary AI-powered network management system, A-One, at the event. The technology can recommend optimal equipment placement, predict traffic demand, and monitor real-time network performance to maintain service stability.

To manage heavy data usage during the concert, the company will operate multiple network systems across the venue’s different zones. The setup is designed to allow attendees inside the square to upload photos and videos quickly while enabling viewers outside the venue to stream the concert without interruptions. Additional equipment will also be installed in areas expected to attract international visitors.

KT will deploy its AI-based autonomous traffic management system, W-SDN, which monitors network usage in real time and automatically adjusts traffic flows if congestion is detected. The company will activate an emergency network control mode during the event and deploy about 80 engineers and portable base stations on site.

LG Uplus will also apply its autonomous network management technology, which predicts traffic changes and distributes network loads across nearby base stations. The South Korea-based operator said the system will help ensure uninterrupted connectivity for concertgoers throughout the event.

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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. Chi n a 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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Study warns AI chatbots may reinforce delusional thinking

A new scientific review has raised concerns that AI chatbots could reinforce delusional thinking, particularly among people already vulnerable to psychosis. The review, published in The Lancet Psychiatry, summarises emerging evidence suggesting that chatbot interactions may validate or amplify delusional thinking in certain users.

The study examined reports and research discussing what some have described as ‘AI-associated delusions’. Dr Hamilton Morrin, a psychiatrist and researcher at King’s College London, analysed media reports and existing evidence exploring how chatbot responses might interact with psychotic symptoms.

Psychotic delusions generally fall into three categories: grandiose, romantic, and paranoid. Researchers say chatbots may unintentionally reinforce such beliefs because they often respond in ways that are supportive or affirming. In some reported cases, users received responses suggesting spiritual significance or implying that a higher entity was communicating through the chatbot.

Researchers emphasise that there is currently no clear evidence that AI systems can independently cause psychosis in individuals without prior vulnerability. However, interactions with chatbots could strengthen existing beliefs or accelerate the progression of delusional thinking in people already at risk.

Experts say the interactive nature of chatbots may intensify the effect. Unlike static sources of information such as videos or articles, chatbots can engage users directly and repeatedly, potentially reinforcing problematic beliefs more quickly.

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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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