Digital standards

Trump unveils gold smartphone and new 5G wireless service

US President Donald Trump and his sons have launched a mobile phone service called Trump Mobile 5G, alongside plans to release a gold-coloured smartphone branded with the Trump name.

The service is being offered through partnerships with all three major US mobile networks, though they are not named directly.

The monthly plan, known as the ’47 Plan’, costs $47.45- referencing Trump’s position as the 45th and 47th president. Customers can join their current Android or iPhone devices, either with a physical SIM or an eSIM.

A new Trump-branded Android device, the T1, will launch in September. Priced at $499, it comes with Android 15, a 6.8-inch screen and biometric features like fingerprint scanning and AI facial recognition.

At a press event in New York, Donald Trump Jr. and Eric Trump introduced the initiative, saying it would combine high-quality service with an ‘America First’ approach.

They emphasised that the company is US-based, including its round-the-clock customer service, which promises real human support instead of automated systems.

While some critics may see the move as political branding, the Trump Organisation framed it as a business venture.

The company has already earned hundreds of millions from Trump-branded consumer goods. As with other mobile providers, the new service will fall under the regulatory oversight of the Federal Communications Commission, led by a Trump-appointed chair.

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ChatGPT and generative AI have polluted the internet — and may have broken themselves

The explosion of generative AI tools like ChatGPT has flooded the internet with low-quality, AI-generated content, making it harder for future models to learn from authentic human knowledge.

As AI continues to train on increasingly polluted data, a loop forms in which AI imitates already machine-made content, leading to a steady drop in originality and usefulness. The worrying trend is referred to as ‘model collapse’.

To illustrate the risk, researchers compare clean pre-AI data to ‘low-background steel’ — a rare kind of steel made before nuclear testing in 1945, which remains vital for specific medical and scientific uses.

Just as modern steel became contaminated by radiation, modern data is being tainted by artificial content. Cambridge researcher Maurice Chiodo notes that pre-2022 data is now seen as ‘safe, fine, clean’, while everything after is considered ‘dirty’.

A key concern is that techniques like retrieval-augmented generation, which allow AI to pull real-time data from the internet, risk spreading even more flawed content. Some research already shows that it leads to more ‘unsafe’ outputs.

If developers rely on such polluted data, scaling models by adding more information becomes far less effective, potentially hitting a wall in progress.

Chiodo argues that future AI development could be severely limited without a clean data reserve. He and his colleagues urge the introduction of clear labelling and tighter controls on AI content.

However, industry resistance to regulation might make meaningful reform difficult, raising doubts about whether the pollution can be reversed.

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Scientists convert brain signals into words using AI

Australian scientists have developed an AI model that converts brainwaves into spoken words and sentences using a wearable EEG cap.

The system, created at the University of Technology Sydney, marks a significant step in communication technology and cognitive care.

The deep learning model, designed by Daniel Leong, Charles Zhou, and Chin-Teng Lin, currently works with a limited vocabulary but has achieved around 75% accuracy. Researchers aim to improve this to 90% by expanding training data and refining brainwave analysis.

Bioelectronics expert Mohit Shivdasani noted that AI now detects neural patterns previously hidden from human interpretation. Future uses include real-time thought-to-text interfaces or direct communication between people via brain signals.

However, breakthrough opens new possibilities for patients with speech or movement impairments, pointing to future human-machine interaction that bypasses traditional input methods.

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Armenia plans major AI hub with NVIDIA and Firebird

Armenia has unveiled plans to develop a $500mn AI supercomputing hub in partnership with US tech leader NVIDIA, AI cloud firm Firebird, and local telecoms group Team.

Announced at the Viva Technology conference in Paris, the initiative marks the largest tech investment ever seen in the South Caucasus.

Due to open in 2026, the facility will house thousands of NVIDIA’s Blackwell GPUs and offer more than 100 megawatts of scalable computing power. Designed to advance AI research, training and entrepreneurship, the hub aims to position Armenia as a leading player in global AI development.

Prime Minister Nikol Pashinyan described the project as the ‘Stargate of Armenia’, underscoring its potential to transform the national tech sector.

Firebird CEO Razmig Hovaghimian said the hub would help develop local talent and attract international attention, while the Afeyan Foundation, led by Noubar Afeyan, is set to come on board as a founding investor.

Instead of limiting its role to funding, the Armenian government will also provide land, tax breaks and simplified regulation to support the project, strengthening its push toward a competitive digital economy.

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Amazon launches AU$ 20 bn investment in Australian solar-powered data centres

Amazon will invest AU$ 20 billion to expand its data centre infrastructure in Australia, using solar and wind power instead of traditional energy sources.

The plan includes power purchase agreements with three utility-scale solar plants developed by European Energy, one of which—Mokoan Solar Park in Victoria—is already operational. The other two projects, Winton North and Bullyard Solar Parks, are expected to lift total solar capacity to 333MW.

The investment supports Australia’s aim to enhance its cloud and AI capabilities. Amazon’s commitment includes purchasing over 170MW of power from these projects, contributing to both data centre growth and the country’s renewable energy transition.

According to the International Energy Agency, electricity demand from data centres is expected to more than double by 2030, driven by AI.

Amazon Web Services CEO Matt Garman said the move positions Australia to benefit from AI’s economic potential. The company, already active in solar projects across New South Wales, Queensland and Victoria, continues to prioritise renewables to decarbonise operations and meet surging energy needs.

Instead of pursuing growth through conventional means, Amazon’s focus on clean energy could set a precedent for other tech giants expanding in the region.

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AI health tools need clinicians to prevent serious risks, Oxford study warns

The University of Oxford has warned that AI in healthcare, primarily through chatbots, should not operate without human oversight.

Researchers found that relying solely on AI for medical self-assessment could worsen patient outcomes instead of improving access to care. The study highlights how these tools, while fast and data-driven, fall short in delivering the judgement and empathy that only trained professionals can offer.

The findings raise alarm about the growing dependence on AI to fill gaps caused by doctor shortages and rising costs. Chatbots are often seen as scalable solutions, but without rigorous human-in-the-loop validation, they risk providing misleading or inconsistent information, particularly to vulnerable groups.

Rather than helping, they might increase health disparities by delaying diagnosis or giving patients false reassurance.

Experts are calling for safer, hybrid approaches that embed clinicians into the design and ongoing use of AI tools. The Oxford researchers stress that continuous testing, ethical safeguards and clear protocols must be in place.

Instead of replacing clinical judgement, AI should support it. The future of digital healthcare hinges not just on innovation but on responsibility and partnership between technology and human care.

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Taiwan tightens rules on chip shipments to China

Taiwan has officially banned the export of chips and chiplets to China’s Huawei and SMIC, joining the US in tightening restrictions on advanced semiconductor transfers.

The decision follows reports that TSMC, the world’s largest contract chipmaker, was unknowingly misled into supplying chiplets used in Huawei’s Ascend 910B AI accelerator. The US Commerce Department had reportedly considered a fine of over $1 billion against TSMC for that incident.

Taiwan’s new rules aim to prevent further breaches by requiring export permits for any transactions with Huawei or SMIC.

The distinction between chips and chiplets is key to the case. Traditional chips are built as single-die monoliths using the same process node, while chiplets are modular and can combine various specialised components, such as CPU or AI cores.

Huawei allegedly used shell companies to acquire chiplets from TSMC, bypassing existing US restrictions. If TSMC had known the true customer, it likely would have withheld the order. Taiwan’s new export controls are designed to ensure stricter oversight of future transactions and prevent repeat deceptions.

The broader geopolitical stakes are clear. Taiwan views the transfer of advanced chips to China as a national security threat, given Beijing’s ambitions to reunify with Taiwan and the potential militarisation of high-end semiconductors.

With Huawei claiming its processors are nearly on par with Western chips—though analysts argue they lag two to three generations behind—the export ban could further isolate China’s chipmakers.

Speculation persists that Taiwan’s move was partly influenced by negotiations with the US to avoid the proposed fine on TSMC, bringing both countries into closer alignment on chip sanctions.

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Switzerland’s unique AI path: Blending innovation, governance, and local empowerment

In his recent blog post ‘Advancing Swiss AI Trinity: Zurich’s entrepreneurship, Geneva’s governance, and Communal subsidiarity,’ Jovan Kurbalija proposes a distinctive roadmap for Switzerland to navigate the rapidly evolving landscape of AI. Rather than mimicking the AI power plays of the United States or China, Kurbalija argues that Switzerland can lead by integrating three national strengths: Zurich’s thriving innovation ecosystem, Geneva’s global leadership in governance, and the country’s foundational principle of subsidiarity rooted in local decision-making.

Zurich, already a global tech hub, is positioned to drive cutting-edge development through its academic excellence and robust entrepreneurial culture. Institutions like ETH Zurich and the presence of major tech firms provide a fertile ground for collaborations that turn research into practical solutions.

With AI tools becoming increasingly accessible, Kurbalija emphasises that success now depends on how societies harness the interplay of human and machine intelligence—a field where Switzerland’s education and apprenticeship systems give it a competitive edge. Meanwhile, Geneva is called upon to spearhead balanced international governance and standard-setting for AI.

Kurbalija stresses that AI policy must go beyond abstract discussions and address real-world issues—health, education, the environment—by embedding AI tools in global institutions and negotiations. He notes that Geneva’s experience in multilateral diplomacy and technical standardisation offers a strong foundation for shaping ethical, inclusive AI frameworks.

The third pillar—subsidiarity—empowers Swiss cantons and communities to develop AI that reflects local values and needs. By supporting grassroots innovation through mini-grants, reimagining libraries as AI learning hubs, and embedding AI literacy from primary school to professional training, Switzerland can build an AI model that is democratic and inclusive.

Why does it matter?

Kurbalija’s call to action is clear: with its tools, talent, and traditions aligned, Switzerland must act now to chart a future where AI serves society, not the other way around.

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Deepseek searches soar after ChatGPT outage

ChatGPT users faced widespread disruption on 10 June 2025 after a global outage hit OpenAI’s services, affecting both the chatbot and associated APIs. OpenAI has yet to confirm the cause, stating only that users are experiencing high error rates and delays.

The blackout halted work for many creative teams who rely on the tool to generate content and meet deadlines. While some were stalled, others turned to alternatives, sparking a surge in interest in rival AI chatbots.

Searches for DeepSeek, a Chinese-developed AI model, jumped 109% to over 2.1 million on the outage day. Claude AI saw a 95% increase in queries, while interest in Google Gemini and Microsoft Copilot also spiked significantly.

Industry experts say the incident underscores the risk of overdependence on a single platform and highlights the growing maturity of competing AI tools. While frustrating for many, the disruption appears to be fuelling broader competition and diversification in the generative AI market.

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Google pushes users to move away from passwords

Google urges users to move beyond passwords, citing widespread reuse and vulnerability to phishing attacks. The company is now promoting alternatives like passkeys and social sign-ins as more secure and user-friendly options.

Data from Google shows that half of users reuse passwords, while the rest either memorise or write them down. Gen Z is leading the shift and is significantly more likely to adopt passkeys and social logins than older generations.

Passkeys, stored on user devices, eliminate traditional password input and reduce phishing risks by relying on biometrics or device PINs for authentication. However, limited app support and difficulty syncing across devices remain barriers to broader adoption.

Google highlights that while social sign-ins offer convenience, they come with privacy trade-offs by giving large companies access to more user activity data. Users still relying on passwords are advised to adopt app-based two-factor authentication over SMS or email, which are far less secure.

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