Ireland confronts rising energy strain from data centres

Ireland faces mounting pressure over soaring electricity use from data centres clustered around Dublin. Facilities powering global tech giants have grown into a major energy consumer, accounting for over a fifth of national demand.

The load could reach 30 percent by 2030 as expanding cloud and AI services drive further growth. Analysts warn that rising consumption threatens climate commitments and places significant strain on grid stability.

Campaigners argue that data centres monopolise renewable capacity while pushing Ireland towards potential EU emissions penalties. Some local authorities have already blocked developments due to insufficient grid capacity and limited on-site green generation.

Sector leaders fear stalled projects and uncertain policy may undermine Ireland’s role as a digital hub. Investment risks remain high unless upgrades, clearer rules and balanced planning reduce the pressure on national infrastructure.

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AI chatbot comes to Shinagawa station in Japan

JR Central will trial an AI-operated language service for travellers at JR Shinagawa Station in Tokyo, Japan. The service, running from 15 December to mid-March, allows passengers to access a dedicated site via smartphone by scanning a QR code at the station.

Named ‘JRTok-AI,’ the chatbot provides ticketing information, handles large luggage, and performs service operations. It supports English, Chinese, Korean, French, and Spanish, offering location-based details and English commentary on the history and culture along the Tokaido Shinkansen route.

The trial aims to enhance travel convenience and gather feedback to inform service expansion. JR Central said enhancements and a broader rollout will be considered based on the results of this experiment.

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AI helps you shop smarter this holiday season

Holiday shoppers can now rely on AI to make Black Friday and Cyber Monday less stressful. AI tools help track prices across multiple retailers and notify users when items fall within their budget, saving hours of online searching.

Finding gifts for difficult-to-shop-for friends and family is also easier with AI. By describing a person’s interests or lifestyle, shoppers receive curated recommendations with product details, reviews, and availability, drawing from billions of listings in Google’s Shopping Graph.

Local shopping is more convenient thanks to AI features that enhance the shopping experience. Shoppers can check stock at nearby stores without having to call around, and virtual try-on technology allows users to see how clothing looks on them before making a purchase.

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Pope Leo warns teens not to outsource schoolwork to AI

During a livestream from the Vatican to the National Catholic Youth Conference in Indianapolis, Pope Leo XIV warned roughly 15,000 young people not to rely on AI to do their homework.

He described AI as ‘one of the defining features of our time’ but insisted that responsible use should promote personal growth, not shortcut learning: ‘Don’t ask it to do your homework for you.’

Leo also urged teens to be deliberate with their screen time and use technology in ways that nurture faith, community and authentic friendships. He warned that while AI can process data quickly, it cannot replace real wisdom or the capacity for moral judgement.

His remarks reflect a broader concern from the Vatican about the impact of AI on the development of young people. In a previous message to a Vatican AI ethics conference, he emphasised that access to data is not the same as accurate intelligence. That youth must not let AI stunt their growth or compromise their dignity.

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Creativity that AI cannot reshape

A landmark ruling in Munich has put renewed pressure on AI developers, following a German court’s finding that OpenAI is liable for reproducing copyrighted song lyrics in outputs generated by GPT-4 and GPT-4o. The judges rejected OpenAI’s argument that the system merely predicts text without storing training data, stressing the long-established EU principle of technological neutrality that, regardless of the medium, vinyl, MP3, or AI output, the unauthorised reproduction of protected works remains infringement.

Because the models produced lyrics nearly identical to the originals, the court concluded that they had memorised and therefore stored copyrighted content. The ruling dismantled OpenAI’s attempt to shift responsibility to users by claiming that any copying occurs only at the output stage.

Judges found this implausible, noting that simple prompts could not have ‘accidentally’ produced full, complex song verses without the model retaining them internally. Arguments around coincidence, probability, or so-called ‘hallucinations’ were dismissed, with the court highlighting that even partially altered lyrics remain protected if their creative structure survives.

As Anita Lamprecht explains in her blog, the judgement reinforces that AI systems are not neutral tools like tape recorders but active presenters of content shaped by their architecture and training data.

A deeper issue lies beneath the legal reasoning, the nature of creativity itself. The court inferred that highly original works, which are statistically unique, force AI systems into a kind of memorisation because such material cannot be reliably reproduced through generalisation alone.

That suggests that when models encounter high-entropy, creative texts during training, they must internalise them to mimic their structure, making infringement difficult to avoid. Even if this memorisation is a technical necessity, the judges stressed that it falls outside the EU’s text and data mining exemptions.

The case signals a turning point for AI regulation. It exposes contradictions between what companies claim in court and what their internal guidelines acknowledge. OpenAI’s own model specifications describe the output of lyrics as ‘reproduction’.

As Lamprecht notes, the ruling demonstrates that traditional legal principles remain resilient even as technology shifts from physical formats to vector space. It also hints at a future where regulation must reach inside AI systems themselves, requiring architectures that are legible to the law and laws that can be enforced directly within the models.

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Greece accelerates AI training for teachers

A national push to bring AI into public schools has moved ahead in Greece after the launch of an intensive training programme for secondary teachers.

Staff in selected institutions will receive guidance on a custom version of ChatGPT designed for academic use, with a wider rollout planned for January.

The government aims to prepare educators for an era in which AI tools support lesson planning, research and personalised teaching instead of remaining outside daily classroom practice.

Officials view the initiative as part of a broader ambition to position Greece as a technological centre, supported by partnerships with major AI firms and new infrastructure projects in Athens. Students will gain access to the system next spring under tight supervision.

Supporters argue that generative tools could help teachers reduce administrative workload and make learning more adaptive.

Concerns remain strong among pupils and educators who fear that AI may deepen an already exam-driven culture.

Many students say they worry about losing autonomy and creativity, while teachers’ unions warn that reliance on automated assistance could erode critical thinking. Others point to the risk of increased screen use in a country preparing to block social media for younger teenagers.

Teacher representatives also argue that school buildings require urgent attention instead of high-profile digital reforms. Poor heating, unreliable electricity and decades of underinvestment complicate adoption of new technologies.

Educators who support AI stress that meaningful progress depends on using such systems as tools to broaden creativity rather than as shortcuts that reinforce rote learning.

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Popular Python AI library compromised to deliver malware

Security researchers have confirmed that the Ultralytics YOLO library was hijacked in a supply-chain attack, where attackers injected malicious code into the PyPI-published versions 8.3.41 and 8.3.42. When installed, these versions deployed the XMRig cryptominer.

The compromise stemmed from Ultralytics’ continuous-integration workflow: by exploiting GitHub Actions, the attackers manipulated the automated build process, bypassing review and injecting cryptocurrency mining malware.

The maintainers quickly removed the malicious versions and released a clean build (8.3.43); however, newer reports suggest that further suspicious versions may have appeared.

This incident illustrates the growing risk in AI library supply chains. As open-source AI frameworks become more widely used, attackers increasingly target their build systems to deliver malware, particularly cryptominers.

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Smarter AI processing could lead to cleaner air, say UCR engineers

As AI continues to scale rapidly, the environmental cost of powering massive data centres is becoming increasingly urgent. Machines require substantial amounts of electricity and water to stay cool, and a significant portion of this energy comes from fossil-fuel sources.

Scientists at UC Riverside’s Bourns College of Engineering, led by Professors Mihri and Cengiz Ozkan, have proposed a novel solution called Federated Carbon Intelligence (FCI). Their system doesn’t just prioritise low-carbon energy; it also monitors the health of servers in real-time to decide where and when AI tasks should be run.

Using simulations, the team found that FCI could reduce carbon dioxide emissions by up to 45 percent over five years and extend the operational life of hardware by about 1.6 years.

Their model takes into account server temperature, age and physical wear, and dynamically routes computing workloads to optimise both environmental and machine-health outcomes.

Unlike other approaches that only shift workloads to regions with cleaner energy, FCI also addresses the embodied emissions of manufacturing new servers. Keeping current hardware running longer and more efficiently helps reduce the carbon footprint associated with production.

If adopted by cloud providers, this adaptive system could mark a significant milestone in the sustainable development of AI infrastructure, one that aligns compute demand with both performance and ecological goals. The researchers are now calling for pilots in real data centres.

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Gemini 3 struggles to accept the year 2025

Google’s new AI model, Gemini 3, was left temporarily confused when it refused to accept that the year was 2025 during early testing by AI researcher Andrej Karpathy.

The model, pre-trained on data only through 2024 and initially disconnected from the internet, accused Karpathy of trickery and gaslighting before finally recognising the correct date.

Once Gemini 3 accessed real-time information, it expressed astonishment and apologised for its previous behaviour, demonstrating the model’s quirky but sophisticated reasoning capabilities. The interaction went viral online, drawing attention to both the humour and unpredictability of advanced AI systems.

Experts note that incidents like this illustrate the limitations of LLMs, which, despite their reasoning power, cannot inherently perceive reality and rely entirely on pre-training data and connected tools.

Observers emphasise that AI remains a powerful human aid rather than a replacement, and understanding its quirks is essential for practical use.

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AI teaching leaves Staffordshire students frustrated

Students at the University of Staffordshire in the UK have criticised a coding course after discovering much of the teaching was delivered through AI-generated slides and voiceovers.

Participants in the government-funded apprenticeship programme said they felt deprived of knowledge and frustrated that the course relied heavily on automated materials.

Concerns arose when learners noticed inconsistencies in language, suspicious file names, and abrupt changes in voiceover accents during lessons.

Students reported raising these issues with university staff, but the institution maintained the use of AI, asserting it supported academic standards while remaining ethical and responsible.

Critics argue that AI teaching diminishes engagement and reduces the opportunity to acquire practical skills needed for career development.

Experts suggest students supplement AI-driven courses with hands-on learning and critical thinking to ensure the experience remains valuable and relevant to their professional goals.

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