Capacity development

Mount Fuji eruption simulated in an AI video for Tokyo

Residents of Tokyo have been shown a stark warning of what could happen if Mount Fuji erupts.

The metropolitan government released a three-minute AI-generated video depicting the capital buried in volcanic ash to raise awareness and urge preparation.

The simulation shows thick clouds of ash descending on Shibuya and other districts about one to two hours after an eruption, with up to 10 centimetres expected to accumulate. Unlike snow, volcanic ash does not melt away but instead hardens, damages powerlines, and disrupts communications once wet.

The video also highlights major risks to transport. Ash on train tracks, runways, and roads would halt trains, ground planes, and make driving perilous.

Two-wheel vehicles could become unusable under even modest ashfall. Power outages and shortages of food and supplies are expected as shops run empty, echoing the disruption seen after the 2011 earthquake.

Officials advise people to prepare masks, goggles, and at least three days of emergency food. The narrator warns that because no one knows when Mount Fuji might erupt, daily preparedness in Japan is vital to protect health, infrastructure, and communities.

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Google pushes staff to embrace AI to stay ahead

Google is urging its workforce to adopt AI in everyday tasks instead of relying solely on traditional methods.

CEO Sundar Pichai has warned that falling behind in AI could risk the company’s competitive edge, especially as rivals like Microsoft, Amazon and Meta push their staff to embrace similar tools.

Early trials inside Google suggest a significant boost in efficiency, with engineers reporting a 10% increase in weekly productivity after adopting AI.

The company has launched a training initiative called AI Savvy Google to accelerate the shift. The programme provides courses, toolkits and hands-on sessions to help employees integrate AI into their workflows.

One of the standout tools is Cider, an AI-powered coding assistant already used by half of the engineers with access to it.

Executives believe AI will soon become an essential part of software engineering. Brian Saluzzo, a senior leader at Google, told staff that internal AI tools will continue to improve and become deeply embedded in coding work.

The company stresses the importance of using AI to support rather than replace workers, with the training programme designed to upskill employees instead of pushing them aside.

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Nvidia launches Spectrum-XGS to build global AI factories

American technology company Nvidia has unveiled Spectrum-XGS Ethernet, a new networking technology designed to connect multiple data centres into unified giga-scale AI factories.

With AI demand skyrocketing, single facilities are hitting limits in power and capacity, creating the need for infrastructure that can operate across cities, nations and continents.

Spectrum-XGS extends Nvidia’s Spectrum-X Ethernet platform, introducing what the company calls a ‘scale-across’ approach, alongside scale-up and scale-out models.

Integrating advanced congestion control, latency management, and telemetry nearly doubles the performance of the Nvidia Collective Communications Library, allowing geographically distributed data centres to function as one large AI cluster.

Early adopters like CoreWeave are preparing to link their facilities using the new system. According to Nvidia, the technology offers 1.6 times greater bandwidth density than traditional Ethernet and features Spectrum-X switches and ConnectX-8 SuperNICs, optimised for hyperscale AI operations.

The company argues that the approach will define the next phase of AI infrastructure, enabling super-factories to manage millions of GPUs while improving efficiency and lowering operational costs.

Nvidia CEO Jensen Huang described the development as part of the AI industrial revolution, highlighting that Spectrum-XGS can unify data centres into global networks that act as vast, giga-scale AI super-factories.

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Dell expands AI innovation hub in Singapore to drive regional growth

Dell Technologies has launched a new Asia Pacific and Japan AI Innovation Hub in Singapore, strengthening its role in advancing AI across the region.

The hub extends the company’s Global Innovation Hub, which has already received more than US$50 million in investment since 2019. Its focus is on driving AI transformation, enablement and leadership, in line with Singapore’s National AI Strategy 2.0.

Instead of offering only infrastructure, the hub delivers end-to-end support, from strategy to deployment, helping enterprises bridge the gap between ambition and practical results. Research shows 62% of Singaporean businesses prefer such holistic partnerships.

Since 2024, the hub has developed about 50 AI prototypes and carried out more than 100 proof-of-concepts, workshops and demonstrations across areas such as generative and predictive AI.

The projects have already influenced multiple sectors. In energy, AI solutions are strengthening infrastructure resilience and enhancing customer engagement with digital humans and chatbots.

In telecommunications, AI is supporting agility and operational efficiency, while in education, cloud-based technologies are empowering research and innovation.

Dell’s AI Centre of Excellence Lab further supports these initiatives by testing solutions for AI PCs and edge computing in collaboration with academic and hardware partners.

A strong emphasis is also placed on skills development. By the end of 2025, the hub aims to train around 10,000 students and mid-career professionals in AI engineering, platform engineering and related fields.

Working with 10 local institutes, Dell is addressing the talent shortage reported by nearly half of Singaporean organisations. Events such as the Dell InnovateFest and the Dell Innovation Challenge provide platforms for students and partners to showcase ideas and create solutions for social good.

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Senior OpenAI executive Julia Villagra departs amid talent war

OpenAI’s chief people officer, Julia Villagra, has left the company, marking the latest leadership change at the AI pioneer. Villagra, who joined the San Francisco firm in early 2024 and was promoted in March, previously led its human resources operations.

Her responsibilities will temporarily be overseen by chief strategy officer Jason Kwon, while chief applications officer Fidji Simo will lead the search for her successor.

OpenAI said Villagra is stepping away to pursue her personal interest in art, music and storytelling as tools to help people understand the shift towards artificial general intelligence, a stage when machines surpass human performance in most forms of work.

The departure comes as OpenAI navigates a period of intense competition for AI expertise. Microsoft-backed OpenAI is valued at about $300 billion, with a potential share sale set to raise that figure to $500 billion.

The company faces growing rivalry from Meta, where Mark Zuckerberg has reportedly offered $100 million signing bonuses to attract OpenAI talent.

While OpenAI expands, public concerns over the impact of AI on employment continue. A Reuters/Ipsos poll found 71% of Americans fear AI could permanently displace too many workers, despite the unemployment rate standing at 4.2% in July.

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Google claims Gemini uses less water and energy per text prompt

Google has published new estimates on the environmental footprint of Gemini, claiming a single text prompt uses about five drops of water and 0.24 watt-hours of electricity. The company says this equates to 0.03 grams of carbon dioxide emissions.

According to Google, efficiencies have reduced Gemini’s energy consumption and carbon footprint per text prompt by factors of 33 and 44 over the past year. Chief technologist Ben Gomes said the model now delivers higher-quality responses with a significantly lower footprint.

The company argued that these figures are significantly lower than those suggested in earlier research. However, Shaolei Ren, the author of one of the cited papers, said Google’s comparisons were misleading and incomplete.

Ren noted that Google compared its latest onsite-only water figures against his study’s highest total figures, creating the impression that Gemini was far more efficient. He also said Google omitted indirect water use, such as electricity-related consumption, from its estimates.

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South Korea unveils five-year AI blueprint for ‘super-innovation economy’

South Korea’s new administration has unveiled a five-year economic plan to build what it calls a ‘super-innovation economy’ by integrating AI across all sectors of society.

The strategy, led by President Lee Jae-myung, commits 100 trillion won (approximately US$71.5 billion) to position the country among the world’s top three AI powerhouses. Private firms will drive development, with government support for nationwide adoption.

Plans include a sovereign Korean-language AI model, humanoid robots for logistics and industry, and commercialising autonomous vehicles by 2027. Unmanned ships are targeted for completion by 2030, alongside widespread use of drones in firefighting and aviation.

AI will also be introduced into drug approvals, smart factories, welfare services, and tax administration, with AI-based tax consultations expected by 2026. Education initiatives and a national AI training data cluster will nurture talent and accelerate innovation.

Five domestic firms, including Naver Cloud, SK Telecom, and LG AI Research, will receive state support to build homegrown AI foundation models. Industry reports currently rank South Korea between sixth and 10th in global AI competitiveness.

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Google enhances AI Mode with personalised dining suggestions

Google has expanded its AI Mode in Search to 180 additional countries and territories, introducing new agentic features to help users make restaurant reservations. The service remains limited to English and is not yet available in the European Union.

The update enables users to specify their dining preferences and constraints, allowing the system to scan multiple platforms and present real-time availability. Once a choice is made, users are directed to the restaurant’s booking page.

Partners supporting the service include OpenTable, Resy, SeatGeek, StubHub, Booksy, Tock, and Ticketmaster. The feature is part of Google’s Search Labs experiment, available to subscribers of Google AI Ultra in the United States.

AI Mode also tailors suggestions based on previous searches and introduces a Share function, letting users share restaurant options or planning results with others, with the option to delete links.

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Meta strikes $10 billion cloud deal with Google

Meta has signed a cloud computing deal with Google worth more than $10 billion, marking one of the most significant agreements in the industry.

The six-year partnership will see Meta use Google Cloud’s servers, storage, networking and other services to power its massive AI projects.

The deal comes as Meta accelerates its AI infrastructure spending, with CEO Mark Zuckerberg pledging hundreds of billions of dollars for new data centres.

Last month, Meta raised its capital expenditure forecast to $72 billion and disclosed plans to offload $2 billion in data centre assets to outside partners.

The partnership highlights a growing trend of rival technology giants collaborating on AI infrastructure. Just weeks earlier, OpenAI struck a similar deal to use Google Cloud services despite being a competitor in the AI field.

These agreements have boosted Google Cloud’s performance, which saw a 32% jump in second-quarter revenue in July, surpassing market expectations.

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New robotic system uses AI to analyse water quality

A new study in Robot Learning has introduced a robotic system that combines machine learning with decision-making to analyse water samples. The approach enables robots to detect, classify, and distinguish drinking water on Earth and potentially other planets.

Researchers used a hybrid method that merged the TOPSIS decision-making technique with a Random Forest Classifier trained on the Water Quality and Potability Dataset from Kaggle. By applying data balancing techniques, classification accuracy rose from 69% to 73%.

The robotic prototype includes thrusters, motors, solar power, sensors, and a robotic arm for sample collection. Water samples are tested in real time, with the onboard model classifying them as drinkable.

The system has the potential for rapid crisis response, sustainable water management, and planetary exploration, although challenges remain regarding sensor accuracy, data noise, and scalability. Researchers emphasise that further testing is necessary before real-world deployment.

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