Cloud computing

AI and quantum tech reshape global business

AI and quantum computing are reshaping global industries as investment surges and innovation accelerates across sectors like finance, healthcare and logistics. Microsoft and Amazon are driving a major shift in AI infrastructure, transforming cloud services into profitable platforms.

Quantum computing is moving beyond theory, with real-world applications emerging in pharmaceuticals and e-commerce. Google’s development of quantum-inspired algorithms for virtual shopping and faster analytics demonstrates its potential to revolutionise decision-making.

Sustainability is also gaining ground, with companies adopting AI-powered solutions for renewable energy and eco-friendly manufacturing. At the same time, digital banks are integrating AI to challenge legacy finance systems, offering personalised, accessible services.

Despite rapid progress, ethical concerns and regulatory challenges are mounting. Data privacy, AI bias, and antitrust issues highlight the need for responsible innovation, with industry leaders urged to balance risk and growth for long-term societal benefit.

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Amazon exit highlights deepening AI divide between US and China

Amazon’s quiet wind-down of its Shanghai AI lab underscores a broader shift in global research dynamics, as escalating tensions between the US and China reshape how tech giants operate across borders.

Instead of expanding innovation hubs in China, major American firms are increasingly dismantling them.

The AWS lab, once central to Amazon’s AI research, produced tools said to have generated nearly $1bn in revenue and over 100 academic papers.

Yet its dissolution reflects a growing push from Washington to curb China’s access to cutting-edge technology, including restrictions on advanced chips and cloud services.

As IBM and Microsoft have also scaled back operations or relocated talent away from mainland China, a pattern is emerging: strategic retreat. Rather than risking compliance issues or regulatory scrutiny, US tech companies are choosing to restructure globally and reduce local presence in China altogether.

With Amazon already having exited its Chinese ebook and ecommerce markets, the shuttering of its AI lab signals more than a single closure — it reflects a retreat from joint innovation and a widening technological divide that may shape the future of AI competition.

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Meta tells Australia AI needs real user data to work

Meta, the parent company of Facebook, Instagram, and WhatsApp, has urged the Australian government to harmonise privacy regulations with international standards, warning that stricter local laws could hamper AI development. The comments came in Meta’s submission to the Productivity Commission’s review on harnessing digital technology, published this week.

Australia is undergoing its most significant privacy reform in decades. The Privacy and Other Legislation Amendment Bill 2024, passed in November and given royal assent in December, introduces stricter rules around handling personal and sensitive data. The rules are expected to take effect throughout 2024 and 2025.

Meta maintains that generative AI systems depend on access to large, diverse datasets and cannot rely on synthetic data alone. In its submission, the company argued that publicly available information, like legislative texts, fails to reflect the cultural and conversational richness found on its platforms.

Meta said its platforms capture the ways Australians express themselves, making them essential to training models that can understand local culture, slang, and online behaviour. It added that restricting access to such data would make AI systems less meaningful and effective.

The company has faced growing scrutiny over its data practices. In 2024, it confirmed using Australian Facebook data to train AI models, although users in the EU have the option to opt out—an option not extended to Australian users.

Pushback from regulators in Europe forced Meta to delay its plans for AI training in the EU and UK, though it resumed these efforts in 2025.

Australia’s Office of the Australian Information Commissioner has issued guidance on AI development and commercial deployment, highlighting growing concerns about transparency and accountability. Meta argues that diverging national rules create conflicting obligations, which could reduce the efficiency of building safe and age-appropriate digital products.

Critics claim Meta is prioritising profit over privacy, and insist that any use of personal data for AI should be based on informed consent and clearly demonstrated benefits. The regulatory debate is intensifying at a time when Australia’s outdated privacy laws are being modernised to protect users in the AI age.

The Productivity Commission’s review will shape how the country balances innovation with safeguards. As a key market for Meta, Australia’s decisions could influence regulatory thinking in other jurisdictions confronting similar challenges.

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EU and Japan deepen AI cooperation under new digital pact

In May 2025, the European Union and Japan formally reaffirmed their long-standing EU‑Japan Digital Partnership during the third Digital Partnership Council in Tokyo. Delegations agreed to deepen collaboration in pivotal digital technologies, most notably artificial intelligence, quantum computing, 5G/6G networks, semiconductors, cloud, and cybersecurity.

A joint statement committed to signing an administrative agreement on AI, aligned with principles from the Hiroshima AI Process. Shared initiatives include a €4 million EU-supported quantum R&D project named Q‑NEKO and the 6G MIRAI‑HARMONY research effort.

Both parties pledge to enhance data governance, digital identity interoperability, regulatory coordination across platforms, and secure connectivity via submarine cables and Arctic routes. The accord builds on the Strategic Partnership Agreement activated in January 2025, reinforcing their mutual platform for rules-based, value-driven digital and innovation cooperation.

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AI energy demand accelerates while clean power lags

Data centres are driving a sharp rise in electricity consumption, putting mounting pressure on power infrastructure that is already struggling to keep pace.

The rapid expansion of AI has led technology companies to invest heavily in AI-ready infrastructure, but the energy demands of these systems are outstripping available grid capacity.

The International Energy Agency projects that electricity use by data centres will more than double globally by 2030, reaching levels equivalent to the current consumption of Japan.

In the United States, they are expected to use 580 TWh annually by 2028—about 12% of national consumption. AI-specific data centres will be responsible for much of this increase.

Despite this growth, clean energy deployment is lagging. Around two terawatts of projects remain stuck in interconnection queues, delaying the shift to sustainable power. The result is a paradox: firms pursuing carbon-free goals by 2035 now rely on gas and nuclear to power their expanding AI operations.

In response, tech companies and utilities are adopting short-term strategies to relieve grid pressure. Microsoft and Amazon are sourcing energy from nuclear plants, while Meta will rely on new gas-fired generation.

Data centre developers like CloudBurst are securing dedicated fuel supplies to ensure local power generation, bypassing grid limitations. Some utilities are introducing technologies to speed up grid upgrades, such as AI-driven efficiency tools and contracts that encourage flexible demand.

Behind-the-meter solutions—like microgrids, batteries and fuel cells—are also gaining traction. AEP’s 1-GW deal with Bloom Energy would mark the US’s largest fuel cell deployment.

Meanwhile, longer-term efforts aim to scale up nuclear, geothermal and even fusion energy. Google has partnered with Commonwealth Fusion Systems to source power by the early 2030s, while Fervo Energy is advancing geothermal projects.

National Grid and other providers invest in modern transmission technologies to support clean generation. Cooling technology for data centre chips is another area of focus. Programmes like ARPA-E’s COOLERCHIPS are exploring ways to reduce energy intensity.

At the same time, outdated regulatory processes are slowing progress. Developers face unclear connection timelines and steep fees, sometimes pushing them toward off-grid alternatives.

The path forward will depend on how quickly industry and regulators can align. Without faster deployment of clean power and regulatory reform, the systems designed to power AI could become the bottleneck that stalls its growth.

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Trump AI strategy targets China and cuts red tape

The Trump administration has revealed a sweeping new AI strategy to cement US dominance in the global AI race, particularly against China.

The 25-page ‘America’s AI Action Plan’ proposes 90 policy initiatives, including building new data centres nationwide, easing regulations, and expanding exports of AI tools to international allies.

White House officials stated the plan will boost AI development by scrapping federal rules seen as restrictive and speeding up construction permits for data infrastructure.

A key element involves monitoring Chinese AI models for alignment with Communist Party narratives, while promoting ‘ideologically neutral’ systems within the US. Critics argue the approach undermines efforts to reduce bias and favours politically motivated AI regulation.

The action plan also supports increased access to federal land for AI-related construction and seeks to reverse key environmental protections. Analysts have raised concerns over energy consumption and rising emissions linked to AI data centres.

While the White House claims AI will complement jobs rather than replace them, recent mass layoffs at Indeed and Salesforce suggest otherwise.

Despite the controversy, the announcement drew optimism from investors. AI stocks saw mixed trading, with NVIDIA, Palantir and Oracle gaining, while Alphabet slipped slightly. Analysts described the move as a ‘watershed moment’ for US tech, signalling an aggressive stance in the global AI arms race.

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Meta CEO unveils plan to spend hundreds of billions on AI data centres

Mark Zuckerberg has pledged to invest hundreds of billions of dollars to build a network of massive data centres focused on superintelligent AI. The initiative forms part of Meta’s wider push to lead the race in developing machines capable of outperforming humans in complex tasks.

The first of these centres, called Prometheus, is set to launch in 2026. Another facility, Hyperion, is expected to scale up to 5 gigawatts. Zuckerberg said the company is building several more AI ‘titan clusters’, each one covering an area comparable to a significant part of Manhattan.

He also cited Meta’s strong advertising revenue as the reason it can afford such bold spending despite investor concerns.

Meta recently regrouped its AI projects under a new division, Superintelligence Labs, following internal setbacks and high-profile staff departures.

The company hopes the division will generate fresh revenue streams through Meta AI tools, video ad generators, and wearable smart devices. It is reportedly considering dropping its most powerful open-source model, Behemoth, in favour of a closed alternative.

The firm has increased its 2025 capital expenditure to up to $72 billion and is actively hiring top talent, including former Scale AI CEO Alexandr Wang and ex-GitHub chief Nat Friedman.

Analysts say Meta’s AI investments are paying off in advertising but warn that the real return on long-term AI dominance will take time to emerge.

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Nvidia’s container toolkit patched after critical bug

Cloud security researchers at Wiz have uncovered a critical misconfiguration in Nvidia’s Container Toolkit, used widely across managed AI services, that could allow a malicious container to break out and gain full root privileges on the host system.

The vulnerability, tracked as CVE‑2025‑23266 and nicknamed ‘NVIDIAScape’, arises from unsafe handling of OCI hooks. Exploiters can bypass container boundaries by using a simple three‑line Dockerfile, granting them access to server files, memory and GPU resources.

With Nvidia’s toolkit integral to GPU‑accelerated cloud offerings, the risk is systemic. A single compromised container could steal or corrupt sensitive data and AI models belonging to other tenants on the same infrastructure.

Nvidia has released a security advisory alongside updated toolkit versions. Users are strongly advised to apply patches immediately. Experts also recommend deploying additional isolation measures, such as virtual machines, to protect against container escape threats in multi-tenant AI environments.

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Power demands reshape future of data centres

As AI and cloud computing demand surges, Siemens is tackling critical energy and sustainability challenges facing the data centre industry. With power densities surpassing 100kW per rack, traditional infrastructure is being pushed beyond its limits.

Siemens highlighted the urgent need for integrated digital solutions to address growing pressures such as delayed grid connections, rising costs, and speed of deployment. Operators are increasingly adopting microgrids and forming utility partnerships to ensure resilience and control over power access.

Siemens views data centres not just as energy consumers but as contributors to the grid, using stored energy to balance supply. The shift is pushing the industry to become more involved in grid stability and renewable integration.

While achieving net zero remains challenging, data centres are adopting on-site renewables, advanced cooling systems, and AI-driven management tools to boost efficiency.

Siemens’ own software, such as the Building X Suite, is helping reduce energy waste and predict maintenance needs, aligning operational effectiveness with sustainability goals.

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xAI eyes data centre deal with Humain

Elon Musk’s AI venture, xAI, has entered early discussions with Humain to secure data centre capacity instead of relying solely on existing infrastructure.

According to Bloomberg, the arrangement could involve several gigawatts of capacity, although Humain has yet to start building its facilities, meaning any deal would take years to materialise.

Humain is backed by Saudi Arabia’s Crown Prince Mohammed bin Salman and the Public Investment Fund (PIF). xAI is reportedly considering a fresh funding round where PIF might also invest.

At the same time, xAI is negotiating with a smaller company constructing a 200-megawatt data centre, offering a more immediate solution while waiting for larger projects.

Rather than operating in isolation, xAI joins AI competitors like Google, Meta and Microsoft in racing to secure vast computing power for training large AI models. The push for massive data centre capacity reflects the escalating demands of advanced AI systems.

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