ai

DeepSeek and others gain traction in US and EU

A recent survey has found that most US and the EU users are open to using Chinese large language models, even amid ongoing political and cybersecurity scrutiny.

According to the report, 71 percent of respondents in the US and 87 percent in the EU would consider adopting models developed in China.

The findings highlight increasing international curiosity about the capabilities of Chinese AI firms such as DeepSeek, which have recently attracted global attention.

While the technology is gaining credibility, many Western users remain cautious about data privacy and infrastructure control.

More than half of those surveyed said they would only use Chinese AI models if hosted outside China. However, this suggests that while trust in the models’ performance is growing, concerns over data governance remain a significant barrier to adoption.

The results come amid heightened global competition in the AI race, with Chinese developers rapidly advancing to challenge US-based leaders. DeepSeek and similar firms now face balancing global outreach with geopolitical limitations.

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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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YouTube Shorts brings image-to-video AI tool

Google has rolled out new AI features for YouTube Shorts, including an image-to-video tool powered by its Veo 2 model. The update lets users convert still images into six-second animated clips, such as turning a static group photo into a dynamic scene.

Creators can also experiment with immersive AI effects that stylise selfies or simple drawings into themed short videos. These features aim to enhance creative expression and are currently available in the US, Canada, Australia and New Zealand, with global rollout expected later this year.

A new AI Playground hub has also been launched to house all generative tools, including video effects and inspiration prompts. Users can find the hub by tapping the Shorts camera’s ‘create’ button and then the sparkle icon in the top corner.

Google plans to introduce even more advanced tools with the upcoming Veo 3 model, which will support synchronised audio generation. The company is positioning YouTube Shorts as a key platform for AI-driven creativity in the video content space.

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5G traffic surges under growing AI usage

AI-driven applications are reshaping mobile data norms, and 5G networks are feeling the pressure. Analysts warn that uplink demand generated by tools like virtual assistants and AR platforms could exceed the current 5G capacity by around 2027. Traditional networks are built to handle heavier downlink traffic, leaving them under stress as AI flows increase in the opposite direction.

At the same time, artificial intelligence is playing a constructive role by helping optimise these strained networks. AI techniques, such as predictive traffic forecasting, dynamic spectrum allocation, beamforming, and energy management, are improving efficiency and reducing operational costs. Networks are becoming smarter in detecting congestion and self-adjusting to maintain performance.

Industry discussions point to 5G‑Advanced, also known as 5.5G, as a key evolution that embeds AI and machine learning into network architecture. These upgrades promise higher uplink speeds, tighter latency control, and built‑in intelligence for optimisation and automation. Edge computing is set to play a central role by bringing AI decision‑making closer to users.

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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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Teens turn to AI for advice and friendship

A growing number of US teens rely on AI for daily decision‑making and emotional support, with chatbots such as ChatGPT, Character.AI and Replika. One Kansas student admits she uses AI to simplify everyday tasks, using it to choose clothes or plan events while avoiding schoolwork.

A survey by Common Sense Media reveals that over 70 per cent of teenagers have tried AI companions, with around half using them regularly. Roughly a third reported discussing serious issues with AI, sometimes finding it as or more satisfying than talking with friends.

Experts express concern that such frequent AI interactions could hinder development of creativity, critical thinking and social skills in young people. The study warns adolescents may become overly validated by AI, missing out on real‑world emotional growth.

Educators caution that while AI offers constant, non‑judgemental feedback, it is not a replacement for authentic human relationships. They recommend AI use be carefully supervised to ensure it complements rather than replaces real interaction.

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Quantum computing faces roadblocks to real-world use

Quantum computing holds vast promise for sectors from climate modelling to drug discovery and AI, but it remains far from mainstream due to significant barriers. The fragility of qubits, the shortage of scalable quantum software, and the immense number of qubits required continue to limit progress.

Keeping qubits stable is one of the most significant technical obstacles, with most only lasting microseconds before disruption. Current solutions rely on extreme cooling and specialised equipment, which remain expensive and impractical for widespread use.

Even the most advanced systems today operate with a fraction of the qubits needed for practical applications, while software options remain scarce and highly tailored. Businesses exploring quantum solutions must often build their tools from scratch, adding to the cost and complexity.

Beyond technology, the field faces social and structural challenges. A lack of skilled professionals and fears around unequal access could see quantum benefits restricted to big tech firms and governments.

Security is another looming concern, as future quantum machines may be capable of breaking current encryption standards. Policymakers and businesses must develop defences before such systems become widely available.

AI may accelerate progress in both directions. Quantum computing can supercharge model training and simulation, while AI is already helping to improve qubit stability and propose new hardware designs.

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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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