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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At the same time, outdated regulatory processes are slowing progress.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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New benchmark exposes limits of current AI tools

A new coding competition has exposed the limitations of current AI models, with the winner solving just 7.5% of programming problems. The K Prize, launched by Databricks and Perplexity co-founder, aims to challenge smaller models using real-world GitHub issues in a contamination-free format.

Despite the low score, Eduardo Rocha de Andrade took home the $50,000 top prize. Konwinski says the intentionally tough benchmark helps avoid inflated results and encourages realistic assessments of AI capability.

Unlike the better-known SWE-Bench, which may allow models to train on test material, the K Prize uses only new issues submitted after a set deadline. Its design prevents exposure during training, making it a more reliable measure of generalisation.

A $1 million prize remains for any open-source model that scores over 90%. The low results are being viewed as a necessary wake-up call in the race to build competent AI software engineers.

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Children turning to AI for friendship raises alarms

Children and teenagers are increasingly turning to AI not just for help with homework but as a source of companionship.

A recent study by Common Sense Media revealed that over 70% of young people have used AI as a companion. Alarmingly, nearly a third of teens reported that their conversations with AI felt as satisfying, or more so, than talking with actual friends.

Holly Humphreys, a licensed counsellor at Thriveworks in Harrisonburg, Virginia, warned that the trend is becoming a national concern.

She explained that heavy reliance on AI affects more than just social development. It can interfere with emotional wellbeing, behavioural growth and even cognitive functioning in young children and school-age youth.

As AI continues evolving, children may find it harder to build or rebuild connections with real people. Humphreys noted that interactions with AI are often shallow, lacking the depth and empathy found in human relationships.

The longer kids engage with bots, the more distant they may feel from their families and peers.

To counter the trend, she urged parents to establish firm boundaries and introduce alternative daily activities, particularly during summer months. Simple actions like playing card games, eating together or learning new hobbies can create meaningful face-to-face moments.

Encouraging children to try a sport or play an instrument helps shift their attention from artificial friends to genuine human connections within their communities.

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AI music tools arrive for YouTube creators

YouTube is trialling two new features to improve user engagement and content creation. One enhances comment readability, while the other helps creators produce music using AI for Shorts.

A new threaded layout is being tested to organise comment replies under the original post, allowing more explicit and focused conversations. Currently, this feature is limited to a small group of Premium users on mobile.

YouTube also expands Dream Track, an AI-powered tool that creates 30-second music clips from simple text prompts. Creators can generate sounds matching moods like ‘chill piano melody’ or ‘energetic pop beat’, with the option to include AI-generated vocals styled after popular artists.

Both features are available only in the US during the testing phase, with no set date for international release. YouTube’s gradual updates reflect a shift toward more intuitive user experiences and creative flexibility on the platform.

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DeepMind engineers join Microsoft’s AI team

Microsoft has aggressively expanded its AI workforce by hiring over 20 specialists from Google’s DeepMind research lab in recent months. Notable recruits, now part of Microsoft AI under EVP Mustafa Suleyman, include former DeepMind engineering head Amar Subramanya, product managers and research scientists such as Sonal Gupta, Adam Sadovsky, Tim Frank, Dominic King, and Christopher Kelly.

This talent influx aligns with Suleyman’s leadership of Microsoft’s consumer AI division, which is responsible for Copilot, Bing, and Edge, and underscores the company’s push to solidify its lead in personal AI experiences. Meanwhile, this hiring effort unfolds against a backdrop of 9,000 layoffs globally, highlighting Microsoft’s strategy to redeploy resources toward AI innovation.

However, regulators are scrutinising the move. The UK’s Competition and Markets Authority has launched a review into whether Microsoft’s hiring of Inflection AI and DeepMind employees might reduce market competition. Microsoft maintains that its practice fosters, rather than limits, industry advancement.

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ASEAN urged to unite on digital infrastructure

Asia stands at a pivotal moment as policymakers urge swift deployment of converging 5G and AI technologies. Experts argue that 5G should be treated as a foundational enabler for AI, not just a telecom upgrade, to power future industries.

A report from the Lee Kuan Yew School of Public Policy identifies ten urgent imperatives, notably forming national 5G‑AI strategies, empowering central coordination bodies and modernising spectrum policies. Industry leaders stress that aligning 5G and AI investment is essential to sustain innovation.

Without firm action, the digital divide could deepen and stall progress. Coordinated adoption and skilled workforce development are seen as critical to turning incremental gains into transformational regional leadership.

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Altman warns AI voice cloning will break bank security

OpenAI CEO Sam Altman has warned that AI poses a serious threat to financial security through voice-based fraud.

Speaking at a Federal Reserve conference in Washington, Altman said AI can now convincingly mimic human voices, rendering voiceprint authentication obsolete and dangerously unreliable.

He expressed concern that some financial institutions still rely on voice recognition to verify identities. ‘That is a crazy thing to still be doing. AI has fully defeated that,’ he said. The risk, he noted, is that AI voice clones can now deceive these systems with ease.

Altman added that video impersonation capabilities are also advancing rapidly. Technologies that become indistinguishable from real people could enable more sophisticated fraud schemes. He called for the urgent development of new verification methods across the industry.

Michelle Bowman, the Fed’s Vice Chair for Supervision, echoed the need for action. She proposed potential collaboration between AI developers and regulators to create better safeguards. ‘That might be something we can think about partnering on,’ Bowman told Altman.

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