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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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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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 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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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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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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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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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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Amazon is shutting down its AI research lab in Shanghai, marking another step in its gradual withdrawal from China. The move comes amid continuing US–China trade tensions and a broader trend of American tech companies reassessing their presence in the country.
The company said the decision was part of a global streamlining effort rather than a response to AI concerns.
A spokesperson for AWS said the company had reviewed its organisational priorities and decided to cut some roles across certain teams. The exact number of job losses has not been confirmed.
Before Amazon’s confirmation, one of the lab’s senior researchers noted on WeChat that the Shanghai site was the final overseas AWS AI research lab and attributed its closure to shifts in US–China strategy.
The team had built a successful open-source graph neural network framework known as DGL, which reportedly brought in nearly $1 billion in revenue for Amazon’s e-commerce arm.
Amazon has been reducing its footprint in China for several years. It closed its domestic online marketplace in 2019, halted Kindle sales in 2022, and recently laid off AWS staff in the US.
Other tech giants including IBM and Microsoft have also shut down China-based research units this year, while some Chinese AI firms are now relocating operations abroad instead of remaining in a volatile domestic environment.
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An Indian teenager has created a low-cost AI device that translates slurred speech into clear Hindi, helping patients with paralysis and neurological conditions communicate more easily.
Pranet Khetan’s innovation, Paraspeak, uses a custom Hindi speech recognition model to address a long-ignored area of assistive tech.
The device was inspired by Khetan’s visit to a paralysis care centre, where he saw patients struggling to express themselves. Unlike existing English models, Paraspeak is trained on the first Hindi dysarthic speech dataset in India, created by Khetan himself through recordings and data augmentation.
Using transformer architecture, Paraspeak converts unclear speech into understandable output using cloud processing and a neck-worn compact device. It is designed to be scalable across different speakers, unlike current solutions that only work for individual patients.
The AI device is affordable, costing around ₹2,000 to build, and is already undergoing real-world testing. With no existing market-ready alternative for Hindi speakers, Paraspeak represents a significant step forward in inclusive health technology.
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