Cybercrime incidents have surged as AI tools enable more convincing scams, leading to sharply rising losses in Estonia. Authorities reported thousands of phishing and fraud cases affecting individuals and businesses.
Criminals are using AI to generate fluent messages in Estonian, removing a key warning sign that once helped people detect scams. Experts say language accuracy has made fraudulent calls and messages harder to identify.
Growing awareness of scams is also fuelling public anxiety, with some users considering abandoning digital services. Officials warn that loss of trust could undermine confidence in digital systems.
Authorities are urging stronger safeguards and public education to counter the cybersecurity threats. Banks, telecom firms and digital identity providers are introducing new protections while campaigns aim to improve digital awareness.
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Researchers at MIT have developed a new approach that combines generative AI with wireless signals to detect objects hidden behind obstacles. The system uses Wi-Fi-like millimetre wave signals to build partial reconstructions and then completes missing details with AI.
Traditional methods struggled with limited visibility due to how signals reflect off surfaces, often leaving large portions of objects undetected. The new technique, Wave-Former, uses generative AI to fill missing data, improving reconstruction accuracy by nearly 20%.
An extended system, called RISE, takes the concept further by mapping entire indoor environments. By analysing reflected signals from human movement, the system reconstructs room layouts using a single stationary radar, removing the need for mobile sensors.
Applications range from warehouse automation to smart home robotics, where understanding hidden objects and human positions is critical. Unlike camera-based systems, the technology also preserves privacy, marking a significant step forward in wireless sensing capabilities.
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Tokyo authorities are accelerating the adoption of generative AI across public administration, aiming to improve efficiency and address labour shortages. Municipal governments across the capital are increasingly integrating AI into daily operations.
A new AI platform with GovTech Tokyo enables public employees to build customised applications without advanced technical skills. Built on open-source software, the system lowers costs and removes barriers linked to development and infrastructure.
Practical applications include document drafting tools, regulatory search systems, and internal chatbots. Early deployments, such as in Sumida Ward, show reduced operational costs and faster workflows compared to outsourcing solutions.
GovTech Tokyo, established in 2023 to lead digital transformation, continues to expand support frameworks and expertise. Plans are underway to enable the sharing of AI applications across municipalities, strengthening collaboration and standardising innovation across the capital.
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Researchers led by Michigan State University developed an AI model that predicts chemical effects on gene expression, speeding up drug discovery. The system analyses chemical structures to determine whether compounds increase or decrease activity in specific genes.
The model was trained on vast datasets of experimental results, allowing it to filter complex biological signals and produce reliable predictions. The approach allows virtual screening of millions of compounds, reducing the need for early-stage lab testing.
Study identified promising compounds for treating hepatocellular carcinoma and idiopathic pulmonary fibrosis, two diseases with limited therapeutic options. Lab and animal tests confirmed several compounds reduced tumour growth or showed promise for lung disease treatment.
Findings highlight the growing role of AI in medicine, with researchers emphasising that collaboration across computational science, biology, and clinical practice remains essential to bringing new therapies from discovery to real-world use.
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Mass layoffs across major tech firms, including Amazon’s 16,000 job cuts, have intensified concerns that AI will replace white-collar workers. Headlines suggest a rapid shift, yet broader labour data tells a more measured story.
US employment has grown by 1.1% since the launch of ChatGPT in November 2022, reaching over 157 million workers. Service industries expanded significantly, adding more than two million jobs, while goods-producing sectors declined modestly.
Overall trends indicate no major disruption to the labour market so far.
Sector-level data reveals uneven shifts. The information industry recorded the steepest losses, particularly in media, telecoms, and content production, where automation and long-term structural changes continue to reduce headcounts.
Meanwhile, highly automatable roles such as telemarketing and call centres saw the sharpest declines.
Professional services present a more complex picture. Legal, engineering, and consulting roles have grown or remained stable, defying expectations of widespread displacement.
Hiring continues to exceed layoffs in several sectors, though younger workers appear increasingly vulnerable as competition intensifies in AI-exposed roles.
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Tether has launched an AI framework that runs large language models on smartphones and non-NVIDIA GPUs. The system is part of its QVAC platform and uses Microsoft’s BitNet architecture, along with LoRA techniques to reduce memory and computational requirements.
The framework enables cross-platform training on AMD, Intel, Apple Silicon, and mobile GPUs, allowing models with up to 1 billion parameters to be fine-tuned on phones in under 2 hours.
Larger models with up to 13 billion parameters are also supported on mobile devices. BitNet’s 1-bit architecture reduces VRAM requirements by nearly 78%, enabling larger models to run on limited hardware.
Performance improvements benefit inference, with mobile GPUs outperforming CPUs, enabling on-device training and federated learning. By reducing reliance on cloud infrastructure, the system offers more flexible AI development for distributed environments.
Tether’s expansion into AI mirrors a broader trend in the crypto sector, where companies are investing in AI infrastructure, autonomous agents, and high-performance computing.
Industry activity includes record revenue growth for AI and HPC operations, blockchain-integrated AI agents, and new tools for secure on-chain transactions.
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Google has expanded Personal Intelligence across AI Mode in Search, the Gemini app, and Gemini in Chrome for US users. Rollout follows early adoption, where users responded positively to more tailored and context-aware assistance.
Personal Intelligence connects data across services such as Gmail and Google Photos to deliver highly personalised responses. Queries no longer need full context, as the system uses past purchases, travel history, and preferences to deliver relevant suggestions.
Use cases range from customised shopping recommendations and technical troubleshooting to travel planning and itinerary creation. Suggestions adapt to user habits, including preferred brands, past bookings, and time constraints, delivering more precise results.
Privacy remains central to the rollout, with users retaining control over which apps are connected. Data from personal services is not directly used to train AI models, while limited interaction data helps improve performance over time.
Access is currently limited to personal Google accounts, excluding enterprise and education users.
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Plans to accelerate technological leadership have been outlined by the HM Treasury and the Department for Science, Innovation and Technology, with a £2.5 billion investment targeting AI and quantum computing.
Ambition has been reinforced by Rachel Reeves, who positioned AI as a central driver of economic growth, alongside closer European ties and regional development. Strategy aims to secure the fastest adoption of AI across the G7 while supporting domestic innovation ecosystems.
Significant funding in the UK will be directed towards a Sovereign AI initiative, quantum infrastructure and research capacity. Plans include procurement of large-scale quantum systems and targeted investment in startups, helping companies scale while strengthening national capabilities in advanced technologies.
Expectations surrounding quantum computing are framed as transformative, with potential to reshape industries from healthcare to energy. Combined investment reflects a broader effort to align innovation policy with long-term economic growth and global competitiveness.
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The Pentagon is accelerating efforts to replace Anthropic after the company was designated a supply-chain risk, marking a sharp shift in US defence AI strategy. The move follows a breakdown in talks over safeguards governing military use of AI, particularly around surveillance and autonomous weapons.
Cameron Stanley, the Pentagon’s chief digital and AI officer, said engineering work is underway to deploy alternative large language models in government-controlled environments. He indicated that while transitioning from Anthropic’s tools could take more than a month, new systems are expected to be operational soon.
The decision threatens a $200 million contract and could exclude Anthropic from future defence partnerships. The US administration has set a six-month timeline for federal agencies to shift away from the company, signalling a broader push to diversify AI suppliers and reduce dependency risks.
Rival providers are already stepping in. OpenAI and xAI have been approved for classified work, while Google is introducing Gemini AI tools across the Pentagon workforce, initially on unclassified networks before expanding into sensitive environments.
Anthropic has challenged the designation in court, arguing it violates constitutional protections and could harm its business. Despite the legal dispute, defence officials have made clear they are moving forward with an ‘AI-first’ strategy to accelerate the adoption of advanced models across military operations.
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Chey Tae-won warned that the global memory chip shortage could last for years, with structural supply constraints likely to continue into the next decade. Speaking on the sidelines of Nvidia GTC 2026 in San Jose, he said limited wafer capacity remains a key bottleneck for the semiconductor industry.
‘The shortage stems from a lack of wafer capacity, and securing additional wafers takes at least four to five years,’ Chey said. ‘We expect the industry-wide supply shortfall to persist at over 20 percent through 2030.’
He added that SK Hynix is implementing initiatives such as adjusting production schedules and diversifying supplier partnerships to stabilise prices. CEO Kwak Noh-jung is expected to provide further details on these new steps to manage volatility linked to the memory chip shortage.
Despite growing pressure to expand manufacturing overseas, Chey stressed that the group will prioritise domestic production to better respond to the ongoing memory chip shortage. ‘Building capacity outside Korea takes the same amount of time, regardless of location,’ he said. ‘Korea already has the infrastructure in place, allowing for a much faster response.’
He also highlighted the challenges of building fabrication plants abroad, including the need for reliable electricity and water supplies, as well as access to skilled engineering talent.
On competition in the high-bandwidth memory market, Chey noted that rising demand driven by artificial intelligence is reshaping supply dynamics. ‘AI requires graphics processing units (GPUs), and GPUs require HBM. We will do our best,’ he said, while cautioning that excessive focus on HBM could worsen the memory chip shortage for conventional DRAM used in smartphones and personal computers.
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