Nigeria has been advised to develop its coal reserves to benefit from the rapidly expanding global AI economy. A policy organisation said the country could capture part of the projected $650 billion AI investment by strengthening its energy supply capacity.
AI infrastructure requires vast and reliable electricity to power data centres and advanced computing systems. Technology companies worldwide are increasing energy investments as competition intensifies and demand for computing power continues to grow rapidly.
Nigeria holds nearly five billion metric tonnes of coal, offering a significant opportunity to support global energy needs. Experts warned that failure to develop these resources could result in major economic losses and missed industrial growth.
The organisation also proposed creating a national corporation to convert coal into high-value energy and industrial products. Analysts stressed that urgent government action is needed to secure Nigeria’s position in the emerging AI-driven economy.
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Tech companies competing in AI are increasingly expecting employees to work longer weeks to keep pace with rapid innovation. Some start-ups openly promote 70-hour schedules, presenting intense effort as necessary to launch products faster and stay ahead of rivals.
Investors and founders often believe that extended working hours improve development speed and increase the chances of securing funding. Fast growth and fierce global competition have made urgency a defining feature of many AI workplaces.
However, research shows productivity rises only up to a limit before fatigue reduces efficiency and focus. Experts warn that excessive workloads can lead to burnout and make it harder for companies to retain experienced professionals.
Health specialists link extended working weeks to higher risks of heart disease and stroke. Many experts argue that smarter management and efficient use of technology offer safer and more effective paths to lasting productivity.
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AI is now being used to create ‘deathbots’, chatbots designed to mimic people after they die using their messages and voice recordings. The technology is part of a growing digital afterlife industry, with some people using it to maintain a sense of connection with loved ones who have passed away.
Researchers at Cardiff University studied how these systems recreate personalities using digital data such as texts, emails, and audio recordings. The findings described the experience as both fascinating and unsettling, raising questions about memory, identity, and emotional impact.
Tests showed current deathbots often fail to accurately reproduce voices or personalities due to technical limitations. Researchers warned that these systems rely on simplified versions of people, which may distort memories rather than preserve them authentically.
Experts believe the technology could improve, but remain uncertain whether it will become widely accepted. Concerns remain about emotional consequences and whether digital versions could alter how people remember those who have died.
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Educators in the US are increasingly using AI to address resource shortages, despite growing frustration with fragmented digital platforms. A new survey highlights rising dependence on AI tools across schools and universities in the US.
The study found many educators in the US juggle numerous digital systems that fail to integrate smoothly. Respondents said constant switching between platforms adds to workload pressures and burnout in the US education sector.
AI use in the US is focused on boosting productivity, with educators applying tools to research, writing and administrative tasks. Many also use AI to support student learning as budgets tighten in the US.
Concerns remain in the US around data security, ethics and system overload. Educators said better integration between AI and learning tools could ease strain and improve outcomes in the US classroom.
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Lawmakers in New York have introduced a bill proposing a three year pause on permits for new data centres. Supporters say rapid expansion linked to AI infrastructure risks straining energy systems in New York.
Concerns in New York focus on rising electricity demand and higher household bills as tech companies scale AI operations. Critics across the US argue local communities bear the cost of supporting large scale computing facilities.
The New York proposal has drawn backing from environmental groups and politicians in the US who want time to set stricter rules. US senator Bernie Sanders has also called for a nationwide halt on new data centres.
Officials in New York say the pause would allow stronger policies on grid access and fair cost sharing. The debate reflects wider US tension between economic growth driven by AI and environmental limits.
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Engineers are working to make robots move with greater balance and fluidity, bringing machines closer to human-like motion. Progress depends heavily on actuators, the components that convert energy into precise physical movement.
Traditional electric motors have enabled many robotic breakthroughs, yet limitations in efficiency, safety and responsiveness remain clear. Machines often consume too much power, overheat at small sizes and lack the flexibility needed for smooth interaction.
Major manufacturers including Schaeffler and Hyundai Mobis are now designing advanced actuators that provide better control, real-time feedback and improved energy efficiency. Such innovations could allow humanoid robots to operate safely alongside workers and perform practical industrial tasks.
Researchers are also experimenting with softer materials and air-powered systems that behave more like muscles than rigid machinery. Continued advances could eventually produce robots capable of natural, graceful movement, opening new possibilities for everyday use.
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Organisations undergoing finance transformations are discovering that traditional system cutovers rarely go as planned. Hidden manual workarounds and undocumented processes often surface late, creating operational risks and delays during ERP migrations.
Agentic AI is emerging as a solution by deploying autonomous software agents that discover real workflows directly from system data. Scout agents analyse transaction logs to uncover hidden dependencies, allowing companies to build more accurate future systems based on actual operations.
Simulator agents to stress test new systems by generating thousands of realistic transactions continuously. When problems arise, agents analyse errors and automatically recommend fixes, turning testing into a continuous improvement process rather than a one-time checkpoint.
Sentinel agents monitor financial records in real time to detect discrepancies before they escalate into compliance risks. Leaders say the approach shifts focus from single go-live milestones to ongoing resilience, with teams increasingly managing intelligent systems instead of manual processes.
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The UAE Ministry of Higher Education and Scientific Research has partnered with Microsoft to develop AI agents to help university students find jobs. The initiative was announced in Dubai during a major policy gathering in the UAE.
The collaboration in the UAE will use Microsoft Azure to build prototype AI agents supporting personalised learning and career navigation. Dubai-based officials said the tools are designed to align higher education with labour market needs in the UAE.
Four AI agents are being developed in the UAE, covering lifelong skills planning, personalised learning, course co creation and research alignment. Dubai remains central to the project as a hub for higher education innovation in the UAE.
Officials in the UAE said the partnership reflects national priorities around innovation and a knowledge based economy. Microsoft said Dubai offers an ideal environment to scale AI driven education tools across the UAE.
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Researchers at Mass General Brigham have unveiled BrainIAC, an artificial intelligence model capable of analysing brain MRI scans to predict age, dementia risk, tumour mutations, and cancer survival. The model demonstrates remarkable flexibility, handling a wide variety of medical tasks with high accuracy.
BrainIAC employs self-supervised learning to identify features from unlabeled MRI datasets, allowing it to adapt to numerous clinical applications without requiring extensive annotated data. Its performance surpasses that of conventional task-specific AI frameworks.
Tests on nearly 49,000 MRI scans across seven different tasks revealed the model’s ability to generalise across both healthy and abnormal images. It successfully tackled both straightforward tasks, such as scan classification, and complex challenges, including tumour mutation detection.
The team highlights BrainIAC’s potential to accelerate biomarker discovery, improve diagnostic tools, and personalise patient care. While results are promising, researchers note that further studies on additional imaging techniques and larger datasets are necessary to validate its broader clinical use.
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Renowned physicist John Martinis, a Nobel Prize winner, is pursuing a new quantum computing breakthrough. His early work proved electrical circuits could behave like quantum particles, enabling modern quantum machines.
Momentum grew when Martinis led Google’s ‘quantum supremacy’ experiment, outperforming classical computers in specialised tasks. Scaling remains difficult because fragile qubits, complex wiring and manufacturing limits reduce reliability.
Startup QoLab, founded in 2024, is redesigning quantum chip architecture to solve those hardware problems. Integrating components onto chips could reduce wiring, improve stability and enable larger systems.
Useful quantum computers could transform chemistry, materials science and complex simulations beyond classical limits. Martinis believes hardware innovation and scalable manufacturing will determine future industry leaders.
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