An image made with a drone shows air handling units on the roof of a CloudHQ data center in Ashburn, Virginia. An image made with a drone shows air handling units on the roof of a CloudHQ data center in Ashburn, Virginia. Mon 8 Dec 2025 07.00 ESTLast modified on Mon 8 Dec 2025 08.41 EST A coalition of more than 230 environmental groups has demanded a national moratorium on new datacenters in the US, the latest salvo in a growing backlash to a booming artificial intelligence industry that has been blamed for escalating electricity bills and worsening the climate crisis. The green groups, including Greenpeace, Friends of the Earth, Food & Water Watch and dozens of local organizations, have urged members of Congress to halt the proliferation of energy-hungry datacenters, accusing them of causing planet-heating emissions, sucking up vast amounts of water and for exacerbating electricity bill increases that have hit Americans this year. The push comes amid a growing revolt against moves by companies such as Meta, Google and Open AI to plow hundreds of billions of dollars into new datacenters, primarily to meet the huge computing demands of AI.

An aerial view of an Amazon Web Services Data Center known as U.S. East 1 in Ashburn, Virginia, on Oct. 20 | REUTERS STOCKHOLM/LONDON - The global boom in data centers as companies increasingly outsource information storage and ramp up use of energy-intensive artificial intelligence is creating a key challenge for the industry -- how to keep cool. An outage at the world's biggest exchange operator CME Group from late Thursday that halted trade on its popular currency platform and in futures spanning foreign exchange, commodities, Treasuries and stocks has put a spotlight on data centers overheating. The problem was a cooling issue at data centers operated by Dallas-headquartered CyrusOne, which operates more than 55 centers in the U.S., Europe and Japan. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.

New analysis reveals why America's $5 trillion AI race against China proves as consequential as the Cold War, citing economic dominance and national security at stake.

Artificial intelligence company Anthropic announced a $50bn investment in computing infrastructure on Wednesday that will include new datacenters in Texas and New York . "We're getting closer to AI that can accelerate scientific discovery and help solve complex problems in ways that weren't possible before," Anthropic's CEO, Dario Amodei, said in a press release. Building the massive information warehouses takes an average of two years in the US and requires copious amounts of energy to fuel the facilities. The company, maker of the AI chatbot Claude, popular with businesses adopting AI, said in a statement that the "scale of this investment is necessary to meet the growing demand for Claude from hundreds of thousands of businesses while keeping our research at the frontier". Anthropic said its projects will create about 800 permanent jobs and 2,400 construction jobs.

Several large tech firms that are active in AI have set goals to hit net zero by 2030, but a new forecast of the energy and water required to run large data centres shows they're unlikely to meet those targets As the AI industry rapidly expands, questions about the environmental impact of data centres are coming to the forefront - and a new forecast warns the industry is unlikely to meet net zero targets by 2030. Fengqi You at Cornell University in New York and his colleagues modelled how much energy, water and carbon today's leading AI servers could use by 2030, taking into account different growth scenarios and possible data centre locations within the United States. They combined projected chip supply, server power usage and cooling efficiency with state-by-state electrical grid data to conduct their analysis. While not every AI company has set a net zero target, some larger tech firms that are active in AI, such as Google, Microsoft and Meta have set goals with a deadline of 2030. "The rapid growth of AI computing is basically reshaping everything," says You. "We're trying to understand how, as a sector grows, what's going to be the impact?"

An aerial view of an Amazon Web Services Data Center known as US East 1 in Ashburn, Virginia on 20 October 2025. An aerial view of an Amazon Web Services Data Center known as US East 1 in Ashburn, Virginia on 20 October 2025. Thu 30 Oct 2025 16.50 EDTLast modified on Fri 31 Oct 2025 05.25 EDT Amazon has made its first financial disclosures since the disastrous outage suffered by its cloud computing division that brought everything from smart beds to banks offline. In spite of the global outage, Amazon Web Services has continued to grow, and this quarter reported a 20% increase in revenue year over year. Wall Street estimated that AWS would bring in $32.42bn in net sales in the third quarter, with the company reporting actual revenue of $33bn.

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Inferring demographic attributes such as age, sex, or income level from human mobility patterns enables critical applications such as targeted public health interventions, equitable urban planning, and personalized transportation services. Existing mobility-based demographic inference studies heavily rely on large-scale trajectory data with demographic labels, leading to limited interpretability and poor generalizability across different datasets and user groups. We propose HiCoTraj (Zero-Shot Demographic Reasoning via Hierarchical Chain-of-Thought Prompting from Trajectory), a framework that leverages LLMs' zero-shot learning and semantic understanding capabilities to perform demographic inference without labeled training data. HiCoTraj transforms trajectories into semantically rich, natural language representations by creating detailed activity chronicles and multi-scale visiting summaries. Then HiCoTraj uses a novel hierarchical chain of thought reasoning to systematically guide LLMs through three cognitive stages: factual feature extraction, behavioral pattern analysis, and demographic inference with structured output. This approach addresses the scarcity challenge of labeled demographic data while providing transparent reasoning chains. Experimental evaluation on real-world trajectory data demonstrates that HiCoTraj achieves competitive performance across multiple demographic attributes in zero-shot scenarios.

How do distributed neural circuits drive purposeful movements from the complex musculoskeletal system? This characterization is critical towards not just furthering our understanding of the generation of movement, but, importantly, guiding us towards therapeutic targets for diseases affecting motor control. The neural processes leading to movements have been relatively well posited and understood due to the quantitative nature of the behavioral outputs involved. Classic approaches have largely focused on optimization principles, including limb control, to achieve human-like behavioral trajectories. These largely theoretical models of sensorimotor control can recapitulate observed movement trajectories by hypothesizing the presence of a controller guiding the complex movements. However, these models cannot predict how neuronal populations in each brain region affects the resulting movement and vice-versa. On the other hand, breakneck advances in hardware techniques have led to vast improvements in our ability to record large-scale multi-regional neural data. These recordings have enabled dimensionality reduction and modeling techniques to elucidate the structure in high-dimensional neural activity during different conditions, and relate the neural activity directly to kinematic outcomes. However, these data-driven models typically do not consider the biophysical underpinnings of the musculoskeletal system, and thus fail to elucidate the computational role of neural activity in driving the musculoskeletal system such that the body reaches a desired state.