AI's growing thirst for water is becoming a public health risk "Bubble" is probably the word most associated with "AI" right now, though we are slowly understanding that it is not just an economic time bomb; it also carries significant public health risks. Beyond the release of pollutants, the massive need for clean water by AI data centres can reduce sanitation and exacerbate gastrointestinal illness in nearby communities, placing additional strain on local health infrastructure. AI's energy consumption is massive and increasingly water-dependent Generative AI is artificial intelligence that is able to generate new text, photos, code and more, and it has already infiltrated the lives of most people around the globe. ChatGPT alone is reported to receive around one billion queries in a single day, pointing to huge demand at the individual level. This, however, is only the tip of the iceberg.

If the US Has to Build Data Centers, Here's Where They Should Go A new analysis tries to calculate the coming environmental footprint of AI in the US and finds that the ideal sites for data centers aren't where they're being built. A data center for cryptocurrency mining, cloud services, and AI computing in Stutsman County, North Dakota.Video: halbergman/Getty Images Tech companies have invested so much money in building data centers in recent months, it's actively driving the US economy--and the AI race is showing no signs of slowing down. Meta chief Mark Zuckerberg told President Donald Trump last week that the company would spend $600 billion on US infrastructure--including data centers--by 2028, while OpenAI has committed already to spending $1.4 trillion. An extensive new analysis looks at the environmental footprint of data centers in the US to get a handle on what, exactly, the country might be facing as this buildout continues over the next few years--and where the US should be building data centers to avoid the most harmful environmental impacts. The study, published in the journal Nature Communications on Monday, uses a variety of data, including demand for AI chips and information on state electricity and water scarcity, to project the potential environmental impacts of future data centers through the end of the decade. The study models a number of different possible scenarios on how data centers could affect the US and the planet--and cautions that tech companies' net zero promises aren't likely to hold up against the energy and water needs of the massive facilities they're building.

Water is essential for agricultural productivity. Assessing water shortages and reduced yield potential is a critical factor in decision-making for ensuring agricultural productivity and food security. Crop simulation models, which align with physical processes, offer intrinsic explainability but often perform poorly. Conversely, machine learning models for crop yield modeling are powerful and scalable, yet they commonly operate as black boxes and lack adherence to the physical principles of crop growth. This study bridges this gap by coupling the advantages of both worlds. We postulate that the crop yield is inherently defined by the water availability. Therefore, we formulate crop yield as a function of temporal water scarcity and predict both the crop drought stress and the sensitivity to water scarcity at fine-scale resolution. Sequentially modeling the crop yield response to water enables accurate yield prediction. To enforce physical consistency, a novel physics-informed loss function is proposed. We leverage multispectral satellite imagery, meteorological data, and fine-scale yield data. Further, to account for the uncertainty within the model, we build upon a deep ensemble approach. Our method surpasses state-of-the-art models like LSTM and Transformers in crop yield prediction with a coefficient of determination ($R^2$-score) of up to 0.82 while offering high explainability. This method offers decision support for industry, policymakers, and farmers in building a more resilient agriculture in times of changing climate conditions.

Water from Air could produce enough daily water for a family of four.

Amazon, Microsoft and Google are operating datacentres that use vast amounts of water in some of the world's driest areas and are building many more, an investigation by SourceMaterial and the Guardian has found. With Donald Trump pledging to support them, the three technology giants are planning hundreds of datacentres in the US and across the globe, with a potentially huge impact on populations already living with water scarcity. "The question of water is going to become crucial," said Lorena Jaume-Palasí, founder of the Ethical Tech Society. "Resilience from a resource perspective is going to be very difficult for those communities." Efforts by Amazon, the world's largest online retailer, to mitigate its water use have sparked opposition from inside the company, SourceMaterial's investigation found, with one of its own sustainability experts warning that its plans are "not ethical".

In response to climate change, assessing crop productivity under extreme weather conditions is essential to enhance food security. Crop simulation models, which align with physical processes, offer explainability but often perform poorly. Conversely, machine learning (ML) models for crop modeling are powerful and scalable yet operate as black boxes and lack adherence to crop growths physical principles. To bridge this gap, we propose a novel method that combines the strengths of both approaches by estimating the water use and the crop sensitivity to water scarcity at the pixel level. This approach enables yield loss estimation grounded in physical principles by sequentially solving the equation for crop yield response to water scarcity, using an enhanced loss function. Leveraging Sentinel-2 satellite imagery, climate data, simulated water use data, and pixel-level yield data, our model demonstrates high accuracy, achieving an R2 of up to 0.77, matching or surpassing state-of-the-art models like RNNs and Transformers. Additionally, it provides interpretable and physical consistent outputs, supporting industry, policymakers, and farmers in adapting to extreme weather conditions.

Leo Prieto's passion for nature started during his childhood by the sea. "I was obsessed with what was under the surface. I'd anchor myself to a rock with my snorkel, and I was fascinated by all the little animals doing things that go unnoticed." His teenage years coincided with the arrival of the internet in Chile, where he became a web pioneer, launching and selling several startups. Inevitably, his interests in the environment, the internet and business merged, driven by the feeling that technological advances should not be wasted.

Water scarcity – an increasingly important topic of conversation as countries across the Middle and East and Africa grapple with rising concerns around future water shortages, which not surprisingly often results in civil unrest. Currently the Middle East and North Africa is the most water-scarce region in the world, according to the United Nations. With at least 17 countries well below the water line, water is being consumed faster than it can be replenished. Only a year ago, the City of Cape Town was in the headlines with a forecasted Day Zero where the city's taps would be turned off in order to preserve the remaining water supply (13.5% of normal) for critical services. Fortunately, the city avoided Day Zero through a combination of water saving measures and well-timed rain.

Important resources like minerals, oil and diamonds often go hand-in-hand with conflict and poor governance. But when it comes to one particular resource -- the most important resource of all -- many think a different theory will hold true. Often referred to as the water wars thesis, it suggests that growing water scarcity will drive violent conflict as access to water dries up for certain communities. Analysts worry that people, opportunistic politicians and powerful corporations will battle for dwindling water supply, inflaming tensions. In a new study, researchers tried to map out how water wars will emerge around the world and which countries are most likely to see water-related conflict in the coming decades.