Here's a sobering look at the environmental footprint of AI infrastructure. The water consumption for training and running large language models this year has matched what the entire bottled water industry uses annually. Meanwhile, the carbon emissions generated are stacking up to levels comparable to a major metropolitan area like New York City. This raises serious questions about the true cost of scaling AI systems and whether we're accounting for these environmental trade-offs in our push toward automation.