AI Is Thirsty

Today I used ChatGPT to get some help making a browser plugin. I posted my queries, then watched as the code and text spilled down the screen. This is the part of large language-models that I dig! As a hobbyist developer, getting suggestions of customized lines of software can be a powerful way to learn. But as it turns out, using ChatGPT consumes a lot of an unexpected resource: Water. The code wasn’t quite what I was looking for, so I chatted with ChatGPT for 15 minutes or so, slowly coaxing it to revise. By the time I was done, we’d gone back and forth about 20 times. And during that exchange? Microsoft’s servers probably used about as much water as if I’d just bought a half-liter bottle … and spilled it on the ground. AI, it turns out, is incredibly thirsty tech — ploughing through torrents of fresh water every day. Given that we’re likely to see large-language-model AI woven into ever more apps and appliances these days, it’s worth pondering just how much water our booming use of AI will consume. Why precisely does large-language-model AI require water? Back in April, <a href="https://arxiv.org/abs/2304.03271" rel="noopener ugc nofollow" target="_blank">a group of researchers pondered this question as they created an estimate of AI’s water consumption. </a>As they note in <a href="https://arxiv.org/abs/2304.03271" rel="noopener ugc nofollow" target="_blank">their paper (which is here free in full</a>), the main use of water is when tech firms train their AI, and when the firms are running inferences (i.e. when you, I or anyone else interacts with the model). <a href="https://clivethompson.medium.com/ai-is-thirsty-37f99f24a26e">Read More</a>