San Francisco: Training artificial intelligence (AI) models like GPT-3 in data centres can directly consume 7,00,000 litres of clean fresh water (enough for producing 370 BMW cars or 320 Tesla electric vehicles), a new study has shown.
According to the ‘Making AI less Thirsty’ research paper, many AI models are trained and deployed on power-hungry servers housed inside warehouse-scale data centres, which are often known as energy hogs and millions of litres of clean freshwater consumed for generating electricity to power data centre servers and for cooling these servers.
Cooling those data centres also makes the AI chatbots incredibly thirsty.
According to the authors, the volume of fresh, clear water necessary to train GPT-3 is equal to the amount of water needed to fill the cooling tower of a nuclear reactor.
Moreover, OpenAI has not provided information regarding the duration needed to train GPT-3, which has made it challenging for the researchers to estimate, according to Gizmodo.
However, Microsoft, which has partnered with the AI startup and built supercomputers for AI training, claims that its latest supercomputer, which would require extensive cooling, contains 10,000 graphics cards and over 285,000 processor cores, providing a glimpse into the vast scale of the operation behind artificial intelligence.
The researchers further explained that ChatGPT needs to ‘drink’ a 500 ml bottle of water for a simple conversation of roughly 20-50 questions and answers, depending on when and where ChatGPT is deployed.
“While a 500 ml bottle of water might not seem too much, the total combined water footprint for inference is still extremely large, considering ChatGPT’s billions of users,” the researchers said.
Further, the researchers stated that by using a principled methodology to estimate the fine-grained water footprint, they concretely showed that AI models such as Google’s LaMDA can consume a stunning amount of water in the order of millions of litres.
(IANS)
