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'ChatGPT needs a 500ml bottle of water to answer 20-50 questions': Survey

There is a significant water footprint of artificial intelligence models requiring environmentally sustainable practices in AI development and deployment.

Published on: May 18, 2023 05:34 PM IST
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Artificial Intelligence (AI) has shown great progress, but a recent study highlights the significant water consumption of AI models in data centres making it an environmental concern. The study uncovers the environmental cost of training and deploying large AI models, emphasizing the need for sustainable practices.

The Thirsty Reality of AI Models:

ChatGPT like AI models training are questioned to be harmful for environment. (REUTERS)
ChatGPT like AI models training are questioned to be harmful for environment. (REUTERS)

Large AI models like GPT-3 and GPT-4 have a hidden water footprint. Training GPT-3 in Microsoft's US data centres can consume up to 700,000 liters of fresh water, equivalent to producing hundreds of cars. ChatGPT, for a simple conversation, "drinks" a 500ml bottle of water, considering its billions of users.

(We asked OpenAI CEO Sam Altman about this. Read here: 'Met PM Modi; discussed AI disadvantage, regulation,' says ChatGPT's Sam Altman)

Data Centres' Water Consumption:

Data centres, where AI models reside, are energy-intensive and water-thirsty. Google's US data centres alone consumed 12.7 billion liters of freshwater for cooling in 2021. These centres rely on water-intensive cooling systems and require significant amounts of water for power generation.

Why Are AI Models Water Intensive?

The study suggests training AI models during cooler hours to reduce water loss through evaporation. It calls for the industry to develop environmentally friendly AI models. Uncovering and addressing the water footprint of AI models is crucial, considering freshwater scarcity and aging water infrastructure.

Environmental Considerations:

As we explore the potential of AI and models like ChatGPT, it is vital to be mindful of their environmental impact. With freshwater scarcity and droughts increasing, sustainable practices are essential. Addressing the hidden water footprint of AI models is crucial for a sustainable future.

 
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