NAMRATA-WOKE
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1 year ago Helpful recent articles:
To quench AI's thirst, the way we build, operate datacenters needs to change: Depending on how and where the datacenter is built and whether the servers are air or liquid cooled, the amount of water used can vary wildly.
AI Chatbots Guzzle Enormous Amounts of Water, Study Finds: Researchers find that training ChatGPT consumed at least 700,000 litres of water, and the average conversation is equivalent to spilling a 500ml bottle.
The Mounting Human and Environmental Costs of Generative AI: Dr. Sasha Luccioni, Researcher and Climate Lead at Hugging Face delves into the downsides of AI, including the environmental toll of mining rare minerals.
Making AI Less “Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI Models: A new paper from University of Colorado Riverside and University of Texas Arlington attempts to estimate a water consumption figure for AI chat models such as Google Bard and ChatGPT.
Report on ChatGPT Model’s Emissions Offers Rare Glimpse of AI’s Climate Impacts: A new report by Stanford University researchers finds that training the model behind ChatGPT released emissions equivalent to that of 9 cars over the course of their lifetimes. If AI is scaled up, the resulting carbon footprint could rival that of cryptocurrencies.
This is the AI balancing act: between its huge potential and growing emissions: Louis-David Benyayer, Affiliate Professor at ESCP Business School on how we balance AI's potential and its environmental impact.
- more from newsletters between Jan-April.
adamj89
Some of the questions at the SOGS live event were centered around water use; there seems to be interest in this topic.
What is the water footprint of AI? Is the GSF looking into this? Decarbonization alone cannot make software green | State of Green Software
Can the cooling water for data centers be reused?