Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model This article co-authored by Alexandra Sasha Luccioni, Sylvain Viguier, and Anne-Laure Ligozat estimates that BLOOM, a Large Language Model, with 176 billion parameters, emits 24.7 tonnes of CO2 during a single training. Abstract: Progress in machine learning (ML) comes with a cost to the […]
Deep Learning has a Terrible Carbon Footprint Dr. Joy Buolamwini writes on her LinkedIn post: I’ve been thinking about the hope expressed that AI can help mitigate climate change. Yes, AI can be used to find more efficient ways to use energy. DeepMind proved itself useful to Google in 2016 by reducing data center cooling […]
ChatGPT’s Electricity Consumption Kaspar Groes Albin Ludvigsen estimates that ChatGPT may have consumed as much electricity as 175’000 people. He writes: Estimating ChatGPT’s electricity consumption, on the other hand, is in principle simpler, because we do not need to know in which geographic regions ChatGPT is running. Below I explain how one can go about […]
EU Parliament Votes to Require Companies to Introduce Climate Transition Plans Mark Segal reports for esgtoday.com on June 1, 2023: Lawmakers in the European Parliament voted 366-225 on Thursday on new rules requiring companies to identify and address the impact of their activities and value chains on human rights and the environment, as well as […]
As the AI industry booms, what toll will it take on the environment? Maanvi Singh analyzes the hidden energy and environmental costs of training, maintaining and deploying complex and large AI algorithms for The Guardian. To read the full article, please click on this link.
What’s the Environmental Impact of Generative AI Tools? By Jason Nelson for decrypt.co In this article published in decrypt.co, Jason Nelson examines the environmental impact of training and deploying generative AI models such as ChatGPT. Please click on this link to read the article in full.
Easily measure the carbon footprint of emails, streaming or video conferencing & compare the impact of these uses with that of building your devices. Please click on this link to measure the carbon footprint of your digital use.
Please consider submitting your work to the Special Issue on “AI & Big Data Analytics for Emergency Preparedness and Responses Systems”. The deadline for submission is 15 December 2022. For more information, please refer to the call for papers here.