Mastodawn

Dr Sasha Luccioni, the researcher behind #CodeCarbon and much more, is giving a seriously insightful talk about the impact of AI on the environment, economy and society c/o #AlanTuringInstitute
https://youtube.com/live/IVa98vXorgg?is=D69DmKrp3NxWzyyL

The Turing Lectures: Making AI (truly) sustainable - from environmental costs to social impacts

YouTube

Dmian 🇪🇺May 24

I'm getting tired of Ecosia's shenanigans. On one side, the site doesn't honor settings. I always set it for worldwide results in English (I'm in Spain), and it ends up reverting to results from Spain in Spanish. 😒🤷‍♂️
On the other hand, they're embedding AI everywhere (like a button in type of content). Really, it's a contradictory message. Use #EcoLogits, use #CodeCarbon, show me your AI prompts use less resources than a normal search and I'll believe you. Until then, please stop. #Ecosia

Alexis Perrier Oct 1, 2025

You can track your carbon footprint when training #ML models or running any other type of #python code with #codecarbon

https://github.com/mlco2/codecarbon

Here is a really good tutorial on Colab

How to Track Emissions when Training Machine Learning Models

https://colab.research.google.com/github/climatechange-ai-tutorials/tracking-ml-emissions/blob/main/Tracking_Emissions_from_ML_Models_(Revised).ipynb

GitHub - mlco2/codecarbon: Track emissions from Compute and recommend ways to reduce their impact on the environment.

Track emissions from Compute and recommend ways to reduce their impact on the environment. - mlco2/codecarbon

GitHub

Dan Stowell Jul 31, 2024

Measuring the CO2 footprint of an AI model http://mcld.co.uk/blog/2024/measuring-the-co2-footprint-of-an-ai-model.html #ai #carbonfootprint #codecarbon

The Turing Lectures: Making AI (truly) sustainable - from environmental costs to social impacts

GitHub - mlco2/codecarbon: Track emissions from Compute and recommend ways to reduce their impact on the environment.

Measuring the CO2 footprint of an AI model :: mcld.co.uk blog