Track and reduce CO2 emissions from your computing
AI can benefit society in many ways but, given the energy needed to support the computing behind AI, these benefits can come at a high environmental price.
CodeCarbon is a lightweight software package that seamlessly integrates into your Python codebase. It estimates the amount of carbon dioxide (CO2) produced by the cloud or personal computing resources used to execute the code.
It then shows developers how they can lessen emissions by optimizing their code or by hosting their cloud infrastructure in geographical regions that use renewable energy sources
Calling out: Read more on Medium
A single datacenter can consume large amounts of energy to run computing code. An innovative new tracking tool is designed to measure the climate impact of artificial intelligence.
Kadan Lottick, Silvia Susai, Sorelle Friedler, and Jonathan Wilson. Energy Usage Reports: Environmental awareness as part of algorithmic accountability. NeurIPS Workshop on Tackling Climate Change with Machine Learning, 2019. https://arxiv.org/abs/1911.08354
Dashboard
Visualizing the outputs & insights
Call for action
Use CodeCarbon, Contribute to its development, and spread the word!
We look forward to developers and researchers using the tool and sharing their feedback
We look forward to developers contributing to CodeCarbon development
We also encourage you to spread the word about CodeCarbon among your colleagues and peers in conferences, on social media platforms, and developer forums
