This video belongs to the openHPI course clean-IT: Towards Sustainable Digital Technologies. Do you want to see more?
An error occurred while loading the video player, or it takes a long time to initialize. You can try clearing your browser cache. Please try again later and contact the helpdesk if the problem persists.
To enable the transcript, please select a language in the video player settings menu.
About this video
Read a blog-post version of this openXchange live talk here on Medium!
Machine Learning and Artificial Intelligence require immense amounts of computing resources to develop, train, and test the models. While they can be used in many ways to save CO2-emissions, the resulting energy consumption can not be neglected. In order for customers to assess and optimize their energy usage during the development of ML models, Krallmann AG has developed a Carbon Monitor for Machine Learning (CMML), which is presented in this openXchange live talk.
Tibebu Biru works as a Data Scientist at the Krallmann AG. He began his career at the Jacobs University in Bremen, where he achieved his Bachelor’s degree in Electrical and Computer Engineering. Afterward, he received a Master’s degree from the Johannes Kepler University in Linz in Informatics. In 2020, Tibebu Biru started working at the Krallmann AG. Among other things, he helped develop the “Carbon Monitor for machine Learning”, which he will be presenting today.