Green AI: towards an ecologically viable machine learning

The Green AI project’s main goal is to conceive a systemic and multi-component approach to the problem of the Artificial Intelligence’s ecological impact. Thus, it focuses on cloud and mobile computing, transfer learning, model reuse, active learning and evolutionary computing, among others.

The project was born in 2019 from an initiative of Inria Chile in partnership with PUC-Rio  and has received a 1st funding in the framework of the CLIMAT AmSud program as a project-test. A Green AI work meeting took place at PUC-Rio in March 2020 and was an opportunity to associate LNCC researchers.

The project was then presented at the GECCO 2020 Workshop of July 8th 2020 by Nayat Sanchez-Pi and Luis Marti from Inria Chile, with the participation of Mariza Ferro from LNCC, Estaban Clua from the Universidade Federale Fluminense and Romain Rouvoy from the Université de Lille and Inria- SPIRALS team.

Researchers from LNCC under the coordination of Mariza Ferro joined the project, as well as researchers from other countries CMM (Centro de Modelamento Matematico de Chile), Universidad de la Republica (Uruguay) and Universidad de Asuncion (Paraguay).

The new version of the project was selected at the end of the 1st Call for projects CLIMAT AmSud program and will receive fundings from Inria, the ANID and Conacyt. Brazilian CAPES does not take part of the CLIMAT AmSud program at the moment of the 1st call.

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