Upcoming seminars and events

October, 3rd 2022, Meeting with Odyssee agency to discuss about Green AI for the ecological shift of the territory.

• October, 4th 2022 - Samuel Rincé . Calculating the multi-criteria impacts of the manufacture and use of digital equipment, servers, and the cloud.

Abstract: Boavizta is an association dedicated to the development of methodologies, tools, and datasets that facilitate the measurement of the multi-criteria environmental impact of digital equipment. Boavizta's work is open source and state-of-the-art in terms of life cycle assessment. The group has about 100 members involved in about 15 projects. The presentation will start with the mission of Boavizta and the importance of the different works carried out within the association. We will talk in particular about two tools developed internally and open source. Datavizta is a website for visualizing carbon impact data provided by manufacturers. Boaviztapi is a multi-criteria impact calculation API for servers, cloud instances, or electronic components (CPU, RAM, etc.). We will also present the bottom-up calculation method of the API.

• October, 10th 2022 - Nicolas Tirel. Advances in ASR for schoolchildren

Abstract: During the previous seminar, we presented an ASR for children in a classroom context to learn mathematics using their voices. We used at this time DeepSpeech, an open-source implementation developed by Mozilla and inspired by the Silicon Valley AI Lab, with a result of 18% in WER. Since that, we have changed DeepSpeech to Coqui STT, adapt the corpus with a more realistic one and designed a specific language model to get even better results. The following seminar will go through our journey, with a more spontaneous dataset and a lighter model.

• October, 17th 2022 - Simon Lebeaud, team member . A review of state of the art tracking and object detection

Abstract:

Click here to the past seminars and events !

Reading group

Our reading group meets quaterly and provides foundations and up-to-date information on topics in power-efficient deep learning, mathematical statistics and optimization. We give participants valuable experience in leading group discussions and share state-of-the-art machine learning. For each session, papers are assigned in advance, and one to two participant guide the discussion.

Click here to the previous reading group !