4 citations · 5 across the 7 of their papers we have counts for
8 papers
The Rising Unsustainability of AI Graphics Cards Production
Clément Morand, Aurélie Névéol, Anne-Laure Ligozat
The rapid advancement of Artificial Intelligence (AI) has been accompanied by significant increases in computational and environmental costs, driven by large-scale investments in A…
Environmental Footprint of GenAI Research: Insights from the Moshi Foundation Model
Marta López-Rauhut, Loic Landrieu, Mathieu Aubry +1
New multi-modal large language models (MLLMs) are continuously being trained and deployed, following rapid development cycles. This generative AI frenzy is driving steady increases…
Is Knowledge Distillation Actually Greener? A Case Study in Machine Translation
Joseph Attieh, Timothee Mickus, Anne-Laure Ligozat +2
Knowledge distillation (KD) is a technique to compress a larger teacher system into a smaller student. In machine translation, KD is commonly evaluated through translation quality…
The Environmental Impacts of Language Model Training Keep Rising Now is the Time to Catch Impacts on the Rebound
Clément Morand, Anne-Laure Ligozat, Aurélie Névéol
Recent Machine Learning (ML) approaches have shown increased performance on benchmarks at the cost of escalating compute demands. Hardware, algorithmic and carbon optimizations hav…
How Green Can AI Be? A Study of Trends in Machine Learning Environmental Impacts
Clément Morand, Anne-Laure Ligozat, Aurélie Névéol
The compute requirements associated with training Artificial Intelligence (AI) models have increased exponentially over time. Optimisation strategies aim to reduce the energy consu…
Estimating The Carbon Footprint Of Digital Agriculture Deployment: A Parametric Bottom-Up Modelling Approach
Pierre La Rocca, Gaël Guennebaud, Aurélie Bugeau +1
Digitalization appears as a lever to enhance agriculture sustainability. However, existing works on digital agriculture's own sustainability remain scarce, disregarding the environ…
Coca4ai: checking energy behaviors on AI data centers
Paul Gay, Éric Bilinski, Anne-Laure Ligozat
Monitoring energy behaviors in AI data centers is crucial, both to reduce their energy consumption and to raise awareness among their users which are key actors in the AI field. Th…
How digital will the future be? Analysis of prospective scenarios
Aurélie Bugeau, Anne-Laure Ligozat
With the climate change context, many prospective studies, generally encompassing all areas of society, imagine possible futures to expand the range of options. The role of digital…