University of Helsinki
The Academy of Finland decided to fund our project proposal on “Green NLP – controlling the carbon footprint in sustainable language technology” from the call on sustainable and energy-efficient ICT solutions. We are looking forward to three years of exciting research and work together with our colleagues from TurkuNLP and CSC.
GreenNLP addresses the problem of increasing energy consumption caused by modern solutions in natural language processing (NLP). Neural language models and machine translation require heavy computations to train and their size is constantly growing, which makes them expensive to deploy and run. In our project we will reduce the training costs and model sizes by clever optimizations of the underlying machine learning algorithms with techniques that make use of knowledge transfer and compression. Furthermore, we will focus on multilingual solutions that can serve many languages in a single model reducing the number of actively running systems. Finally, we will also openly document and freely distribute all our results to enable efficient reuse of ready-made components to further decrease the carbon footprint of modern language technology.
Raul Vazquez from the Fotran team 