Green NLP - controlling the carbon footprint in sustainable language technology

Bidragets beskrivning

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.
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Startår

2023

Slutår

2025

Beviljade finansiering

Filip Ginter Orcid -palvelun logo
318 971 €



Rollen i Finlands Akademis konsortium

Övriga parter i konsortiet

Leader
Helsingfors universitet (353164)
334 233 €
Partner
CSC – IT Center for Science (353166)
273 519 €

Finansiär

Finlands Akademi

Typ av finansiering

Akademiprojekt med särskild inriktning

Övriga uppgifter

Finansieringsbeslutets nummer

353167

Vetenskapsområden

Data- och informationsvetenskap

Forskningsområden

Tietojenkäsittelytieteet

Identifierade teman

green transition, sustainable development