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 The Norwegian Meteorological Institute develops short range sea ice information with two goals. 
 Firstly, short range sea ice products provide valuable information for Arctic navigators. 
 Secondly, sea ice is essential to force numerical weather prediction systems at high latitudes. 
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 This presentation will explore both sea ice goals of the Norwegian Meteorological Institute under the framing of recent achievements in machine learning developments for sea ice forecasting. 
 We show that deep learning sea ice concentration prediction systems are able to outperform baseline and physical forecasts. 
 Additionally, we highlight the importance of supplying numerical weather prediction systems with reliable, up to date, sea ice information.