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research.google | ||
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deepmind.google
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| | | | | This has been a year of incredible progress in the field of Artificial Intelligence (AI) research and its practical applications. | |
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niklasriewald.com
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| | | | | Is it possible to replace numerical weather prediction with deep learning? Certainly not yet. But first work is being done to investigate this question. In this post I want to discuss a paper called "MetNet: A Neural Weather Model for Precipitation Forecasting" that Google Research published back in March 2020 and in which they try... | |
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blog.research.google
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| | | | | [AI summary] Google Research introduces MetNet-2, a deep learning model that enhances 12-hour precipitation forecasting with improved accuracy and efficiency compared to traditional physics-based methods. | |
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www.paepper.com
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| | | When you have a big data set and a complicated machine learning problem, chances are that training your model takes a couple of days even on a modern GPU. However, it is well-known that the cycle of having a new idea, implementing it and then verifying it should be as quick as possible. This is to ensure that you can efficiently test out new ideas. If you need to wait for a whole week for your training run, this becomes very inefficient. | ||
