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Artificial intelligence can predict rain with unprecedented accuracy

DeepMind has developed an artificial intelligence system that is capable of forecasting the weather with remarkable precision. The company, which specializes in developing artificial intelligence for problem solving, has now decided to include meteorology as an important field of action in its portfolio.

Using satellites and a collection of data, such as wind direction and strength, meteorologists can predict whether or not a fallout will occur in a given area before it actually occurs. Weather measurements are taken up to two hours in advance when there is a chance of rain, to ensure that outdoor events, civil aviation, and emergency response actions can be carried out as planned in the event of a storm.

DeepMind's model makes use of the most recent minutes in order to design the upcoming ones 89. 

Even though current models are effective at accurately forecasting low-intensity rains, their operational usefulness is limited because they produce blurry images after lengthy waiting periods, which results in reduced performance when medium or heavy rain is encountered. DeepMind's technology, on the other hand, allows for significantly more accurate forecasting.

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Because of the association of data collected by high-precision radars, it is possible to carry out the measurement every five minutes in a radius of one kilometer with the help of precipitation anticipation algorithms and high-precision radars. The artificial intelligence can predict rain up to 89 minutes in advance thanks to generative modeling, which observes 20 current minutes and projects the future.

According to academics, the system has been approved for use by more expert meteorologists in the United Kingdom because of its accuracy and usefulness, with a hit rate that is 89 percent higher than that of alternative methods. A report on the findings, written in collaboration with the Met Office, and published in the scientific journal Nature condensed the findings into a single article.

Radar rainfall forecasting, according to the company, has never been done before because of the statistical, economic, and cognitive analysis that went into developing the approach. Despite the fact that this was a remarkable achievement, the researchers acknowledge that more work needs to be done in order to improve the accuracy of long-term predictions as well as predictions for rare and intense events. "Future work will necessitate the development of additional methods for assessing performance as well as the specialization of even greater degrees for specific real-world applications," the researchers explained.

DeepMind does not intend to commercialize the technology; however, the company believes that taking this step will assist other researchers in developing improved versions of artificial intelligence that incorporate new data and verification techniques. The fact is that this is a beautiful example of how machine learning and algorithms can assist environmental scientists in solving problems, as well as in foreseeing events that are caused by climate change.


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