Wednesday, October 6, 2021

g-f(2)544 THE BIG PICTURE OF THE DIGITAL AGE (10/6/2021), MIT Technology Review, DeepMind’s AI predicts almost exactly when and where it’s going to rain




ULTRA-condensed knowledge


"g-f" fishing of golden knowledge (GK) of the fabulous treasure of the digital ageArtificial Intelligence, Hard science problems (10/6/2021)  g-f(2)426 


Opportunity 

First protein folding, now weather forecasting: London-based AI firm DeepMind is continuing its run applying deep learning to hard science problems, MIT Technology Review



    • The firm worked with UK weather forecasters to create a model that was better at making short term predictions than existing systems.
    • In a blind comparison with existing tools, several dozen experts judged DGMR’s forecasts to be the best across a range of factors—including its predictions of the location, extent, movement, and intensity of the rain—89% of the time. The results were published in a Nature paper.
    • Forecasting rain, especially heavy rain, is crucial for a lot of industries, from outdoor events to aviation to emergency services. But doing it well is hard.


                  Genioux knowledge fact condensed as an image




                  References





                  Extra-condensed knowledge


                  Lessons learned 

                  The best existing forecasting techniques use massive computer simulations of atmospheric physics, MIT Technology Review


                    • These work well for longer-term forecasting but are less good at predicting what’s going to happen in the next hour or so, known as nowcasting. Previous deep-learning techniques have been developed, but these typically do well at one thing, such as predicting location, at the expense of something else, such as predicting intensity.
                    • The DeepMind team trained their AI on radar data. Many countries release frequent snapshots throughout the day of radar measurements that track the formation and movement of clouds. 



                    Condensed knowledge




                    Opportunity 

                    The biggest takeaway here is that DeepMind is finally starting to tick off a bucket list of real-world science problems, MIT Technology Review



                    • To test the approach, the team asked 56 weather forecasters at the Met Office (who were not otherwise involved in the work) to rate DGMR in a blind comparison with forecasts made by a state-of-the-art physics simulation and a rival deep-learning tool; 89% said that they preferred the results given by DGMR.
                    • DeepMind’s collaboration with the Met Office is a good example of AI development done in collaboration with the end user, something that seems like an obviously good idea but often does not happen


                    Some relevant characteristics of this "genioux fact"

                    • Category 2: The Big Picture of the Digital Age
                    • [genioux fact deduced or extracted from geniouxfacts]
                    • This is a “genioux fact fast solution.”
                    • Tag Opportunities those travelling at high speed on GKPath
                    • Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).
                    • Type of validity of the "genioux fact". 

                      • Inherited from sources + Supported by the knowledge of one or more experts.


                    References


                    “genioux facts”: The online programme on MASTERING “THE BIG PICTURE OF THE DIGITAL AGE”, g-f(2)544, Fernando Machuca, October 6, 2021, blog.geniouxfacts.comgeniouxfacts.comGenioux.com Corporation.


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                    PhD with awarded honors in computer science in France

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