Machine learning research is focusing less on the practical aspect of the field.The woeful reality is that most of the machine learning research is based around novel discovery of architectures or techniques where as lot's of novel application based works are being sidelined in big conferences like NeurIPS. Reviewers are even disappointed to see the word "application" in the papers. It would be much better if applied research to solve real life problems related to health, medicine, agriculture, environment, design and other scientific aspects were much appreciated and focused. What do you guise think about this aspect? Should applications of this revolutionary field be more appreciated and focused upon or should all the focus be on the core structures? Let me know in the discussion section ✌️
Check out the article for more details.: https://www.technologyreview.com/2020/08/18/1007196/ai-research-machine-learning-applications-problems-opinion/
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Machine learning Is widely used in all spheres of life for example people tracker, image classification, face detection. Many scientific resources say about it. I've read there it-jim.com/expertise/machine-learn...