Machine learning and artificial intelligence to improve scientific research 

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Most scientists come up with mathematical models that could be used to simulate physics. It was rightly said by George Box that “all models are wrong but some are useful”. A mathematical model is mostly based on considering a few conditions that make up the physical process and gives us results to some degree of accuracy given a number of controlled physical parameters or conditions.

The advent of machine learning and artificial intelligence is going to change the method of mathematical modeling, making it obsolete. The method of modeling of future will involve computational models which are generated in real-time, considering all the physical parameters associated with a physical process. The results: a complex computational model which is being updated in real-time, which can be used to predict with much accuracy the results we are looking for.

This method will not only put an end to multiple models with limited capability but also to ambiguity, bias and limitations of current models. The newer computation models will not be limited to a given condition but can be used in every condition.