Mathematica Neural networks in Wolfram Mathematica

AI Thread Summary
Wolfram Mathematica can be utilized to create neural networks for scientific research applications, extending beyond basic tasks like digit recognition. Users are exploring its potential for solving complex mathematical and physical problems, such as differential equations related to Einstein's relativity. While some view Mathematica's neural network capabilities as limited, others argue that they can contribute to meaningful discoveries and scientific papers. The discussion highlights ongoing efforts in physics-informed machine learning as a promising area for AI applications. Overall, Mathematica's efficiency in handling neural networks for serious research is still being evaluated.
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Is it reasonable to do specific neural networks in WM?
Hello,
I have a question about the use of functions and overall creation of neural networks in the Wolfram Mathematica (WM) program. I wonder if it is realistic to make meaningful neural networks usable at least partially for scientific research in WM? By scientific research, I do not mean the study of neural networks directly, but their application to some specific mathematical or physical problems. Something like using NDSolve to solve the differential equations of e.g. Einstein's relativity, which may in turn lead to a new discovery or in general to the preparation of a scientific paper.

Or is it just a toy or a teaching aid for very specific tasks such as converting handwritten digits to digital digits shown in the WM tutorial?

Thank you for your opinions.
 
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