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Hm... what happens if you've got a neural network trained to make decisions in the financial domain?

Is there a way to exploit the difference between numeric precision underlying the neural network and the precision used to represent the financial transactions?






Neural networks are by their very nature a bit vague, random and unpredictable. Their output is not suitable as a direct, real monetary value you can rely on. At best, they predict trends, approximations or classifications.



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