my opinion is that AI is very good at deterministic modeling - those things where inputs and outputs are governed by certain relationships that can be modeled (even mildly chaotic relationships). These could include things like weather forecasting, medical diagnosis (robotic doctors/surgeons), software that could replace accountants+lawyers, self driving cars, etc.
But the financial markets are something else altogether - they do not follow any physical or natural laws. Daily price movements are governed by factors that are at least an order of magnitude more complex and discontinuous than any other system we know of. I don't think there will ever be an AI program that will achieve 100% accuracy in predicting market price direction one day in advance. If such a program came about in the future, there eventually would be multiple players competing for the same profits, thereby reducing the forecast efficacy.
Take a look at Bayesian Machine Learning. In a nut shell, really good machine learning algorithms take into account the fact that nothing can be predicted with certainty, but we can provide a best guess, and an estimate what the uncertainy surrounding that estimate is. Sort of like how the Kalman Filter estimates the mean and covariance of a stochastic process.
I use machine learning for my real time trading system, and in no way do I expect it to 100% accurate. I just expect it do be able enter trades where the expectation is positive (i.e over a large number of trades, I expect to be profitable) and the variance on that expectation is withing my risk managment tolerances. Even if I expect it to be positive, I don't expect it to work on its own on any market.... there is a lot of human touch required to tune these algorithms. And the algorithm doesn't find the opportunity on its own, the human has to show it the way.
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