...as is everything in life...garbage in...garbage out.
not sure what you mean with "I don't understand how you can continue to argue that the input data doesn't matter while using AlphaGo or image recognition as your examples.. in those cases the input data PERFECTLY PREDICT the outcomes."
Do you know that the algorithms behind GO attempt to accomplish one of the most complex tasks human kind has ever tried to accomplish software to simulate? Next, I
never claimed the input data are not relevant. Please read again what I said.
And your other comments are utter nonsense. Here is why:
You say "If you are given all or most of the pixels of an image, you have been given all the relevant information needed to predict what the image is."
-> That is completely incorrect. So when you feed in an image, how do you expect your algorithm to know that the image is a cat, or car? How do you train your algorithm to recognize whether an image of a handwritten note is written by a woman or a man? When you give the computer an image then it knows
nothing about the image. When you feed in millions or billions of images the machine still knows nothing. Only when you design a clever algorithm that starts building associations is when a machine starts to understand what each image might be or the differences between images necessary in order to classify different images.
You say "The moves made during a game of Go is the only factor determining the outcome of the game!"
-> Again, full blown nonsense. All past data fed into the machine is also used to help the machine to make a next move. The relationship between Google GO making decisions and the data that was fed into the system is incredibly, mind staggering complex and took
YEARS to develop. All past data also determine the next move the machine makes NOT only the moves made during the game.
You say "The input data in these cases were the perfect input data, the only input data needed to solve the problem. "
-> Also incorrect, you could potentially only feed 1/3 or 1/2 of the available data into the machine and it most likely would still make amazing and strong moves. Of course the more data made available the better given the computational power is there to support such data processing.
You say "The application to markets is much more complex. There is no clear-cut objective, and the actual underlying forces that drive them are not directly observable."
-> The only thing in your whole post that is correct is that markets are more complex. Yes they are. Thank you for reveling something we did not know before.
However your subsequent statement again is incorrect:"There is no clear-cut objective, and the actual underlying forces that drive them are not directly observable. "
-> The objective is absolutely and perfectly clear: "Make predictions about future market moves", or, "classify whether the next 1 hour price series more likely exhibit trending or mean reverting tendencies". The underlying forces that drive markets are PERFECTLY observable, they are just not available in their entirety. Hence the name of the game is PREDICTION. What surprises you here?
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And RandomWalker, to be honest, this has nothing to do with whether your IQ is higher or lower. You could have spent 30 minutes (by the way you can still do that) reading some informative intro into this subject and you would have spared embarrassing yourself. But coming out and making false over false over false statement does indeed make you look a little stupid or at least highly uninformed.
I don't understand how you can continue to argue that the input data doesn't matter while using AlphaGo or image recognition as your examples.. in those cases the input data PERFECTLY PREDICT the outcomes.
