A neural network is a kind of computer program with millions of possible configurations. Only some of those configurations will get the program to do what you want (like drive a car). But there’s no way of knowing what the right configurations are. So, when a neural net “learns” to drive a car, what it’s actually doing is trying out lots of possible configurations to see if they help it to drive a car. It starts by trying them at random, which doesn’t help at all. By pure chance, it will try something that does actually help, a little bit. So it keeps what worked, and continues trying out different things. By trial and error, it works out the right configuration to drive a car.
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