This isn’t an accurate explanation, but it should convey the principle of how machine learning works.
Basically, a computer takes a huge amount of samples of art, and generates something new more or less completely at random, either from scratch, or by actually sampling bits of the original dataset.
It’ll then see which if the random products came closest to matching the data, and pick the next seed for it’s random number generator to be close to the most successful one it’s used so far.
It repeats this process millions upon millions of time, each time creating a random number generator weighted slightly closer to matching it’s dataset.
Now you take this principle, and you pair it with some PhD level mathematics in order to optimize the process, pick the right random number generators, evaluate the datasets and stuff like that, and eventually you get something that will coincide close ebough to what you want it to do.
It’s not so much an AI as it is a big pile of data calculus and statistics, that barfs out very carefully filtered and weighted nonsense, such that it comes close enough to what you want it to do, often very effectively.
Latest Answers