Trying to understand Deep Learning but all the resources I’m finding are like: “and inside this black box is where the magic little goblin twists his dials and out comes your probability!”
Ugh.
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We don’t know. That’s what a black box is, ultimately. It’s a box where you insert data, and it outputs responses, based on processes you don’t or can’t fully understand.
In practice, neural networks are nightmarishly complicated nests of feedback loops. We can’t understand them because they don’t do anything we can recognize with the inputs, for all that the outputs are generally usable. They work kinda the same way our own brains do, where you can go from getting a stream of electrochemical inputs coming down the optic nerves, to thinking, “I am going to pet that cat,” with zero conscious steps occurring between those two events. The brain did a lot of *stuff* and output a desire to pet the cat.
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