eli5: How do you design a deep learning algorithm?
In: Technology
The basic idea with machine learning is that you tell the computer the “rules” of the game (for game, read whatever problem you’re trying to solve – possibly an actual game), give it some way to score its performance, then let it play using random behaviour thousands of times. If it does well, it gets a reward that encourages that play in the future. If it does poorly, it gets some kind of punishment that makes it less likely to do that again.
One example of this I like is the Matchbox computer, [Menace](https://www.youtube.com/watch?v=R9c-_neaxeU), that can learn to play noughts and crosses (tic-tac-toe). You colour the 9 squares on a grid. Then, you need a box for each possible configuration of the grid. In each box, you out a bunch of beads of the colours which are possible moves from that point. To start a game, you pick the first box, shake it, take out a random bead, then go in that square. Then the opponent makes their move. Then you find the next relevant box, shake it, take out a bead, make that move, and continue. Eventually, if the computer wins, you reinforce the behaviour by adding more beads of those colours to the boxes you used. If it loses, you take out those beads. Gradually, over a lot of time, the machine is more likely to pick the moves that have been successful in the past.
Another approach might be to have two systems battling against each other. This is how some of the Deepfake software works. One machine is trying to generate pictures of a person, and another is trying to work out which picture is real and which is generated. If the guesser gets it right, it wins. If not, the generator wins. Whichever wins gets a “reward” that makes it more likely to do something similar. Repeat for a long time and you have one machine that’s really good at making pictures of faces and another that’s good at spotting fakes.
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