How good are you at Super Mario World? Chances are, you’re not as good as a neural network and genetic algorithms.
MarI/O may be just that, and it’s really good at Super Mario World. In the video above, you’ll see MarI/O beating a level of the game with ease, and a quick explainer on what made it so efficient (I won’t say ‘good’ because it left a lot of points on the board).
Creator Seth Bling has published the source code for his efforts so you can try it yourself. Seth tells us he’s got a degree in Computer Science, and has always been interested in machine learning. MarI/O was his first project involving genetic programming, and only took him “a couple weeks” to get up and running.
MarI/O is a neural network that appears to be learning how to play Super Mario World by trial and error — just like you or I would. After playing the game for a bit, MarI/O learns which enemies do what (and when), then seems to decide on the best method for bypassing that enemy — just like you or I would.
MarI/O may not be as well known, but it seems to work similarly to Google’s DeepMind, which taught itself to play Atari games better than actual humans. I guess machines aren’t as snobby about graphics as we are.
But don’t take my word for it; watch the video, and marvel at MarI/O knowing it may only be a matter of time before the machines learn our routines and turn destroying humans into their own little game.
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