Have you ever put something down, only to forget where you put it? Suppose you know for certain that you left whatever it is in your room. It will take a certain amount of time to search your room in order to find the thing. What if you can’t remember which room of the house you might have left it in. Now, instead of searching your room, you have to search the entire house. Logically, you’d expect that searching a larger area would mean the search is likely to take longer. So imagine my surprise when my digital organisms consistently found better answers much faster when doing a larger search.
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Artificial life systems have a reputation for finding all sorts of obscure bugs in your code, no matter how rare or unlikely the conditions to cause the bug are. I’ve got an oddball one. It causes a run time error and shuts down the entire system, and it is an extraordinarily unlikely event, happening once in every 4,294,967,296 possible values. Let me just make sure that bug is what I think it is with a couple of tests.
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Let’s use artificial life to evolve intelligence. Because AI is hard; evolution is easy.

I’m not the first one to think of this idea. Quite a few people have taken a stab at it. It’s not even the first time I’ve implemented something to play with the notion—nymphs, grubs, figures… It’s very important that whatever else happens with the project, it will have a nifty name! This time, thanks to a conversation with my brother and co-host, they’re called “dorg.” It’s short for “digital organisms,” because, that’s what they are. They’re little bits of running software that sit on my computer and pretend to be alive.
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