When the power supply for my old laptop died a few months ago, I didn't want to spend the $70 that Dell wanted for a new one so I bought a cheap $20 one off Amazon. This promptly broke after a couple of months of use. It stopped charging my laptop but the battery didn't discharge while it was plugged in, so I wasn't bothered that much since I mostly use the computer when it's plugged in anyway.
I got a new laptop last week and I thought I'd try out Arch since I've been getting a little bored with the Debian universe lately. My old laptop had CrunchBang on it, which was fun to play around with and very fast but I thought I'd challenge myself and try something that wasn't based on Debian.
I got bored on Saturday afternoon so I decided to sit down and write a program that would use a neural network to automatically organize my video collection, renaming files with names like The.Conversation.1974.720p.BluRay.x264-AMiABLE [PublicHD] to something more readable like The Conversation (1974). This is my life…
Anyway, I didn't (still don't) know much of anything about neural networks, so I read some words about them and about genetic algorithms. In doing so, I ended up completing this exercise that uses a genetic algorithm to find a sequence of digits and operators that yields a certain target number. The problem I had was that his examples all parsed the sequences from left to right, ignoring order of operations (e.g. 6+5*4/2+1 = 23 instead of 17). I thought it would be fun to try to actually get the right result from these expressions, so I set out to write a simple parser for them.
I saw this post on Reddit this afternoon and it reminded me how terrible Google Translate generally is. Here's the image: Someone in the comments also linked to Translation Party, which translates between English and Japanese until the same thing comes out twice. It shows a lot of interesting problems with the model that Google uses to do translations. This one came off of a bottle of Rain-X I had lying around.