Inspirobot.me
I have no idea how Inspirobot is generating it’s seemingly endless depth of inspirational memes. Templating? Markov chains? Neural network? Tons and tons of hand-edited entries?
If I had to guess, I’d say that a template seems the most likely, based on where the cohesion breaks down: it seems to have a good grasp on the grammar of the inspirational image, which most Markov chains are bad at. And a character-based neural net would likely make up some words on occasion, unless it had much more training data and lower entropy than this seems to.
If I had to implement something like this, I might try a meaning-swerving approach, using something like ConceptNet or WordNik to find substitutes for words in inspirational phrases, but a massive Tracery grammar might be faster to implement. And, of course, you can mix and match some of these to get the input data for the templates.
If anyone knows how it actually works, do let me know.
Meanwhile, I think I’ve found a new motto for the blog…
