AI Weirdness: the strange side of machine learning

Tag: textgenrnn

Total 35 Posts
How to begin a song

How to begin a song

So a while ago I made my first Twitter/Mastodon bot, a very simple little bot called TheSingalongBot. It came out of a chance conversation at the XOXO conference with Kate Compton and Gretchen McCulloch, and all it does is toot/tweet/twoot the first line of a song. Humans
How to make high-tech pies sound really old

How to make high-tech pies sound really old

A while ago I made a bunch of new pies. Well, I didn’t *make* them because they were neural network invented titles and although it tried to imitate the list of pies I gave it, the neural net’s imitations are imperfect. The neural network, after all, is a
CNN headlines, according to a neural net

CNN headlines, according to a neural net

The world is a chaotic and confusing place. Could advanced artificial intelligence help us make sense of it? Well, possibly, except that today’s “artificial intelligences” are not exactly what you’d call sophisticated. With a couple of hundred virtual neurons (as opposed to 16 billion neurons in the human
It’s neural net Halloween costume time

It’s neural net Halloween costume time

People use neural networks for translating languages, recommending movies, delivering ads, and more, but this here is one of my favorite applications: utter surrealism. Last year I trained a neural network on 4,500 Halloween costumes that you readers helped me collect. This year, I teamed up with the New
Neural Horror Picture Show

Neural Horror Picture Show

(Images generated by BigGAN) Neural networks are a kind of machine learning algorithm that learn to imitate the examples I give them. They’re pretty good at picking up on the feel of craft beer names vs guinea pig names, or metal bands vs my little ponies. So they should
New neural net snakes

New neural net snakes

There’s a kind of neural network that learns to imitate whatever text you give it, whether that’s recipes, song lyrics, or even the names of guinea pigs. Their imitations are often imperfect (they only know what’s in their dataset and therefore end up accidentally coming up with
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