Google Deep Dream Program: How It Works

Google's Deep Dream is probably one of the trippiest computer programs you're likely to see. All you have to do is upload an image, tell the program to look for patterns, and wait as Google reveals exactly what your picture looks like to it.

The whole Deep Dream program started when Google decided to train an artificial neural network by showing it millions of training examples and gradually adjusting network parameters until the network gave the classifications it wanted. In this case, Google aimed to create a program that could search for images.

Yet one of the challenges of neural networks is understanding what exactly goes on at each layers of the artificial neurons. Each image is fed into the input layer, when then talks to the next layer until the "output" layer is reached. What's fascinating, though, is that this program can actually show researchers what it's "thinking" and "seeing."

The Deep Dream program relies on the idea that the program recognizes shapes and patterns and then generates images on the picture. It essentially works to recognize objects within a picture and then overlays the objects on the picture.

Why do the pictures look so trippy? That's because Deep Dream actually undergoes something similar to what humans experience during hallucinations. It's been given free rein to follow the impulse of any recognizable imagery and exaggerate it in a self-reinforcing loop.

Google has actually open sourced the code that they used to generate the strange-looking image. In fact, you can download it all for yourself here.

With that said, there are also several websites that have popped up where you can use this code. Just upload your image and wait for the time it takes to process.

Related Stories

Quantum Teleportation May be Possible: Electrons Remain Entangled Even After Separation

Violent Video Games: Playing These May Help Reduce Stress, But Increase Aggression

For more great science stories and general news, please visit our sister site, Headlines and Global News (HNGN).